coral reef ecosystem pattern detection
DESCRIPTION
Synoptic analysis of habitat structure, reef architecture, and ocean chemistry in Pacific Panamá using novel oceanographic and chemical sensor platforms including an underwater mass spectrometer and a 3-D benthic imaging dive sled. Results were used to guide coral reef conservation efforts surrounding a UNESCO World Heritage Site and Marine Protected Area in the Eastern Tropical Pacific.TRANSCRIPT
ADVANCING SPATIAL-TEMPORAL CONTINUITY IN CORAL REEF ECOSYSTEM PATTERN DETECTION
A Thesis Presented to
The Faculty of Moss Landing Marine Laboratories
San José State University
In Partial Fulfillment
of the Requirements for the Degree
Master of Science
by
Luis Camilli
December 2007
Copyright © 2007
Luis Camilli
ALL RIGHTS RESERVED
ABSTRACT
ADVANCING SPATIAL-TEMPORAL CONTINUITY IN CORAL REEF ECOSYSTEM PATTERN DETECTION
by
Luis Camilli
A towed, chemical sensor platform and a diver-based, automated imaging
system were developed to characterize seafloor morphologies and coral architecture
across centimeter to kilometer spatial scales, and resolve sub-meter variability in
ambient ocean chemistry across basin scale seascapes. Quantitative, thematic, water
chemistry maps and benthic habitat mosaics were generated from high resolution
underwater mass spectrometry and stereo, 3-D digital reef imagery. Integrated
analysis of data from satellite sensors, SCUBA surveys, video sampling, and a
moored observatory were used in concert to validate biogeochemical and structural
comparisons of coral habitats surrounding Parque Nacional Coiba, a UNESCO
World Heritage site in Pacific Panamá.
ACKNOWLEDGEMENTS
This work is dedicated in memory of my mother Valerie, who devoted her life to teaching others how
to learn.
Field surveys in Panamá were funded by the U.S. Fulbright Program, the
Wildlife Conservation Society (WCS), and the Ocean Life Institute (OLI). The Woods Hole Oceanographic Institution (WHOI) and The University of Sydney Australian Centre for Field Robotics (ACFR) provided in-kind support for sensor development and engineering facilities. The Autoridad Nacional del Ambiente (ANAM) and the Autoridad Marítima de Panamá (AMP) supplied research clearance and permits. The Liquid Jungle Laboratory (LJL) Panamá provided laboratory and diving facilities. I would especially like to acknowledge Dr. Oscar Pizarro and Dr. Richard Camilli for their enthusiasm, scientific acumen and creative engineering that inspired me throughout this endeavor. Many thanks to José Miguel Guevara of the ANAM office Unidad Técnica Nacional de Cambio Climático y Desertificación for his collaboration in creating GIS thematic habitat maps for the Republic of Panamá. Dr. Juan Maté of the Smithsonian Tropical Research Institute (STRI) was an invaluable source of information when identifying coral and invertebrate species. I am grateful to Belsi Medina and Dalys deGracia of The United States Embassy Cultural Affairs Office in Panamá for facilitating visiting scholar visas and arranging lectures. I would like to extend a warm thanks to Bryan Becker and Rachel Fulton for their assistance with SCUBA diving surveys. Buzos Boca Brava and SCUBA Coiba dive companies provided equipment and vessels for this project. Eduardo Bertrand kindly reviewed the veracity of this document in Spanish translation. I would like to recognize the dedication, patience and encouragement of Alpana Patel during my graduate career and her assistance processing dive data and editing this manuscript. Thanks to Jerrold Lundquist for his invaluable career advise and support of my scholarship. I would like to thank Dr. Jean Whelan and Dr. Hanumant Singh for sponsoring me as a guest student at WHOI and allowing me to participate and learn from their research. My kind gratitude is extended to Dr. Gary Greene and Dr. Jon Geller for their mentorship during my residence at Moss Landing Marine Laboratories and for serving on my thesis committee. Finally, ¡mucho gusto! to the little ‘tranquilo’ village of Santa Catalina and to all the great people I have had the good fortune to meet and interact with during my academic sojourn.
CONTENTS
LIST OF TABLES……………………………………………………………… x LIST OF FIGURES………………………………………………………………xi INTRODUCTION .............................................................................................................. 1
Regional Geomorphology of the Gulf of Chiriquí & Coiba Island .....................................5
Climate, Physical Oceanography, ENSO, & Upwelling Effects .........................................8
Marine Biogeography of Pacific Panamá ..........................................................................10
Community Interactions on Pacific Panamá Coral Reefs..................................................12
Spatial -Temporal Scales of Observation in Coral Reef Ecology......................................13
Representing the nature of complex adaptive systems ..........................................13
Scale dependence and emergent structures............................................................14
Geospatial and geostatistical approaches...............................................................15
Sampling biases .....................................................................................................16
Validating remotely sensed phenomena ................................................................17
Traditional subtidal ecology ..................................................................................18
A new approach to ecological field surveys ..........................................................19
Scientific Rationale............................................................................................................21
Ecologic questions .................................................................................................21
Hypotheses and predictions ...................................................................................22
METHODS, EQUIPMENT, & EXPERIMENTAL DESIGN.......................................... 23
A Brief Overview of Mass Spectrometer Instruments and Theory ...................................23
TETHYS-Towfish: A Towed, Integrated, Chemical Sensing Platform ............................24
TETHYS: An in-situ, underwater, mass spectrometer ..........................................25
Photo-optical chlorophyll and CDOM fluorometers .............................................26
SCUBA-COP: The SCUBA-diver Operated Chemical-Optical Imaging Platform ..........28
Stereo-optical imaging system and auxiliary sensors ............................................29
High Definition (HD) Video Camera ................................................................................32
Experimental Design..........................................................................................................34
Assumptions...........................................................................................................34
Field survey design ................................................................................................35
Integrated Field Survey Method ........................................................................................36
Measuring in-situ ocean chemical gradients with the TETHYS-Towfish.............36
High precision reef imaging with the SCUBA COP dive sled ..............................39
Simultaneous HD video and traditional SCUBA surveys .....................................41
Analytical Methods............................................................................................................42
Satellite data and GIS integration ..........................................................................42
Chemical transect data analysis .............................................................................43
High definition video and REEF CHECK data analysis .......................................45
SCUBA COP data analysis....................................................................................46
RESULTS ......................................................................................................................... 48
Comparing Offshore and Coastal Chemical Transects......................................................48
Temperature and salinity........................................................................................48
Panamá Liquid Jungle Laboratory Underwater Tropical Observatory .................52
Oxygen...................................................................................................................55
Carbon dioxide.......................................................................................................60
Chlorophyll-a .........................................................................................................66
Chromophoric Dissolved Organic Matter (CDOM)..............................................69
Methane..................................................................................................................78
Nitrogen .................................................................................................................81
Point Source Hydrocarbons ...................................................................................84
Diurnal to nocturnal respiration and productivity transitions ................................85
Groundtruthing SeaWiFs Satellite Data.............................................................................88
Using SeaWiFs to quantify a red tide ....................................................................93
HD Videography and Conventional Subtidal Survey Results ...........................................96
Characterizing habitats with snorkel & SCUBA ...................................................96
Quantifying benthic cover......................................................................................98
Common hard corals encountered .........................................................................99
Overall benthic composition ..................................................................................99
Quantifying scleractinian coral cover among dive locations...............................102
SCUBA COP Survey Results ..........................................................................................107
Data processing and mosaics ...............................................................................107
Automated image segmentation and classification..............................................109
DISCUSSION................................................................................................................. 112
Comparison of Traditional Diving Survey Results with HD Video ................................112
SCUBA COP: Visualizing an Automatically Intelligent Machine..................................114
Time versus Space and trade-offs in resolution...................................................114
Synoptic perspectives of swath mosaics ..............................................................115
Expert training for fully automated post processing............................................115
Comparing Coastal and Island Water Chemistry.............................................................116
Complex mixing of terriginous and offshore water.............................................117
Identifying eutrophic and oligotrophic water masses ..........................................119
Implications of excessive allochthonous input ....................................................122
Respiration and photosynthesis............................................................................124
Dwelling on Upwelling: The Deeper Implication ...........................................................126
Explaining coastal temperature-salinity anomalies .............................................127
Wind driven seiches.............................................................................................127
Calculating potential seiche heights for the Gulf of Chiriquí ..............................131
Alternate hypothesis: Internal Waves from Tidal Oscillations............................132
Coral Reefs, Fringing Reefs, Patch Reefs, and Coral Communities ...............................134
Marine Conservation Issues in the Gulf of Chiriquí........................................................135
Rapid coastal land use change .............................................................................135
Fishing out the fisheries .......................................................................................136
Recreational SCUBA diving................................................................................136
Legislation, Economics and Enforcement ...........................................................137
Advancing Continuity of Observation in Dynamic Marine Environments .....................139
CONCLUSION............................................................................................................... 142
REFERENCES ............................................................................................................... 146
APPENDIX..................................................................................................................... 163
SCUBA Coiba dive logs ..................................................................................................163
Benthic Categories from REEF CHECK v.2004.............................................................164
Results from REEF CHECK v. 2004 Point Intercept Transect (PIT) method.................165
Benthic Category Codes and Coral Species.....................................................................169
Offshore TETHYS-Towsled Transects Summary Statistics............................................170
Coastal TETHYS-Towsled Transects Summary Statistics..............................................171
Coral Field Guide for the Gulf of Chiriquí, Panamá ......................................................172
LIST OF TABLES
Table 1: Table of TETHYS mass spectrometer specifications........................................ 28 Table 2: SCUBA COP stereo imaging system specifications. ........................................ 31 Table 3: Sony high definition video recorder specifications. .......................................... 33 Table 4: Table showing correlations of salinity and temperature to other parameters
measured during offshore and inter- island chemical transects. ............................... 51 Table 5: Benthic cover summary statistics for dive locations in the Gulf of Chiriquí .. 100 Table 6: Summary statistics: Univariate one way ANOVA percent cover of
scleractinian coral among 4 similar islands. Analysis of variance using percent cover data Arcsine Square Root transformed to perform a univariate, one way ANOVA testing differences of percent cover among geographically similar offshore islands. The statistical null hypothesis Ho: “There is no statistically significant difference (P<0.05 two tailed test) between hard coral percent cover between 4 islands surveyed” was rejected since the probability of rejecting the null hypothesis (H0) when that hypothesis is true (Type I error) was significantly less (0.0001) than the a-priori alpha value chosen (ά = 0.05)............ 106
Table 7: Binocular vision permits the use of texture-based decision algorithms and 3 dimensional stereo as methods for coral classification. Example of tabulated results from an automatic segmentation and classification output. Corresponding benthic categories and the relative contribution from each of 6 classes are calculated over the total area of the mosaic from the colormap image in figure 42. The current implementation allows the user to prescribe the number of classes while the EM algorithm derives the characteristics of each class......................................................................................................................... 111
Table 8: Benthic Categories used for multi method comparisons during transect surveys. ................................................................................................................... 164
Table 9: Table of Benthic Category Codes and Coral Species created to train automated image segmentation and classification.................................................. 169
Table 10: Summary Statistics for TETHYS-Towfish Chemical Surveys of Offshore Transects and Islands. Arrows between locations indicate transects sampled between locations.................................................................................................... 170
Table 11: Summary Statistics for TETHYS-Towfish Chemical Surveys of Coastal Transects and Islands. ............................................................................................. 171
LIST OF FIGURES
Figure 1: Map of the Republic of Panamá (Scale1:200,000) showing study area location and size relative to three major Pacific gulfs. The red lines inside of the square indicate survey transects............................................................................ 3
Figure 2: Geologic Map (scale 1:800,000) showing dominant morphology of study region and isobaths (10 to 1000 meters) in the Gulf of Chiriquí and the Gulf of Montijo. This map is a synthesis of information from U.S.S. Hannibal (1934-1936) navigational surveys, and geologic data provided by the Department of Mineral Resources, Panamá (DGRM 1991) and Lonsdale & Fornari (1980). ........... 7
Figure 3: A towed, integrated chemical sensing platform: The prototype TETHYS-TowFish (length 1.5 m) shown with CTD, fluorometers, and TETHYS underwater mass spectrometer located in the larger pressure housing. ................... 25
Figure 4: TETHYS mass spectrometer with underwater pressure housing removed...... 26 Figure 5: The SCUBA diver operated Chemical-Optical imaging Platform
(SCUBA-COP). Stereo cameras, batteries, and integrated electronics are contained in underwater pressure housings below the platform next to an oxygen optode and CTD. Stereo strobes are mounted to either side of the platform. The surface GPS antenna is located next to the propulsion device on the topside of the sled. The checkerboard pattern in front of the SCUBA COP was used underwater during field trials to calibrate optics....................................... 30
Figure 6: The stereo camera imaging system with pressure housing removed showing digital cameras (1 monochrome and 1 color) and the integrated PC 104 computer, ethernet, Internal Motion Unit, and hard drive storage. Lithium ion battery power is contained in a separate pressure housing. ................................ 31
Figure 7: Commercially available high definition digital video recorder and pressure housing........................................................................................................ 33
Figure 8: Survey map (scale 1:800,000) showing island and coastal locations, towed chemical transects, dive sites, and isobaths. Towed chemical transects are represented by a solid red line. ................................................................................. 38
Figure 9: Diver imaging underwater coral habitats with SCUBA COP. Strobes lights, mounted on both sides, are synchronized at 2 Hz to uniformly illuminate areas independent of ambient lighting. An internal motion unit senses vehicle attitude (pitch, roll, heading) and logs relative position during imaging. A propulsion devise helps the diver maintain a constant velocity while photographing. Stereo images are captured by digital cameras synchronized with the strobes and a computer located in the middle pressure housing................. 40
Figure 10: Diver surveying coral habitat with traditional Point Intercept Transect (PIT) method. Benthic categories are recorded on a dive slate every 0.5 meters along a 50 meter transect tape to provide quantitative information on spatial coverage, diversity, health, and substrate morphology............................................. 42
Figure 11: In-situ temperature data overlain onto Landsat TM satellite imagery. The color gradient indicates water temperature (°C) with cooler regions
represented in blue and warmer regions in red. Observe the cooler temperatures along the coastal transect. ......................................................................................... 49
Figure 12: Salinity data overlain onto Landsat satellite imagery. The color gradient indicates salinity concentrations [‰] in parts per thousand (ppt) also reported as Practical Salinity Units (PSU). Lower salinity is represented in blue and higher salinity in red. Note the higher salinity near the coast compared to offshore. .................................................................................................................... 50
Figure 13: Cumulative year 2006 plots generated from time series data provided by the Panamá Liquid Jungle Laboratory Underwater Tropical Observatory (PLUTO). Large temperature-salinity fluctuations occur from April to May with a steady decline in pH from July into December. Photosynthetically available radiation (PAR) decreases between August and October, during the height of the rainy season. ........................................................................................ 53
Figure 14: PLUTO data from January through April 2007. Large temperature and salinity fluctuations begin in February and extend through mid March over nearly 4 meter tidal amplitudes................................................................................. 54
Figure 15: A scatterplot of (oxygen/argon) mass spectrometer measurements with temperature measurements from the towed CTD. The linear trend represents a positive correlation of 0.231. .................................................................................... 56
Figure 16: Oxygen measurements overlain onto Landsat imagery. Low levels occur between Canales de Afuera Island and Canales de Tierra. Similarly Secas Island to Boca Chica transects exhibit lower oxygen (top left corner). Comparatively high levels were observed near Uvas Island and periodically northwest of Coiba.................................................................................................... 57
Figure 17: This graph shows a vertical profile from a transect from Boca Chica to the Secas island group. The dips in the tracklog correspond to the TETHYS-Towfish slowing and diving and then climbing toward the surface again as the boat accelerates. Units are dimensionless, red indicates higher dissolved oxygen levels, blue indicates lower levels. Longitude is plotted on the (x) axis, Latitude is plotted on the (y) axis and depth in meters is plotted on the (z) axis. The horizontal variability in oxygen suggests two different water masses interacting along a vertical front in the euphotic zone.............................................. 59
Figure 18: TETHYS mass spectrometer measurements (dimensionless) of carbon dioxide gradients across towed transects Feb. 2007. Note the lower levels northwest of the Secas Islands, and the high degree of variability between Uvas Island and Coiba Island. Low levels were noticed between Canales de Afuera and Canales de Tierra Island..................................................................................... 61
Figure 19: Scatterplot showing carbon dioxide and salinity relationship from offshore towed chemical transects. A correlation value of ( -0.451) was calculated for 842 data points suggesting carbon dioxide may be governed in part by salinity in these waters.................................................................................. 62
Figure 20: Concentrations of chlorophyll-a [µg/L] across all towed transects. Colorbar represents lower levels of chlorophyll in blue and higher levels in red.
Chlorophyll levels are generally elevated near coastal zones, and especially high towards the mainland areas of Boca Chica which is a mangrove estuary. ....... 66
Figure 21: Average chlorophyll-a values [µg/L]binned by 1 meter depth across all TETHYS - TowFish surveys. Bars represent mean concentration at each depth, lines represent the first standard deviation of means. ............................................... 67
Figure 22: Mean CDOM concentrations [QSU] binned by 1 meter depths across all towed TETHYS-Towfish transects. Bars represent mean CDOM concentrations and lines extending from the bar graph indicate the first standard deviation. CDOM concentrations appear to increase with depth in the euphotic zone (0-13 meters) and drastically decrease to near zero from 13 meters to 15 meters depth. ............................................................................................................. 70
Figure 23: CDOM concentrations [QSU] of all TowSled-TETHYS chemical transects overlain on Landsat satellite image. Colorbar indicates higher concentrations in red and lower concentrations in blue. Note the high levels of CDOM in the coastal embayments. .......................................................................... 71
Figure 24: CDOM and temperature scatterplot from offshore towed transects. Temperature °C is plotted on the (x) axis and CDOM concentration [QSU] is plotted on the (y) axis. The linear interpolation represents a negative correlation of -0.298 between the two parameters.................................................... 72
Figure 25: CDOM and salinity scatterplot from offshore towed transects. Salinity concentration in parts per thousand [‰] is plotted on the (x) axis and CDOM concentration [QSU] is plotted on the (y) axis. The linear interpolation represents a positive correlation of 0.245 between the two parameters. .................. 73
Figure 26: CDOM concentrations [QSU] from TowFish-TETHYS survey in Bahia Honda overlain on satellite imagery. Dips in the tracklog show vertical profiles taken at periodic intervals down to 12 meters depth. Data shows significant vertical variability in CDOM concentrations. Differences in surface concentrations from east to west may be indicative of circulation patterns within the bay. Red areas represent higher CDOM concentrations and blue areas show lower CDOM. A point source of CDOM is noticed near the north shore of Managua island with values exceeding 50 QSU......................................... 74
Figure 27: Alongshore coastal CDOM transect from Santa Catalina to Canales de Tierra. 3-D color plot showing variations of CDOM concentrations [QSU] as a function of salinity, longitude, and depth. Higher CDOM concentrations (shown in red) decrease abruptly to near zero (shown in blue) traveling westward along the coast (x) axis. CDOM concentrations increase with lower salinity values (y) axis. CDOM concentrations along the depth (z) axis show a vertical mixing boundary between distinct hyposaline (freshwater)masses and normal salinity ocean water. ..................................................................................... 76
Figure 28: Changes of CDOM concentrations [QSU] in the water column between the coastal Santa Catalina Island and Octavios Island represented in dimensional space (latitude, longitude, depth). Significant changes in CDOM were noticed during a vertical profile to 15 meters depth. A mass of water with high CDOM concentrations near 30 [QSU] shown in red, advected past the
fluorometer during an upcast. Horizontal variations in CDOM were also quantified in the surface water as shown by the differences in blue hues. ............... 77
Figure 29: Scatterplot of salinity [‰] concentrations-(x) axis; and methane on (y) axis from all Towsled-TETHYS offshore transects. Methane and salinity are negatively correlated (-0.368)................................................................................... 79
Figure 30: Methane measurements from TowSled-TETHYS chemical surveys. In mass spectrometry, ratios of methane to water CH4:H2O employ water as a conservative tracer to help differentiate methane from other hydrocarbons. Higher methane is indicated in red and lower levels in blue. High levels of methane were encountered near the Secas Islands and north to Boca Chica, and along coastal regions adjacent to the Gulf of Montijo. The variegation of color between Coiba Island and Uvas Island shows mixing between water masses. ........ 80
Figure 31: Nitrogen isotope ratios plotted along TowSled-TETHYS chemical survey tracklogs. Lower 14N to15N ratios (relative 15N enrichment) was dominant near the Secas Islands and the central Gulf of Chiriquí............................ 83
Figure 32: Example of a TETHYS mass spectrum from 12 meters depth approximately 3 km south of Santa Catalina coastal area, indicating the presence of trace levels of hydrocarbons (Camilli et al. 2007)................................. 84
Figure 33: Scatterplot of carbon dioxide and oxygen collected along a transect from Boca Chica to Secas Island with the Towfish-TETHYS platform. Units are dimensionless............................................................................................................ 86
Figure 35: Time series color plot of SeaWiFs chlorophyll-a data representing a spatial domain investigated by this study. Chlorophyll concentrations are averaged over latitudes (6° N to 8°N) for each month. The highlighted area shows the timeframe surveyed in this project with the Towfish-TETHYS platform. Concentration of chlorophyll- a [mg/m3] is shown by the colorbar with lower concentrations in blue and higher in red. Blank areas represent signal attenuation due to atmospheric interference (e.g. cloud cover). Note the punctuated seasonality of chlorophyll levels. ........................................................... 89
Figure 36: Color image of SeaWiFs remotely sensed chlorophyll-a concentrations [mg/m3] covering the spatial extent of this project during the first week of the towed chemical surveys. The SeaWiFs imagery represents average chlorophyll-a concentrations over a spatial extent where 1 pixel = 9 km2. ............. 91
Figure 37: Satellite remote sensing groundtruth: A comparison of raw SeaWiFs chlorophyll-a data with TETHYS-TowFish data. SeaWiFs data are indicated as orange squares, and TETHYS-TowFish data are indicated by green circles. The vertical alignment of SeaWiFs data along the (x) axis (longitude) is an artifact of SeaWiFs coarser resolution (1 degree longitude). Data points were averaged across latitudes 7°N to 8 °N, encompassing the entire towed area. The spatially dense TETHYS-Towfish chlorophyll-a data nests well within SeaWiFs surface measurements. Note the equivalence of concentration values where 1[µg/L] = 1[mg/m3]. ...................................................................................... 92
Figure 38: SeaWiFs chlorophyll-a concentrations [mg/m3] coinciding with a severe hemotalasia (red tide) observed in the study area during May 2007.
Chlorophyll-a concentrations in the Gulf of Chiriquí at times exceeded [30 mg/m3], nearly two orders of magnitude greater than TETHYS-Towsled measurements [0.251 µg/L] collected in February 2007. ......................................... 95
Figure 39: Relative contribution of hard coral, recently killed coral, and coral rubble to overall benthic percent cover at dive locations in the Gulf of Chiriquí. Standard error is reported in benthic coverage summary statistics table................ 103
Figure 40: A “Box-Whisker Plot” graphical representation of hard coral percent cover among dive sites in the Gulf of Chiriquí. The lower and upper lines of the “box” are the 25th and 75th percentiles of the sample. The distance between the top and bottom of the box is the interquartile range. A line in the middle of the box represents the sample median and when it is not centered within the box, is an indication of skewness. The lines extending above and below the box the “whiskers” show the total sample extent, with the maximum value represented by the upper whisker and the minimum value signified by the lower whisker. The notches “pinching” the sides of the box are a graphic confidence interval about the median of a sample.................................................................................. 104
Figure 41: Spatial scale and resolution of a typical mosaic swath: The top image represents an entire 50 X 3 meter swath ( composed of more than 150 overlapping images) that was captured with SCUBA COP stereo cameras, in one pass. The serpentine morphology of the top mosaic swath is a result of underwater currents that affected the diver and instrument. An internal motion unit (IMU) onboard SCUBA COP enables post processing correction of vehicle attitude and displacement relative to object being imaged. An enlargement of the area represented by the smaller dotted square in the top figure is shown below where you can distinguish a SCUBA diver in the right hand corner placing an underwater transect tape- the white stripe in middle of swath. With no digital compression, each individual image in the swath can be enlarged to its maximum resolution where 1 pixel = 1cm......................................................... 108
Figure 42 The mosaic to the left represents a 14 meter long subsection of a 50 meter transect from Isla Uvas, comprised of more than 40 overlapping individual images. Adjacent and to the right of this mosaic is a computer generated automated classification of six user prescribed classes that were used to produce a color-coded segmented image from the coral mosaic. These segmentations roughly correspond to distinct benthic categories of coverage. In this example, light blue areas correspond to sand; light green corresponds to a mixture of rubble and sand. Dark red and blue hues tend to be hard corals. The blue stripe in the middle is the transect tape.................................................... 110
Figure 43: Comparison of high definition video with SCUBA diver Point Intercept Transect (PIT) method - REEFCHECK protocol. Blue bars represent benthic percent coverage estimates (pooled for all 7 dive locations) across 10 categories using video swath methods. Yellow bars represent PIT percent cover estimates across the same categories. Standard error for each category is reported in the summary statistics (Table 5) for the HD video method and (Appendix Fig. 54 through 59) for the PIT method. ............................................................................. 113
Figure 44: Methane variability in the water column near the coastal region of Santa Catalina represented in dimensional space (latitude, longitude, depth). The vertical profile represents methane variability over depth and the horizontal plane shows variability across the surface. Areas in red show higher levels of methane and areas in blue show lower levels (dimensionless units). ..................... 118
Figure 45: 3-Dimensional scatterplot showing the relationship of chlorophll-a, carbon dioxide, and oxygen over the Boca Chica to Secas Island transect. Strong correlations between oxygen, carbon dioxide and chlorophyll are revealed. .................................................................................................................. 120
Figure 46: CDOM – Salinity scatterplot of Boca Chic to Secas Island transect showing a strongly negative correlation between CDOM and salinity in these waters. The CDOM – salinity relationship suggests large influences of freshwater input over this shallow shelf (<50 m) depth. ........................................ 121
Figure 47: Map (scale 1:400,000) of major rivers (blue lines) and population centers (red triangles) in relation to chemical survey area (red lines). According to a GIS analysis of year 2000 Panamá national census data, approximately 103,000 inhabitants live in the Gulf of Montijo drainage basin. The Gulf of Montijo is a shallow, mangrove-estuarine system with 24 major tributaries emptying into the basin. ................................................................................................................. 124
Figure 48: Cumulative PLUTO measurements for the month of February 2007 corresponding to Towfish-TETHYS survey time periods. Notice the high frequency and large amplitude temperature fluctuations ranging from 16 °C to 28°C over a 24 hour cycle. Salinity values remain above 28 PSU and there is a tendency for pH to become more alkaline with these pulses suggesting that these pulses are coming from offshore water masses rather than terrestrial freshwater. Also note the nearly 4 meter tidal amplitude occurring from February 17th- 24th................................................................................................. 128
Figure 49: Graph of calculated potential seiche amplitudes in the Gulf of Chiriquí using various wind velocities encountered during the survey. Wind velocity (y-axis) is presented in cm/s and equivalent miles per hour. Seiche height is plotted in centimeters.............................................................................................. 132
Figure 50: Conceptual diagram relating scales of observation in marine ecology to natural phenomena in the marine environment. The dashed asymptote represents a theoretical horizon between biologic and physical process operating in the marine environment. The figure in the middle is an anthropomorphized symbol emphasizing human scale in relation to these factors. Ovals represent spatial temporal attributes of each sensing technology and the manner in which they overlap. ................................................................... 141
Figure 51: Average monthly visibility (meters) plotted from 3 year SCUBA Coiba dive logs. The red solid lines show visibility at a small island less than 1 km from the coast. The dashed blue line shows visibility at a dive site on the north end of Coiba approximately 30 km from the coast................................................. 163
Figure 52: Average monthly water temperature (°C) at a Coiba Island dive site over a 3 year period. Orange line shows temperature at depth, and blue line shows
surface temperature. Data provided by Rachel Fulton and Herbie Sunk of SCUBA Coiba......................................................................................................... 164
Figure 53: REEFCHECK results: Mean % Benthic Cover: Isla Canales de Afuera. The following figures provide a data summary for SCUBA diver REEFCHECK V.4.0 protocol for transects in the Gulf of Chiriquí Panamá (February 2007). Graphs depict mean percent benthic cover of 10 categories at each site. Data points were collected every 0.5 meters along 50 meter transects perpendicular to shore at depth ranges from 6 to 12 meters. Lines extending above the bars represent standard error (+/- SE). Site locations are given in geographical coordinates below each title. Table 8 provides an explanation of each benthic category shown in the graphs.................................................................................. 165
Figure 54: REEFCHECK results: Mean % Benthic Cover: Isla Uvas .......................... 166 Figure 55: REEFCHECK results: Mean % Benthic Cover: Isla Canales de Tierra ...... 166 Figure 56: REEFCHECK results: Mean % Benthic Cover: Punta Miel, Bahia Honda. 167 Figure 57: REEFCHECK results: Mean % Benthic Cover: Isla Managua, Bahia
Honda...................................................................................................................... 167 Figure 58: REEFCHECK results: Mean % Benthic Cover: Punta Damas, Isla Coiba.. 168 Figure 59: A field guide (in Spanish) of corals and sponges commonly encountered
in the Gulf of Chiriquí. Created as a part of this thesis, for the Autoridad Nacional del Ambiente (ANAM) - the environmental and parks authority of the Republic of Panamá. ............................................................................................... 172
INTRODUCTION
The word Panamá meaning “place of many fish” is likely derived from the
indigenous Guaraní people who inhabited the isthmus during pre-Columbian times
(Room 2006). Ancient midden deposits suggest that the bounty of these fecund tropical
waters filled the hulls of dugout cayucos for more than five centuries before the arrival of
the first conquistadores (Linares de Sapir 1968). A lucrative and expanding fishery has
certainly defined modern production since the mid 1950’s (FAO 2007, Nansen 1987).
Unfortunately, Panamá may be just one instance in a global trend where revelries of
halcyon eras are being qualified with more sobering accounts of fisheries decline and
habitat degradation.
Rapid deterioration of coral reefs in the Eastern Pacific along the coasts of Costa
Rica and Panamá were first observed during the 1970’s and continued into the 1990’s
(Glynn 1973, Guzmán 1991, Glynn & Ault 2000). Recently two major regions on the
Pacific coast of Panamá, the Gulf of Chiriquí and the Gulf of Montijo (Fig. 1), were cited
as “critical areas” highly vulnerable to anthropogenic disturbance and pollution (ANAM
2003, Delgado-Pena 2002). The coastal regions that surround these gulfs are currently
experiencing a significant land use change due to unregulated construction, commercial
agriculture, septic waste increase and rapid population expansion.
The occurrence of coral reefs and the distribution of most reef-building corals are
limited to shallow warm water regions of the tropics and subtropics (Veron 1995).
Because corals have evolutionarily adapted to low nutrient conditions, coral reefs are
2
particularly susceptible to eutrophication via anthropogenic nutrient loading (Fabricius
2005, Lapointe & Thacker 2002). Deleterious natural and human effects of terrestrial
nutrient input may be potentially amplified because this region experiences high seasonal
freshwater discharge with rainfall of up to 3500 mm/yr (Guzman et al. 2004) and are
downstream from commercial cattle ranches and agricultural areas with intensive
fertilizer use.
Coastal areas encompassing the Gulf of Chiriquí, Panamá currently function as
small ports for artisanal fishermen, however, little is known about the structure and
diversity of coral habitats or other invertebrate communities in these coastal regions or
what is causing the recent crustacean and general fishery decline in the nearshore (FAO
2002, Glynn 2004, Maté 2006, Suman 2005).
3
Figure 1: Map of the Republic of Panamá (Scale1:200,000) showing study area location and size relative to three major Pacific gulfs. The red lines inside of the square indicate survey transects.
In 1991 the Coiba National Park, located on the south eastern border of the Gulf
of Chiriquí, was created, and in July of 2005 became a UNESCO1 World Heritage Site
(ANAM 1991, ANAM 2006). Coiba National Park, with an estimated marine area of
216,543 hectares, forms part of the 2Eastern Pacific Marine Conservation Corridor (UNF
2004). In 2006 The Smithsonian Tropical Research Institute (STRI) began work to
establish a scientifically informed management plan for the Special Marine Protected
Zone in the Coiba National Park (Maté 2006).
1 United Nations Education Science and Cultural Organization 2 A multi lateral governmental agreement composed of the following territories: Galapagos Islands (Ecuador), Cocos Islands (Costa Rica), Mapelo and Gorgona Islands (Colombia), Coiba Island (Panamá)
4
Marine conservation applications require repeatable scientific inquires and
quantitative, archiveable, ecological baselines to characterize complex underwater
morphologies and study changes in species distributions or habitat states (Jackson 1995,
Edgar 2004, Hughes & Connel 1999). Laboratory experiments are limited in their ability to
detect geochemical and metabolic changes of coral reefs over large temporal scales and
spatial dimensions. Field-based surveys are often intractable and costly both in terms of time
and monetary resources (Garza-Perez et al. 2004, Mumby et al. 1999, Yates 2003). In
order to identify threatened marine habitats, a reliable diagnostic which incorporates high
resolution mapping and quantitative analysis at multiple spatial levels is needed to
efficiently monitor and respond to changes in the health of coral ecosystems (Goodman
& Ustin 2000, Lam et al. 2006, Edgar et al. 2004, Niegel 2003).
Caribbean reef ecosystems of Panamá have been well studied (Jackson et. al.
1989; Guzmán & Garcia 2002; Andrefouet & Guzmán 2005, Toller & Knowlton 2001),
but fewer comprehensive assessments of coral habitats exist for Pacific coastal areas
(Hurtado 1991, Chemonics 2004). Most regional studies have focused on small numbers
of reefs without an adequate spatial scale to capture the diversity of habitats and species
and require an increase in effort and sampling scale in order to comprehensively evaluate
the complexity of these (Pacific) coastal zones (Guzmán et al. 2004).
5
Regional Geomorphology of the Gulf of Chiriquí & Coiba Island
An elegant example of biologic and geologic time scales intersecting
paradigmatically within the study of natural history and structure of coral reefs is
elucidated independently in early accounts on the subject. The theory of atoll formation
originally proposed by geologist Charles Lyell in (1833) was rejected and modified by
his colleague, the naturalists Charles Darwin (1842). As this theory developed, it was
subsequently revised by other contemporaries, namely Joseph Jukes (1849) and James
Dana (1872), when it became apparent that biological processes could operate on
geologic time scales. Eventually evidence for Darwin’s theory of coral-reefs was given
credence with the work of an early pioneer of submarine geomorphology, Ferdinand
Wilhelm3 when he postulated in 1859 that thick layers of dolomitic limestone in the
eastern Alps were formed during extended periods of geologic subsidence. As we now
know from the field of paleoceanography, geophysical process acting over long time
scales and across large distances can exhibit profound effects on hard coral species
distributions in the marine environment (Grigg & Hey 1992, Aronson et al. 2005).
Multi disciplinary evidence suggests that there were already significant biotic
changes taking place in the marine environment as the Panamá-Costa Rica arc began
colliding with South America in the late Mesozoic through the end of the Cenozoic era,
circa 10 million years ago (Jackson 1993, Cortés 1997). During Cretaceous to Oligocene
periods 36 coral genera exist in the fossil record, decreasing to 18 genera in the Miocene,
3 Baron von Richthofen
6
compared to 6 known genera in the modern Holocene epoch (Durham 1966). The
isthmus assumed its present position during the late Pliocene epoch only 3 to 3.5 million
years ago and effectively cut off the deep-water circulation4 between the Pacific and the
Caribbean (Sing & Harmon 2005). Igneous rocks along the Pacific coast, formed during
the Tertiary, are thought to be part of an older oceanic plateau associated with the
Galapagos hot spot, an oceanic volcanic island arc complex that was generated by Nazca
plate and Cocos plate tectonic interactions (Lonsdale & Klitgord 1978).
The Gulf of Chiriquí contains several prominent, offshore island complexes
including Isla Coiba (493 km2), Isla Cebaco (80 km2) Islas Ladrones, Islas Secas, and
Islas Contreras. Other islands like Jicarón, Leones, Gobernadora, Verde, Canales de
Afuera, Ranchería, Papagayo, Canales de Tierra, and Jicarita are part of a group of more
than forty smaller island clusters scattered near the coast. Coastal areas in the gulf are a
mélange of mid to late Tertiary volcanics, and much newer Quaternary period alluvial
sedimentary series (Fig. 2). Smaller island clusters are predominantly basalt outcrops
once associated with the mainland before sea level rise (DGRM 1991, Cortés 1997).
Coiba Island, the largest in the region, shares geomorphologies similar to the mainland
Azuero peninsula. Due to tectonic rising as the Pacific plate subsided under the
Caribbean at the end of the Tertiary, and its proximity to the coast, Coiba Island is a
mixture of volcanic rock and carbonate lithologies overlain by sedimentary soils of
secondary genesis. Immediately to the southwest is the submarine Coiba Ridge, an
4 The Panamá Canal uses a system of freshwater lochs and man made lakes to bridge the inter-ocean gap, however significant transport of ship bilge waters may be cross fertilizing oceans and changing local marine communities.
7
upfaulted fragment of normal oceanic crust, and approximately 100 km east of Coiba
island lies an active transverse fault less than 1000 meters below sealevel (Lonsdale &
Fornari 1980).
Figure 2: Geologic Map (scale 1:800,000) showing dominant morphology of study region and isobaths (10 to 1000 meters) in the Gulf of Chiriquí and the Gulf of Montijo. This map is a synthesis of information from U.S.S. Hannibal (1934-1936) navigational surveys (USA 1995, USA 1996), and geologic data provided by the Department of Mineral Resources, Panamá (DGRM 1991) and (Lonsdale & Fornari 1980).
8
Climate, Physical Oceanography, ENSO, & Upwelling Effects
The climate of Panamá is largely affected by the position of a low atmospheric
pressure zone known as the Inter Tropical Convergence Zone (ITCZ) which also affects
seasonal evolution of geostrophic currents in the Panamá Bight. During the rainy season
(December through May), the ITCZ is located to the North of Panamá and produces light
and variable winds and ocean circulation in the Panamá Bight is anticyclonic (west)
which creates a southerly flowing coastal current. Glynn and Maté claim that the
southerly flow of the Panamá Current is especially strong in the dry season and near the
Azuero Peninsula it can attain velocities of up to 50-60 cm/second (Glynn & Maté 1997).
Starting in October and continuing into the dry season (January to March) the
ITCZ moves South of Panamá, producing a dominant period of northeasterly tradewinds
known as the Panamá Jet5, which results in a reversal of water circulation and becomes a
cyclonic gyre with a coastal current flowing to the north (Rodriguez-Rubio & Stuardo
2002). Upwelling develops in the Bay of Panamá during the dry season when northeast
tradewinds from the Caribbean blow over to the Pacific through a physiographic gap in
the central mountain range which divides the Isthmus. This wind stress creates seasonal
Ekman pumping and displaces nutrient-poor coastal surface water with cool, nutrient
rich, water masses (Rodrıguez-Rubio & Schneider 2003).
5 The Panamá Jet has a width of about 200 km, and extends for about 500 km into the Bight of Panamá creating a prevailing northerly wind stress in the Gulf of Panama that can exceed 0.1 Nm-2 (Rodríguez-Rubio & Schneider 2003).
9
Cold water pulses from wind induced upwelling in the Gulf of Panamá (January
to March) range from 15° C to 18° C, with a range of 10° C annually. The warmer non-
upwelling environment of the Gulf of Chiriquí produces mean sea surface temperatures
(SST) of 27° C to 29° C (Schloder & D’Croz 2004, D’Croz & Maté 2004). In addition to
seasonal upwelling, the coastal oceanography of the Bay of Panamá is affected by
episodic sea warming attributed to the E1 Niño Southern Oscillation (ENSO) which
occurs on a 4 to 9 year interval (Glynn et al. 1984; Glynn 2000, Glynn et al. 2001).
Large temperature fluctuations can be detrimental to tropical coral communities.
Warming in the Gulf of Panamá to temperatures above 20° C negatively effected growth
rates of Pocillipora damicornis (Glynn & Stewart 1973) and an increase of ambient SST
from 1° C to 4° C during an exceptionally strong ENSO caused mass bleaching and
mortality of many eastern Pacific zooxanthellate6 corals (Glynn et al. 2001). A
laboratory experiment testing thermal tolerance within the genus Pocillopora between the
Gulf of Panamá upwelling site and the non-upwelling Gulf of Chiriquí indicated that
Pocillopora damicornis species collected from the Gulf of Panamá demonstrated higher
vulnerability to thermal stress than the same coral types from the Gulf of Chiriquí
(D’Croz & Maté 2004).
6 Corals containing photosynthetic endosymbionts, especially from the phylum Dinoflagellata (Veron 1995).
10
Marine Biogeography of Pacific Panamá
Littoral areas located along the Southern Isthmus of Panamá demonstrate highly
complex ecological interactions and distributions of endemic and migratory marine
species due in part to the overlap of continental ecotones, tropical weather patterns and
the convergence of powerful sea currents (Cortés 1997, Glynn & Ault 2000, Watts &Wu
2005). In the Republic of Panamá, there is estimated 290 km2 of reefs along both
Caribbean and Pacific coasts, however much higher diversity (about 68 hard coral
species) occurs in the Caribbean, (Chemionics 2004, Clifton et al. 1997) compared to 33
known species7 from 11 genera living along the Pacific coast (Cortés &Guzmán 1998).
Two major gulfs, divided by the mainland Azuero Peninsula, are situated along a
predominantly east-west axis on the Pacific coast of Panamá (Fig. 1). The Gulf of
Panamá which is the Pacific outlet for the Panamá Canal is a substantial part of the
marine area between Panamá and Colombia. Further west, The Gulf of Chiriquí and the
smaller Gulf of Montijo are the dominate water bodies located between the Azuero
Peninsula and Punta Burica which defines the western Panamá - Costa Rica border.
The Gulf of Chiriquí, Panamá is part of a larger biogeographic region of the
eastern tropical Pacific referred to as the Panamic Province stretching approximately
from Ecuador (3 º S) to Southern Mexico (16º N). Before the closure of the isthmus
Pacific coral fauna were more similar to those of the Caribbean, but in terms
scleractinian corals, the whole eastern tropical Pacific is now considered a sub province
11
of the Indo-Pacific faunal assemblages (Cortés 1997, Glynn & Wellington 1983, Guzmán
& Cortés 1993). Whether these differences can be attributed to vicariance (i.e.,
speciation and extinctions), immigration or ancient land closure is still up for debate.
Nonetheless it has also been observed that associated invertebrate taxa (sponges,
alcyonarians, soft corals, anemones, zoanthids, polychaete worms, bryozoans, mollusks,
echinoderms, and tunicates), contribute relatively little to the epibenthos of coral
communities of the Eastern Tropical Pacific when compared to other biogeographic
regions (Glynn & Ault 2000).
Corals of the Eastern Pacific near Central America are generally characterized by
low species diversity and discontinuous or patchy distribution over areas less than a few
hectares (Glynn & Ault 2000, Cortés 1997). In Pacific Panamá communities are mostly
composed of fringing reefs located on islands and patches near the coast, situated
predominately within the Gulf of Chiriquí (Garzon-Ferriera et al. 2002). The coral reefs
in the non-upwelling Gulf of Chiriquí are purported as being more abundant 8 and larger,
with higher species diversity, and more vertical buildup than the Gulf of Panamá (Glynn
& Maté 1997).
7 Hard coral species composition: 25 ahermatypic corals and no hydrocorals (Cortés & Guzmán 1998). 8 The largest reef in the Gulf of Chiriquí is located near Coiba Island and covers approximately 1.6 Km2 (Guzmán et al. 2004, Glynn and Maté 1997).
12
Community Interactions on Pacific Panamá Coral Reefs
As a background to coral ecosystem function in this region, it is worthwhile
noting some previously studied ecological interactions on coral reefs in Pacific Panamá.
An early investigation of coral community structure on opposite sides of the Isthmus of
Panamá showed a negative correlation of diversity with abundance, and demonstrated, in
the Pacific habitats, monospecific dominance of Pocillopora damicornis in areas of high
coral coverage, except in areas of disturbance exposed to extensive predation from
Acanthaster sp. (Porter 1974). The Pocillopora spp. corals are predated on by a diverse
assortment of organisms including the fish Arothron meleagris, gastropods Quolyula
monodonta (Coralliophila madrepora), Jenneria pustulata, and hermit crabs including
Aniculus elegans and Trizopagurus magnificus. A shrimp species Alpheus lottini
provides a symbiotic defense against the crown of thorns Acanthaster species (Cortés &
Guzmán 1998). Similarly the obligate crustacean symbionts Trapezia ferruginea and
Trapezia corrallina exert a defensive behavior near Pocillopora sp. and clean coral
mucus and debris thereby increasing survivorship of the coral (Glynn et al. 1985). The
damselfish Stegastes acapulcoensis is capable of inflicting severe damage to Pavona sp.
corals , but is only able to kill branching tips of the Pocillopora sp. due to its fingerlike
morphology. Reduced pocilliporid colonies at depth are thought to be affected by intense
grazing pressure from parrotfish and pufferfish (Wellington 1982). Other complex
relationships have been noted such as nutrient inputs increasing algal turf thereby
13
initiating spatial competition which triggers increases in asexual reproductive
mechanisms of corals (Cortés 1997).
Spatial -Temporal Scales of Observation in Coral Reef Ecology
Representing the nature of complex adaptive systems
Expanding upon an empirical epistemology sensu Aristotle, 9 our understanding
of ecosystem dynamics would necessarily be structured by temporal and spatial scales of
observation. Efforts to link pattern to function and process in ecology are further
confounded by the intrinsic heterogeneity, variability and complexity of natural systems.
These complex adaptive systems produce emergent properties or self-organization as a
consequence of interactions between heterogeneous components at different spatio-
temporal scales (Ratze et al. 2007). Hierarchy Theory (Allen & Starr 1982) attempts to
decompose ecological complexity by conceptually organizing scales of observations
among various levels of resolution, as functional components of higher-level entities.
Related contemporary theories suggests that ecologic processes in marine systems
are often constrained by abiotic (i.e., physical) factors such as climatic, geologic, and
hydrodynamic processes which function across larger spatial-temporal scales (Karlson &
Cornell 1998, Hatcher et al. 1987, Glenn et al. 2000, Selig et al 2006). It follows that
9 In reference to Aristotle’s opus The Physics ~322 BC; from the translation by (Barnes 1984)
14
information output is sensitive to choices of appropriate scales of analysis10 and
representation which are ecologically relevant to the organism or process of interest.
Functionally speaking, factors such as movement of an organism, its reproduction rate, or
life span might determine time scales of interest for biological analysis. In terms of
ecological inquiry, species richness and diversity at the community or seascape level may
be driven by an assortment of biogeographical factors influencing habitat area,
disturbance levels, productivity, and exposure to anthropogenic effects (Cornell &
Karlson 2000, Edinger et al. 2000).
Scale dependence and emergent structures
Perceptions of variability in abundance, diversity, concentration, dispersion,
habitat complexity, and other ecological concepts can also be affected by artifacts of
sample scale or systematic representation rather than an inherent difference in the way
communities are organized (Gustafson 1998, Miller et al. 2004, Pech et al 2007,
Breckling et al 2006). In order to explain scale-dependent patterns observed in reef
communities we must be able to adequately measure patchy, stochastic environments and
account for emergent structures that appear increasingly homogenous over larger spatial
dimensions and longer time scales (Raffaelli 2006, Connell et al. 1997, Murdoch &
Aronson 1999, Hughes 1996, Bellwood & Hughes 2001, Edinger et al. 2001, Pandolfini
10 The concept of cartographic scale used in the field of geography is where a representative fraction relates distance over the earth’s surface to distance on a map. Often expressed in terms of a ratio, a large scale map (e.g., 1:250) shows higher spatial resolution (more detail over a smaller area) while a small scale map (e.g., 1:250,000) represents a greater area with less detail.
15
2002, Ruiz-Zarate & Arias-Gonzalez 2004, Aronson et al. 2005, Hughes & Connell 1999,
Dornelas et al. 2006).
Geospatial and geostatistical approaches
Partially as a way to overcome fractal-like scaling problems (Borrough 1981,
Halley et al. 2004), in the field of ecology the term “fine scale” generally refers de facto
to high precision (resolution) or a small study area while “broad scale” refers to coarser
resolution or a larger study area (range). When interpreting datasets from a Geospatial
perspective, three further qualifiers help to differentiate spatial-temporal attributes.
Grain or support refers to the finest level of spatial or temporal resolution of each
sampled unit available within a given data set. Extent refers to size of the study area
(domain) or the duration of the study. Spacing is the average distance (or time interval)
between samples. (Turner et al. 1989, Gustafson 1998, Skoien & Bloschl 2006). Three
geostatistical parameters used to quantify spatial distributions of variables of interest are
mean, spatial variance and integral scale. The mean represents average behavior within a
domain, spatial variance captures heterogeneity in space, and the integral scale is a
measure of the average distance over which a variable is correlated in space (Skoein &
Bloschl 2006).
16
Sampling biases
Because it is rarely feasible to exhaustively sample ecological phenomena with
infinite detail, most data collection schemes are discrete and periodic by nature and
therefore exhibit a characteristic sampling frequency in time or in space that may affect
data output. Time series analyses are commonly employed for investigating physical
oceanographic phenomena (e.g., currents, tides, El Niño cycles) and for studying a range
of ecological factors (e.g., community interactions, population dynamics). Using an
analogy from signal processing theory, a phenomenon known as aliasing11 can occur in
the frequency domain if signals are not sampled at a sufficient rate.12
Spatial heterogeneity can be thought of as varying degrees of complexity in the
manner in which finite elements are configured and distributed in time and space. Under-
sampling can cause information loss in a spatial domain, especially when there are
discontinuous distribution of elements or when the sample frequency is too low to
capture the fundamental signal pattern. For example, in an ecological field survey, if
samples are taken at large spatial intervals relative to the underlying variability there will
be an effective smoothing of small scale spatial variability (Prada et al. 2007).
Conversely, if the extent or area where samples are taken is small relative to the
underlying variability large scale variability will not be represented.
11 Artifacts produced when sampling intervals are too great to permit faithful replication of the original signal. Higher frequency components are under-sampled and appear shifted to lower frequencies when reconstructed. 12 The Nyquist principle demonstrates that a sample rate must be at least twice the maximum bandwidth of an analog signal in order to allow the signal to be represented with no information loss. No additional information or (signal fidelity) is gained by sampling faster than this rate. Nyquist, Harry (April 1924) “Certain factors affecting telegraph speed.” Bell System Technical Journal, p. 324.
17
Validating remotely sensed phenomena
Remote sensing techniques enable large areas of reef architecture with extents of
10’s to 100’s of kilometers be studied, but most satellite sensors are inadequate for
distinguishing marine habitats below hectare scales (Mumby et al. 1998) and methods to
accurately classify reef elements from these images are still largely confined to the
identification of general reef features in shallow tropical waters (Knight et al. 1997).
Discrepancies in sampling scale and resolution are hard to overcome when studying
habitats remotely and most approaches require a significant amount of in situ sampling to
validate the use of imagery and analytical methods. For example, an experiment to
conduct a large scale habitat assessment of reefs within the San Blas archipelago in
Caribbean Panamá used SCUBA diver in situ validation or “groundtruthing” of Landsat
images to test how remotely sensed geomorphologic gradients can explain larger regional
patterns of coral diversity (Andrefouet & Guzmán 2005).
When traditional classification schemes (e.g., SCUBA transects) and remote
sensing classifications are compared, the range of agreement between the two methods is
anywhere from 30% to 85% (Lesser 2004). Acoustical images generated from
hydrophones, sidescan sonar, and multibeam transducer arrays are useful for
characterizing geomorphology and mapping benthic habitats (Greene et al. 2007, Prada et
al. 2007) across various scales, however, because acoustical reflections mainly reveal
hard surfaces, in situ sampling is necessary to validate, interpret, and derive proxies for
biological systems.
18
Traditional subtidal ecology
Quantitative underwater sampling of marine biota is largely based on SCUBA
diver surveys which incorporate quadrat, point intercept, or various transect methods to
collect data on frequency, density, abundance, and diversity of underwater communities
(Obura 2001; Jameson et al. 2001, Linton & Warner 2003, Jimenez & Cortés 2003,
Lopez-Victoria & Zea 2005, Samways & Hatton 2001, Edinger et al. 1998). Accepted
in-situ methods for sampling benthic communities at the broadest spatial scales include
timed swims, Manta Tows, and video swaths, while point-intercept and line-intercept
transects, photographic quadrats, and randomized quadrat subsampling increase
information at smaller spatial scales (Kramer et al. 2005, Bass 1996, Page et al. 2001).
Although SCUBA divers can improvise and sample based on features of interest
and recognize when an area is being revisited, they are physically limited in the spatial
and temporal resolution at which they can adaptively sample. Traditional diving surveys
are often time intensive resulting in less replication and inherently affected by observer
bias in determining percent cover and abundance (Samways & Hatton 2001, Hill &
Wilkinson 2004, Lewis 2004). Drawbacks of quadrat surveys are that flat surfaces may
be over represented relative to complex surfaces while the disadvantage with point
intercept (PIT) methods are that rare and uncommon species are under sampled (Hill &
Wilkinson 2004, Lam et al. 2006). An advantage of video transects gathered by SCUBA
divers or Remotely Operated Vehicle (ROV) includes less field time incurred over wider
survey areas and a permanent record for future analysis (Lam et al. 2006). However
19
precision of these methods depend on the sampling frequency of the apparatus and the
ability to take photos or video from exactly the same spot.
Similarly, quantitative efforts to detect small changes in tropical reef chemistry
are challenging, difficult and costly. Satellite ocean color optical sensors such as
SeaWiFs13 have been used to study relationships between ocean chemistry,
phytoplankton blooms and productivity over large spatial domains in the open ocean
(Moore et al. 1999). However, in coastal areas, tidal and wind mixing of terriginous
nutrient inputs can significantly amplify biological and chemical variability over
gradients ranging from centimeter to kilometer spatial scales, and taking place on an
order of minutes to days. In-situ chemical sampling in shallow, coastal, aquatic
environments typically involves collection of discrete field samples which are then
transported to a laboratory for analysis (Grasshoff et al. 1999). This approach inherently
limits spatial resolution and temporal density when studying dynamic biogeochemical
processes.
A new approach to ecological field surveys
In-situ sensors are capable of making rapid, real time measurements with multi-
dimensional observational capabilities and avoid laboratory artifacts associated with
sample handling, storage, and possible sample degradation over time. Within the past
decade new ocean sensing applications for satellites, airborne systems, moorings, and
13 The Sea-viewing Wide Field of view Sensor deployed into low earth orbit in 1997.
20
ship based surveys as well as an assortment of new technologies like 14AUV’s, ROV’s,
15gliders, and towed platforms have enabled more comprehensive assessment and
comparison of biologic processes in the sea (Pizarro et al. 2006, Davis et al 2004, Camilli
2004).
Towed vehicles, to date, have offered nearly synoptic coverage of coastal areas in
three dimensions, however only at intermediate resolutions (Glenn et al., 2000, Chen &
Gardner 2004). Recent advances in optical imaging systems coupled with precision
navigation (Pizarro 2004, Sing et al. 2004, Bingham et al. 2006, Bingham & Seering
2006) have enabled successful AUV and ROV surveys, and now diver-based imaging
systems are beginning to facilitate rapid, high resolution optical surveys of the benthos
(Camilli et al. 2007) with fully automated data processing (Johnson-Roberson 2006,
Clement et al. 2006). When optical and chemical sensing technologies like these are
directed in concert toward ecologic applications, they can provide invaluable information
about the composition, morphology, distribution and habitat states across spatial scales
ranging from centimeters to hundreds of meters, and resolve small and rapid changes in
ambient water chemistry across basin scale seascapes.
14 Autonomous Underwater Vehicles 15 (e.g., Slocum glider and SeaBed and REMUS AUV’s)
21
Scientific Rationale
Ecologic questions
1. What types of shallow marine habitats and sessile communities exist in the Gulf of Chiriquí?
a. What are the fundamental morphologies of the shallow littoral seafloor (i.e. bathymetry and substrate) and the architectural structure of dominant reef systems in this gulf?
b. What types of organisms or assemblages inhabit these areas? c. How does species coverage and habitat extent of scleractinian coral vary
among geographically similar islands and how does this compare with coastal areas surrounding the gulf?
2. During the dry season, what are fundamental chemical, temperature, and salinity,
characteristics of shallow water masses (<30 meters deep) in the Gulf of Chiriquí? 3. What is the concentration and spatial distribution of Chromophoric Dissolved
Organic Matter (CDOM), chlorophyll-a, oxygen, carbon dioxide, nitrogen, and methane in Gulf of Chiriquí during the dry season?
a. How do concentrations of these components vary spatially when comparing coastal zones to offshore areas and islands?
4. Do indicators of productivity and respiration measured by chlorophyll-a, oxygen,
CDOM, and carbon dioxide in the water column vary between reef areas?
22
Hypotheses and predictions
Hypothesis 1: If there is considerable terrestrial freshwater input into the
oceans, higher levels of CDOM and methane coupled with lower
salinity will be observed along the coast when compared with
offshore islands.
Hypothesis 2: If the Gulf of Chiriquí possesses well mixed surface water
(0 to 5 meters deep), there should be similar levels of ambient
carbon dioxide, oxygen, and nitrogen within this euphotic
environment, when comparing among locations.
Hypothesis 3: Due to infrequent precipitation during the dry season,
surface water temperature and salinity measurements in the Gulf of
Chiriquí should be similar offshore and near the coastal mainland.
Hypothesis 4: Assuming the ability to detect unique assemblages, if coral
habitats are the same among islands in the Gulf, there should be no
significant difference between percent coverage of corals when
comparing sample populations from islands that are similar in size,
and relative distance from the mainland.
23
METHODS, EQUIPMENT, & EXPERIMENTAL DESIGN
It is of great use to the sailor, to know the length of his line, though he cannot with it fathom all the depths of the ocean
John Locke (1632–1704)
A Brief Overview of Mass Spectrometer Instruments and Theory
Mass spectrometers are used to measure isotopes which are atoms of the same
element with equal number of protons, but with different masses due to differing numbers
of neutrons. Mass spectrometry is a broad discipline, using various configurations of
electric (E fields) and magnetic (B fields) or Radio Frequency (RF) to isolate ions.
Despite these various approaches, most consist of four general components: the sample
inlet, an ion source, a mass analyzer, and a detector system. As a brief review of a typical
mass spectrometer process, 16 a gaseous sample passes through a membrane into an inlet
chamber where a superheated filament bombards the sample with a stream of electrons
and cleaves off one or more electrons from the sample to give a positive ion. These ions
are accelerated in a highly focused beam through a vacuum field of (≤ 10-6 Torr) to
eliminate friction and turbulence and ensure equivalent kinetic energy as the ions are then
deflected by a varying magnetic field which focuses the ion stream to a charged detector
plate. The amount of deflection, based on physical laws described by Maxwell’s
16 Based largely on (Armentrout 2003)
24
Equations,17 and the Lorentz Force,18 depends on the overall mass of the sample and the
number of positive charges on the ion. Lighter ions and ions with higher charges are
deflected more. The beam of ions colliding with the detector plate produces a current
which is proportional to the number of ions arriving and is subsequently amplified to
produce a signal that can be recorded. The mass to charge ratio (m/z) is a direct way of
measuring the mass of individual isotopes across a spectrum.
TETHYS-Towfish: A Towed, Integrated, Chemical Sensing Platform
A towed, integrated chemical sensing platform developed by R. Camilli at the
Woods Hole Oceanographic Institution (WHOI) enables high resolution in-situ
measurements of chemical species (i.e. O2, CO2, CH4, N2) chlorophyll, CDOM, salinity
and temperature. This towed platform is equipped with a TETHYS underwater mass
spectrometer, two Seapoint fluorometers (chromophoric dissolved organic matter and
chlorophyll), and a SeaBird 49 Conductivity, Temperature, Depth (CTD) sensor. The
TETHYS-TowFish platform (Fig. 3) with sensors included weighs approximately 40kg in
air and is 1.5 meters in length. It can be deployed and operated by a single person from a
small boat and can be towed at velocities up to 5 m/s.
17 Maxwell, James Clerk (1865) A Dynamical Theory of the Electromagnetic Field 18 The force exerted on a charged particle in an electromagnetic field
25
Figure 3: A towed, integrated chemical sensing platform: The prototype TETHYS-TowFish (length 1.5 m) shown with CTD, fluorometers, and TETHYS underwater mass spectrometer located in the larger pressure housing.
TETHYS: An in-situ, underwater, mass spectrometer
The TETHYS mass spectrometer (Fig. 4) is a 4th generation in-situ mass
spectrometer that is optimized for endurance, depth, detection of low molecular weight
chemicals, long-term accuracy, and overall reliability. TETHYS uses membrane inlet
technology, with electron impact ionization, and a linear cycloidal mass analyzer with a
Faraday cup detector. It is a compact, self-contained, and platform independent system
(Table 1) that uses low power and can be adapted for extended use and deployment on
moorings, cabled observatory nodes, autonomous underwater vehicles, remotely operated
vehicles, human occupied submersibles, and towed platforms. The underwater mass
spectrometer is sensitive to broad classes of dissolved chemicals. Its predecessor, the
GEMINI mass spectrometer (Camilli et al. 2004, Camilli & Sakellariou et al. 2007) was
deployed on a variety of platform configurations to investigate hydrothermal vents, sub-
26
aerial volcanoes, deep sea ocean floor gas hydrates, hydrocarbon seeps and to measure
in-situ chemical pathyways in the Giant Barrel Sponge Xestospongia muta.
Figure 4: TETHYS mass spectrometer with underwater pressure housing removed.
Photo-optical chlorophyll and CDOM fluorometers
Chlorophyll and CDOM absorb and re-emit energy at specific wavelengths in the
ultraviolet spectrum which enables precise quantification of these compounds by
measuring unique absorption and fluorescent properties. Two independent fluorometers
were used to measure simultaneous CDOM and chlorophyll-a concentrations in-situ. The
27
Seapoint Chlorophyll Fluorometer (SCF) uses modulated blue LED lamps and a blue
excitation filter to excite chlorophyll-a. The fluorescent light emitted by the chlorophyll-a
passes through a red emission filter and is detected by a silicon photodiode. The low level
signal is then processed using synchronous demodulation circuitry to generate an output
voltage proportional to chlorophyll-a concentration. The SCF used in this experiment
provides an excitation wavelength of 470 nm and an emission wavelength of 685 nm over
a sensing volume of 340 mm3 with minimum detectable concentrations of [0.02 µg/L].
The other sensor used, a Seapoint Ultraviolet Fluorometer (SUVF) gives
measurements of CDOM by using modulated ultraviolet LED lamps and an excitation
filter to excite CDOM present in water. The fluorescent light emitted by the CDOM
passes through a blue emission filter and is detected by a silicon photodiode. The signal is
then processed using the same synchronous demodulation circuitry to generate an output
voltage proportional to CDOM concentrations. The SUVF excitation wavelength is 370
nm and the emission wavelength is 440 nm over a sensing volume of 340 mm3 with a
minimum detectable concentrations of [0.1 µg/L] (quinine sulfate). A standard metric for
reporting CDOM fluorescence is expressed as quinine sulfate units19 (QSU). Optically,
the value of 1 QSU is equivalent to the fluorescence emission of [1 µg/L] quinine sulfate
solution integrated from 350 to 600 nm with an excitation wavelength of 337 nm (Chen
& Gardner 2004, Kelble et al 2005). Voltage output from the CDOM fluorometer was
converted into QSU concentrations based on the manufacturer’s derived standard
relationships of voltage output, gain, and signal sensitivity. Similarly, chlorophyll-a
19 Where 1 QSU = 1 μg quinine sulfate per liter = 1 part per billion (ppb)
28
measurements reported in [µg/L] were adjusted according to signal gain and instrument
sensitivity.
Table 1: Table of TETHYS mass spectrometer specifications.
TETHYS mass spectrometer specifications: Mass range 1-150 amu Mass resolution 0.01amu Power 15 Watts Maximum depth 5,000m Endurance ~1 year Response time 5 seconds Sensitivity (LOD) ~1 ppb Weight ~10kg Displacement <14 L Moving parts none
SCUBA-COP: The SCUBA-diver Operated Chemical-Optical Imaging Platform
The SCUBA diver operated Chemical-Optical imaging Platform (SCUBA COP)
is an integrated imaging system developed at the University of Sydney Australian Centre
for Field Robotics (ACFR) by Dr. Oscar Pizarro. SCUBA COP (Fig. 5) was designed to
spatially characterize and quantify complex underwater habitats benthic substrates,
geomorphology, and ultimately to help understand the variability of complex underwater
habitats. A commercially available underwater propulsion system (dive scooter) was
29
mounted on the SCUBA-COP platform to enable divers to dynamically control the sled
movement and sample larger areas at speeds of up to 1.5 m/s.
Stereo-optical imaging system and auxiliary sensors
This self-contained dive sled collects and stores 12-bit, 1.4 megapixel stereo pairs
using one color and one monochrome camera (Fig 6 & Table 2). Simultaneously, this
device is able to internally log vehicle attitude, depth, temperature, and oxygen
concentrations to an embedded PC-104 motherboard. Data is transmitted to the internal
computer and data logger from an integrated onboard sensor suite consisting of a 3DM-
GX1 Internal Motion Unit (IMU) for heading, pitch, and roll; an Aanderaa Optode to
measure oxygen and temperature, and a SeaBird pressure sensor for depth. An integrated
GPS unit and antennae triangulates and logs surface position before dive missions. Two
strobes, mounted 40 centimeters on either side of the binocular camera housing, were
synchronized to flash at 2Hz. The strobes minimize exposure time and the effects of
variable ambient lighting. Aperture, strobe illumination, and focus range were optimized
during field trials. An underwater checkerboard pattern was imaged before the start of
each dive in order to later rectify optical distortions20 created by imperfect lenses21 and
account for changes in the index of refraction.
20 Defocus, chromatic, and spherical optical aberrations which occur in underwater light environments. 21 These phenomena are caused by changes in the index of refraction as light travels through water, and then through air within the camera housings before it reaches the lenses of the cameras and light sensors.
30
Figure 5: The SCUBA diver operated Chemical-Optical imaging Platform (SCUBA-COP). Stereo cameras, batteries, and integrated electronics are contained in underwater pressure housings below the platform next to an oxygen optode and CTD. Stereo strobes are mounted to either side of the platform. The surface GPS antenna is located next to the propulsion device on the topside of the sled. The checkerboard pattern in front of the SCUBA COP was used underwater during field trials to calibrate optics.
31
Figure 6: The stereo camera imaging system with pressure housing removed showing digital cameras (1 monochrome and 1 color) and the integrated PC 104 computer, ethernet, Internal Motion Unit, and hard drive storage. Lithium ion battery power is contained in a separate pressure housing.
Table 2: SCUBA COP stereo imaging system specifications
SCUBA COP stereo camera specifications: Camera 1 Monochrome Camera 2 Color Maximum depth 1,000 m Image Resolution 1.4 Megapixel Sampling Frequency >1 Hz Digital Resolution 12 bit Computer PC 104 Internal Motion Unit 3DM-GX1 Memory Internal HD 20 gig
32
The nature of the imaging platform’s optical resolution and video-like sample rate
allows observation at multiple scales of interest. Point-based samples or swaths several
tens of meters long can be sampled with similar precision. Individual frames are
typically post processed to correct for known light and optical distortions and then
stitched together to create 50 meter long by 1.5 meter wide 2-D mosaics of each surveyed
reef section. Each 50 meter swath is composed of approximately 150 images on average
with significant serial image overlap that ensures high swath image density and allows
for maximum precision when aligning and joining pixel points during post processing.
High Definition (HD) Video Camera
A commercially available Sony digital High Definition video camera (Fig. 7)
model HDR-UX1 was used to capture video swaths to compare with the SCUBA COP
imagery. It records NTSC22 Video (1080i) format to DVD media and is housed in an
acrylic underwater housing (Table 3).
22 National TV Standards Committee using 1080 lines of vertical resolution interlaced (non-progressive scan) displayed at 29.97 frames per second.
33
Figure 7: Commercially available high definition digital video recorder and pressure housing.
Table 3: Sony high definition video recorder specifications
Sony High Definition Video specifications: Model Sony HDR-UX1 Sensor CMOS 2100K Optical Resolution <1 cm Maximum depth 50 m Video format AVCHD Sampling Resolution 12 Mbps Housing Iketlite Digital Memory Storage DVD
34
Experimental Design
For any thing X being considered in the current context, the assertion P(X) is likely to be useful for achieving goals like G, provided that we apply in conjunction with certain heuristically appropriate inference methods…
Marvin Minsky 1991
Assumptions
For benthic surveys of substrate and sessile organisms, it is assumed that the
REEF CHECK and Australian Institute for Marine Science (AIMS) protocols will
provide rigorous methods for quantitative comparison and statistical inferences of sample
populations. Furthermore, it is assumed that these benthic communities, due primarily to
their sessile nature, will not change substantially over the duration of the study. The
prototype imaging platform is presumed to have the ability to optically resolve benthic
details at least equivalent to a SCUBA diver conducting a traditional transect survey.
For chemical surveys, mass peaks from the mass spectrometer in combination
with chlorophyll-a and CDOM values, when combined with temperature and salinity
measurements, should be able to coarsely approximate nutrient dynamics and changes in
water masses over kilometer distances and smaller. Some of the following qualitative
guidelines will be used to direct quantitative analysis and interpretation.
Salinity and temperature related to depth will help to show movements and
mixing patterns within the surface water column. 15N isotope enrichment shown by low
14N:15N ratios might be indicative of non-upwelling waters such as riverine water or
35
surface ocean water interacting strongly with the atmosphere. High methane coupled
with low salinity will show areas of freshwater input to the sea. High carbon dioxide and
low oxygen should classify areas with high rates of respiration. Low oxygen and high
carbon dioxide levels will outline areas of high productivity. A combination of depleted
15N shown by high 14N: 15N ratios along with high concentrations of carbon dioxide,
methane, and CDOM, coupled with low oxygen levels, will be a fair proxy for
identifying areas experiencing eutrophication.
Field survey design
LandSat TM imagery and navigation charts23 for the Gulf of Chiriquí, geologic, 24
river, and population data25 were integrated in a GIS environment (ARC MAP
version.9.0). This compiled information was used to choose dive sites and guide transects
for chemical survey tows. Long chemical transects were conducted to capture coastal to
offshore concentration gradients in bio-active chemicals, temperature, and salinity. Dive
survey sites were chosen in order to compare coral communities between offshore islands
within the Gulf of Chiriquí. Navigational charts and mesoscale information from year
2000 LandSat satellite imagery aided in choosing island areas similar in size, bathymetry,
and distance from the mainland. Isla Managua, located within a coastal embayment
called Bahia Honda, was chosen as a natural control to compare with the three offshore
23 Central America: South Coast of Panamá - Isla de Coiba from a survey by the U.S.S. Hannibal in 1934, (USA 1994). 24 Data source: Department of Mineral Resources, Panamá. Direccion General de Recursos Minerales (DGRM 1991).
36
islands. Isla Canales de Tierra was chosen to represent a nearshore island because of its
location less than 1 km from the coastal mainland.
Integrated Field Survey Method
Measuring in-situ ocean chemical gradients with the TETHYS-Towfish
While underway, long chemical transects (Fig. 8) within the Gulf of Chiriquí were
conducted to characterize the natural variability of biologically active elements in the
water, investigate photosynthetic and respiratory dynamics, deep water upwellings,
riverine inputs, and to identify possible anthropogenic contaminants.
For this project, the mass spectrometer was configured to monitor selected ion
peaks corresponding to methane, nitrogen isotopes (14N-14N and 14N-15N), oxygen,
hydrogen sulfide, argon, and carbon dioxide. Additionally, the TETHYS unit conducted
full spectral scans (1-200 AMU) at 10 minute intervals to enable identification of
anthropogenic pollution (e.g., hydrocarbons, industrial or toxic compounds).
Fluorometer and CTD data were sampled asynchronously at 1Hz. Bathymetry
was coarsely estimated with a hull mounted, single beam acoustic depth profiler with data
streams integrated into a Garmin GPS chartplotting device and laptop computers. Geo-
referencing of all towfish chemical data was accomplished during this survey effort using
25National Census of Panama conducted in 2000. Republica de Panamá (2000) Censos nacionales de poblacion y vivienda, 14 de mayo de 2000.
37
a transom mounted Furuno GPS Navigator recording time (GMT) and position fixes at
1Hz. Latitute and longitude coordinates were synchronized and merged with TETHYS,
CTD, and fluorometer data based on internally logged towfish time stamps. Towcable
horizontal and vertical position offset was accounted for by calculating the cable layback
length (12 meters), vessel velocity (speed over ground) and the depth recorded by the
CTD at 1 Hz.
Average tow velocity was 2.5 m/s with each transect lasting up to 6 hours. The
towfish is negatively buoyant in sea water but was designed to assume a dynamic
stability when underway due to its vertical and horizontal control surfaces (fins). An
oscillating depth or “Tow-Yo” approach was conducted by periodically slowing the boat
velocity so that the towfish would perform a vertical cast, diving to a maximum depth of
12 meters and then climbing with increasing boat velocity until returning to its near
surface depth (1 meter below surface). This technique provided a vertical profile of the
water column at regular time intervals and was also employed when substantial change
was detected in the surface waters. The geo-referenced datasets collected during coastal
and offshore transects (Fig. 8) were used to inform and select smaller scale optical reef
surveys with the SCUBA COP.
38
Figure 8: Survey map (scale 1:800,000) showing island and coastal locations, towed chemical transects, dive sites, and isobaths. Towed chemical transects are represented by a solid red line.
39
High precision reef imaging with the SCUBA COP dive sled
After arriving in an area of interest (determined in part by examining navigational
charts and vessel soundings), a snorkel reconnaissance was used to confirm the presence
of coral communities before dives. A stratified approach was used to spatially randomize
transects within dive sites based on random compass bearings and distances (10-100
meters) from the anchored dive vessel. Surface position was gathered using a handheld
Garmin 76Cx model GPS unit. The stored GPS waypoints were later cross-referenced
with GPS surface position data collected by SCUBA COP before and after immersions.
Two imaging devices were used to survey seven locations in the Gulf of Chiriquí,
using three 50 m tape-based linear transects per site, oriented perpendicular to shore to
standardize swath coverage. Each transect was spaced a minimum of 20 meters apart.
Serial transects were captured at 2 meter altitudes by one diver equipped with a Sony
HDR-UX1 digital high definition (HD) video camera followed by a second diver
operating the SCUBA COP stereo imaging system (Fig. 9) which also logged depth and
motion information.
40
Figure 9: Diver imaging underwater coral habitats with SCUBA COP. Strobes lights, mounted on both sides, are synchronized at 2 Hz to uniformly illuminate areas independent of ambient lighting. An internal motion unit senses vehicle attitude (pitch, roll, heading) and logs relative position during imaging. A propulsion devise helps the diver maintain a constant velocity while photographing. Stereo images are captured by digital cameras synchronized with the strobes and a computer located in the middle pressure housing.
41
Simultaneous HD video and traditional SCUBA surveys
The first diver (capturing images with the HD video camera) carried a 2 meter
plumb line with attached lead weight that served as an altitude reference for the camera
and other divers swimming over the transect tape. At the beginning and end of each
transect, the diver operating the HD video camera recorded a 360º panorama to capture
contextual information. After the diver operating SCUBA COP had imaged the transect
length, the diver continued to image the surrounding area in a methodical manner by
swimming parallel to the transect tape in multiple passes spaced 2 meters apart to create a
dense overlapping grid26. Areas imaged directly over the underwater transect tape with
SCUBA COP were used for comparison with High Definition NTSC Video (1080i), and
Point Intercept Transects (PIT) methods adapted from REEF CHECK v. 2004.
REEF CHECK is the United Nation’s official community-based coral reef
monitoring program which uses a general set of biological indicators as a proxy in
determining global reef ecosystem health and types of human impacts to these areas
(Hodgson 2000). Divers using the PIT method identified 1 of 10 benthic categories
(Table 8 appendix) directly below the tape every 0.5 m along each of the three replicate
50 meter swaths and recorded data on an underwater dive slate (Fig. 10).
26 This methodical survey method is popularly referred to as “mowing the lawn”
42
Figure 10: Diver surveying coral habitat with traditional Point Intercept Transect (PIT) method. Benthic categories are recorded on a dive slate every 0.5 meters along a 50 meter transect tape to provide quantitative information on spatial coverage, diversity, health, and substrate morphology.
Analytical Methods
Satellite data and GIS integration
With increasing validation and interpretation, satellite remote sensing is becoming
an increasingly reliable way to quantify CDOM and chlorophyll concentrations over
large areas (Hoge 2002, Arnone et al. 2003). SeaWiFs ocean color time series satellite
data was obtained, courtesy of the National Aeronautics and Space Administration
43
(NASA) GIOVANNI27 program. Raw ASCII data provided by the Ocean Biology
Processing Group (OBPG) was used as “groundtruth” to compare with data from in situ
measurements obtained by towfish survey during the same time period (Feb 10 - Feb 25,
2007). The SeaWiFs imagery represents average chlorophyll-a concentrations over a
spatial extent where 1 pixel = 9 km2.
Landsat Thematic Mapper ™ imagery from the year 2000 was color processed
and joined with ERDAS IMAGINE (v 9.1) software and used as a base image for
planning chemical and diver transects within the Gulf of Chiriquí. Finally, coastal rivers
and population centers were digitized and placed into a Geographical Information System
(GIS ArcMap v. 9.0) and merged with digitized navigation charts for bathymetric and
Global Positioning Satellite (GPS) location verification.
Chemical transect data analysis
Chemical data points were integrated into a GIS environment to aid spatial
analysis. Raw machine data were converted into data matrices for each parameter and
concentrations were plotted using Excel and Matlab v. 9.0 software. Colormaps were
created to show concentration gradients, then georectified and overlain on Landsat
Thematic Mapper (Landsat TM) year 2000 RGB satellite imagery. The TETHYS data is
presented as ratios, a standard method used in mass spectrometry that reduces data
artifacts associated with temperature, pressure, and instrument performance (deHoffman
2002, Smith 2004).
27 Goddard Earth Sciences Data and Information Services Center Interactive Online Visualization ANd
44
Correlation coefficients (Eq. 1) were calculated to relate observations of temperature and salinity to other biologic parameters including CDOM, methane, carbon dioxide, and chlorophyll of offshore transects.
Equation 1: Equation to calculate correlation coefficients were a value of -1 is a perfect negative correlation, a value of 1 is a perfect positive correlation, and a value of 0 is lack of correlation.
Corresponding scatterplots of the strongest correlations were made to compare
data relationships between parameters and search for outliers in the data sets. Standard
deviations (Eq. 2) were reported for all means in salinity, temperature, CDOM and
chlorophyll measurements.
Equation 2: Equation used to calculate standard deviation (the square root of variance) where (x) is the sample mean average summed (Σ) across all (N) number of samples to give a confidence interval of the first standard deviation ≈ 0.683.
aNalysis Infrastructure (GIOVANNI).
45
High definition video and REEF CHECK data analysis
In order to interpret quantitative estimates of substrate and coral cover from the
video swaths, a standardized, international coral reef monitoring protocol developed by
the Australian Institute of Marine Science (AIMS) was used to systematically analyze the
video transects (Page et al 2001). Five fixed and non-overlapping video monitor points
were used to sample a fractional time interval based on the total elapsed video time code.
Sections were calculated and segmented so that along each 50 meter transect, 500 data
points were uniformly identified for the entire video swath. Each data point was then
assigned to (1 of 10) benthic categories used for the PIT method.
Data collected with underwater slates were transcribed onto spreadsheets in order
to calculate percent cover and standard deviation among 3 transects at each of the seven
dive sites within the gulf. Variability among transects was tested with a univariate one-
way Analysis of Variance ANOVA to statistically evaluate significant differences in
coral cover within the Gulf of Chiriquí. Histograms and a Cochran’s C-test were used to
test for normality of data distributions and homogeneity of variances. Percent cover data
were arcsine square-root transformed, a smoothing method commonly used for
proportions (Zar 1996) that allows data to conform to assumptions of normality and
homoscedasticity necessary for general linear regression models.
46
SCUBA COP data analysis
Accurate interpretation of satellite, photographic or video imagery typically
requires human experts to classify a subset of points contained within an image.
Considerable effort is involved in analyzing dense data sets which forces spatial
undersampling and inherently results in information loss. Alternatively, automated
segmentation and classification of coral is possible due to the fact that morphologically
different coral will possess uniquely shaped surfaces. Binocular vision permits the use of
texture-based decision algorithms and 3 dimensional stereo as methods for coral
classification (Johnson-Roberson et al. 2006).
A simpler 2-D version of this approach was used to automatically discriminate
and classify SCUBA-COP imagery and quantify benthic coverage. The technique
utilizes an array of digital filters which describe a visual texture when tuned at different
scales and orientations (Varma & Zisserman 2002). Texture output from these filters
combined with color information become feature vectors associated with each pixel in an
image or mosaic.
These feature vectors are clustered using the Expectation Maximization (EM)
algorithm (Dempster et al. 1977). The EM algorithm probabilistically determines unique
classes and which pixels belong to each of these classes. This application is used for
computational pattern recognition (Delleart 2002, Bilmes 1998, Belongie et al. 1998)
because the likelihood function can be simplified by assuming the existence of values for
latent or hidden parameters. An iterative optimization method is used to estimate these
parameters from some set of measured data input (in this case pixel texture and color).
47
The current implementation allows the user to prescribe the number of classes while the
EM algorithm derives the characteristics of each class.
As a further discrimination tool, coral fluorescence was tested in small field
experiments where SCUBA COP strobe lights were outfitted with one blue and one
yellow light filter during some sampling efforts to observe if any corals fluoresced. One
of the corals commonly found in the Gulf of Chiriquí, Pavona varians (often found in
rocky crevices and is thought to be able to readily adapt to low light situations) has been
observed to fluoresce in aquaria (Riddle 2007). Developing a method to digitally filter
this subset of color information in Red Green Blue (RGB) dimensional space is
underway.
48
RESULTS
Comparing Offshore and Coastal Chemical Transects
The towfish platform transects covered approximately 300 km during 5 days of
towed survey. During this time more than 35,000 discrete chemical sample
measurements were made with the TETHYS mass spectrometer, CTD, chlorophyll-and
CDOM fluorometers. These data (mass spectrometer, CTD, and fluorometer) all
indicated significant chemical gradients occurring both vertically and horizontally within
water masses 0.25 to 15 meters deep.
Temperature and salinity
Temperature and salinity measurements are commonly used by marine scientists
to characterize water masses (Knauss 2005, Kennish 2001). From February 14th to
February 21st at an average tow depth of 2 meters, average water temperature was 28.14
°C and average salinity was [31.95 ‰] across the Gulf of Chiriquí and the Gulf of
Montijo (N=35,953 samples). Salinity and temperature measurements for all coastal
areas surveyed were [31.85 ‰] and 28.7 °C respectively, while offshore regions
measured [31.24 ‰] and 29.9°C. Contrary to expectations, coastal transects over a
shallow shelf less than 30 meters deep, adjacent to the Gulf of Montijo, exhibited on
average, lower temperature (Fig. 11) and higher salinity (Fig. 12) than offshore transects
which lie over deeper, open water and are further away from freshwater input.
49
Figure 11: In-situ temperature data overlain onto Landsat TM satellite imagery. The color gradient indicates water temperature (°C) with cooler regions represented in blue and warmer regions in red. Observe the cooler temperatures along the coastal transect.
Salinity measurements [31.95 ‰] were near the lower range of previous studies
that reported between [30 ‰] and [35 ‰] during the dry season. 28
28 Source: (Glynn & Maté 1997) The authors also report average salinity for both the Gulf of Panamá and the Gulf of Chiriquí declining to between [24 ‰] and [30 ‰] during the rainy season.
50
Figure 12: Salinity data overlain onto Landsat satellite imagery. The color gradient indicates salinity concentrations [‰] in parts per thousand (ppt) also reported as Practical Salinity Units (PSU). Lower salinity is represented in blue and higher salinity in red. Note the higher salinity near the coast compared to offshore.
Strong, localized, salinity and temperature gradients were noticed along coastal
areas between Bahia Honda and Santa Catalina, and along the eastern shore of Canales de
Afuera Island (Fig. 11). The largest salinity outlier along the coast was near the small
artisinal fishing port of Santa Catalina. Here average salinity was [26.76‰] +/-8.4 SD
significantly lower than all other coastal areas surveyed [32 ‰] +/- 0.13 SD. Although
Bahia Honda did not vary much from the coastal averages in terms of salinity, it did have
51
higher variability [31.9 ‰] +/- 3.9 SD. (Table 11; Appendix). To investigate
temperature and salinity effects on other parameters, a correlation matrix was assembled.
The strongest correlations for the offshore chemical transects and among offshore islands
was between salinity-methane and salinity-carbon dioxide (Table 4).
Table 4: Table showing correlations of salinity and temperature to other parameters
measured during offshore and inter- island chemical transects.
Correlation Coefficients for Offshore Transects CDOM CH4 CO2 O2 CHLa
Salinity 0.245 -0.368 -0.451 -0.172 0.061 Temperature -0.298 0.187 0.250 0.231 -0.130
When compared to other inter island regions in the gulf of Chiriquí, the greatest
chemical heterogeneity in water masses were between Canales de Afuera Island and
Canales de Tierra Island. It may be that this inter-island area (about 5 km from shore)
lies at the mixing boundary of two large water masses, where warmer water of the Gulf
of Chiriquí meets cooler mixed water coming from the Gulf of Montijo.
52
Panamá Liquid Jungle Laboratory Underwater Tropical Observatory (PLUTO)
Time series data publicly available from The Panamá Liquid Jungle Laboratory
Underwater Tropical Observatory (PLUTO) located just off of Canales de Tierra Island
(7° 40’ 14.7” N and 81° 39’ 28.0” W) concordantly show marked seasonal changes of
temperature and salinity (Fig. 13). PLUTO29 is a cabled sensor platform tethered at 18
meters depth and measures real time parameters of salinity, temperature, pressure, water
current speed and direction, chlorophyll, turbidity, oxygen, pH, and down-welling light at
two depths. PLUTO time series data for year 2006 (Fig 13) shows that between the
months of April and May, large and frequent swings in temperature from 16° C to 28°C,
occur with similarly large fluctuations of salinity ranging from 27 to 31 Practical Salinity
Units (PSU).
29 PLUTO was developed by WHOI scientist Scott Gallager, and engineers Steve Lerner, and Andy Girard and deployed at the Liquid Jungle Laboratory, Panamá in 2006.
53
Figure 13: Cumulative year 2006 plots generated from time series data provided by the Panamá Liquid Jungle Laboratory Underwater Tropical Observatory (PLUTO). Large temperature-salinity fluctuations occur from April to May with a steady decline in pH from July into December. Photosynthetically available radiation (PAR) decreases between August and October, during the height of the rainy season.
54
Figure 14: PLUTO data from January through April 2007. Large temperature and salinity fluctuations begin in February and extend through mid March over nearly 4 meter tidal amplitudes.
Similarly, a higher resolution plot of PLUTO February 2007 dataset help to
corroborate the magnitude of variation in surface temperatures and salinity measured
with the TETHYS-Towfish (Fig. 14). During the month of February and into March
55
temperatures oscillate dramatically between 16°C to 29°C with corresponding salinity
ranges from 26 PSU to 33 PSU. When these events are analyzed over 24 hour periods,
there are high frequency oscillations occurring as fast as every 5 to 10 minutes. The
PLUTO data set for the month of February 2007 also shows high variability in
chlorophyll concentrations which seem to be associated in part with temperature
fluctuations occurring over large, tidal oscillations of up to 4 meters. Both the PLUTO
and TETHYS-Towfish data sets coincide with known seasonal upwelling events that
occur in the Gulf of Panamá from December to April. These periodic temperature
fluctuations might be explained if currents are entraining cold water masses generated by
upwelling approximately 150 km to the southeast in the Gulf of Panamá.
Oxygen
Oxygen levels were slightly positively correlated with temperature during
offshore transects (Fig. 15). Low levels of oxygen were noticed between Canales de
Afuera Island and Canales de Tierra. In the same way, the Secas Island to Boca Chica
transects exhibited lower oxygen. Comparatively high levels were observed near Uvas
Island and periodically again northwest of Coiba Island (Fig. 16).
56
Oxygen & Temperature (Depth 0-5 meters)Offshore Transects in the Gulf of Chiriqui,
Scatterplot: N=842 datapoints
6
6.2
6.4
6.6
6.8
7
7.2
7.4
7.6
7.8
8
28 28.5 29 29.5 30 30.5 31
Temperature (Celcius)
O2/
Ar (
m/z
32)
/(m/z
40)
O2/ArLinear (O2/Ar)
Figure 15: A scatterplot of (oxygen/argon) mass spectrometer measurements with temperature measurements from the towed CTD. The linear trend represents a positive correlation of 0.231.
Many estimates of net community production are based on changes in oxygen
concentration in the mixed layer with implications to the euphotic zone defined as water
above the 1% ambient light level (Falkowski et al. 2003). Argon is used as a conservative
tracer because it is an inert (non reactive) element that does not directly contribute to life
processes. Coupling the two measurements provides a baseline to measure changes in
oxygen which is vital to most life processes in the euphotic zone. Dissolved
oxygen/argon (O2/Ar) ratios are indicative of net community production (NCP) in mixed
oceanic layers because although oxygen and argon share similar physical solubility
57
properties with respect to temperature (Emerson et al. 1999), only oxygen is dynamically
produced and consumed through the processes of photosynthesis and respiration (Kaiser
et al. 2005). At small spatial scales, interstitial water chemistry of coral reefs can deviate
from surface seawater where oxygen is depleted while dissolved inorganic carbon, H +,
inorganic nutrients, sulfide, dissolved calcium and methane concentrations are generally
elevated (Tribble et al. 1990).
Figure 16: Oxygen measurements overlain onto Landsat imagery. Low levels occur between Canales de Afuera Island and Canales de Tierra. Similarly Secas Island to Boca Chica transects exhibit lower oxygen (top left corner). Comparatively high levels were observed near Uvas Island and periodically northwest of Coiba.
58
Over some transects of this study, dissolved oxygen saturation, measured as a
ratio of oxygen ion peak intensity to argon ion peak intensity, exhibited more variation as
a function of horizontal distance than with depth. An example of the horizontal
variability in oxygen saturation recorded during a February 14th 2007 transect from Boca
Chica to the Secas Islands is shown in (Fig. 17). This island group is located on the edge
of a shallow continental shelf ranging from 30 to 50 meters in depth (Fig. 2).
To add context to this observation, an East to West current with a velocity of 0.5
to 1 m/s was encountered during this transect, suggesting that larger circulation patterns
may play a significant role in the chemical profile.
59
Figure 17: This graph shows a vertical profile from a transect from Boca Chica to the Secas island group. The dips in the tracklog correspond to the TETHYS-Towfish slowing and diving and then climbing toward the surface again as the boat accelerates. Units are dimensionless, red indicates higher dissolved oxygen levels, blue indicates lower levels. Longitude is plotted on the (x) axis, Latitude is plotted on the (y) axis and depth in meters is plotted on the (z) axis. The horizontal variability in oxygen suggests two different water masses interacting along a vertical front in the euphotic zone.
Dissolved oxygen Boca Chica to Isla Seca Transect
60
Carbon dioxide
Higher carbon dioxide levels relative to other areas (Fig. 18) were noticed
especially near Uvas Island, in the waters near the Secas Islands and going north towards
Boca Chica and the Chiriquí mainland (Appendix: Tables 10 & 11). When salinity is
compared with carbon dioxide levels, carbon dioxide levels increase as salinity decreases
(Fig. 19). This suggests that freshwater sources acting over smaller areas in this region
could be more important in determining carbon dioxide levels than atmospheric (open
ocean water) sources. Carbon dioxide levels also give an indication of net respiration in
the waters, but have other implications for the hard corals in this region.
61
Figure 18: TETHYS mass spectrometer measurements (dimensionless) of carbon dioxide gradients across towed transects Feb. 2007. Note the lower levels northwest of the Secas Islands, and the high degree of variability between Uvas Island and Coiba Island. Low levels were noticed between Canales de Afuera and Canales de Tierra Island.
.
62
Figure 19: Scatterplot showing carbon dioxide and salinity relationship from offshore towed chemical transects. A correlation value of ( -0.451) was calculated for 842 data points suggesting carbon dioxide may be governed in part by salinity in these waters.
Carbon dioxide, carbonate systems, and biocalcification of coral reefs
Dissolved inorganic carbon in seawater occurs in three forms: carbon dioxide
(CO2 ) aqueous/gas, bicarbonate ion (HCO3-), and carbonate ion ( CO32-). Calcification,
in a reef context, is the process by which corals utilize Ca2+ (calcium) and CO32-
(carbonate) dissolved in seawater to secrete the calcium carbonate mineral known as
aragonite. Corals precipitate aragonitic calcium carbonate (CaCO3) to produce
supportive exoskeletons.
CO2/Ar & Salinity (Depth 0-5 meters)Offshore Transects in the Gulf of Chiriqui,
Scatterplot: N=842 datapoints
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
30.8 31 31.2 31.4 31.6 31.8 32 32.2 32.4
Salinity [ppt]
CO
2/A
r (m
/z 4
4)/ (
m/z
40)
CO2ArLinear (CO2Ar)
63
The carbonate system in surface waters is governed by carbon dioxide solubility,
carbon dioxide uptake in photosynthesis, and carbonate uptake as calcite and aragonite.
As (CO2) dissolves in seawater it dissociates into bicarbonate (HCO3-) and carbonate
( CO32-) respectively. The stoichiometric equation (CO2 + H2O + CaCO3 ↔ 2 HCO3- +
Ca2+ ) describes the way the addition of CO2 increases CaCO3 dissolution into and
removal of CO2 enhances precipitation (Kleypas et al. 1999). The overall acidity of water
is an important factor in determining how CO2 is used in reef systems. As a reminder,
the pH scale is a logarithmic scale that ranges between 0 to 14 with 7 being neutral,
greater than 7 alkaline, and less than 7 acidic. In this context, total alkalinity (AT ) is a
measure of the ability of a solution to neutralize acids to an equivalence point of
carbonate or bicarbonate. In normal seawater pH is alkaline, ranging from 8.0 to 8.2.
Under these conditions [HCO3-] is approximately 10 times that of [CO32-] (Kleypas et al.
1999).
Biotic feedback process can also affect rates of calcification and how corals
calcify in various CO2 environments (Chisholm 2000, Kawahata et al. 1997, Marubini &
Atkinson 1999). Calcification may even enhance photosynthesis by providing protons
for conversion of bicarbonate to aqueous carbon dioxide (McConnaughey & Whelan
1997). As a very simplified rule, increasing CO2 (i.e. via respiration) implies increasing
acidity while photosynthesis in the water column decreases acidity by using available
CO2. However, larger scale biogeochemical studies have identified factors such as the
change in solubility of CO2 in ocean water due to an increase of anthropogenic and
64
atmospheric CO2 input to the oceans (Druffel 1997) that may have more profound global
effects on corals by decreasing saturation rates.
Equation 3: Calcium carbonate saturation state Ω
spKCOCa'
]][[ 23
2 −+
=Ω
The calcium carbonate saturation state (Ω) describes the tendency of a solution to
support precipitation or dissolution of calcium carbonate. This is described by (Eq. 3),
where K’sp is the solubility product of calcite or aragonite (Kleypas et al. 1999). The
calcium carbonate saturation state (Ω) is mostly determined by carbonate (CO32-) because
calcium (Ca2+) is conservative in seawater. The carbonate chemistry of tropical surface
water is generally considered a small factor influencing calcium-carbonate precipitation
by corals because surface seawater is supersaturated (Ω>1) with respect to aragonite
(Kleypas et al.1997, Gattuso et al. 1998). In summary, carbon dioxide affects the way
scleractinian corals build and maintain reefs by affecting the ambient acidity of coastal
water. The aragonite saturation state decreases as a function of increasing acidity. Reef
building requires a net positive balance of calcium carbonate production and greater
saturation states (i.e. less acidic) favor more precipitation of calcium carbonate.
PLUTO 2006 data shows pH ranging near 8.0 and falling as low as 7.4 between
April and May with pH trends generally declining from July to December (Fig. 13). Low
pH levels near 7.0 also occurred during this study period (Fig. 14). In the early seventies,
65
reported horizontal reef growth of Pocillopora sp. was 21.4 % per year on Secas Island
(Glynn 1973). The effect of high CO2 levels increasing ambient acidity might be of
importance for Pacific Panamánian reefs because (Cortés 1997) shows that Eastern
Pacific reefs generally have low cementation rates. Future studies should experimentally
test the Uvas, Secas, and Canales de Tierra islands to determine if coral skeletogenesis is
being affected by periodically high levels of carbon dioxide in the surrounding waters.
66
Chlorophyll-a
The Gulf of Chiriquí generally had higher chlorophyll levels30 than areas surveyed in the Gulf of Montijo over the study period (Fig. 20).
Figure 20: Concentrations of chlorophyll-a [µg/L] across all towed transects. Colorbar represents lower levels of chlorophyll in blue and higher levels in red. Chlorophyll levels are generally elevated near coastal zones, and especially high towards the mainland areas of Boca Chica which is a mangrove estuary.
In this study, all chlorophyll data was pooled and binned into 1 meter depth
increments to test if there were vertical distribution patterns occurring within the
30 As a larger time-ordered comparison, (Glynn and Maté 1997) graphically show maximum yearly average chlorophyll concentrations for the gulf peaking consistently in February through March over three years, starting with a maximum value near [5 mg/m3] in 1985 and decreasing monotonically to just above [1 mg/m3] in 1988.
67
watercolumn (Fig. 21). The most noticeable difference was the abrupt decline in
chlorophyll concentration below 13 meters. Vertically this contrasts the majority of the
water above which indicates rather uniform distributions of chlorophyll concentrations.
Figure 21: Average chlorophyll-a values [µg/L]binned by one meter depth across all TETHYS - TowFish surveys. Bars represent mean concentration at each depth, lines represent the first standard deviation of means.
Average chlorophyll-a for offshore transects [0.24 µg/L] +/- SD 0.02 were higher
than coastal transects [0.16 μg /L] +/- SD 0.06. The offshore leg from Isla Seca area to
Boca Chica contained the highest average chlorophyll concentrations [0.31 μg /L] +/- SD
0.05. The eastern shore of Coiba (Ensenada Arena through Punta Damas) ranged in
Average Chlorophyll a concentrations Gulf of Chiriqui (N=35,395)
2-3m
7-8m8-9m
10-11m11-12m12-13m
0-1m1-2m
3-4m4-5m5-6m6-7m
9-10m
13-14m14-15m
0.000 0.050 0.100 0.150 0.200 0.250 0.300 0.350
Dep
th (0
-15m
) int
erva
ls =
1m
chl a [ug/L] and Standard Deviation
68
values near [0.025 μg /L] (Table 10 appendix) However, traveling north between Coiba
and Canales de Afuera low values were observed [0.18 μg /L] average +/- SD 0.03.
Low values were recorded all along the coast up until Santa Catalina [0.20 μg /L]
+/- SD 0.08 where values began increasing again. Northwest along the coast, past Bahia
Honda, going from Canales de Tierra north to Ensenada Pixvae (the next largest bay)
were the lowest values recorded throughout the survey [0.05 μg /L] +/- SD 0.05.
69
Chromophoric Dissolved Organic Matter (CDOM)
In the coastal ocean, dissolved organic matter (DOM), coming from river runoff
and terrestrial water tables, transports terriginous carbon to the sea and becomes an
integral part of many biogeochemical processes (Hitchock et al. 2004). CDOM from
terrestrial sources is primarily derived from water-soluble humic substances (like tannins)
which color the water yellow to brown hues and absorb the majority of light energy near
the blue (400 nm) wavelengths. However, CDOM is also produced in-situ within the
ocean through the release of organic molecules from organisms primarily via pathways of
excretion, grazing, and during bacterial and viral lysis (Coble et al., 2004).When light
energy is absorbed by CDOM, a series of photochemical reactions produce hydrogen
peroxide (H2O2), hydroxyl (-OH), small organic compounds, and trace gases such as
CO2, CO, and COS (Blough & Del Vecchio 2002). Open ocean surface waters are
eventually depleted of CDOM because photochemical processes (bleaching) decrease
absorption and fluorescence properties, which degrade over slower timescales (tens of
days to months) in coastal waters (Blough & Del Vecchio, 2002).
CDOM levels across the Gulf appeared to increase with increasing depth (Fig.
22). A colormap of CDOM concentrations over the entire survey is shown in (Fig 23).
Along the coast CDOM concentrations averaged 5.5 QSU, and comparatively 2.87 QSU
offshore (> 1km past Canales de Tierra). Around Canales de Afuera island showed levels
spiking to 4.0 QSU which was surprisingly higher than the area surveyed on Coiba’s
eastern shore (2.1 QSU) (near the river outlets of Rio Catival and the Rio San Juan in
70
Bahia Damas). Besides exhibiting higher average CDOM concentrations compared to
offshore, at times, coastal areas showed orders of magnitude variability between sites.
Average CDOM concentrations Gulf of Chiriqui (N=35,395)
2-3m
7-8m8-9m
10-11m11-12m12-13m
0-1m1-2m
3-4m4-5m5-6m6-7m
9-10m
13-14m14-15m
0 2 4 6 8 10 12 14 16 18
Dep
th (0
-15m
) int
erva
ls =
1m
Colored Dissolved Organic Matter [QSU] and Standard Deviation
Figure 22: Mean CDOM concentrations [QSU] binned by 1 meter depths across all towed TETHYS-Towfish transects. Bars represent mean CDOM concentrations and lines extending from the bar graph indicate the first standard deviation. CDOM concentrations appear to increase with depth in the euphotic zone (0-13 meters) and drastically decrease to near zero from 13 meters to 15 meters depth.
71
Figure 23: CDOM concentrations [QSU] of all TowSled-TETHYS chemical transects overlain on Landsat satellite image. Colorbar indicates higher concentrations in red and lower concentrations in blue. Note the high levels of CDOM in the coastal embayments.
Significant fluxes of riverine dissolved organic matter, cause CDOM to decrease
linearly with increasing salinity (deSouza-Sierra et al.,1997, Chen & Gardner 2004). A
positive relationship where CDOM increases as salinity increases can happen when there
is a subsurface source of CDOM or when surface concentrations are low because of
sparse freshwater input or extreme bleaching of CDOM by sunlight (Coble et al 2004).
During the month of January through February 2007, there was zero precipitation and
72
limited cloud cover, thus bleaching of CDOM in the upper surface waters (0-1m) might
contribute to relative enrichment.
According to a pooled analysis of offshore CDOM data points in this study,
subsurface biological production of CDOM positively correlates with salinity (Table 4).
CDOM is negatively correlated with temperature in offshore transects (Fig. 24) and
together these both suggest that offshore CDOM, if it is not well mixed and coastally
generated, might be produced in-situ or linked to waters coming from a deeper, denser
thermocline.
CDOM & Temperature (Depth 0-5 meters)Offshore Transects in the Gulf of Chiriqui,
Scatterplot: N=842 datapoints
0
0.2
0.4
0.6
0.8
1
1.2
1.4
28 28.5 29 29.5 30 30.5 31
Temperature (Celcius)]
CD
OM
[QSU
]
CDOMLinear (CDOM)
Figure 24: CDOM and temperature scatterplot from offshore towed transects. Temperature °C is plotted on the (x) axis and CDOM concentration [QSU] is plotted on the (y) axis. The linear interpolation represents a negative correlation of -0.298 between the two parameters.
73
CDOM & Salinity (Depth 0-5 meters)Offshore Transects in the Gulf of Chiriqui,
Scatterplot: N=842 datapoints
0
2
4
6
8
10
12
14
30.8 31 31.2 31.4 31.6 31.8 32 32.2 32.4 32.6
Salinity (ppt)]
CDO
M [Q
SU]
CDOMLinear (CDOM)
Figure 25: CDOM and salinity scatterplot from offshore towed transects. Salinity concentration in parts per thousand [‰] is plotted on the (x) axis and CDOM concentration [QSU] is plotted on the (y) axis. The linear interpolation represents a positive correlation of 0.245 between the two parameters.
Even though salinity – CDOM - temperature relationships appear weakly coupled
in offshore surface waters down to 5 meters depth (Fig. 25), strong vertical gradients and
highly localized anomalies were found to dominate along coastal regions of the Gulf of
Chiriquí. For example, CDOM measurements from the coastal area of Bahia Honda
increased by over one order of magnitude as depth increased from the surface to 10
meters depth (Fig 26). The highest CDOM concentrations [>50 QSU] occurred near the
north shore of Managua Island which is an island located in the center of Bahia Honda.
74
This area supports a small settlement of fishermen, suggesting that the fishing village
might be a significant CDOM source from organic waste and runoff. Measures of
salinity (Carman et al. 2007) were only of 7 PSU at the mouth of the Rio Managua, a
river near a mangrove area to the east of the island in Bahia Honda.
Figure 26: CDOM concentrations [QSU] from TowFish-TETHYS survey in Bahia Honda overlain on satellite imagery. Dips in the tracklog show vertical profiles taken at periodic intervals down to 12 meters depth. Data shows significant vertical variability in CDOM concentrations. Differences in surface concentrations from east to west may be indicative of circulation patterns within the bay. Red areas represent higher CDOM concentrations and blue areas show lower CDOM. A point source of CDOM is noticed near the north shore of Managua island with values exceeding 50 QSU.
75
The coastal areas from Santa Catalina to Canales de Tierra Island (located just to
the south of Bahia Honda) exhibited noticeable difference both vertically and
horizontally within the watercolumn (Fig. 27). A rapid attenuation of CDOM signal was
observed ranging from very high levels [>50 QSU] in the east near Santa Catalina,
coupled with low salinity measurements down to [6.0 ‰]. Freshwater input coming from
a submarine groundwater source might explain the precipitious drop in salinity observed
so close to shore at depths near 10 meters.
CDOM concentrations dropped off to near zero going west along the coast over a
distance of approximately ½ kilometer while salinity rapidly increased concentrations to
reach [≈33.5‰]. Given this relationship, there appears to be a significant terrestrial input
of freshwater contributing to coastal CDOM near Santa Catalina and Bahia Honda as
opposed to offshore. This might be expected considering that the coastal areas of Boca
Chica, Bahia Honda, and Santa Catalina border the mouths of large mangrove-estuary
systems, while the inter-island portion of the Gulf of Chiriquí may be relatively buffered
from terrestrial watersheds due to their distance away from these sources.
76
Figure 27: Alongshore coastal CDOM transect from Santa Catalina to Canales de Tierra. 3-D color plot showing variations of CDOM concentrations [QSU] as a function of salinity, longitude, and depth. Higher CDOM concentrations (shown in red) decrease abruptly to near zero (shown in blue) traveling westward along the coast (x) axis. CDOM concentrations increase with lower salinity values (y) axis. CDOM concentrations along the depth (z) axis show a vertical mixing boundary between distinct hyposaline (freshwater)masses and normal salinity ocean water.
An interesting eularian perspective of the temporal mode of change within these
water masses was also witnessed during a vertical cast with the towfish near Santa
Catalina Island (Fig. 28). The sensor platform remained stationary at depth for a period
77
of approximately five minutes while a water mass with high CDOM concentrations
advected past the sensor and continued during the upcast. This was especially noticeable
due to the lower CDOM concentrations during the downcast. Interestingly, there was an
inverse relationship with lower methane and higher CDOM concentrations and visa versa
during this cast.
Figure 28: Changes of CDOM concentrations [QSU] in the water column between the coastal Santa Catalina Island and Octavios Island represented in dimensional space (latitude, longitude, depth). Significant changes in CDOM were noticed during a vertical profile to 15 meters depth. A mass of water with high CDOM concentrations near 30 [QSU] shown in red, advected past the fluorometer during an upcast. Horizontal variations in CDOM were also quantified in the surface water as shown by the differences in blue hues.
78
Methane
In addition to the CTD (temperature and salinity) measurements, methane and
carbon dioxide data also provide evidence that basin chemistry dynamics within the Gulf
of Chiriquí may at times function independently. The TETHYS mass spectrometry data
shows elevated methane and carbon dioxide in shallow coastal areas near Boca Chica
(north of the Secas Islands), between Uvas Island and Coiba, and near the coastal region
of Santa Catalina. A strong negative correlation (-0.805) of salinity and CDOM (Fig.
29) supports the idea of dissolved organic material being carried by freshwater sources
out from the mangrove-estuaries in the central Gulf of Chiriquí. Similarly, a combination
of high methane (CH4) relative to other areas (Fig. 30) surveyed suggests that these
islands reside in predominantly non-upwelling waters with a significant amount of
freshwater input being carried along the shallow shelf. Comparatively low values of
methane were measured in shallow areas along the islands of Coiba, Canales de Afuera,
and Canales de Tierra (Fig. 30).
79
Methane & Salinity (Depth 0-5 meters)Offshore Transects in the Gulf of Chiriqui,
Scatterplot: N=842 datapoints
0
0.002
0.004
0.006
0.008
0.01
0.012
30.8 31 31.2 31.4 31.6 31.8 32 32.2 32.4 32.6
Salinity (ppt)]
CH4
/Wat
er (M
/Z15
/ M
Z17)
CDOMLinear (CDOM)
Figure 29: Scatterplot of salinity [‰] concentrations-(x) axis; and methane on (y) axis from all Towsled-TETHYS offshore transects. Methane and salinity are negatively correlated (-0.368).
80
Figure 30: Methane measurements from TowSled-TETHYS chemical surveys. In mass spectrometry, ratios of methane to water CH4:H2O employ water as a conservative tracer to help differentiate methane from other hydrocarbons. Higher methane is indicated in red and lower levels in blue. High levels of methane were encountered near the Secas Islands and north to Boca Chica, and along coastal regions adjacent to the Gulf of Montijo. The variegation of color between Coiba Island and Uvas Island shows mixing between water masses.
81
Nitrogen
Typically, nitrogen is thought to be a limiting nutrient in coastal ocean waters
(Ryther & Dunstan 1971). Nitrogen isotopic (15N) enrichment (low 14N /15N values)
patterns are shown to occur in the western Gulf of Chiriquí between the Secas Islands and
the Boca Chica estuarine mainland (Fig. 31). Contextually, these waters also exhibited
the lowest oxygen levels observed as well as high methane, carbon dioxide, and
chlorophyll. Microbial redox processes converting nitrate to nitrite (denitrification) are
known to occur in suboxic regions with high organic carbon content at low oxygen levels
(Grasshoff et al. 1999, Falkowski & Raven 1997). However traditional nitrate/nitrite
analysis would be required to establish if and quantify how these factors affect reefs in
the area.
Nitrogen cycling processes in coastal aquatic systems
The denitrification process takes nitrate and converts it into nitrogen.
Denitrification might be occurring in the waters of the middle gulf of Chiriquí given the
lower oxygen content of these waters, however deconvolving biotic and atmospheric
interplay in coastal nitrogen systems is a complex issue (Barile & Lapointe 2005).
Dynamic biologic processes occur where nitrogen gas (N2) is reduced (fixed) into
biologically available ammonium (NH4+) by photoautotrophs like cyanobacteria,
ubiquitous in the water column. Even epilithic biofilms and bacteria living on bleached
corals are thought to provide significant levels of nitrogen fixation for dead reefs (Davey
82
et al. 2007). Subsequent heterotrophic oxidation into intermediate compounds such as
(NO3- and NO2-) by nitrifying bacteria eventually reduces to (N2O and back to (N2)
(Ward et.al 2007). During microbial nitrogen transformations, differential enzymatic
reaction rates between 15N and 14N result in an accumulation of 14N in product reactions
and 15N in residual substrates. Nitrification and nitrogen fixation can therefore result in
depleted 15N (Sutka et al. 2004). As a caveat, this rule depends on oxygen availability in
the water column.
Nitrite may also be excreted by phytoplankton when surplus nitrate and phosphate
stimulate heavy blooms (Grasshoff et al. 1999). This scenario, results in 15N enrichment
of nitrate through the processes of denitrification by phytoplankton. Relative biomass
confounds the process as decaying organisms are rapidly decomposed by proteolytic
bacteria into ammonia (NH3) which can be toxic in large concentrations to fish and some
invertebrates.
83
Figure 31: Nitrogen isotope ratios plotted along TowSled-TETHYS chemical survey tracklogs. Lower 14N to15N ratios (relative 15N enrichment) was dominant near the Secas Islands and the central Gulf of Chiriquí.
Nitrogen limitation in coral systems
Although the zooxanthellae present in corals living in oligotrophic waters are
generally believed to be nitrogen limited, a laboratory analysis of the carbon to nitrogen
ratios in zooxanthellae pellets from P. damicornis and P. lobata from the Gulf of Panamá
suggests nitrogen sufficiency and that coral symbionts can tolerate limited nutrification
over short periods of upwelling in the Gulf of Panamá, but not chronic nutrification when
corals are also exposed to warm temperature (Schloder & D’Croz 2004). Data from this
84
study might be useful in the future to choose sampling areas where corals exist in
ambient water with high temperature and 15N enrichment (a potential environment for
denitrification processes) to examine if the hypothesis for the Gulf of Panamá will hold
true for corals in the Gulf of Chiriquí.
Point Source Hydrocarbons
Carbon dioxide TETHYS data did not identify any point sources of hydrocarbon
pollution or toxic industrial chemicals during the swath surveys. However, spectral data
indicates that relatively low concentrations of light hydrocarbons are present in some
coastal areas. (Fig. 32) provides an example TETHYS spectrum recorded at 12 meters
depth and approximately 3 km from the town of Santa Catalina showing ion peak
signatures consistent with trace amounts of light hydrocarbons.
100
1000
10000
100000
0 5 10 15 20 25 30 35 40 45 50 55 60
M/Z
Ion
coun
ts
Figure 32: Example of a TETHYS mass spectrum from 12 meters depth approximately 3 km south of Santa Catalina coastal area, indicating the presence of trace levels of hydrocarbons (Camilli et al. 2007).
85
Diurnal to nocturnal respiration and productivity transitions
During the tow from the Chiriquí mainland out to the Secas Island group, the
TETHYS mass spectrometer real-time graphical display indicated patches of high oxygen
and carbon dioxide mass counts occurring in tandem. A post processing analysis
revealed a strong positive correlation (+ 0.844) between oxygen and carbon dioxide in
these waters (Fig. 33). Although the chemical sensor platform used in this study was
configured as a towed device to enable wide area surveys, an exploratory experiment was
conducted using the instrument as a stationary observatory. The towfish was tethered to
the transom of the anchored research vessel at a depth of 5 meters and left running
overnight. (Figure 34) shows a 12 hour time series (7 p.m. to 7 a.m) of carbon dioxide
and oxygen measurements from a small cove located on Isla Seca. A night dive
confirmed large communities of Rhodophyta and other algae on the sea floor at a depth of
10 meters.
86
Carbon Dioxide & Oxygen scatterplotBoca Chica to Isla Seca Transect
N=250 datapoints
0.165
0.17
0.175
0.18
0.185
0.19
0.195
0.2
0.205
5.4 5.6 5.8 6 6.2 6.4 6.6 6.8 7
Oxygen
Car
bon
Dio
xide
Coefficient of Correlation = 0.844
Figure 33: Scatterplot of carbon dioxide and oxygen collected along a transect from Boca Chica to Secas Island with the Towfish-TETHYS platform. Units are dimensionless.
Graphing the amount of dissolved gases according to an elapsed time interval
reveals a monotonic decrease of CO2 and O2 with both values increasing again as night
turns to day. A similar coupling of carbon dioxide to oxygen levels that was observed
during the day tows was present (Fig. 33), but had only diminished in overall magnitude.
An oxygen drawdown seems to happen at a slightly faster rate initially and then begins
increasing at a faster rate than carbon dioxide with the transition to daylight. This lag
may indicate differential changes in metabolism and respiration as the sun rises and light
begins to penetrate the euphotic zone. While a longer time series at multiple locations is
87
needed to provide meaningful ecological information, these results underscores the
potential usefulness of TETHYS mass spectrometry to provide a Eularian perspective of
dynamic respiration/production processes.
Overnight Time Series 02 and CO2Secas Island; N=1087datapoints
5.9
6
6.1
6.2
6.3
6.4
6.5
6.6
6.7
6.8
2/14/0
7 19:1
2
2/14/0
7 20:2
4
2/14/0
7 21:3
6
2/14/0
7 22:4
8
2/15/0
7 0:00
2/15/0
7 1:12
2/15/0
7 2:24
2/15/0
7 3:36
2/15/0
7 4:48
2/15/0
7 6:00
2/15/0
7 7:12
Date and Time
O2/
Ar r
atio
0.135
0.145
0.155
0.165
0.175
0.185
CO
2/A
r rat
io
Figure 34: Oxygen and carbon dioxide overnight time series (12 hours) measured with TETHYS mass spectrometer in the Secas islands. The arrow near the (x) elapsed time axis represents midnight. Note the decreased overall variability from 1 a.m. -2 a.m., which increases as night turns to day. Y axis values for both carbon dioxide and oxygen are dimensionless.
88
Groundtruthing SeaWiFs Satellite Data
For satellite optical sensors the water leaving radiances visible from the sea
surface are representative of only the upper 20 % of the euphotic zone (Falkowski &
Raven 1997). At smaller spatial scales, benthic-derived CDOM can increase significant
absorption in blue wavelengths due to sediment resuspension, production from corals and
sea grasses, and scattering due to mineral particles derived from aragonite precipitation
within the water column (Lesser 2004). A further complication in obtaining accurate
chlorophyll measurements from satellite is the presence of heavy cloud cover over Pacific
Panamá during the rainy season, typically lasting from June through October (Fig. 35).
Signal attenuation due to atmospheric scattering and absorption often results in data loss
and uncertainty when interpreting chlorophyll concentration data for the rainy season and
confounds comparisons with the less cloudy and significantly drier winter months.
89
Figure 35: Time series color plot of SeaWiFs chlorophyll-a data representing a spatial domain investigated by this study. Chlorophyll concentrations are averaged over latitudes (6° N to 8°N) for each month. The highlighted area shows the timeframe surveyed in this project with the Towfish-TETHYS platform. Concentration of chlorophyll- a [mg/m3] is shown by the colorbar with lower concentrations in blue and higher in red. Blank areas represent signal attenuation due to atmospheric interference (e.g. cloud cover). Note the punctuated seasonality of chlorophyll levels.
Higher spatial resolution measurements obtained in-situ with the towed platform
during February were used to compare with remotely sensed data sets from SeaWiFs.
Fortuitously, ideal conditions for groundtruthing were encountered because there was
zero precipitation and very little cloudcover during field surveys (Fig. 35). Averaging of
raw SeaWiFs data for the month of February 2007 over a spatial area extending from 7°N
90
to 8°N latitude and 81°W to 82°W (representing an area of approximately 12,350 km2)
resulted in mean chlorophyll concentrations of [0.16 mg/m3]. Chlorophyll concentrations
ranging from [0.1 mg/m3] to [0.2 mg/m3] are typical near coral reefs and open ocean
areas (Lesser 2004). Each pixel grid from the SeaWiFs imagery represents temporally
averaged chlorophyll-a concentration over a 9 km2 area. This provides a synoptic
estimate of chlorophyll-a in the surface waters over the eastern Gulf of Chiriquí and the
Gulf of Montijo (Fig. 36) during the entire study period. The Towfish - TETHYS
fluorometer measurements were able to reveal finer concentration patterns that scale well
to SeaWiFs coarser measurements (Fig. 37), as well as provide detailed information
about vertical distributions of chlorophyll that the satellite is unable.
91
Figure 36: Color image of SeaWiFs remotely sensed chlorophyll-a concentrations [mg/m3] covering the spatial extent of this project during the first week of the towed chemical surveys. The SeaWiFs imagery represents average chlorophyll-a concentrations over a spatial extent where 1 pixel = 9 km2.
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in situ "groundtruth" of Chlorophyll a ConcentrationsGulf of Chiriqui, Panamá February 2007
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TowFish [ug/L] SeaWifs [mg/m^3]
Figure 37: Satellite remote sensing groundtruth: A comparison of raw SeaWiFs chlorophyll-a data with TETHYS-TowFish data. SeaWiFs data are indicated as orange squares, and TETHYS-TowFish data are indicated by green circles. The vertical alignment of SeaWiFs data along the (x) axis (longitude) is an artifact of SeaWiFs coarser resolution (1 degree longitude). Data points were averaged across latitudes 7°N to 8 °N, encompassing the entire towed area. The spatially dense TETHYS-Towfish chlorophyll-a data nests well within SeaWiFs surface measurements. Note the equivalence of concentration values where 1[µg/L] = 1[mg/m3].
93
Using SeaWiFs to quantify a red tide
Coral mortality has been connected with red tides appearing periodically along
the Pacific coasts of Costa Rica and Panamá (Guzmán et al. 1990). In general, red tide
phenomena are associated with strong sunlight exposure, large fluxes of riverine or
rainfall and stable, stratified, water columns (Jimenez 1989). Following the transition out
of the winter dry season and the onset of heavy rains, a hemotalasia (red tide) was
observed along coastal areas extending from the Gulf of Montijo and west towards the
Gulf of Chiriquí. It began circa April 28th and lasted until approximately May 14th, 2007.
Water quality was highly turbid, purple to black in color, and underwater visibility was
near zero. Fish, bird and turtle mortalities were confirmed (personal field observation),
and dolphin deaths near the Gulf of Montijo were reported in local media. Fishermen
from local villages near this study ceased fishing and anecdotally commented that this
particular red tide was one of the worst they could remember in recent history (personal
field observation).
At least one dinoflagellate species, Gymnodinium catenatum, has been observed
in conjunction with previous red tides occurring in the western Gulf of Chiriquí (Soler et
al. 2003). Other chlorophyll-rich dinoflagellate species are known to contribute to red
tides along the eastern tropical Pacific coast including Gonyaulax monilata (toxic to fish
and other higher order vertebrates) and Pyrodinium bahamense, Exuviaella compressa,
Prorocentrum micans, Peridinium pellucidum , and Pyrodinium bahamense (Soler 2003).
The diatom Skeletonerna costatum associated with red tides near Ecuador has been
94
shown to contribute to chlorophyll concentrations greater than [100 mg/m3] (Jimenez
1989).
Remotely sensed CDOM and chlorophyll concentrations can be useful predictors
of red tides (Coble et al 2004, Hu et al 2005). The results from the Towsled-TETHYS
groundtruthing discussed earlier provides greater confidence in the regional reliability of
chlorophyll measurements obtained with SeaWifs and the inferences we can draw from
them. A retrospective analysis of SeaWifs chlorophyll-a data for the month of May
2007, during the red tide, showed the highest levels of chlorophyll-a in four years.
According to May 2007 monthly averaged 9 km2 data sets from SeaWiFS for the
Gulfs of Chiriquí and Montijo (Fig. 38) the red tide that enveloped this study area had
values exceeding [30 mg/m3]. This is nearly two orders of magnitude31 greater than the
total average surface chlorophyll-a concentration [0.251 µg/L] SD +/- 0.11 measured in
February of 2007 with the TETHYS-Towsled fluorometers. Future studies are needed to
determine the frequency, duration and causality of these red tide events.
31 The units of concentration have a metric identity where 1[μg /L] = 1[mg/m3].
95
Figure 38: SeaWiFs chlorophyll-a concentrations [mg/m3] coinciding with a severe hemotalasia (red tide) observed in the study area during May 2007. Chlorophyll-a concentrations in the Gulf of Chiriquí at times exceeded [30 mg/m3], nearly two orders of magnitude greater than TETHYS-Towsled measurements [0.251 µg/L] collected in February 2007.
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HD Videography and Conventional Subtidal Survey Results
Characterizing habitats with snorkel & SCUBA
Snorkeling and diving reconnaissance confirmed the presence of coral
communities, and sponge – gorgonian communities in the coastal region between the
Gulf of Montijo and Bahia Honda. Specifically these areas were submarine basalt
pinnacles just off the coast, small protected coves (i.e. Playa Banco, Río Ballena, and
Cimarrones) and the nearshore micro islands of Isla Octavios, Islotes de Cativo and Isla
Santa Catalina. A future survey effort scheduled for late 2008 will quantify the coverage,
extent, and diversity of these particular benthic communities.
To date, many organisms in the Pacific-Central America region have yet to be
accurately identified and taxonomically cataloged. In fact, a recent inventory of
octocorals collected in the gulfs of Chiriquí and Panamá found four new species of
Pacifigorgia making a total of 15 known Pacifigorgia species for Panamá, and 31 species
for the eastern Pacific biogeographic province (Breedy & Guzmán 2005). The sighting
of Aplysina chiriquíensis, described by (Diaz et a.l 2005) as a new species, was verified
at several locations including Bajo Negro (a submarine pinnacle), Isla Canales de Tierra,
and Isla Pacora, generally at depths greater than 12 meters. Abundant seafan and
softcoral communites were also observed in this region. Leptogorgia cofrini described by
(Breedy & Guzmán 2005) as a new species of octocoral as well as Pacifigorgia sculpta,
(Breedy & Guzmán 2004) was identified growing on rocky basalt outcrops. Soft coral,
gorgonian and sponge communities were most often encountered in large boulder areas
97
with swift currents (estimated between 0.5 m/s to 1 m/s) and cold water pulses with 5°C
changes in ambient temperature (∆ ≥ -5°C) at depths near 20 meters. Hard corals, if
present, existed in isolated patches closer to the surface.
A blue ascidian, Rhopalaea birkelandi (a solitary form) was frequently
encountered as part of the sponge/gorgonian assemblages, and less sighted was the red
Eusynstyela sp. (cf. tincta) the colonial form with small individuals (3 mm to 5 mm
diameter). Although cosmopolitan ascidians have been identified near the Panamá Canal,
the first documentation of native ascidians in Pacific-Panamá waters was in the Gulf of
Chiriquí in 2006 (Carman et al. 2007).
Given the understudied nature of this region and the fact that the Panamá Canal
passes approximately 13,100 ships annually between two oceans (Panamá Canal
Authority 2006) leaves many questions unanswered concerning the interplay between
local endemism and invasive colonization being facilitated by shipping traffic vectors
(Carlton & Geller 1993, Forsman et al. 2005).
Although this study primarily focused on the identification and distribution of
hermatypic corals,32 some soft corals33 were identified to Family and occasionally Genus
level during field surveys. Some of the more common invertebrate species34 encountered
included Aplysina Chiriquíensis, and other Aplysina sp. sponges, the coral eating sponge
Cliona sp., seafans and gorgonians such as Pacifigorgia sp., and Leptogorgia sp., soft
32Taxonomic Order: Stylasterina, Milleporina and Scleractinia. 33Taxonomic Order: Octocorallia (Alcyonacea), Telestacea, and Gorgonacea. 34 Primary sources for field identification were: (Allen & Steene 1998, Sprung 1999, Glynn & Maté 1997, Cortés & Guzmán 1998).
98
corals Muricea sp., Carijoa multiflora, Tubastraea coccinea, brittle stars Echinotrix sp.,
an assortment of unidentified octocorals, and various nudibranches. Although sponges
were often encountered in rocky, rugose areas, they were conspicuously absent in hard
coral patches in shallow water.
Quantifying benthic cover
Reef building corals generally belong to the order Scleractinia, a group in the
subclass Zoantharia. These hard corals many of which secrete external skeletons of
aragonite (Veron 1995) are predominantly hermatypic (containing zooxanthellate
organisms) and may include both solitary and colonial forms. This investigation verified
the presence of scleractinian corals at all sights except Punta Damas on the eastern coast
of Coiba Island. Instead, this area was dominated by rhodolith patches less than 1m2 area
per patch, and spaced discontinuously between 1 and 1.5 m apart. Rhodolith patches were
interspersed with a filamentous Cyanophyte (red-brown algae) that was the dominate
growth over sandy areas in the Punta Damas – Punta Clara region. The northern extent of
this area surveyed has two large river inputs nearby, Río Catival and Río San Juan, but
surprisingly lacks temporally stable35 seagrass communities. Although hard coral was
present at all sights (except Punta Damas/Punta Clara), the spatial distribution of
scleractinians was generally confined within about 30 meters of shore at depths less than
10 meters.
35 As per communication with Dr. Juan Maté of the Smithsonian Tropical Research Institute, Panamá.
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Common hard corals encountered
The most common hard coral species encountered during the dive surveys
include: Family Agariciidae: Pavona clavus, Gardineroseris planulata, Pavona gigantea,
Pavona varians, and Pavona maldivensis (which was rare and only on rocky outcrops).
Other common scleractinians were Family Pocilloporidae: Pocillopora elegans,
Pocillopora damicornis, Pocillorpora capitata; Family Poritidae: Porites lobata; Family
Siderastreidae: Psammacora stellata. The Family Fungiidae: Cyclocerus curvata was not
commonly encountered. The scleractinian coral Pavona Chiriquíensis (Maté 2003) was
observed in separate colonies at Isla Canales de Tierra and in turbid waters near Isla
Managua in Bahía Honda.
Overall benthic composition
Bottom substrate composition and structure are often strongly correlated with
algal and coral assemblages (Edinger et. al. 2000; Bellwood & Hughes 2001), and
ecological paradigms predict high coral cover and associated species diversity in areas of
intermediate disturbance (Connell 1978, Glynn & Ault 2000, McClanahan et al. 2005).
Comparisons of benthic categories with REEF CHECK point intercept transect, video
transect and SCUBA COP methods were conducted at different dive locations among
islands to determine underlying patterns of coral distribution and coverage as they relate
to benthic substrate (Table 5).
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Table 5: Benthic cover summary statistics for dive locations in the Gulf of Chiriquí
Mean Percent Cover and Standard Error (S.E.) of Benthic Categories in the Gulf of Chiriqui, Panamá using HD video method
Punta Damas
Isla Managua
Isla Uvas
Punta Miel
Canales de Tierra
Canales de Afuera
Isla Seca
Site Name
Latitude & Longitude
N7 30 00.7 W81 40 12.2
N7 44 30.4 W81 31 06.8
N7 48 55.2 W81 45 34.0
N7 44 26.2 W81 32 24.1
N7 44 40.8 W81 34 40.0
N7 41 43.32 W81 36 49.0
N 7.57.197 W82.00.684
Benthic Categories
Mean percent cover % +/- Standard Error (S.E.)
Hard Coral 0 1.2 (0.58)
18.4 (2.06)
4.4 (0.81)
16.6 (1.63)
18.4 (1.44)
4.6 (0.40)
Soft Coral 0 0.2 (0.2)
0 0.2 (0.2)
0 0 0
Recently Killed Coral
0 0.6 (0.24)
5.2 (1.50)
1.2 (0.73)
3 (0.32)
0.8 (0.37)
0.6 (0.40)
Nutrient Indicator Algae
44.6 (3.67)
17 (5.44)
0 5.2 (1.16)
0 18.6 (2.96)
0.2 (0.20)
Sponge 0 0 0 0 0 0 0
Rock 0 2.6 (0.51)
0 35.4 (2.62)
0 0 0
Rubble (coral)
10.4 (0.93)
15.4 (2.66)
24.6 (2.04)
23.2 (1.16)
66.4 (1.96)
19.6 (1.17)
21.8 (2.80)
Sand 38.2 (2.92)
51.4 (4.88)
15.8 (1.28)
30.4 (3.17)
14 (1.67)
6.6 (0.98)
32 (2.07)
Silt 0 11.6 (2.54)
0 0 0 0 0
Other (Rhodolith)
6.8 (0.86)
0 36 (2.10)
0 0 36 (3.91)
40.8 (1.98)
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Unexpectedly, Isla Managua and Punta Miel, both areas located in a coastal
embayment and exposed to river inputs from Río Corotú, Río Managua, Río Salmón, and
Río Luis, contained corals but in an extremely restricted area. Corals, often solitary
individuals or small colonies, were only found less than 15 meters from shore, with
distributions that quickly dissipated with depth and distance from shore. Visibility was
extremely poor during these dives and there were noticeable differences in substrate
ranging from rugose basalt boulders in the shallow nearshore, and a sudden change to a
dense, silt sand matrix devoid of corals.
Similar sized offshore embayments such as the areas sampled on Isla Uvas and
Canales de Tierra had significantly greater scleractinian coverage over larger areas. These
islands exhibited dense, structurally complex, carbonate reef architectures and
monospecific dominance of Pocillopora damicornis over large areas. Generally reefs
were found on the northern (unexposed) shores of islands in shallow(<10 meter) waters
over a continuous sloping shelf. Other coral communities were found around shallow
rocky areas on the southern (exposed) shores, but were highly discontinuous and patchy
and did not form reefs. A early study on Isla Uva found 11 scleractinian species and two
species of Millepora in an area that was otherwise dominated by P. damicornis and
evidently thriving in the presence of Crown-of-Thorns (Acanthaster spp.) predation
(Glynn 1973).
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Isla Canales de Afuera, which is comparable in size and distance from the
mainland as Isla Uvas, and has a similar benthic morphology, only showed moderate
coral cover in proportion to abundant rhodolith patches. Others (Glynn & Wellington
1983 and Cortés 1997) have reported large areas of dead Pocillopora sp. corals covered
in crustose coralline algae in the vicinity. Rhodoliths may be an important source of
calcium carbonate uptake and deposition for these reef systems because coralline algae
bind adjacent substrata, providing calcified tissue barriers against erosion that also serves
to provide hard substrata for larval settlement (Chisholm 2000).
Quantifying scleractinian coral cover among dive locations
Quantifying the live cover of scleractinian corals and their associated mortality is
important in understanding the overall structure and health of reef habitats. Results from
(Fig. 39) collected with HD Video swath and those from the REEF CHECK surveys
(Appendix: Figs 53 through 58) will be used to compare with the potentially richer,
automatic output from the data sets collected with SCUBA COP. Future efforts will train
the automated system to differentiate between live coral, coral colonies, and perhaps even
identify octocorals, sponges and algae to family or species level.
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Benthic Composition of Coral Communities in the Gulf of Chiriquí
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(Bahia Honda)Isla Managua
(Bahia Honda)Punta Miel
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Isla Uvas Isla Seca(Barracuda)
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Hard Corals Recently Killed Coral Coral Rubble
Figure 39: Relative contribution of hard coral, recently killed coral, and coral rubble to overall benthic percent cover at dive locations in the Gulf of Chiriquí. Standard error is reported in benthic coverage summary statistics table.
A comparison of hard coral percent coverage of the subtidal island areas surveyed
by HD video methods (Fig. 39) shows Isla Uvas with the highest percent cover (18.4%)
followed by Isla Canales de Afuera (18.4%), Isla Canales de Tierra (16.6%), and Isla
Secas with (4.6%) live coral cover. A whisker box plot (Fig 40) provides a graphic
display of inter-site variability of hard coral cover. Isla Managua (located in the enclosed
embayment of Bahia Honda) showed low coral cover with only (1.3%). However, Punta
Miel which defines the western point of Bahia Honda, and is less than 1 km away from
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Isla Managua, exhibited higher coral coverage with (4.4%). This may in part be due to
its exposure to flushing from strong currents or cooler water circulation from water
masses moving longshore, or simply because of a dilution factor related to being further
from riverine inputs of Bahia Honda.
Figure 40: A “Box-Whisker Plot” graphical representation of hard coral percent cover among dive sites in the Gulf of Chiriquí. The lower and upper lines of the “box” are the 25th and 75th percentiles of the sample. The distance between the top and bottom of the box is the interquartile range. A line in the middle of the box represents the sample median and when it is not centered within the box, is an indication of skewness. The lines extending above and below the box the “whiskers” show the total sample extent, with the maximum value represented by the upper whisker and the minimum value signified by the lower whisker. The notches “pinching” the sides of the box are a graphic confidence interval about the median of a sample.
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Strictly speaking Managua island and Punta Miel are part of the coastal
geography associated within Bahia Honda. Because of their proximity to land, Isla
Managua and Punta Miel are presumably affected by freshwater input. These two sites
share similarly low percent live coral cover much like the Isla Seca site, on an island that
lies more than 20 km offshore. This may be explained in part by the chemical
components of this study that indicate significant terrestrial input affecting the Isla Secas
archipelago.
In order to test statistically significant differences in percent cover of hard coral
between four offshore islands, an Analysis of Variance (ANOVA) was conducted
between the Uvas, Canales de Tierra, Canales de Afuera, and Secas Islands. The
estimated level of significance (ά value of 0.05) was chosen because the ability to detect
an effect was considered high based on the considerable amount of variability shown
graphically between populations. Results of the ANOVA (Table 6) indirectly support the
alternate hypothesis, that one or more of the samples, (i.e., Secas Island) might be drawn
from populations with different means. The whisker box plot (Fig. 40) suggests a
bimodal distribution of coral coverage between the six dive locations.
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Table 6: Summary statistics: univariate one way ANOVA percent cover of scleractinian coral among 4 similar islands. Analysis of variance using percent cover data Arcsine Square Root transformed to perform a univariate, one way ANOVA testing differences of percent cover among geographically similar offshore islands. The statistical null hypothesis Ho: “There is no statistically significant difference (P<0.05 two tailed test) between hard coral percent cover between 4 islands surveyed” was rejected since the probability of rejecting the null hypothesis (H0) when that hypothesis is true (Type I error) was significantly less (0.0001) than the a-priori alpha value chosen (ά = 0.05).
Univariate one-way ANOVA % cover Hard Coral among Gulf of Chiriquí offshore islands
Source of variation
df SS MS F P-value
Among groups 3 0.179825 0.059942 17.40715 0.000114
Within groups 12 0.041322 0.003444
Total 15 0.221147
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SCUBA COP Survey Results
Data processing and mosaics
Almost 500 GB of stereo imagery were collected during six diving days. This
corresponds to nearly seven hours of bottom imagery and roughly 5km linear data, which
accounting for overlap represents area coverage of 7500 m2. Significantly more area was
surveyed with the SCUBA COP than with the video camera and REEF CHECK methods.
However, the fraction of the SCUBA COP data set which corresponds to the structured
linear transects surveyed by HD video and REEF CHECK will eventually be used for
quantitative comparison with these other methods. At this point the mosaic swath
processing can be divided into strips and applied to any subsection of the data ranging
from (tens) to (hundreds) of square meters (Fig. 41).
Coral or other organisms exhibiting morphological plasticity, or rare species that
are by nature morphologically identical may require additional verification with
complementary or alternate methods. Currently the automated classification is only
related to ecologically relevant classes after the fact; however the ability to discriminate
coral from other substrate classes remains robust. Future development of software
processing routines will use human-labeled “expert” classification of the video-transects
to define classes that have ecological significance. The remaining human-labeled data
will be used as groundtruth to test and improve accuracy in automated classification. The
improved classification will then be extended to surveyed areas beyond the 50 meter
linear transects to provide dense geostatistic summaries for all coral benthic mosaics.
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Figure 41: Spatial scale and resolution of a typical mosaic swath: The top image represents an entire 50 X 3 meter swath ( composed of more than 150 overlapping images) that was captured with SCUBA COP stereo cameras, in one pass. The serpentine morphology of the top mosaic swath is a result of underwater currents that affected the diver and instrument. An internal motion unit (IMU) onboard SCUBA COP enables post processing correction of vehicle attitude and displacement relative to object being imaged. An enlargement of the area represented by the smaller dotted square in the top figure is shown below where you can distinguish a SCUBA diver in the right hand corner placing an underwater transect tape- the white stripe in middle of swath. With no digital compression, each individual image in the swath can be enlarged to its maximum resolution where 1 pixel = 1cm.
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Automated image segmentation and classification
At this point, digital filtering resulted in the segmentation of the mosaic image
shown in (Fig. 42) and input of the vector components into the Expectation Maximum
(EM) algorithm enabled a classification of a 2.5 dimension swath. This image shows a
subsection of a 50 meter mosaic from Isla Uvas, comprised of more than 40 overlapping
images resulting in a strip representing approximately 14 meters in length. Six user
prescribed classes were used to produce a color-coded gradient of segmentation which
roughly corresponds to distinct categories of coverage (Camilli et al. 2007). In this
example, light blue corresponds to sand, while light green corresponds with a mixture of
rubble and sand. Dark red and blue hues tend to be hard coral. Next, the relative
contribution of each class is calculated for the total mosaic area to create an estimate of
percent cover by each category. A demonstration of this process is shown in (Table 7)
which provides a statistical summary of the proportions found in the SCUBA COP swath
subsection (Fig. 42).
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.
Figure 42 The mosaic to the left represents a 14 meter long subsection of a 50 meter transect from Isla Uvas, comprised of more than 40 overlapping individual images. Adjacent and to the right of this mosaic is a computer generated automated classification of six user prescribed classes that were used to produce a color-coded segmented image from the coral mosaic. These segmentations roughly correspond to distinct benthic categories of coverage. In this example, light blue areas correspond to sand; light green corresponds to a mixture of rubble and sand. Dark red and blue hues tend to be hard corals. The blue stripe in the middle is the transect tape.
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Table 7: Binocular vision permits the use of texture-based decision algorithms and 3 dimensional stereo as methods for coral classification. Example of tabulated results from an automatic segmentation and classification output. Corresponding benthic categories and the relative contribution from each of 6 classes are calculated over the total area of the mosaic from the colormap image in figure 42. The current implementation allows the user to prescribe the number of classes while the EM algorithm derives the characteristics of each class.
Class Color Type Relative Coverage 1 Blue hard coral 0.143 2 light blue sand 0.066 3 light green rubble/sand 0.647 4 orange rubble 0.045 5 red hard coral 0.047 6 dark red hard coral 0.052
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DISCUSSION
Hey man of science with your perfect rules of measure, can you improve this place with the data that you gather?
Bad Religion (1989)
Comparison of Traditional Diving Survey Results with HD Video
In many reef systems, geomorphology, and sediment structure influence
invertebrate and algal recruitment, attachment and sheltering habitat (Franklin et al. 2003,
Nugues & Roberts 2003, Vermeij 2005). For the purposes of this study, percent cover of
each of ten categories was used to characterize the benthic substrate and sessile
organisms across dive sites. When REEF CHECK v. 2004 protocol is compared on
exactly the same transects with the HD video results (Fig. 43) the most significant
differences across 7 dive locations in the Gulf of Chiriquí was the ability to distinguish
between sand and algae. The REEF CHECK traditional Point Intercept Transect (PIT)
method tends to overestimate sand cover and underestimate algal cover and coral rubble.
Both methods function equally well in determining hard coral, sediment, and rhodolith
percent cover.
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Method Comparison Video Swath & Diver Transect Benthic Cover, Gulf of Chiriqui Panama
0
10
20
30
40
50
Hard Coral
Soft Cora
l
Recently
Killed Cora
l
Nutrient
Indica
tor Alga
eSpo
ngeRock
Coral Rubb
leSand Silt
Rhodolith
Benthic Category
Mean
% C
over
HD Swath Video Point Intercept
Figure 43: Comparison of high definition video with SCUBA diver Point Intercept Transect (PIT) method - REEFCHECK protocol. Blue bars represent benthic percent coverage estimates (pooled for all 7 dive locations) across 10 categories using video swath methods. Yellow bars represent PIT percent cover estimates across the same categories. Standard error for each category is reported in the summary statistics (Table 5) for the HD video method and (Appendix Fig. 54 through 59) for the PIT method.
A similar study found that rare benthic categories are more easily detected with
video methods that record a swath of the benthos, than with methods such as REEF
CHECK (PIT) where only point samples lying under a transect are observed (Lam et al.
2006). The inherent advantage of a traditional survey method is the ability to distinguish
features lying under sediment or algal cover while in the field, which might explain some
of the differences noticed in the results of this study. That withstanding, some advantages
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of video and photogrammetric surveys include the ability to survey and archive larger
areas, and more points of interest with greater detail, and the capacity to provide
contextual information visually which can be a useful indicator of overall coral
community stability.
SCUBA COP: Visualizing an Automatically Intelligent Machine
Time versus Space and trade-offs in resolution
Advances in digital imaging and signal processing have blurred the distinctions
between video and photographic technology. Video methods, although temporally dense
with 24 or more frames per second, may actually be less useful than photographic
methods for certain applications where capturing rapid motion is not essential. It is
computationally expensive and difficult to reduce the time dimensions captured in video
in a robust manner that allows for synoptic spatial analysis. At the current state of the art,
video analysis still relies on a subsample of the total number of images to compute spatial
density or coverage, and this compression of time makes statistical inference less certain.
Current memory storage capabilities also limit digital archiving of high resolution
images at high frequency sample rates. Comparatively, photographic processes are able
to sample smaller areas with higher resolution but suffer from the inability to image large
areas simultaneously. This spatial – temporal tradeoff in resolution is solved in part with
technological innovation like the hybrid imaging system onboard SCUBA COP which
combines high optical resolution with a near-video sample rate.
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Synoptic perspectives of swath mosaics
Besides the tangible optimization of resolution afforded by this technique, a
unique perceptual experience occurs when one observes small slices of time spread over
large surfaces within the context of the swath images. The gestalt emerging from the
mosaics adds important contextual information and no doubt influences the way we view
our environment. In the case of understanding the reef as it relates to the assemblage of
individual organisms, and emergent spatial-temporal continuity begins to transcend
merely an intersection of various components. Borrowing from branches of philosophy
and mathematics to conceptualize these ontological primitives of overlap and connection,
the cognitive awareness that these swath mosaics invoke might be better understood as a
kind of mereotopology that addresses relations of part to whole and relations of part to
part within a whole (Varzi 2000, Simons 1987, Casati & Varzi 1999).
Expert training for fully automated post processing
Work has begun using a human expert to train pixel coordinates by identifying
particular organisms and benthic categories a posteriori to be used as output for a fully
automated image classification system. Initially a publicly available software program is
being used to create a library of expertly classified points generated from SCUBA COP
imagery. The Visual Basic software, Coral Point Count with Excel extensions (CPCe) is
a standalone software package and graphic user interface (GUI) that randomly distributes
points onto an underwater photographic image (Kohler & Gill 2006). This enables the
user to visually identify features of interest (e.g., coral, algae, rubble) lying under each
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point. Because the points for identification are distributed randomly over the image, the
percentage of points over-lying each benthic category can be calculated, and statistics can
be compiled to estimate the population of each category over a region of interest.
Coral category codes being used with CPCe were created based on hardcoral and
octocoral species known to inhabit Pacific Panamá. General benthic categories are at this
point being based on the REEF CHECK protocol to enable a retroactive comparison of
data gathered during this project which will help to validated and gauge the accuracy of
the algorithm output at each dive site. For each 50 meter transect, 20 non-overlapping
images gathered with the SCUBA COP were chosen and 20 random points were assigned
to each image for classification. A library (Appendix: Table 9) of expertly classified
points with unique image coordinates is being compiled for future use as input into a
higher level, fully automated, support vector machine (SVM) classification routine.
Comparing Coastal and Island Water Chemistry
High seasonal turbidity, due in part to elevated plankton abundance, occurs near
mainland upwelling centers like the Gulf of Panamá, however high turbidity due to
seasonal freshwater discharge and sporadic flooding is more notable in the Gulf of
Chiriquí where underwater visibility can be reduced to less than 0.5 m during heavy
runoff (Glynn & Ault 2000). Adding to this complexity, cool hypersaline pulses were
noticed in this study along coastal stretches near the Gulf of Montijo to Pixvae, indicating
that these areas are periodically influenced by upwelling. Although the data was not
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collected methodically, post hoc analysis of SCUBA Coiba company dive logs (year
2004 – 2006) from multiple dive sites near Isla Octavios (along the coast) and northwest
Coiba Island (offshore) provide at least a sense of variability in temperature and visibility
conditions over a three year period (Appendix: Figs. 51 & 52). Anecdotally they support
the notion of cool water arriving in this region around February through April
concomitant with diminishing water quality. As well, visibility seems to be consistently
less near the coast than further offshore.
Complex mixing of terriginous and offshore water
Overall, data from this study imply that the offshore inter-island area water
chemistry is relatively well mixed and may be influenced by deep upwellings, while
coastal areas near Boca Chica may be more influenced by freshwater inputs, particularly
during the rainy season as runoff volumes increase. These survey transects provide
evidence that the variability can be extreme. For example, a small plume of brackish
water with salinity less than [10 ‰] and high methane was found near the coast of Santa
Catalina (Fig. 44). This model of mixing suggests complex, time varying, dynamics that
would necessarily impact marine habitats within the Gulf of Chiriquí.
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Figure 44: Methane variability in the water column near the coastal region of Santa Catalina represented in dimensional space (latitude, longitude, depth). The vertical profile represents methane variability over depth and the horizontal plane shows variability across the surface. Areas in red show higher levels of methane and areas in blue show lower levels (dimensionless units).
Terrestrial runoff onto coral reefs increases sedimentation rates, turbidity,
Particulate Organic Matter (POM) and dissolved inorganic nutrient (DIN) levels.
Excessive nutrient flux can lead to eutrophic conditions which directly effects coral
biology, community structures, and reduces species richness (Fabricius 2005, Thomas et
al. 2003, Orpin et. al. 2004). In a similar manner, physiological limits to growth and
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survival in symbiotic reef corals are governed by a functional response of respiration to
turbidity (Anthony & Connolly 2004).
Identifying eutrophic and oligotrophic water masses
Areas with the combination of indicators for eutrophication as defined by this
study, were found on the towed transect from Boca Chica (Bahia Muertos) to Isla Secas.
Here, high methane, nitrogen, and high carbon dioxide coupled with slightly lower
oxygen, and higher chlorophyll values were observed. Relating the combined
observations of oxygen, carbon dioxide, and chlorophyll implies that both respiration and
production are tied to overall chlorophyll concentrations in these waters (Fig 45). This
combination of factors as well as a negative CDOM - salinity relationship (Fig. 46)
suggests that these waters are more eutrophic than waters further offshore and originate
from a terrestrial, freshwater source.
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Figure 45: 3-Dimensional scatterplot showing the relationship of chlorophll-a, carbon dioxide, and oxygen over the Boca Chica to Secas Island transect. Strong correlations between oxygen, carbon dioxide and chlorophyll are revealed.
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CDOM and Salinity scatterplotBoca Chica to Isla Seca Transect
N=250 datapoints
0
1
2
3
4
5
6
7
8
31.1 31.2 31.3 31.4 31.5 31.6 31.7 31.8
Salinity [ppt]
CD
OM
[QSU
]CDOMLinear (CDOM)Linear (CDOM)
Coefficient of Correlation = - 0.805
Figure 46: CDOM – Salinity scatterplot of Boca Chic to Secas Island transect showing a strongly negative correlation between CDOM and salinity in these waters. The CDOM – salinity relationship suggests large influences of freshwater input over this shallow shelf (<50 m) depth. The area from Isla Uvas to Isla Coiba also appears to be somewhat influenced by water
masses originating from the shallow shelf region of the Gulf of Chiriquí. The northern
and eastern shores of Coiba Island, especially in the Bahia Damas region, where no
corals were found, exhibited lower methane, and lower chlorophyll values than the other
offshore islands. To the north of Bahia Damas elevated oxygen levels and lower carbon
dioxide suggest increased pockets of primary production in the shallow littoral.
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Implications of excessive allochthonous input
In addition to being a primary area for cattle ranching and rice agriculture,
unregulated construction, real estate development, septic waste increase and rapid
population expansion in this area poses a tangible threat to coastal coral systems in the
Gulf of Chiriquí. Coral reef development might be severely impacted if corals are
exposed to the runoff of nutrients from agricultural fertilizers or raw sewage, and
(Schloder and D’Croz 2004) go on to suggest that the documented detrimental effect
from nitrate enrichment in P. damicornis might be of great relevance for coral
conservation because it is the major reef-building coral species in shallow reef areas in
the eastern Pacific Ocean. A documented case of coral mortality directly attributed to
agricultural runoff in this study region involves the herbicide 2,4 dichlorophenoxyacetic
acid (2,4-D) and 2,4,5 trichlorophenoxyacetic acid (2,4,5-T) which was found in coral
tissues and linked with a 50% to 80% mortality of total live coral cover of Chiriquí reefs
during January-April 1983 (Glynn et. al. 1984). A complementary endeavor for future
terrestrial biologic and limnologic research would be to quantify parameters like fresh
water flux, sedimentation rates, pH, nitrate, nitrite, salinity, oxygen, and phosphate
concentration in river systems that flow into the gulf of Montijo and the gulf of Chiriquí.
This information would facilitate accurate modeling of residence time for nutrients and
contamination in the gulfs which surround the Coiba Island national park.
Stretches of oligotrophic water (high salinity, low CDOM, low chlorophyll) were
observed along the coast between Santa Catalina to Bahia Honda, and resuming
westward to Pixvae. The risk of eutrophication to coastal coral communities along this
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relatively pristine corridor (including areas like Pelonas, Rio Ballena, Octavios Island)
might be elevated due to inherently low coral species diversity, the proximity to human
disturbance, and the influence of input from large terrestrial watersheds from the East in
the Gulf of Montijo, as well as from the West from the Gulf of Chiriquí. Based on this
project’s GIS analysis of Panamá National Census 2000 data, an estimated 103,000
people inhabit the greater Gulf of Montijo drainage basin (Fig. 47) which has 24 major
tributaries emptying into the gulf (PRD 2001).
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Figure 47: Map (scale 1:400,000) of major rivers (blue lines) and population centers (red triangles) in relation to chemical survey area (red lines). According to a GIS analysis of year 2000 Panamá national census data, approximately 103,000 inhabitants live in the Gulf of Montijo drainage basin. The Gulf of Montijo is a shallow, mangrove-estuarine system with 24 major tributaries emptying into the basin.
Respiration and photosynthesis
Along the coastal mainland, the enclosed bay, Bahia Honda and the area
immediately south of Santa Catalina (Punta Brava) near the Gulf of Montijo, exhibited
high CDOM and high methane levels also indicative of terrestrial nutrient input. Both
areas are adjacent to mangrove-estuarine systems. The Boca Chica and Gulf of Montijo
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topography are primarily composed of uplifted sedimentary substrate (Fig. 2) which may
weather rapidly and add to the sediment load volume entering these estuarine areas.
Chronic exposure to high sediment load generated by anthropogenic stress can
result in low recruitment rates of scleractinian corals and decreases in hard coral cover
and coral skeletal density (Dikou & van Woesik 2006). Light limitation, common in
highly turbid and organic-rich estuarine and coastal waters, can limit primary production,
and determine species composition and abundance of primary producers (Kelble et al
2005). Dissolved organic matter which is essentially a mixture of compounds that are
produced by plant and animal decomposition, absorbs photosynthetically available
radiation (PAR)36 and indirectly controls primary production by determining the quantity
and quality of light, available for photosynthesis (Nelson & Guarda 1995, Keble et al.
2005).
Large swings in nutrient availability can affect energy availability in coral
systems. Functionally speaking, net community production is the difference between net
primary photosynthetic production (rate of production organic Material) and
heterotrophic respiration (rate of destruction of organic matter) in a steady state system
(Stumm & Morgan 1981, Falkowski et al 2003).
36 The amount of light at all the wavelengths of the visible spectrum reaching the euphotic zone
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Dwelling on Upwelling: The Deeper Implication
D’Croz and Robertson (1997) claim that coral reef distributions on both the
Caribbean and Pacific coasts of the Isthmus are governed mainly by physical processes
and enhanced seasonality. Accordingly they suggest that eutrophic conditions brought on
by seasonal upwelling occurring in the Gulf of Panamá hinder the development of coral
reefs in the Pacific. Several authors maintain that the Gulf of Chiriquí is a non upwelling
environment. While this might be generally the case, implications of the effect of
upwelling in the Gulf of Panamá for the adjacent Gulf of Chiriquí are currently unknown.
Understanding the total contribution of coral systems to primary production and
nutrient cycling in a highly dynamic environment like the Gulf of Chiriquí is a complex
undertaking, especially when large nutrient pulses may be periodically delivered to the
reef from far, offshore upwelling. Upwelled waters also bring associated biotic and
trophodynamic feedback on reef systems such as changes in respiration and production
levels resulting from interactions between phytoplankton and zooplankton in transport.
Zooplankton, whose abundances can increase due to advective transport and prey
availability from upwellings (Pineda 1991, Gomez-Gutirrez et al 2000) are thought to
provide heterotrophic corals with nutrients such as fixed carbon, nitrogen and phosphorus
that are not supplied by zooxanthellae. Coral feeding rates (Pocillipora gigantea and P.
damicornis in the Gulf of Panamá) vary with changes in zooplankton abundance over the
lunar cycle, suggesting that these corals must adjust to periodic changes in sources of
fixed carbon and nutrients over relatively short timescales (Palardy et al. 2006).
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Explaining coastal temperature-salinity anomalies
This study identified regional pulses of cool, hypersaline water measured along
the coast and warmer, less saline environments offshore (Figs. 11 & 12). Nearshore
measurements at the PLUTO observatory on Canales de Tierra Island also confirmed this
(Fig. 48). Because the Gulf of Chiriquí is a predominantly exposed, south facing body of
water, an attempt was made to explain these phenomena through localized, wind driven
seiching.
Wind driven seiches
Seiches are standing waves that oscillate in a pendulous fashion around a fixed
node and develop as a result of atmospheric, tidal or wind forces. Oscillations of this
type are commonly observed between islands and other semi-enclosed basins such as
bays, gulfs, and harbors (Knauss 2005). Wind driven seiches occur when chronic wind
stress acting across a given fetch of surface water results in a subsequent sloping (piling
up of water) in the direction of the wind. This displacement of water creates a horizontal
pressure gradient (hydrostatic pressure) proportional to the slope of the sea surface.
When wind stress is relaxed, the water returns downslope toward lower pressure,
accelerating proportional to the length of the surface slope. This results in an oscillation
(between the shore and the open ocean in this case) where the motions of water particles
in the standing wave are primarily vertical at the antinodes and become increasingly
horizontal at the nodes (Kennish 2001).
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Figure 48: Cumulative PLUTO measurements for the month of February 2007 corresponding to Towfish-TETHYS survey time periods. Notice the high frequency and large amplitude temperature fluctuations ranging from 16 °C to 28°C over a 24 hour cycle. Salinity values remain above 28 PSU and there is a tendency for pH to become more alkaline with these pulses suggesting that these pulses are coming from offshore water masses rather than terrestrial freshwater. Also note the nearly 4 meter tidal amplitude occurring from February 17th- 24th.
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In order to test if various wind regimes encountered during the survey could be
sufficient to produce a seiche across the Gulf of Chiriquí and erode the thermocline, a
simplified basin model was used to calculate potential seiche heights. The density of the
epilimnion was computed using the measured average values of salinity, temperature, and
depth across the surface waters surveyed. Assumptions for values of the hypolimnion
were based on reports for the Gulf of Panamá during February and March upwelling
season (Glynn & Maté 1997). A wind fetch of 50 km was determined based on GIS
analysis of the distance from the edge of the 100 meter isobath which defines the
majority of the shelf until the nearshore where the surface waters were surveyed. For the
purpose of this calculation the thermocline was assumed to exist at 50 meters37 which
would also be sufficiently shallow enough for a thermocline to exist over the entire shelf.
The gulf was assumed to be a rectangular basin with two antinodes, of uniform depth and
benthic texture, non-sloping and non-turbulent.
37 The equatorial pacific open ocean thermocline ranges between 50 and 100 meters (Kennish 2001).
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Symbolic notation of parameters used for calculating a seiche height:
Assuming the height (H) of a surface seiche can be approximated as a function of: oτ = Surface stress
DC = Coefficient of drag over water (1.6 * 10 -3)
airρ = Density of atmosphere near water surface (1.2*10 -3 g/cm3) windU 2 = Velocity of wind (cm/sec)2
L = Length of the basin (m) g = acceleration due to gravity (9.81 m/sec2)
hypoρ = Density of hypolimnion (g/cm3)
epiρ = Density of epilimnion (g/cm3) ρ = Average density of hypoρ and epiρ z = Average depth (m)
tσ = Equation of state of seawater ↔ depth (m), temperature (° C), salinity [‰]. = Density of surface seawater @ STP ≈ 1027 kg/m3
Epilimnion tσ = (2 m, 28 °C, 32 [‰]) measured (February 2007) Hypolimnion tσ = (50 m, 15 ° C, 35 [‰]) assumed as reported by (Glynn & Maté 1997) Lenth of Basin = 50 kilometer fetch Equations for calculating seiches
The following equations are derived from (Knauss 2005, Fischer et al. 1979, Mei 1989).
Equation 4 Surface Wind Stress
windairDo UC 2ρτ =
Equation 5 Surface setup
zgi oo ρ
τ=
Equation 6 Height of surface seiche
LiH o=
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Equation 7 Seiche slope
⎟⎟⎠
⎞⎜⎜⎝
⎛
−=∠
epihypo
iiρρ
ρ0
Equation 8 Seiche maximum amplitude
2* LiA
∠
=
Calculating potential seiche heights for the Gulf of Chiriquí
Results of the calculated potential seiche heights in relation to wind velocities
over the basin area 50 meters deep were plotted to determine seiching characteristics (Fig
49). The maximum seiche amplitude (Eq. 8) for sustained 1400 m/s (30 mph) winds
acting over a 50 km water surface was only 302.98 cm. This is an order of magnitude
smaller than the 50 meter displacement needed to bring the thermocline to the surface. In
fact, 30 mph winds would have to act constantly over a 500 km fetch to create roughly 30
meter maximum amplitudes. Although there certainly may be storm situations or
typhoons with wind velocities that could cause the thermocline to shoal in this manner,
an alternative explanation for the cold water pulses appearing along the coast should be
explored.
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Calculated Seiche Height in Gulf of ChiriquiEpilimnion = (2 m, 28 deg C, 32 ppt) measured
Hypolimnion = (50 m, 15 deg C, 35 ppt) assumedFetch = 50 kilometers
0
5
10
15
20
25
30
35
0 0.5 1 1.5 2 2.5 3 3.5 4Seiche Height (cm)
Win
d sp
eed
(mph
)
0
200
400
600
800
1000
1200
1400
1600
Win
d sp
eed
(cm
/sec
)
Figure 49: Graph of calculated potential seiche amplitudes in the Gulf of Chiriquí using various wind velocities encountered during the survey. Wind velocity (y-axis) is presented in cm/s and equivalent miles per hour. Seiche height is plotted in centimeters.
Alternate hypothesis: Internal Waves from Tidal Oscillations
A more likely explanation is that the cool pulses observed along the coast with the
towed CTD (Fig. 11) and independently at the PLUTO mooring (Fig. 14 & Fig. 49) were
manifestations of a localized upwelling caused by an internal wave generated by tidally
induced density flows. Internal waves travel slower than surface waves; however they
can attain much greater heights (Mei 1989). These types of waves normally propagate
along a pycnocline and may be caused by tidal oscillations, currents, or higher order
constructive interference from surface waves. Assuming an internal wave hypothesis, a
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mechanism could exist (e.g. Perlin et al. 2005) where cold stratified ocean water advects
westward and northward along the thermocline from primary upwelling areas (i.e. as part
of the Panamá Current during the dry season). The tidal wave might then propagate as an
advancing front, moving across the shallow shelf along the thermocline where it shears
along a density discontinuity near shore (Leichter et al.1996, Mei 1989, Fischer et al.
1979). This phenomenon is hypothesized to occur especially when tidal fronts move over
shallow shelf regions with large tidal amplitudes and begin to resonate over some
fundamental frequency or harmonic related to basin aspect and tidal period (Mei 1989,
Muller & Briscoe 2000). Tides on the Pacific coast of Panamá are semi-diurnal and
amplitudes may range up to 6 meters (D’Croz & Robertson 1997) and the Gulf of
Chiriquí is known to have tidal ranges of 5 meters or more (Glynn & Maté 1997). Tides
observed during this study period reached amplitudes in excess of 4 meters (Fig. 14).
As the unstable water mass shoals into a turbulent bore and begins mixing with
ambient surface water, it could potentially bring dissolved or suspended material and
organisms associated with the thermocline (Piñeda 1991, Svendsen 1997). During
laboratory experiments, high frequency, breaking, internal waves produced turbulent
conditions and increased instantaneous velocities near the bottom (Cacchione 1970). If
these conditions hold true, the internal waves could potentially re-suspend significant
amounts of bottom sediments and organic Material. The velocity of these waves may also
influence nutrient uptake rates for reefs because, at scales of 1 to 10 meters, coral reefs
possess drag coefficients that are ten times larger than drag coefficients for muddy or
sandy seabeds (Monismith 2007). Furthermore, the physical structure of reefs and coral
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sand, trap and mineralize particulate organic matter and are at least partially responsible
for the regeneration of nutrients (ammonium, nitrate, nitrite, phosphate, and silicate) in
oligotrophic coral reef waters (Rasheed et al 2002).
Coral Reefs, Fringing Reefs, Patch Reefs, and Coral Communities
Not much has changed since Charles Darwin’s 1842 description and classification
of coral reefs into the basic morphologies of barrier, fringing, and annular reefs (atolls).
A fourth type of reef architecture, the patch reef is commonly recognized as a distinct
reef type. There is no precise definition, per say, of a patch reef, but generally speaking,
patch reefs are often small, isolated, colonial aggregations or clusters of individual corals
lacking a cohesive spatial morphology or pattern that transcends the variability of size or
spacing of the groups.
While this study has identified areas containing scleractinian corals stretching
along the coast and the offshore islands, true “coral reefs” normally reported in the
literature, are actually infrequently encountered in this region. Fringing reefs are more
common on the offshore islands, while most other assemblages, especially near the coast,
resemble patch reefs. Furthermore, it has been shown that due to the effects of patch size
and habitat type, small patches may contain more species than larger patches and
different patch size may qualitatively contain different community assemblages (Niegel
2003, Prada et al 2007).
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Coral assemblages in Pacific Panamá exhibit relatively low diversity and are
patchy with pronounced zonations (Glynn 1976). Beyond semantics, there is additional
value added in further differentiating between a ‘coral community’ and a ‘patch reef’ that
goes beyond discriminating between physical morphologies or meta-architectures. For
example, a diversity study within the Coiba National Park (MPA) showed that coral
communities sustained higher species richness of scleractinian corals and octocorals than
coral reefs and may serve as an important larval source for replenishing damaged
neighboring areas (Guzmán et al. 2004).
Marine Conservation Issues in the Gulf of Chiriquí
Up until this point, this thesis has characterized the dry season ocean water
environments in which various sessile communities exist in the Gulf of Chiriquí. The
next step is to determine if these conditions exist perennially and if not, to quantify the
magnitude of change and variability. Increased rainfall in the wet season may amplify
both point source and non-point source terriginous and anthropogenic input into these
systems.
Rapid coastal land use change
To elaborate, there are many indirect effects of land use change that affect the
coastal marine environment. Panamá has experienced large scale deforestation (FAO
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2002) which subsequently increases sedimentation and runoff to the sea. Natural land-
sea nutrient buffers like riparian vegetation, estuarine seagrasses and mangroves are
important in ameliorating nutrient and sediment loading onto reef systems. Loss of these
terrestrial and coastal habitats could be problematic to Panamá reefs in general. For
example, an estimated area of 46,480 hectares of mangroves existed in the Gulf of
Chiriquí 15 years ago, and now the mangrove extent has dwindled to approximately 7,
748 hectares (AECI 2002). Additionally, the mangrove and estuarine systems in the Gulf
of Montijo and Gulf of Chiriquí support a commercial and artisanal shrimp fishery and
serves as nurseries for fish, crustacean and various other invertebrates (D’Croz 1993).
Fishing out the fisheries
The effects of over fishing38 or fishing with improper techniques and technologies
also have direct implications that resonate within coral ecosystems and affect coral
community interactions. Shrimp trawlers (e.g. in the Gulf of Montijo) fish close to the
mangrove shoreline over the mudflats and unregulated use of heavy drag nets along the
bottom damages benthic habitat and organisms (Maté 2006).
Recreational SCUBA diving
Recreational SCUBA diving is very popular in Caribbean Panamá and rapidly
becoming a major tourist attraction in Pacific Panamá. The Tourism Institute of Panamá
38 There is a (90%) bycatch associated with the shrimp fishery and even though Panamá’s commercial shrimp fleet is capped at 232 vessels, a significant number of foreign vessels (often illegally) fish along Pacific Panamá’s coast, resulting in conflicts with artisanal fleet over resource usage (Gomez & Castillo 2007).
137
(IPAT) is currently promoting “tourism development zones” with equally vague
definitions of ‘tourism’ and ‘development’. Tourism and sportfishing travel guides
zealously promote the pristine nature of Coiba Island and the Hannibal Banks fishing
grounds. There are currently five official recreational Scuba charters operating in the
greater Gulf of Chiriquí and due to the nature of strong currents flowing around Coiba
Island, only certain areas are suitable for diving tourism39. The increased boat congestion
and anchorages have been physically damaging to these reef areas. An obvious solution
would be to establish a few permanent moorings in heavily used areas where the diving
vessels could tether. A mutually beneficial aspect could be derived by utilizing
recreational diving operations already in existence in the Gulf of Chiriquí to begin a long
term monitoring program with a program such as REEF CHECK. Although this survey
used the REEF CHECK protocol primarily for comparison of results with the prototype
imaging technology, as of yet, no specific survey protocol has been tailored for species
assemblages in the Eastern Pacific. A field identification guide for corals was created as
part of this thesis to train Spanish speaking divers as well as to facilitate environmental
awareness and stewardship of local fishing communities (Appendix: Fig. 59).
Legislation, Economics and Enforcement
Economic pressures and social agendas often govern the success of environmental
stewardship programs. In Panamá, despite the creation during the mid 1990’s of a legal
framework for protecting the marine environment, legislation is confusing and often
39 Personal communication with SCUBA Coiba and Buzos Boca Brava dive operators.
138
contradictory. Institutional oversight of marine resources in Panamá lacks interagency
coordination and is hindered by unstructured, under-funded enforcement (Suman 2002).
Neither does Panamá have a government institution that is able to directly support
scientific research of the environment. Conservation objectives are equally difficult to
achieve without popular support or public awareness of the issues. Coiba Island
possesses a relatively pristine environment 40 with unique terrestrial and marine
biological endemism (IUCN 2004) and has recently been the center of heated controversy
regarding concessions to allow development within the park (Canfield et al. 2005).
This project was funded in part, to facilitate international exchange of ideas and to
provide ecologic information that may be used in an applied manner to directly inform
regional conservation efforts. The baseline chemical data and digital photomosaics of
coral communities generated in this research were integrated into a G.I.S. format and
given to the Autoridad Nacional del Ambiente (ANAM) of Panamá. Results and
recommendations were also presented in public lectures41 to scientists, Non
Governmental Organizations, resource managers and policy makers who were
concurrently developing a strategic management plan for the Coiba Island Marine Park.
40 From 1919 to 2004, Coiba Island was an active penal colony until becoming a World Heritage Site in July 2005. Approximately 2,029 head of cattle, 70 horses, 18 pigs, 200 dogs which belonged to prison staff and inmates still inhabit the island (IUCN 2004). 41 Latin America and the Caribbean U.S. Fulbright conference; El Salvador, (May 07, 2007); Evaluación ecológica opto-química de hábitats del arrecife del Pacífico Panameño, at the Smithsonian Tropical Research Institution (STRI) Earl S. Tupper Auditorium, Panamá, (August 01, 2007).
139
Advancing Continuity of Observation in Dynamic Marine Environments
Noninvasive techniques with rapid information turnaround inherently improve our
understanding of multi-level processes affecting tropical reef systems such as those
within the Pacific Biological Corridor. This thesis creates a new spatial-temporal
continuity for understanding disturbance and change in dynamic underwater
environments. These technologies and methods provide overlapping scales of observation
that enable study of complex adaptive systems by explicitly addressing issues of
resolution, range, frequency and duration of measurement.
At the finest scale, SCUBA COP enables rapid imaging of the benthos at
centimeter-scale pixel resolution across hundreds of meters. Employing hybrid methods
of expert classification and automated image analysis, the features of interest embedded
within the mosaics (e.g. individual coral, a coral colony, and a coral community) are
identified and the relevant information is extracted. With complementary technologies
these community structures can be contextually placed within similar scale or larger
biogeochemical processes to compare factors such as localized water mass mixing,
regional productivity, or ecosystem nutrient cycling.
The TowSled-TETHYS platform, using high frequency sample rates, can produce
chemical measurements with sub-meter scale precision across hundreds of kilometers.
Tethered observatories like PLUTO provide high resolution time series chemical data
140
sets across temporal dimensions on orders ranging from seconds to years. All of these
technologies can be nested within even larger aperture, remote sensing systems such as
SeaWiFs and Landsat TM. These satellites transmit kilometer-scale resolution data over
thousands of kilometers, enabling synoptic observations of ocean-atmospheric-terrestrial
interactions across entire biomes. An ensemble of tools and techniques such as these
enable scientists to begin to quantify and predict relationships associated with
environmental stress and global change as well as examine in finer detail, natural and
human processes affecting biologic organisms, regional communities and entire
ecosystems (Fig. 50).
141
Figure 50: Conceptual diagram relating scales of observation in marine ecology to natural phenomena in the marine environment. The dashed asymptote represents a theoretical horizon between biologic and physical processes operating in the marine environment. The figure in the middle is an anthropomorphized symbol emphasizing human scale in relation to these factors. Ovals represent spatial temporal attributes of each sensing technology and the manner in which they overlap.
142
CONCLUSION
Gulf of Chiriquí coral communities may be highly susceptible to man made
disturbances because of their inherently small and patchy distributions in shallow coastal
areas. As this study demonstrated, hard coral coverage in selected regions of the Gulf of
Chiriquí averages <10 % for relatively “pristine” island regions and is confined to mostly
shallow water areas in less than 15 meters depth. Analysis of transect data among all
sites surveyed showed Uvas Island, Canales de Tierra, and Canales de Afuera as having
the most hard coral coverage with similar variability, while the Secas Island located in
the offshore region of the western Gulf of Chiriquí behaved more like Managua Island
and Punta Miel; both located in the enclosed bay of Bahia Honda along the coast and
possessing low coral coverage. One of the salient observations of community structure
were the distinct habitat zonations that were apparent both near the coast and surrounding
offshore islands. These zones were typified by patchy hard coral assemblages that often
excluded other sessile invertebrates. Other consistently unique demarcations were soft
coral - gorgonian communities which lived at greater depths, in rocky areas with strong
currents and colder water. High algal coverage was common in sandy areas and
rhodolith aggregations often competed with P. damicornis for spatial dominance in patch
reefs of offshore islands.
Offshore surface waters were relatively well mixed from the surface to 15 meters
depth, while the temperature and salinity data from coastal transects showed regional
pulses of cool water with higher salinity than offshore transects. Future studies should
143
investigate if this is a localized upwelling phenomenon caused by tidal oscillations. The
Secas Island region extending from the estuarine mouth of Boca Chica in the western
Gulf of Chiriquí is potentially subject to terrestrial chemical perturbations because it
receives significant freshwater input mixing over shallow bathymetry. Similarly, water
quality changes from nearby coastal regions should be monitored to detect influences
affecting the Coiba marine park and marine life. Islands closer to the coast including
Canales de Tierra and Canales de Afuera may be influenced by water flushing from
Bahia Honda where high levels of CDOM and methane were encountered. Furthermore,
high variability in chemical data sets over the channel between these islands suggests
mixing of distinct water masses coming from the central Gulf of Chiriquí and another
moving west from the Gulf of Montijo. This was observed most notably by the
differences in measurements of carbon dioxide, nitrogen, and methane on either side of
the island chain that extends north from Coiba Island to Canales de Tierra near the
mainland.
Previous studies have shown that salinity values for the Gulf of Chiriquí decrease
during the wet season. This implies more freshwater input from land regions. The
chemical components of this project were measured during the height of the dry season
after approximately 45 days without precipitation. It is expected that even higher levels
of CDOM, chlorophyll-a, and methane would be measured during a similar survey in the
rainy season. The levels of carbon dioxide and oxygen relative to one another may be
harder to predict, however if primary productivity increases to full capacity these levels
might rise in tandem.
144
Areas prone to eutrophication were observed along enclosed coastal areas such as
Bahia Honda and the region to the south of Santa Catalina which is adjacent to the Gulf
of Montijo. Moving west along the coast from Santa Catalina the waters become
increasingly oligotrophic up until the eastern opening of Bahia Honda bay. This trend
continues again going further west along the coast from the other side of Bahia Honda
until the next large bay, Pixvae. These oligotrophic coastal regions are concordantly
where the largest patch reefs were encountered, some even existing near river outputs like
Río Ballena. They also border micro island clusters less than 1 kilometer from shore (i.e.
Octavios, Pelonas and Cativos) which is where exuberant assemblages of gorgonians and
soft corals were encountered. Incidentally these waters also provide Tuna, Bonito,
Wahoo, Pargo, and Spotted ray fishing grounds for local artisanal fleets. Unfortunately
coastal real estate development, construction and agriculture which is rapidly
encroaching on this area may change the pristine nature of this stretch of coast and
negatively affect the littoral reef communities.
It is increasingly evident that humans, compared with other organisms, exert a
disproportional effect on other species inhabiting Earth. For marine conservation
applications it is essential to develop methods that are able to predict the consequences of
human perturbations on otherwise natural processes occurring in aquatic environments.
According to contemporary ecological theory, habitats and diversity of living
assemblages are complex, adaptive systems thought to exist in natural states of dynamic
equilibrium. Rigorous and repeatable measures of natural variability in biological
systems are required in order to establish baselines that enable quantitative comparisons
145
of patterns of change over time and space. This is difficult to achieve given that ecologic
scales of change are often external to coherent notions of human memory and transcend
dimensions of our immediate corporeal existence.
Habitat degradation and diversity loss is not always a natural process of slow
attrition. To avoid extinctions or other ecological travesties attributable to human
negligence, apathy or ignorance, we must enhance our ability to detect small changes and
predict potential threats over large areas in a relatively short time frame. Semi-automated,
in-situ chemical and optical sensor innovation and analytical methods such as the ones
developed for this project, reduce survey time and increase the ability to effectively focus
and tune experimental efforts with complementary field or laboratory methods. In
concert, these technologies and methods will help scale pattern to process and resolve
long-term ecosystem trends in the coastal ocean with much finer dimensional detail.
Scientifically, this thesis elucidates an emergent spatial-temporal continuity in
underwater ecological observation that ranges across several powers in magnitude.
Philosophically, we must give pause to wonder the magnitude of our effect within these
powers.
146
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APPENDIX
SCUBA Coiba dive logs
Figure 51: Average monthly visibility (meters) plotted from 3 year SCUBA Coiba dive logs. The red solid lines show visibility at a small island less than 1 km from the coast. The dashed blue line shows visibility at a dive site on the north end of Coiba approximately 30 km from the coast.
Average Monthly VisibilityOffshore: Coiba Island
Nearshore: Octavia Island
02468
1012141618
J F M A M J J A S O N DMonth
Met
ers
Visi
bilit
y
Surface Coiba Bottom Coiba Surface Octavia Bottom Octavia
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Figure 52: Average monthly water temperature (°C) at a Coiba Island dive site over a 3 year period. Orange line shows temperature at depth, and blue line shows surface temperature. Data provided by Rachel Fulton and Herbie Sunk of SCUBA Coiba.
Benthic Categories from REEF CHECK v.2004
Table 8: Benthic Categories used for multi method comparisons during transect surveys.
Benthic Categories HC hard coral SC soft coral RKC recently killed coral NIA nutrient indicator algae SP sponge RC rock RB coral rubble SD sand SI silt/clay OT other (Rhodolith)
Isla Coiba Average Water Temperature
22
24
26
28
30
J F M A M J J A S O N D
Month
Tem
pera
ture
deg
. C
Surface (<2m) Depth (>10m)
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Results from REEF CHECK v. 2004 Point Intercept Transect (PIT) method
Mean % Benthic Cover: Isla Canales de Afuera(N7 40 41.3 W81 36 39.5)
05
101520253035404550
HC SC RKC NIA SP RC RB SD SI OT
Mean
% C
over
+ -
SE
Figure 53: REEFCHECK results: Mean % Benthic Cover: Isla Canales de Afuera. The following figures provide a data summary for SCUBA diver REEFCHECK V.4.0 protocol for transects in the Gulf of Chiriquí Panamá (February 2007). Graphs depict mean percent benthic cover of 10 categories at each site. Data points were collected every 0.5 meters along 50 meter transects perpendicular to shore at depth ranges from 6 to 12 meters. Lines extending above the bars represent standard error (+/- SE). Site locations are given in geographical coordinates below each title. Table 8 provides an explanation of each benthic category shown in the graphs.
166
Mean % Benthic Cover: Isla Uvas (N7 48 55.2 W81 45 34.0)
0
10
20
30
40
50
60
HC SC RKC NIA SP RC RB SD SI OT
Mean
% C
over
+ -
SE
Figure 54: REEFCHECK results: Mean % Benthic Cover: Isla Uvas
Mean % Benthic Cover: Isla Canales de Tierra(N7 44 40.8 W81 34 40.0)
0
10
20
30
40
50
60
HC SC RKC NIA SP RC RB SD SI OT
Mean
% C
over
+ -
SE
Figure 55: REEFCHECK results: Mean % Benthic Cover: Isla Canales de Tierra
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Mean % Benthic Cover: Punta Miel, Bahia Honda(N7 44 26.2 W81 32 24.1)
0
5
10
15
20
25
30
35
40
HC SC RKC NIA SP RC RB SD SI OT
Mean
% C
over
+ -
SE
Figure 56: REEFCHECK results: Mean % Benthic Cover: Punta Miel, Bahia Honda
Mean % Benthic Cover: Isla Managua, Bahia Honda(N7 44 30.4 W81 31 06.8)
0
10
20
30
40
50
60
70
HC SC RKC NIA SP RC RB SD SI OT
Mean
% C
over
+ -
SE
Figure 57: REEFCHECK results: Mean % Benthic Cover: Isla Managua, Bahia Honda
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Mean % Benthic Cover: Punta Damas, Isla Coiba(N7 30 00.7 W81 40 12.2)
05
101520253035404550
HC SC RKC NIA SP RC RB SD SI OT
Mean
% C
over
+ -
SE
Figure 58: REEFCHECK results: Mean % Benthic Cover: Punta Damas, Isla Coiba
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Benthic Category Codes and Coral Species
Table 9: Table of Benthic Category Codes and Coral Species created to train automated image segmentation and classification
Category Code
Category Species Code
Species Category Code
C Coral GP “Gardineroseris planulata” C SC Soft Coral MB “Millepora boschmai” C RKC Recently Killed Coral MI “Millepora intricata” C MA Macro Algae MP “Millepora platyphylla” C SP Sponge PAC “Pavona clavus” C RC Rock PAF “Pavona frondifera” C RB Coral Rubble PAG “Pavona gigantea” C SD Sand PAM “Pavona maldivensis” C SI Silt PAV “Pavona varians” C CA Coralline Algae POC “Pocillorpora capitata” C TWS Tape, wand, shadow POD “Pocillopora damicornis” C POE “Pocillopora elegans” C POX “Pocillopora eydouxi” C PRL “Porites lobata” C PRP “Porites panamensis” C PSS “Psammocora stellata” C PSO “Psammocora obtusangulata” C LP “Leptoseris papyracea” C DD “Diaseris distorta” C CC “Cycloseris curvata” C ALP “Aplysina Chiriquíensis” SP CAM “Carijoa multiflora” SC TUB “Tubastraea coccinea” SC OCT “Octocoral” SC LEP “Leptogorgia” SC PAG “Pacificorgia SC” NIA “Nutrient Indicator Algae” MA RHO “Rhodolith” CA DCR “Dead Coral Rubble” RB PDC “Physically Damaged Corals” RKC DIS “Diseased corals” RKC RCK “Rock” RC SAN “Sand” SD SIL “Silt sediment” SI T “Transect Tape” TWS TWS “Tape/wand/shadow” TWS
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Offshore TETHYS-Towsled Transects Summary Statistics
Table 10: Summary Statistics for TETHYS-Towfish Chemical Surveys of Offshore Transects and Islands. Arrows between locations indicate transects sampled between locations.
Summary Statistics for Towsled-TETHYS Offshore Transects and Islands:
Average (top) and +/- 1st Std Dev (bottom) Location Bottom
Depth (m) Temp (°C)
Tow Depth (m)
Salinity [‰]
Chl a [µg/L]
CDOM [QSU]
Boca Chica ↔ Isla Secas
-30.56 29.60 -3.31 31.35 0.31 3.86
1.92 0.24 2.66 0.10 0.05 0.99 Isla Seca -19.12 29.77 -2.23 31.40 0.28 3.52 7.68 0.22 2.36 0.05 0.01 0.62 Isla Uvas -45.75 29.79 -2.82 31.23 0.23 1.37 22.98 0.17 2.66 0.07 0.03 0.38 Isla Uvas↔ Coiba -58.10 30.12 -1.44 31.13 0.25 1.52 38.05 0.33 1.94 0.34 0.01 0.48 Isla Rancheria (Coiba) -11.39 29.32 -1.95 31.77 0.26 4.31 6.57 0.30 1.21 0.28 0.01 2.24 Ensenada Arena (Coiba)
-27.96 28.83 -2.44 31.84 0.26 4.77
5.80 1.31 4.05 0.64 0.02 2.23 Punta Clara (Coiba) -10.24 29.45 -1.05 31.60 0.25 2.20 7.96 0.08 1.27 0.02 0.02 1.02 Punta Damas (Coiba) -59.64 29.77 -0.61 31.40 0.15 2.12 27.44 0.68 1.96 0.39 0.09 1.61 Coiba ↔ Can de Afuera -63.97 29.91 -0.25 31.27 0.18 1.46 9.95 0.16 0.84 0.14 0.03 0.59 Canales de Afuera -12.30 28.61 -1.22 32.20 0.25 3.97 17.86 0.18 0.88 0.08 0.03 1.74 Can de Afuera ↔ Can de Tierra
-68.96 29.84 -0.27 31.37 0.25 2.43
8.94 0.16 0.77 0.14 0.01 0.77
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Coastal TETHYS-Towsled Transects Summary Statistics
Table 11: Summary Statistics for TETHYS-Towfish Chemical Surveys of Coastal Transects and Islands.
Summary Statistics for TETHYS-Towfish Coastal Transects and Islands:
Average (top) and +/- 1st Std Dev (bottom) Location Bottom
Depth (m) Temp (°C)
Tow Depth (m)
Salinity [‰]
Chl a [µg/L]
CDOM [QSU]
Sta Catalina -11.37 27.92 -2.24 26.76 0.20 20.25 3.29 0.21 1.95 8.37 0.08 1.51 Sta Cat↔Isla Octavios
-20.48 27.72 -1.84 32.52 0.18 5.49
9.75 0.41 2.49 0.13 0.09 0.49 Isla Octavios ↔ Río Ballena
-29.18 27.80 -1.34 32.53 0.08 4.09
5.47 0.26 2.63 0.06 0.10 0.43 Río Ballena -19.08 27.72 -3.86 32.53 0.21 6.01 1.36 0.47 4.11 0.11 0.09 0.81 Río Ballena ↔ Bahia Honda
-31.79 28.29 -1.42 32.33 0.13 2.22
7.95 0.40 2.66 0.12 0.10 0.41 Bahia Honda ↔ Can de Tierra
-43.17 28.40 -1.84 32.34 0.23 1.11
7.91 0.49 2.96 0.13 0.07 0.29 Bahia Honda -27.09 27.82 -2.77 31.90 0.25 14.27 13.82 0.45 3.73 3.94 0.05 0.05 Can de Tierra ↔ Pixvae
-37.34 28.70 -1.88 32.30 0.05 0.00
11.51 0.34 2.99 0.16 0.06 0.01
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Coral Field Guide for the Gulf of Chiriquí, Panamá
Figure 59: A poster field guide (in Spanish) showing corals and sponges commonly encountered in the Gulf of Chiriquí and their scientific name and classification. Created as a part of this thesis, for the Autoridad Nacional del Ambiente (ANAM) - the environmental and parks authority of the Republic of Panamá.