1. AIP-2 CC&Bio WG Use scenarios Stefano Nativi (CNR) and Gary Geller (NASA/JPL) OGC TC Meeting Valencia, Spain 2 Dec 2008

2. Selected use scenarios CC impact on Pika distribution CC impact on Polar Ecosystems Vegetation changes in Arctic Ecosystems

3. CC IMPACT ON PIKA DISTRIBUTION

4. Abstract distribution of pika and how it is changingThis scenario is driven primarily by scientific research on the distribution of pika and how it is changing. to investigate the interoperability process to determine valuable predictors for the impact of climate change on biodiversityFrom the GEOSS infrastructure perspective, an important objective is to investigate the interoperability process to determine valuable predictors for the impact of climate change on biodiversity to model pika distributions and how they may change with climateUse observations of pika over the last 20 years, plus existing modeling demonstration systems, to model pika distributions and how they may change with climate Users Scientist and decision makers.

5. Context and pre-conditions Area of Interest The US Great Basin region Other regions in Asia may be considered Scientific patrons Dr. Chris Ray (University of Colorado - CO USA) Dr. Falk Huettmann –EWHALE lab- Biology and Wildlife Dept., Institute of Arctic Biology, University of Alaska Fairbanks

6. Context and pre-conditions Resources IPCC data (WMO) Biodiversity datasets (GBIF) Biodiversity datasets (Univ. Colorado) Local CC model: TOPS (NASA/JPL) IP3 ENM server (IP3) IP3 community distributed catalog (IP3)

7. General Approach Researcher selects species of interest based on research needs and data availability Researcher uses GBIF&IP3 components to develop correlation model between species and environment. TOPS data are used if available, otherwise other climate sources can be used. Researcher validates model using additional observations Researcher uses known physiological limits of the species to direct the development of models relating predicted climate change to predicted change in species distribution Researcher uses GBIF&IP3 components to predict how range distributions will contract in the future

8. CC IMPACT ON BIODIVERSITY/ECOSYSTEMS FOR THE POLAR AREA

9. Abstract maps of Arctic biodiversity, habitat and ecological service changesa summarized scenario runs with all relevant metricsThe scenario output will be as maps of Arctic biodiversity, habitat and ecological service changes, as well as a summarized scenario runs with all relevant metrics provided in a simple to comprehend table. –All outputs will carry statistical confidence, and should allow to feed directly into policy making. The scenario models will allow to assess the amount and quality of Ecological Services provided by the ArcticThe scenario models will allow to assess the amount and quality of Ecological Services provided by the Arctic. The activities are intended to be linked with all relevant components of the IPY (International Polar Year). Users This scenario will cater the needs for global public, scientiststhe local decision-maker –the global public, scientists, and more specifically, the local decision-maker for achieving best sustainability options.

10. Context and pre-conditions Predict Future conditions create quantitative associations of biodiversity and habitat with the current and long-term apply these to known and assumed future conditionsTo predict the future scenarios, we will create quantitative associations of biodiversity and habitat with the current and long-term, and then apply these to known and assumed future conditions. Possible biodiversity topics include –Polar Bears presence –plankton, selected benthos species, ringed seals, walrus, narwhale, arctic codand endemic plants. Area of Interest The Arctic (as defined as the 60 degree latitude circle) Scientific patrons Dr. Falk Huettmann –EWHALE lab- Biology and Wildlife Dept., Institute of Arctic Biology, University of Alaska Fairbanks

13. Context and pre-conditions Resources IPCC data (WMO/NCAR) Biodiversity datasets (GBIF) Landasat data (USGS) IP3 community distributed catalog (IP3) IP3 ENM server (IP3)

14. General Approach Environment data has been collected for the Arctic. Biodiversity data has been collected. Group and Stakeholders set up a governance protocol of the project Optimization and Niche Modelling techniques have been developed and validated The user has been trained on use of the niche modeller and applied them globally.Online implementation and fruition

15. VEGETATION CHANGES IN ARTIC ECOSYSTEMS

16. Abstract identify the extent and degree of vegetation changes in response to climate changeThis scenario seeks to identify the extent and degree of vegetation changes in response to climate change in arctic ecosystems, and in particular, the boreal- tundra ecotone. Users –Scientist with expertise in –use of remote sensing –image processing

17. Context and pre-conditions Area of Interest The Arctic (as defined as the 60 degree latitude circle) –with sites where consistent historical satellite data (Landsat) exist Scientist patrons Dr. Douglas Nebert (USGS)

18. Context and pre-conditions Resources –Landsat MSS, 4-band data the primary long-term source of EO data –Climate and weather data records for polar observation sites help establish a local baseline for estimation and comparison. –Elevation data Help understand and extrapolate terrestrial temperature lapse rates from observation sites to test sites. –GeoBrain by GMU –GloVis or Z39.50 client

19. General Approach Identify 30-50 LANDSAT row-path image sites (in tundra, boreal forest, and edge) from the mid-late 1970s and early 2000s Identify suitable imagery pairs for comparison Download and subset imagery pairs (using standard catalog interfaces) Classify the imagery Difference the images to identify changes in the forest landscape calculate and post the change values as registered maps/coverage services