Presentation is loading. Please wait.

Presentation is loading. Please wait.

Presenter Chris Zganjar Spatial Data Analyses Chris Zganjar, Barry Baker, Earl Saxon Multivariate Cluster Analyses Bill Hargrove, Forrest Hoffman Special.

Similar presentations


Presentation on theme: "Presenter Chris Zganjar Spatial Data Analyses Chris Zganjar, Barry Baker, Earl Saxon Multivariate Cluster Analyses Bill Hargrove, Forrest Hoffman Special."— Presentation transcript:

1 Presenter Chris Zganjar Spatial Data Analyses Chris Zganjar, Barry Baker, Earl Saxon Multivariate Cluster Analyses Bill Hargrove, Forrest Hoffman Special Thanks Robert Hijmans Ecoregions under Climate Change A Global Risk Assessment

2 Climate Change is coming to an Ecoregion near you

3 The Nature Conservancy’s 2015 Goal By 2015, The Nature Conservancy will work with others to ensure the effective conservation of places that represent at least 10%* of every Major Habitat Type on Earth.

4 Where, When, and How Much? Can we identify areas of potential refugia? Can we identify areas of severe environmental change?

5 Multivariate Clustering Magnitude of Environmental Change Applications Topics

6 Multivariate Clustering Magnitude of Environmental Change Applications Topics

7 Köppen Classifying Earth’s Systems Omernik Each framework uses different sets of criteria to address different purposes. Bailey Thorntwaite Holdridge Walter and Box

8 Elevation Compound Topographic Index Potential Solar Radiation Available Water Capacity Soil Bulk Density Soil Carbon Density Total Soil Nitrogen Potential Evapotranspiration Precipitation Driest Quarter Precipitation Wettest Quarter Mean Temperature Coldest Q Mean Temperature Warmest Q Bio Temperature Diurnal Temperature Stable Factors Unstable Factors Multivariate Clustering

9 A1FI B1 Emission Scenarios

10 http://www.metoffice.gov.uk/ Spatially Explicit ©David Viner Cell Size: 2.5 o lat x 3.75 o lon

11 topographic variables 2 Models - 2 Scenarios soil variables climate variables Stable Grid Cells: 4 square kilometers Current 2050 A1 2050 B1 2050 A1 UKMO Hadley NCAR / DOE Multivariate Clustering

12 topographic variables 2 Models - 2 Scenarios soil variables climate variables Stable Current 2050 A1 2050 B1 2050 A1 UKMO Hadley NCAR / DOE Geographic Attributes REMOVED Multivariate Clustering

13 Topographic variables Soil variables Climate variables ONLY Geographic and Temporal Attributes REMOVED Multivariate Clustering

14 Data, Data, Data

15 Oak Ridge National Laboratory William W. Hargrove & Forrest M. Hoffman Multivariate Clustering

16 Clusters in a 3-dimensional data space Unique combinations of topographic, soil and climate factors are identified regardless of where or when they occur Sphere color and size indicate the number of map cells per cluster Multivariate Clustering

17 5000 clusters representing current environmental clusters

18 Multivariate Clustering 5000 clusters representing environmental clusters in 2050 2 Climate Models - 2 Emission Scenarios

19 Multivariate Clustering Magnitude of Environmental Change Applications Topics

20 Magnitude of Change

21 Ensemble Mean Environmental Change Maps 2 Models 2 Scenarios

22 Current 2050 Potential Refugia

23 2050 Measure of Climate Change Severity Critical Threat Current

24 Multivariate Clustering Magnitude of Environmental Change Applications Topics

25 Least Change Greatest Change 16km 2 Grid Cell 803 Bailey Ecoregions 500 Current Domains Global data aggregation at three different scales Projected Refugia Highest Risk for Vulnerable Targets

26 Projected magnitude of environmental change under an ensemble mean of 2 GCMs using 2 emission scenarios for 2050, aggregated by Bailey Ecoregions for use by The Nature Conservancy in setting Global Priorities

27 Projected magnitude of environmental change under an ensemble mean of 2 GCMs using 2 emission scenarios for 2050, aggregated by current domains for use by The Nature Conservancy in setting Global Priorities

28 Least Change Greatest Change World Database on Protected Areas Projected Refugia Highest Risk for Vulnerable Targets

29 Least Change Greatest Change Projected Refugia Highest Risk for Vulnerable Targets World Database on Protected Areas

30 Projected magnitude of environmental change under an ensemble mean of 2 GCMs using 2 emission scenarios for 2050, aggregated by ecoregions for use by the UNESCO World Heritage Sites Least Change Greatest Change

31 Where, When, and How Much? Can we identify areas of potential refugia? Can we identify areas of severe environmental change? Yes, We recommend early action to effectively conserve large areas in ecoregions with lowest projected magnitude of change Yes, We recommend and long-term management action to protect the most vulnerable conservation targets in areas of greatest projected magnitude of environmental change.

32 Thank you!


Download ppt "Presenter Chris Zganjar Spatial Data Analyses Chris Zganjar, Barry Baker, Earl Saxon Multivariate Cluster Analyses Bill Hargrove, Forrest Hoffman Special."

Similar presentations


Ads by Google