examples and opportunities for syntheses of long-term cross site data lter network experimental...
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Examples and opportunities for syntheses of long-term cross site data
LTER NetworkExperimental Forest Network
PR (tropical forest)
NC (southern deciduous forest)
MA (northern mixed forest)
MI (northern deciduous forest)
KS (tallgrassprairie)
SW (shrub desert)
WY (shrub steppe)
OR (wet coniferous forest)
Temperate rain forest
Chaparral
Northern mixed forest
Deciduous forest
Montane coniferous forest
Temperate grassland
Shrub desert
Tropical forest
PR (tropical forest)
NC (southern deciduous forest)
MA (northern mixed forest)
MI (northern deciduous forest)
KS (tallgrassprairie)
SW (shrub desert)
WY (shrub steppe)
OR (wet coniferous forest)
Temperate rain forest
Chaparral
Northern mixed forest
Deciduous forest
Montane coniferous forest
Temperate grassland
Shrub desert
Tropical forest
Temperate rain forest
Chaparral
Northern mixed forest
Deciduous forest
Montane coniferous forest
Temperate grassland
Shrub desert
Temperate rain forestTemperate rain forest
ChaparralChaparral
Northern mixed forestNorthern mixed forest
Deciduous forestDeciduous forest
Montane coniferous forestMontane coniferous forest
Temperate grasslandTemperate grassland
Shrub desertShrub desert
Tropical forestTropical forest
Lotic Intersite Nitrogen Experiment
Early Efforts in LTER Climate Committee
1986 Objectives
• Establish baseline meteorological measurements– Characterize each LTER site– Enable intersite comparisons
• Document both cyclic and long-term changes
• Provide a detailed climatic history– Correlate with bio-ecological phenomena– Provide data for modeling
Climate and Hydrology Database harvester Objectives
– Promote use of data for science, management and education
– Maintain a current data warehouse of multi-site, multi-network, long-term climate and streamflow data
– Provide critical background data in learning about and mitigating environmental change on the continental scale
– Provide accessibility to data through a single portal – Provide a web interface to download, graphically
display, and view data– Facilitate intersite science and foster development of
multi-network datasets
ClimDB/HydroDB Web Pages
http://www.fsl.orst.edu/hydrodb/
Implemented in 2002
Funded provided by LTER and USFS
Small amts of funding to sites to organize datainto format for harvester
Funding for programmingof harvester
ClimDB and HydroDB
41 Sites– 24 LTER sites + 2 International LTER sites– 22 USFS sites – 12 sites include USGS gauging stations
327 Measurement Stations– 154 meteorological– 173 stream gauging (includes 65 USGS)
21 daily measurement parameters– Primarily streamflow, air temperature, precipitation
Over 10 million daily values
ClimDB/HydroDBUser downloads by year:
Year Total Files Plots Views
2003 1840 309 1240 291
2004 931 267 566 98
2005 1737 717 829 191
2006 3199 1886 978 335
2007 1972 946 816 210
2008 2494 1259 888 347
2009* 1597 856 537 204
Total 13,770 6240 5854 1676* Through 8-19-2009
Parameter Parameter Code
Units
Air Temperature airtemp Degrees Celsius (C)Atmospheric Pressure atmpressure Hectopascals (hPa)Dew point Temperature dewpoint Degrees Celsius (C)Global Radiation globalrad Megajoules per square meter (MJm-2)
Precipitation precip Millimeters (mm)Relative Humidity rh Percent (%)Resultant Wind Direction
reswinddir Degrees Azimuth
Resultant Wind Speed reswindsp Meters per second (m/sec)Snow Depth (water equivalence)
snowh2o Millimeters (mm)
Soil Moisture sm Megapascal (MPa)Soil Temperature soiltemp Degrees Celsius (C)Stream Discharge discharge Liters per second (l/sec)Vapor Pressure vappressure Hectopascals (hPa)Water Temperature watertemp Degrees Celsius (C)Wind Direction winddir Degrees AzimuthWind Speed windsp Meters per second (m/sec)
Metadata categories about sites
• Research Area Information
• Watershed Spatial Characteristics
• Watershed Ecological Characteristics
• Watershed Descriptions
• Hydrologic Gauging Station
• Meteorological Station
Data Aggregation Rules
• Values flagged with “Q” or “M” will not be included in monthly or yearly aggregation. Values tagged with “E” will be included. The number of valid values used in the aggregation will be displayed. Sites are encouraged to estimate data values rather than reporting questionable or missing data.
• • If all data values (e.g., data values listed in the header line) are all missing for a period of days,
it is not necessary to “fill in” these periods with null data and “missing” flags. • • Each field in the data is parsed and has its leading and trailing spaces removed before
inspection. Then in this order these operations occur:• • If a data value of 9999 is encountered, its flag will be forced to M.• If an invalid flag code is encountered, an error message will be logged and the record ignored.• If a data value of NULL (nothing) is encountered, the flag will be forced to M • If a flag value is G, the flag will be forced to NULL.• If a flag value is M, the data value will be forced to NULL,• In the case of precipitation, if the flag is T but the data value is NULL (e.g., blank), the flag will
be forced to M and a warning message will be logged.
Interest in exploring stream chemistry responses to environmental gradients and
land use change across continent
Priority solutes San Dimas Experimental ForestFernow Experimental ForestCoweeta Hydrologic LaboratoryBonanza Creek Experimental Forest/Caribou-Poker Creeks Research WatershedH.J Andrews Experimental ForestHubbard Brook Experimental ForestTenderfoot EFLuquillo EF Fraser EF Marcell EF SanteeNitrate 1979 1969 1971 1986 1968 1964 1992 1983 1982 1966 1976Ammonium 1979 1970 1971 1995 1968 1964 1993 1983 1982 1977 1976
Dissolved Kjeldahl Nitrogen 1968 1968 1976Total Kjeldahl Nitrogen 1978 1993 1968Total Dissolved Nitrogen 2005 1995 2005 1995 1988 2005 1997 1994Total Nitrogen 2005 1997
Soluble Reactive Phosphorus 1999 1968 1972 1989 1976Orthophosphate measured by IC 1971 1982 1996
Total Dissolved Phosphorus 1968 1983 1968 2003Total Phosphorus 2008 1974 1992 1968
Dissolved Organic Carbon 2005 1995 2001 1995 2007 1983 1990 2004Calcium 1969 1969 1986 1968 1963 1992 1983 1982 1968 1976Potassium 1969 1969 1986 1968 1963 1992 1983 1982 1968 1976
Additional analytes
Magnesium 1969 1969 1986 1968 1963 1992 1983 1982 1980 1976
Sodium 1969 1969 1986 1968 1963 1992 1983 1982 1980 1976
Sulfate 1979 1969 1971 1986 1970 1964 1992 1983 1982 1980 1976
Chloride 1971 1971 1986 1978 1964 1992 1983 1982 1980 1976
Conductivity 1960 1995 1970 1992 1983 1982 1980 1976
ANC/alkalinity 1971 1986 1968 1992 1984 1980
pH 1960 1971 2002 1968 1963 1992 1983 1982 1980 1976
Silica 1971 1986 1969 1964 1983
Total Aluminum 1995 1964
Dissolved Inorganic Carbon 2002 1983
Particulate Organic Carbon 1983
Total Organic Carbon 1992
Color (Pt-Co) 1966
Nitrite 1993
Hardness 1992
Bicarbonate 1971? 1992 1976
Carbonate 1971? 1992
Flouride 1982
Manganese 1995
Total Iron 1986
Current Experimental Forest Synthesis Database Design
Sites
Site web sites
Contacts
Site disclaimers & agreements
Status of data
Basins
Disturbances
Disturbance details
Names
Standardized methods
Labs
Equipment
Methods
Discharge
Data tables
Chemistry parameters tables
Chem data – instantaneousconcentrations
Chem data – integrated & aggregated
concentrations
Samples - instantaneous
Samples – integrated & aggregated
Chem data – fluxes
ChallengesStandardizing data & issues of comparability
Standard units and nomenclature
Methods
Time steps / aggregation methods
Detection limits
Nitrate
Ammonium
Dissolved Kjeldahl Nitrogen
Total Kjeldahl Nitrogen (unfiltered)
Total Dissolved Nitrogen
Total Nitrogen (unfiltered)
Soluble Reactive Phosphorus
Orthophosphate measured by IC
Total Dissolved Phosphorus
Total Phosphorus (unfiltered)
Dissolved Organic Carbon
Total Organic Carbon
Dissolved Inorganic Carbon
Calcium
Potassium
Magnesium
Sodium
Sulfate
Chloride
Silica
Bicarbonate
Carbonate
ANC/alkalinity
pH
Hardness
Conductivity
Total Aluminum
Preliminary ListOf Analytes
Hierarchical parameter categoriesImportance of standard terminology
Example: Total Nitrogen is ambiguous– Total Nitrogen (unfiltered) and – Total Dissolved Nitrogen
chemistry databases can become unwieldy without organized parameters
Chemistry data standardizationExamples of difficult issues
Chemistry data standardizationExamples of difficult issues
Converting to standard unitsClear labels of original & standard units are important
Example: NO3 (mg/L) is ambiguous
– nitrate as nitrogen, NO3-N (mg N/L)
– nitrate as nitrate, NO3 (mg NO3/L)
Pre-population conversion vs. stored procedures to convert on the fly
Chemistry data standardizationExamples of difficult issues
Detection LimitsDocumenting the detection limit of below detection values
is important
– different researchers /labs’ policies on reporting machine-read values below detection and detection limits vs. only reporting detection limits needs to be reconciled
– a code indicating “below detection” is insufficient
– treatment of historic data for which detection limits are unknown needs to be determined
Question driven, collaborative approach and harvester as a product
Synthesis Papers and Products
Topic 1: Informing national nutrient criteria using long term reference basin data
Topic 2: Examining effects of forest disturbance on stream chemistry dynamics, concentrations and fluxes
Topic 3: Cross site comparison of effects of different calculations of fluxes
Products: peer reviewed papers, metadata on sites and methods, databases structured to allow future cross site harvesting
Chem DB
Developed from desire for cross site stream chemistry
synthesis
Idea to build on Clim/HydroDB
harvester but with increasing
complexity
Synthesis and Networks
• Challenges involved in integrating
legacy data
• Planning for synthesis at the beginning easier
• Importance and value of metadata
• Automated data scripts to keep data current
• Huge benefits and learning from comparing dynamics cross site
• Air temperature; daily minimum, maximum, and mean in degrees Celsius (C)
• Atmospheric pressure; daily mean in hectopascals (hPa)
• Dewpoint temperature; daily mean in degrees Celsius (C)
• Global solar radiation; daily total in MegaJoules per square meter (MJm-2)
• Precipitation; daily total in millimeters (mm)
• Relative humidity; daily mean in percent (%)
• Snow depth (water equivalence); daily instantaneous observation in millimeters (mm of water).
• Soil Moisture; daily mean in megapascals (MPa)
• Soil temperature; daily mean in degrees Celsius (C)
• Stream Discharge; daily mean in liters per second (l/sec)
• Vapor pressure; daily mean in hectopascals (hPa)
• Water Temperature; daily minimum, maximum, and mean in degrees Celsius (C)
• Wind direction and resultant wind direction; daily mean in degrees azimuths (deg)
• Wind speed and resultant wind speed; daily mean in meters per second (m/sec)
ClimDB Parameters