john j. kinemanapdrc.soest.hawaii.edu/pride/workshop04/kineman.pdfj. kineman, 2004 “integrate...
TRANSCRIPT
J. Kineman, 2004
John J. KinemanEcosystem Scientist
NOAA/NESDIS National Geophysical Data CenterBoulder, Colorado
Research Associate, Cooperative Institute for Research in the Environmental Sciences (CIRES)University of Colorado, Boulder
Co-Chair, ISSS SIG “The Ecosystem Approach”
Chair, C-GTOS WG (2003) for Coastal Ecosystems
Co-Chair, ISPRS WG on Global Databases
J. Kineman, 2004
What Am I Doing?
1985-93 NOAA-EPA-UNEP Data Integration for Global Change research (GIS, metadata, interpolations, Q/C, etc.)
1998- Modeling ecological distributions from data and niche theory
2002- Applied R&D in Ecosystem Informatics for integrated science, assessment, and management» C-GTOS» PRIDE» CSES (Univ. of Colorado)
J. Kineman, 2004
“Integrate diverse data sets to facilitate research and modeling.”
Spatial/temporal, thematic, and statistical compatibility
Interactive Data ServicesProvide custom data displays and access to data files on-line.
Custom data products can also be assembled on-line for delivery on a variety of media.
http://www.ngdc.noaa.gov/maps/
Dataset Selection: B12
EPA (Corvallis) Climate Database and 2xCO2 Predictions: Marks Regional Water Balance Model and Dailey et al. PRISM Model Precipitation
Principal Investigators
Dr. Danny Marks ManTech Environmental Services, Inc. US Environmental Protection Agency, Corvallis, OR
Christopher Daly Oregon State University, Corvallis, OR
Ronald P. Neilson USDA Forest Service, Corvallis, OR
Donald L. Phillips US Environmental Protection Agency, Corvallis, OR
Summary:
These data represent combined modeling efforts at the US EPA Laboratory in Corvallis Oregon as part of the EPA Global Climate Research Program. Global Circulation Model predictions were applied as anomalies to modern climatologies (observed and modeled) to produce a geographically consistent series of high resolution maps for the conterminous United States, showing current climate and predicted conditions under Carbon Dioxide doubling according to four different models. Dataset consists seven thematic layers, and a total of 230 images: a) Digital Elevation Model, b) Regional mask, c) Topographically-Corrected Surface Wind, d)Control and Model Elevation-Corrected Temperatures, e) Elevation-Corrected Temperature-Interpolated Vapor Pressure, f) PRISM Model Precipitation, g) Model-derived Evapotranspiration. Data is gridded at a resolution of 10km x 10km.
Dataset Description (file lists/download)
Dataset Element Descriptions (file download) Technical Reports
Primary References:
Marks, D. 1992. "A continental-scale simulation of potential evapotranspiration for historical and projected doubled-CO2 climate conditions." In: Gucinski, H., D. Marks, and D. Turner (eds.). 1992. Biospheric Feedbacks to Climate Change: The Sensitivity of Regional Trace Gas Emissions, Evapotranspiration, and Energy Balance to Vegetation Redistribution--Status of Ongoing Research.EPA/600/3-90/078. Corvallis, OR: USEPA.
Daly, C., R.P. Neilson, and D.L. Phillips. 1994. "A statistical-topographic model for mapping climatological precipitation over mountainous terrain." J. Applied Meteorology. Vol. 33 No. 2.
Com
preh
ensi
ve M
etad
ata
and
Tech
nica
l Rep
orts
Source:• assistance• incentives• priorities
Quality:• quality analysis• metadata. • technical reports
Integration:• geospatial-
statistical compatibility
• thematic fusion
Interoperability• comparisons /
combinations• modeling support• multiple formats
Total vegetation (NDVI) with average rainfall (above)Net Primary Production (NPP) with average temperature (below)
Data Integration
J. Kineman, 2004
Modeling the Functional Niche
Data analysis
Combined probability
M
“Character Space”
Adaptive Peak
Axis 1 Axis 2
Suitability
Potential niche model
Ecological “Potentials”
J. Kineman, 2004
Mapping Ecosystem Functions (e.g., potential ecoregions)
A generalized “niche” model to map functional classifications at various levels of aggregation. (Kineman)
Temperature Photosynthetic Radiation PrecipitationPrecipitation Soil Water Holding Soil Water Holding CapacityCapacity
J. Kineman, 2004
Kuchler Vegetation
J. Kineman, 2004
Eastern Hardwood Model (T,P,PET)(Single Mode)
Predicted Suitabilities
Main Kuchlerdistribution
J. Kineman, 2004
Designing for Complex Questions
Developing informatics tools...
for Integrated Assessments and Coastal Observing
Adaptive niche model
nn
iiSHSI
/1
1
= ∏
=
Combined probability
M
Combined probability
M
Combined probability
M
Combined probability
M
Combined probability
M
Functional Niche Models
J.J.Kineman 2003
Define/Prepare Controlling Variables
Temperature Photosynthetic Radiation
Precipitation Soil Water Holding Capacity
Data Integration, Quality Assurance, and Analysis
Predicting Ecological Distributions...
J.J.Kineman 2003
Test Global Eco-unit Model, Vectorized (Kineman)
Building a System for Model-based Adaptive Mapping
Integrating Environmental Observations...
PredictiveMaps
Validation Revision
Multi-variate Stratification
Sele
ctda
ta la
yers
√ temp√ precip√ swhc√ PAR
LUI[N]elevVrelPETLAI
Pdens
Add data layer / time period
Remove data layer
100100507550504576864525
Wei
ght
fact
or
Ran
ge
10<23300<700==<10====<2050<
Res
pons
e fu
nctio
n
linearlinearlinearlinearlogsqrtlinearsqre(3x-7)1/xlinear
Define ClassesDefine trainingDefine thresholds
√ System defined
User Definition Delineation Method√ Cluster analysis
Maximum liklihoodBaysian probabilitiesgradient analysis
OutputInput
Decadal-Annual-Seasonal--Monthly--Daily-Hourly
Tim
eSc
ale
start timeend timetime step(run avg.)
Spat
ial
Scal
e of
uni
t
Coarse------
--Fine
Line
frac
tal
dim
ensi
on (F
D)
1.2D---------1.7D
link FD withspatial scale
Preview
Save Model and ExecuteSet preview background image
Previous Next
Reset defaults
FD = 1.3420
Multi-variate Stratification
Sele
ctda
ta la
yers
√ temp√ precip√ swhc√ PAR
LUI[N]elevVrelPETLAI
Pdens
Add data layer / time period
Remove data layer
Sele
ctda
ta la
yers
√ temp√ precip√ swhc√ PAR
LUI[N]elevVrelPETLAI
Pdens
Sele
ctda
ta la
yers
√ temp√ precip√ swhc√ PAR
LUI[N]elevVrelPETLAI
Pdens
Add data layer / time period
Remove data layer
100100507550504576864525
Wei
ght
fact
or
100100507550504576864525
Wei
ght
fact
or
Ran
ge
10<23300<700==<10====<2050<
Ran
ge
10<23300<700==<10====<2050<
Res
pons
e fu
nctio
n
linearlinearlinearlinearlogsqrtlinearsqre(3x-7)1/xlinear
Res
pons
e fu
nctio
n
linearlinearlinearlinearlogsqrtlinearsqre(3x-7)1/xlinear
Define ClassesDefine trainingDefine thresholds
√ System defined
User Definition Delineation Method√ Cluster analysis
Maximum liklihoodBaysian probabilitiesgradient analysis
Define ClassesDefine trainingDefine thresholds
√ System defined
User DefinitionDefine ClassesDefine trainingDefine thresholds
√ System defined
User Definition Delineation Method√ Cluster analysis
Maximum liklihoodBaysian probabilitiesgradient analysis
Delineation Method√ Cluster analysis
Maximum liklihoodBaysian probabilitiesgradient analysis
OutputInput
Decadal-Annual-Seasonal--Monthly--Daily-Hourly
Tim
eSc
ale
start timeend timetime step(run avg.)
Decadal-Annual-Seasonal--Monthly--Daily-Hourly
Tim
eSc
ale
start timeend timetime step(run avg.)
Spat
ial
Scal
e of
uni
t
Coarse------
--Fine
Spat
ial
Scal
e of
uni
t
Coarse------
--Fine
Line
frac
tal
dim
ensi
on (F
D)
1.2D---------1.7D
link FD withspatial scale
Line
frac
tal
dim
ensi
on (F
D)
1.2D---------1.7D
link FD withspatial scale
Preview
Save Model and ExecuteSet preview background image
Previous Next
Reset defaults
FD = 1.3420Preview
Save Model and ExecuteSet preview background image
Previous Next
Reset defaults
FD = 1.3420 EcologicalModeler
24 April 2002Ecosystem Informatics at NGDC
Define Controlling Variables
Temperature Photosynthetic Radiation
Precipitation Soil Water Holding Capacity
• improved data• time series• new measures• higher resolution• error correction
• validation
Eco-region ModelUSGS-NBII
NOAA
test data
J. Kineman, 2004
Ecoregion Model - carbonSpecies Model - manatee
Ecoregion Model
Model Type FileType SK Gaussian type I GN1.mcdDimensions 3Dim-1 Temperature Tavg001Dim-2 Precipitation PRE043Dim-3 PAR PAR5Parameters
FGDC Model-Attri
bute Meta
data?
Entity-AttributeRelations
J. Kineman, 2004
J. Kineman, 2004
Putting it Together In the Field
Grade AGrade BCyberspace
EOL On-Line Field Guide
Location + DNA New Find
J. Kineman, 2004
The READ Project
Regional
Ecosystems
Assessment
Data
Integrated EcosystemInformatics
Critical CoastalEcosystems
• UNEP Global Resources Information Database• UNEP Division of Early Warning and Assessment• UNFAO• NOAA Regional Integrated Science and Assessment (RISA)
Program (Colorado and Pacific)• NOAA Climate Diagnostics Center (CDC)• NOAA PRIDE initiative• NBII/Pacific Basin Information Node• Global Terrestrial Observing System (GTOS)• National Biological Information Infrastructure (NBII)• World Data Center for Biodiversity and Terrestrial Ecology (BTE)• University of Colorado Cooperative Institute for Research in the
Environmental Sciences (CIRES) and Center for the Study of Earth from Space (CSES).
• East Carolina University [email protected]
Partners
J. Kineman, 2004
Central Questions
• What are the critical issues for coastal ecosystem assessment?
• What new informatics are required to support “integrated science,” “ecosystem assessment,” and “ecosystem (-based) management”?
• How can we best prepare information about the status of coastal ecosystems?
• What is the future of data & information management?
R
E
A
D
J. Kineman, 2004
Is Our Information Concept Too Simple?Decoding
Encoding
InformationSystem
NaturalSystem
“The Map is Not the Territory” – Korzybsky“A Modeling Relation with no Largest (single) Model” – Rosen
1 : ∞
J. Kineman, 2004
Contribution to C-GTOS Implementation Plan and PRIDE report to Congress
Four-part Informatics Holarchy
Source• Observations &
observing programs• Early warning /
detection• Measurement
standards• Sensor technology
Sharing• Distributed data
systems• metadata (standards,
architectures, etc.)• Indexing / archiving• Very large databases• Search technologies
Integration• Analysis & generalizations• Quality & restructuring• Model-based products• Adaptive response to
cross-disciplinary problems
• Information systemtechnology
Synthesis• Problem definition• Strategic thinking• Information needs• Research priorities• Specialized products• Communication &
packaging• Synthesis products• Decision-support
technology
Application / Operation
Design / Definition
Research & Technological Development
Sci
ence
/ P
olic
y P
robl
ems
J. Kineman, 2004
Data & Information Hierarchysupply
• Source– Sensors and observing systems– Measurement standards (national & international)– Data & metadata collection protocols– Level 1 corrections (models and procedures)– Quality assurance and control
• Sharing– Ingest, archive, duplication, developing data sets and databases– Documentation/metadata, data reports– Formatting & structuring (GIS spatial/temporal architecture)– Semantic network search capabilities– Dissemination/access (web access, CD’s, geospatial database enterprise, etc.)
• Integration & modeling– Re-design (resampling, interpolation, field models, etc.)– Model-based combination of variables to produce new data products– Thematic and problem-oriented support (databases, products, & information)– Real-time adaptive response to product needs
• Synthesis– Thematic web sites and Reports– Research support services– Outreach & education– Decision support Product
need
the
tradi
tion
the
futu
re
J. Kineman, 2004
A Problem Orientation Framework
Threats & Opportunities
Integrated Assessments
Detection&
Monitoring
Data Sources Problem Analysis Decision Support
Scenarios
Problem Analysis (Scientific and Political)Should Drive Data and Informatics Priorities
and Decision Support Needs
J. Kineman, 2004
Coastal Implementation Plan for Coastal Implementation Plan for Ecosystems (2004):Ecosystems (2004):
Functional Mapping of Global Functional Mapping of Global Coastal Ecosystem Services:Coastal Ecosystem Services:
InternationalInternationalDeltas ResearchDeltas ResearchDatabaseDatabase
An FAO & NOAA Partnership
J. Kineman, 2004
Coastal GTOS FY03 Recommendations(Ecosystems Working Group)
Suite of ecosystem observations
Begin mapping coastal ecosystem functions (model-based mapping)
Pilot/demo for global deltasScientific assessment
Research support database
J. Kineman, 2004
Eco-Habitat POI/measures (mechanistic and complex)
Ecosystem and Habitat Metrics• Eco-regions (classification)• Habitat/eco-unit conversion• Fragmentation, connectivity,
dimension, contagion, etc.)• Biodiversity (species diversity,
hotspots, coldspots)• Desertification (rate, extent)• Deforestation• ESI (Environmental Sustainability
Index)• Coastal Vulnerability Index (UNEP)• Environmental Sensitivity Index
(RPI/NOAA)• Gap Analysis• Protected or managed ecological areas• Indigenous knowledge (?) • Positive feedback disturbances
(ecological memory) (?)• Creeping change (flip potential) (?)
Status of Biota• Fishery resources• Phytoplankton• Threatened species • Biotic migrations, invasions• Vegetation type, extent, change• Forest resources (type, quantity,
height) • Extent of SAV (submerged
aquatic veg.)• Pathogenic microbes • HABs (harmful algal
blooms)• Turnover / extinction
(“unusual marine mortalities” - Heinz)
• Keystone species• Indicator species
Critical Biological Processes• Chlorophyll• Nutrient cycling (N, C, P)• Leaf Area Index• Evapotranspiration • Peat formation • Primary production • Secondary production• Water BOD• Denitrification • DOM, POM [C, N and P])• Nutrient supply • Respiration• Grazing• Bioaccumulation (pollutants)• Nitrogen saturation index (?)
J. Kineman, 2004
Coastal GTOS FY03 Recommendations(Ecosystems Working Group)
Suite of ecosystem observations
Begin mapping coastal ecosystem functions(model-based mapping)
Pilot/demo for global deltasScientific assessment
Research support database
J. Kineman, 2004
J. Kineman, 2004
Structure FunctionFunction
encoding
decoding
caus
ality
implication
Why Map Functions?
Kineman, 1999; after Rosen
∞ : ∞
This relationship is why systems are complex!
J. Kineman, 2004
Functional Clustering
e.g..• Water
cleansing• Biotic
controls• Micro-
climate• Key
species
FunctionalModel
Functional Cluster Model
=(e.g. Productivity)
FunctionalModel
FunctionalModel
FunctionalModel
J. Kineman, 2004
Coastal GTOS FY03 Recommendations(Ecosystems Working Group)
Suite of ecosystem observations
Begin mapping coastal ecosystem functions (model-based mapping)
Pilot/demos for global deltasScientific assessment
Research support database
J. Kineman, 2004
C-GTOS Implementation Plan
Pilot Projects Recommended:
– Ecological functions and vulnerability in deltas• Spatial models for ecosystem functions and vulnerabilities• Deltas research support database
– Distribution of coastal population, urbanization, and impacts• Coastal urbanization products
– Coastal Conservation and Cultural Sites• Protected resources and areas data
R
E
A
D
J. Kineman, 2004
Deltas are Important System Integrators and Indicators
• Rivers• Lakes• Bays and lagoons• Estuaries• Small Islands and reefs• Deltas
**
* * IPCC Coastal Hotspots
J. Kineman, 2004
Coleman and Huh NASA Study of 42 deltas around the world.
J. Kineman, 2004
Are We Losing Our Coastal Deltas?Are We Losing Our Coastal Deltas?
•• Global land loss on the Global land loss on the coastal coastal marginsmargins ANDAND the the interiorinterior of deltas of deltas since 1980’s.since 1980’s.
•• Land loss and socioLand loss and socio--ecological ecological vulnerability the coming decades..vulnerability the coming decades..
Causes? (needs to be assessed)Causes? (needs to be assessed)•• Dams and other hydrological Dams and other hydrological
diversionsdiversions•• Human land useHuman land use•• Climate change and biotic Climate change and biotic
feedbacks to substrate stability?We need to assess the importance of deltas.
feedbacks to substrate stability?
Coastal GTOS Implementation Plan, 2004.Coastal GTOS Implementation Plan, 2004.
J. Kineman, 2004
New Data! 1985-1992land-lossin the Yukon delta
(Coleman, Huh & Dewit, 2004)
J. Kineman, 2004
Deltaic Systems: A Test Case for Integrated Science Informatics
• Geophysical processes (geology/geophysics, soils, hydrology, sediment transport, substrate stability, geochemistry)
• Climate change (Sea level change, warming, severe storms, wave and tide energy, interanual to decadal change)
• Land loss 1985-2000 (causes, extent, impacts, scenarios, models, forecasts)
• Ecosystem functions/services (ecological processes, vegetation, key species, marine habitats, ecosystem goods and services, ecological indicators)
• Society / vulnerability (aquaculture, agriculture, water quality & availability, land use/urbanization, population, health)
J. Kineman, 2004
Toward A Global Data Service:Available Data
• World Deltas (Coleman, Huh, and DeWitt, 2004)
– 27 CD-ROMS received– 42 deltas around the world
• Maps of the drainage basins• Satellite imagery (300 composits)• Aerial photography
– 18 deltas with detailed studies• environmental history• coastline change• industrialization• agriculture
• Florida Keys (Darby & Hart) – small carbonate deltas organic
characterizations• islands, windy key delta
• 1965-2000 coastline of Vietnam and Mekong Delta (Morgan, UNS)
• Mississippi Delta Database (Hart)
– Major environments of Mississippi Delta
– 520 stations– surface sample geochemistry
and organic characterization, • Deltas of Peninsular India (Hart)
– Mahanadi, Krishna, Godavari, Penner, Cauvery
• Arctic Deltas (Jesse Walker)• Nile Delta (Dale Kiefer & Dan
Stanley)• APN Mega-Deltas of Asia
J. Kineman, 2004
Coleman, Huh, & DeWitt, 2004. Major World Deltas: A Perspective from Space.
J. Kineman, 2004
J. Kineman, 2004
J. Kineman, 2004
J. Kineman, 2004
J. Kineman, 2004
New Data!
J. Kineman, 2004
Development in Bangledesh from Night Lights (Dr. Chris Elvidge, NOAA)
2000
1992/3Urban growth
Difference in stable night lights between 1992 and 2000
J. Kineman, 2004
Topographic & Bathymetric Data Fusion Product
(Hawaiian Islands)
David Divins, NOAA, National Geophysical Data Center
J. Kineman, 2004
ObjectivesREAD will explore new informatics capabilities and information products regarding:
• Vulnerability of ecological goods and services,• Ecosystem change with respect to regional and global drivers• Integrated ecosystem assessment and management issues
In:• Global coastal river deltas (C-GTOS)• Island ecosystems (PRIDE)
For the purpose of:• Understanding and responding to complexity
R
E
A
D
J. Kineman, 2004
READ Products
R
E
A
D
ỏ Websiteỏ Deltas change (D2) research and data support portal prototypeỏ Integrated Science and Ecosystem informatics (general)
ỏ Workshopsỏ Scoping: Issues & information needs (Fall, ’04; 2.5 days )ỏ Science & informatics agenda (Early ’05; 2.5 days)
ỏ Reportsỏ Coastal GTOS Implementation Plan (√); next phase (this year)ỏ Contribution to PRIDE Congressional Report (√)ỏ New University Center for Integrated Science and Informatics
(Fall)ỏ READ Pre-Pilot Phase (√); Pilot Project (this year)
J. Kineman, 2004
NOAA White Water to Blue Water Initiative
WW2BW's international Steering Committeeis working to identify existing programs and develop new partnerships that enhance integrated approaches in areas such as wastewater and sanitation, sustainable agricultural practices, integrated coastal management, sustainable tourism, and environmentally sound marine transportation...