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description: Climate change is expected to alter the distributions and community composition of stream fishes in the Great Lakes region in the 21st century, in part as a result of altered hydrological systems (stream temperature, streamflow, and habitat). Resource managers need information and tools to understand where fish species and stream habitats are expected to change under future conditions. Fish sample collections and environmental variables from multiple sources across the United States Great Lakes Basin were integrated and used to develop empirical models to predict fish species occurrence under present-day climate conditions. Random Forests models were used to predict the probability of occurrence of 13 lotic fish species within each stream reach in the study area. Downscaled climate data from general circulation models were integrated with the fish species occurrence models to project fish species occurrence under future climate conditions. The 13 fish species represented three ecological guilds associated with water temperature (cold, cool, and warm), and the species were distributed in streams across the Great Lakes region. Vulnerability (loss of species) and opportunity (gain of species) scores were calculated for all stream reaches by evaluating changes in fish species occurrence from present-day to future climate conditions. The 13 fish species included 4 cold-water species, 5 cool-water species, and 4 warm-water species. Presently, the 4 cold-water species occupy from 15 percent (55,000 kilometers [km]) to 35 percent (130,000 km) of the total stream length (369,215 km) across the study area; the 5 cool-water species, from 9 percent (33,000 km) to 58 percent (215,000 km); and the 4 warm-water species, from 9 percent (33,000 km) to 38 percent (141,000 km). Fish models linked to projections from 13 downscaled climate models projected that in the mid to late 21st century (204665 and 20812100, respectively) habitats suitable for all 4 cold-water species and 4 of 5 cool-water species under present-day conditions will decline as much as 86 percent and as little as 33 percent, and habitats suitable for all 4 warm-water species will increase as much as 33 percent and as little as 7 percent. This report documents the approach and data used to predict and project fish species occurrence under present-day and future climate conditions for 13 lotic fish species in the United States Great Lakes Basin. A Web-based decision support mapping application termed FishVis was developed to provide a means to integrate, visualize, query, and download the results of these projected climate-driven responses and help inform conservation planning efforts within the region. A geodatabase containing the full dataset of results that are being mapped in FishVis can be downloaded from the FishVis mapping application at http://ccviewer.wim.usgs.gov/FishVis/ or through USGS ScienceBase as a Data Release (Stewart and others, 2016). The geodatabase contains five feature classes, each with their own metadata record and include data attributed to the stream reach (fishvis_reacha83 and fishvis_search_reacha83), catchment (fishvis_catcha83 and fishvis_reacha83), and huc12 (fishvis_huc12a83). The citation for the USGS Scientific Investigation Report that documents this dataset is: Stewart, J.S., Covert, S.A., Estes, N.J., Westenbroek, S.M., Krueger, Damon, Wieferich, D.J., Slattery, M.T., Lyons, J.D., McKenna, J.E., Jr., Infante, D.M., Bruce, J.L., 2016, FishVis, A regional decision support tool for identifying vulnerabilities of riverine habitat and fishes to climate change in the Great Lakes Region: U.S. Geological Survey Scientific Investigations Report 2016-5124, 15 p., http://dx.doi.org/10.3133/sir20165124.; abstract: Climate change is expected to alter the distributions and community composition of stream fishes in the Great Lakes region in the 21st century, in part as a result of altered hydrological systems (stream temperature, streamflow, and habitat). Resource managers need information and tools to understand where fish species and stream habitats are expected to change under future conditions. Fish sample collections and environmental variables from multiple sources across the United States Great Lakes Basin were integrated and used to develop empirical models to predict fish species occurrence under present-day climate conditions. Random Forests models were used to predict the probability of occurrence of 13 lotic fish species within each stream reach in the study area. Downscaled climate data from general circulation models were integrated with the fish species occurrence models to project fish species occurrence under future climate conditions. The 13 fish species represented three ecological guilds associated with water temperature (cold, cool, and warm), and the species were distributed in streams across the Great Lakes region. Vulnerability (loss of species) and opportunity (gain of species) scores were calculated for all stream reaches by evaluating changes in fish species occurrence from present-day to future climate conditions. The 13 fish species included 4 cold-water species, 5 cool-water species, and 4 warm-water species. Presently, the 4 cold-water species occupy from 15 percent (55,000 kilometers [km]) to 35 percent (130,000 km) of the total stream length (369,215 km) across the study area; the 5 cool-water species, from 9 percent (33,000 km) to 58 percent (215,000 km); and the 4 warm-water species, from 9 percent (33,000 km) to 38 percent (141,000 km). Fish models linked to projections from 13 downscaled climate models projected that in the mid to late 21st century (204665 and 20812100, respectively) habitats suitable for all 4 cold-water species and 4 of 5 cool-water species under present-day conditions will decline as much as 86 percent and as little as 33 percent, and habitats suitable for all 4 warm-water species will increase as much as 33 percent and as little as 7 percent. This report documents the approach and data used to predict and project fish species occurrence under present-day and future climate conditions for 13 lotic fish species in the United States Great Lakes Basin. A Web-based decision support mapping application termed FishVis was developed to provide a means to integrate, visualize, query, and download the results of these projected climate-driven responses and help inform conservation planning efforts within the region. A geodatabase containing the full dataset of results that are being mapped in FishVis can be downloaded from the FishVis mapping application at http://ccviewer.wim.usgs.gov/FishVis/ or through USGS ScienceBase as a Data Release (Stewart and others, 2016). The geodatabase contains five feature classes, each with their own metadata record and include data attributed to the stream reach (fishvis_reacha83 and fishvis_search_reacha83), catchment (fishvis_catcha83 and fishvis_reacha83), and huc12 (fishvis_huc12a83). The citation for the USGS Scientific Investigation Report that documents this dataset is: Stewart, J.S., Covert, S.A., Estes, N.J., Westenbroek, S.M., Krueger, Damon, Wieferich, D.J., Slattery, M.T., Lyons, J.D., McKenna, J.E., Jr., Infante, D.M., Bruce, J.L., 2016, FishVis, A regional decision support tool for identifying vulnerabilities of riverine habitat and fishes to climate change in the Great Lakes Region: U.S. Geological Survey Scientific Investigations Report 2016-5124, 15 p., http://dx.doi.org/10.3133/sir20165124.
Citation
Title FishVis, predicted occurrence and vulnerability for 13 fish species for current (1961 - 1990) and future (2046 - 2100) climate conditions in Great Lakes streams.
creation  Date   2018-06-08T02:19:45.078156
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name Dublin Core references URL
URL:http://dx.doi.org/10.5066/F74T6GGG
protocol WWW:LINK-1.0-http--link
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name Dublin Core references URL
URL:http://dx.doi.org/10.5066/F74T6GGG
protocol WWW:LINK-1.0-http--link
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Metadata data stamp:  2018-08-06T20:25:34Z
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notes: This metadata record was generated by an xslt transformation from a dc metadata record; Transform by Stephen M. Richard, based on a transform by Damian Ulbricht. Run on 2018-08-06T20:25:34Z
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organisation Name  CINERGI Metadata catalog
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electronic Mail Addresscinergi@sdsc.edu
Metadata language  eng
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Metadata standard for this record:  ISO 19139 Geographic Information - Metadata - Implementation Specification
standard version:  2007
Metadata record identifier:  urn:dciso:metadataabout:14b360c6-faf1-421d-b4f7-eaa8d351b607

Metadata record format is ISO19139 XML (MD_Metadata)