r03/r03_SEVA_Census_Tract

View In: ArcGIS JavaScript ArcGIS Online Map Viewer ArcGIS Earth ArcGIS Pro

Service Description: A changing climate and its effects on ecosystem services will have broad impacts, however, not all people and communities will be equally affected. This assessment of vulnerability is concerned with identifying communities and geographic areas where climate-change-driven ecological changes have the potential to adversely affect human well-being due to changes in the provision of ecosystem services. Communities that are at greater risk of ecological changes and that lack adaptive capacity are considered more vulnerable. We analyzed vulnerability components of exposure, sensitivity, and adaptive capacity based on available socioeconomic and ecological data. Reporting here includes quantitative and spatially based summaries on community risk, resource sector dependence, and capacity to adapt, as well as an integration of the three vulnerability components. This report extends existing vulnerability reporting focused on national forests by assessing all lands, regardless of ownership, in Arizona and New Mexico. Vulnerability in the Triepke et al. (2019) study is defined as how likely the predominant vegetation is to change under future climate. Vulnerability to climate change was categorized as low, moderate, high, and very high likelihood of change, according to the difference between historic and future climate. The original dataset segments all lands into ecological response units (ERUs)—a classification of lands into 26 ecosystem types (for example, spruce-fir forest, ponderosa pine forest, Juniper grass, semi-desert grassland, sagebush shrubland) to provide a fine subregional landscape analysis. Each ERU is assigned a vulnerability classification and an uncertainty classification based on the agreement of their modeling projections. The polygon geospatial layer was summarized as the percentage of each geography (e.g. census tract) with high or very high likelihood of vegetative change when uncertainty is low or moderate. Calculation using Triepke, F. J., E. H. Muldavin, and M. M. Wahlberg. 2019. Using climate projections to assess ecosystem vulnerability at scales relevant to managers. Ecosphere 10(9):e02854. 10.1002/ecs2.2854

Map Name: r03_SEVA_Census_Tract_01

Legend

All Layers and Tables

Dynamic Legend

Dynamic All Layers

Layers:

SEVA_Census_Tract (0)

Description: A changing climate and its effects on ecosystem services will have broad impacts, however, not all people and communities will be equally affected. This assessment of vulnerability is concerned with identifying communities and geographic areas where climate-change-driven ecological changes have the potential to adversely affect human well-being due to changes in the provision of ecosystem services. Communities that are at greater risk of ecological changes and that lack adaptive capacity are considered more vulnerable. We analyzed vulnerability components of exposure, sensitivity, and adaptive capacity based on available socioeconomic and ecological data. Reporting here includes quantitative and spatially based summaries on community risk, resource sector dependence, and capacity to adapt, as well as an integration of the three vulnerability components. This report extends existing vulnerability reporting focused on national forests by assessing all lands, regardless of ownership, in Arizona and New Mexico. Vulnerability in the Triepke et al. (2019) study is defined as how likely the predominant vegetation is to change under future climate. Vulnerability to climate change was categorized as low, moderate, high, and very high likelihood of change, according to the difference between historic and future climate. The original dataset segments all lands into ecological response units (ERUs)—a classification of lands into 26 ecosystem types (for example, spruce-fir forest, ponderosa pine forest, Juniper grass, semi-desert grassland, sagebush shrubland) to provide a fine subregional landscape analysis. Each ERU is assigned a vulnerability classification and an uncertainty classification based on the agreement of their modeling projections. The polygon geospatial layer was summarized as the percentage of each geography (e.g. census tract) with high or very high likelihood of vegetative change when uncertainty is low or moderate. Calculation using Triepke, F. J., E. H. Muldavin, and M. M. Wahlberg. 2019. Using climate projections to assess ecosystem vulnerability at scales relevant to managers. Ecosphere 10(9):e02854. 10.1002/ecs2.2854

Copyright Text: Triepke, F. J., E. H. Muldavin, and M. M. Wahlberg. 2019

Spatial Reference: PROJCS["North_America_Lambert_Conformal_Conic",GEOGCS["GCS_North_American_1983",DATUM["D_North_American_1983",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-108.0],PARAMETER["Standard_Parallel_1",32.0],PARAMETER["Standard_Parallel_2",36.0],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0]]

Single Fused Map Cache: false

Initial Extent:

Full Extent:

Units: esriMeters

Supported Image Format Types: PNG32,PNG24,PNG,JPG,DIB,TIFF,EMF,PS,PDF,GIF,SVG,SVGZ,BMP

Document Info:

Supports Dynamic Layers: true

MaxRecordCount: 2000

MaxImageHeight: 4096

MaxImageWidth: 4096

Supported Query Formats: JSON, geoJSON, PBF

Supports Query Data Elements: true

Min Scale: 5000000

Max Scale: 0

Supports Datum Transformation: true

Child Resources: Info Dynamic Layer

Supported Operations: Export Map Identify QueryLegends QueryDomains Find Return Updates

r03/r03_SEVA_Census_Tract_01 (MapServer)