Alexa J. McKerrow, PhD (Former Employee)
Science and Products
Aquatic Gap Analysis Vision
The Aquatic Gap Analysis Project (AGAP) works to synthesize existing data and generate new data products to answer complex questions about aquatic species, their habitats and their conservation needs at multiple scales. AGAP is working to build a national data framework that makes data management and sharing efficient.
Species Vision
Our goal is to build species range and predicted habitat maps to support state, regional, and national biodiversity assessments for the conservation status of native vertebrate species and to facilitate the application of this information to land management activities. These data are intended to describe patterns of species geographic location and basic habitat associations.
Land Cover Vision
The goal of the GAP/LANDFIRE National Terrestrial Ecosystems 2011 data is to provide accurate, seamless data on the vegetation and land cover of the United States. The map legend based on NatureServe’s ecological system classification scheme provides detailed information on the vegetation types at a plant community level.
The Gap Analysis Process and Importance
A Gap Analysis consists of mapping three data layers — land cover, predicted distributions of vertebrate species, and a stewardship layer depicting both location and conservation status of protected areas. This data is then assessed to determine how much of a target species’ (plant or animal) habitat is in conserved areas.
Analysis and Visualization of Climate Information to Support USFWS Species Status Assessments
Under the Endangered Species Act, the U.S. Fish and Wildlife Service (USFWS) must evaluate the status of at-risk plants and animals in the U.S. A Species Status Assessment (SSA) is a scientific assessment prepared for each at-risk species to help inform a range of management decisions under the Endangered Species Act. SSA’s are currently needed for more than 350 species, 250 of which are in the So
SERAP: Assessment of Climate and Land Use Change Impacts on Terrestrial Species
Researchers from North Carolina State University and the USGS integrated models of urbanization and vegetation dynamics with the regional climate models to predict vegetation dynamics and assess how landscape change could impact priority species, including North American land birds. This integrated ensemble of models can be used to predict locations where responses to climate change are most lik
SERAP: Modeling of Global and Land Use Change Impacts
The Southeastern United States spans a broad range of physiographic settings and maintains exceptionally high levels of faunal diversity. Unfortunately, many of these ecosystems are increasingly under threat due to rapid human development, and management agencies are increasingly aware of the potential effects that climate change will have on these ecosystems. Natural resource managers and conserv
Southeast Regional Assessment Project (SERAP): Assessing Global Change Impacts on Natural and Human Systems in the Southeast
The Southeastern United States spans a broad range of physiographic settings and maintains exceptionally high levels of faunal diversity. Unfortunately, many of these ecosystems are increasingly under threat due to rapid human development, and management agencies are increasingly aware of the potential effects that climate change will have on these ecosystems. Natural resource managers and conserv
Filter Total Items: 1731
Aquatic Gap Analysis Project (AGAP) Aquatic Species Distribution Modeling on the National Hydrography Dataset Plus Version 2.1
This USGS data release contains products that resulted from aquatic species distribution modeling in the United States on the National Hydrography Dataset Plus Version 2.1. Source data, supporting code and model results are documented in this data release. The file species_model_list.csv provides a list of most recent models for each combination of species, habitat, and region.
U.S. Geological Survey - Gap Analysis Project Species Habitat Richness
The Species Richness Maps included here are based on the Gap Analysis Project (GAP) habitat maps, which are predictions of the spatial distribution of suitable environmental and land cover conditions within the United States for individual species. Individual species habitat distribution models were summed to create the total richness for each vertebrate taxa. The summing process was coded in Pyth
Nelson's Antelope Squirrel (Ammospermophilus nelsoni) mNASQx_CONUS_2001v1 Habitat Map
This dataset represents a species habitat distribution model for Nelson's Antelope Squirrel. These habitat maps are created by applying a deductive habitat model to remotely-sensed data layers within a species' range.
Spotted Owl (Strix occidentalis) bSPOWx_CONUS_2001v1 Habitat Map
This dataset represents a species habitat distribution model for Spotted Owl. These habitat maps are created by applying a deductive habitat model to remotely-sensed data layers within a species' range.
Whip-poor-will (Caprimulgus vociferus) bWPWIx_CONUS_2001v1 Habitat Map
This dataset represents a species habitat distribution model for Whip-poor-will. These habitat maps are created by applying a deductive habitat model to remotely-sensed data layers within a species' range.
Barn Swallow (Hirundo rustica) bBARSx_CONUS_2001v1 Habitat Map
This dataset represents a species habitat distribution model for Barn Swallow. These habitat maps are created by applying a deductive habitat model to remotely-sensed data layers within a species' range.
Brown Creeper (Certhia americana) bBRCRx_CONUS_2001v1 Habitat Map
This dataset represents a species habitat distribution model for Brown Creeper. These habitat maps are created by applying a deductive habitat model to remotely-sensed data layers within a species' range.
Cave Swallow (Petrochelidon fulva) bCASWx_CONUS_2001v1 Habitat Map
This dataset represents a species habitat distribution model for Cave Swallow. These habitat maps are created by applying a deductive habitat model to remotely-sensed data layers within a species' range.
Sonoma Tree Vole (Arborimus pomo) mSTVOx_CONUS_2001v1 Habitat Map
This dataset represents a species habitat distribution model for Sonoma Tree Vole. These habitat maps are created by applying a deductive habitat model to remotely-sensed data layers within a species' range.
Piute Ground Squirrel (Urocitellus mollis) mPGSQx_CONUS_2001v1 Habitat Map
This dataset represents a species habitat distribution model for Piute Ground Squirrel. These habitat maps are created by applying a deductive habitat model to remotely-sensed data layers within a species' range.
Southern Mountain Yellow-legged Frog (Rana muscosa) aSMFRx_CONUS_2001v1 Habitat Map
This dataset represents a species habitat distribution model for Southern Mountain Yellow-legged Frog. These habitat maps are created by applying a deductive habitat model to remotely-sensed data layers within a species' range.
Montane Vole (Microtus montanus) mMOVOx_CONUS_2001v1 Habitat Map
This dataset represents a species habitat distribution model for Montane Vole. These habitat maps are created by applying a deductive habitat model to remotely-sensed data layers within a species' range.
Filter Total Items: 34
Developing fluvial fish species distribution models across the conterminous United States—A framework for management and conservation
This report explains the steps and specific methods used to predict fluvial fish occurrences in their native ranges for the conterminous United States. In this study, boosted regression tree models predict distributions of 271 ecologically important fluvial fish species using relations between fish presence/absence and 22 natural and anthropogenic landscape variables. Models developed for the fres
Authors
Hao Yu, Arthur R. Cooper, Jared Ross, Alexa McKerrow, Daniel J. Wieferich, Dana M. Infante
Methods for evaluating Gap Analysis Project habitat distribution maps with species occurrence data
The National Gap Analysis Project created species habitat distribution models for all terrestrial vertebrates in the United States to support conservation assessments and explore patterns of species richness. Those models link species to specific habitats throughout the range of each species. For most vertebrates, there are not enough occurrence data to drive inductive, range-wide species habitat
Authors
Matthew J. Rubino, Alexa McKerrow, Nathan M. Tarr, Steven G. Williams
Identifying monitoring information needs that support the management of fish in large rivers
Management actions intended to benefit fish in large rivers can directly or indirectly affect multiple ecosystem components. Without consideration of the effects of management on non-target ecosystem components, unintended consequences may limit management efficacy. Monitoring can help clarify the effects of management actions, including on non-target ecosystem components, but only if data are col
Authors
Timothy D. Counihan, Kristen L. Bouska, Shannon K. Brewer, R. B. Jacobson, Andrew F. Casper, Colin G. Chapman, Ian R. Waite, Kenneth R. Sheehan, Mark Pyron, Elise R. Irwin, Karen Riva-Murray, Alexa McKerrow, Jennifer M. Bayer
Applying biodiversity metrics as surrogates to a habitat conservation plan
Unabated urbanization has led to environmental degradation and subsequent biodiversity loss across the globe. As an outcome of unmitigated land use, multi-jurisdictional agencies have developed land use plans that attempt to protect threatened or endangered species across selected areas by which some trade-offs between harm to species and additional conservation approaches are allowed among the pa
Authors
Kenneth G. Boykin, William G. Kepner, Alexa McKerrow
Quantifying the representation of plant communities in the protected areas of the U.S.: An analysis based on the U.S. National Vegetation Classification Groups
Plant communities represent the integration of ecological and biological processes and they serve as an important component for the protection of biological diversity. To measure progress towards protection of ecosystems in the United States for various stated conservation targets we need datasets at the appropriate thematic, spatial, and temporal resolution. The recent release of the LANDFIRE Exi
Authors
Alexa McKerrow, Anne Davidson, Matthew J. Rubino, Don Faber-Langendoen, Daryn (Contractor) Dockter
Refining the coarse filter approach: Using habitat-based species models to identify rarity and vulnerabilities in the protection of U.S. biodiversity
Preserving biodiversity and its many components is a priority of conservation science and how to efficiently allocate resources to preserve healthy populations of as many species, habitats, and ecosystems as possible. We used the U.S. Geological Survey (USGS) Gap Analysis Project (GAP) species models released in 2018, which identify predicted habitats for terrestrial vertebrates in the conterminou
Authors
Anne Davidson, Leah Dunn, Kevin Gergely, Alexa McKerrow, Steven G. Williams, Mackenzie Case
U.S. Geological Survey wildland fire science strategic plan, 2021–26
The U.S. Geological Survey (USGS) Wildland Fire Science Strategic Plan defines critical, core fire science capabilities for understanding fire-related and fire-responsive earth system processes and patterns, and informing management decision making. Developed by USGS fire scientists and executive leadership, and informed by conversations with external stakeholders, the Strategic Plan is aligned wi
Authors
Paul F. Steblein, Rachel A. Loehman, Mark P. Miller, Joseph R. Holomuzki, Suzanna C. Soileau, Matthew L. Brooks, Mia Drane-Maury, Hannah M. Hamilton, Jason W. Kean, Jon E. Keeley, Robert R. Mason,, Alexa McKerrow, James Meldrum, Edmund B. Molder, Sheila F. Murphy, Birgit Peterson, Geoffrey S. Plumlee, Douglas J. Shinneman, Phillip J. van Mantgem, Alison York
By
Ecosystems Mission Area, Natural Hazards Mission Area, Science Synthesis, Analysis and Research Program, Science Analytics and Synthesis (SAS) Program, Alaska Science Center, Earth Resources Observation and Science (EROS) Center , Forest and Rangeland Ecosystem Science Center, Fort Collins Science Center, Geologic Hazards Science Center, Geology, Geophysics, and Geochemistry Science Center, Western Ecological Research Center (WERC), Wildland Fire Science
Gap Analysis Project (GAP) Terrestrial Vertebrate Species Richness Maps for the Conterminous U.S.
The mission of the Gap Analysis Project (GAP) is to support national and regional assessments of the conservation status of vertebrate species and plant communities. This report explains conterminous United States species richness maps created by the U.S. Geological Survey for four major classes in the phylum Chordata: mammals, birds, reptiles, and amphibians. In this work, we focus on terrestrial
Authors
Kevin J. Gergely, Kenneth G. Boykin, Alexa McKerrow, Matthew J. Rubino, Nathan M. Tarr, Steven G. Williams
Protected areas lacking for many common fluvial fishes of the conterminous USA
AimTo assess the effectiveness of protected areas in two catchment scales (local and network) in conserving regionally common fluvial fishes using modelled species distributions.LocationConterminous United States.MethodsA total of 150 species were selected that were geographically widespread, abundant, non‐habitat specialists and native within nine large ecoregions. Species distribution models wer
Authors
Arthur R. Cooper, Yin-Phang Tsang, Dana M. Infante, Wesley M. Daniel, Alexa McKerrow, Daniel J. Wieferich
Patterns of species richness hotspots and estimates of their protection are sensitive to spatial resolution
AimSpecies richness is a measure of biodiversity often used in spatial conservation assessments and mapped by summing species distribution maps. Commission errors inherent those maps influence richness patterns and conservation assessments. We sought to further the understanding of the sensitivity of hotspot delineation methods and conservation assessments to commission errors, and choice of thres
Authors
Alexa McKerrow, Nathan M. Tarr, Matthew J. Rubino, Steven G. Williams
Integrating multiple data sources in species distribution modeling: A framework for data fusion
The last decade has seen a dramatic increase in the use of species distribution models (SDMs) to characterize patterns of species’ occurrence and abundance. Efforts to parameterize SDMs often create a tension between the quality and quantity of data available to fit models. Estimation methods that integrate both standardized and non-standardized data types offer a potential solution to the tradeof
Authors
Krishna Pacifici, Brian J. Reich, David A.W. Miller, Beth Gardner, Glenn E. Stauffer, Susheela Singh, Alexa McKerrow, Jaime A. Collazo
Long-term fish monitoring in large rivers: Utility of “benchmarking” across basins
In business, benchmarking is a widely used practice of comparing your own business processes to those of other comparable companies and incorporating identified best practices to improve performance. Biologists and resource managers designing and conducting monitoring programs for fish in large river systems tend to focus on single river basins or segments of large rivers, missing opportunities to
Authors
David L. Ward, Andrew F. Casper, Timothy D. Counihan, Jennifer M. Bayer, Ian R. Waite, John J. Kosovich, Colin Chapman, Elise R. Irwin, Jennifer S. Sauer, Brian Ickes, Alexa McKerrow
By
Core Science Systems Mission Area, Ecosystems Mission Area, Science Synthesis, Analysis and Research Program, Gap Analysis Project, Science Analytics and Synthesis (SAS) Program, Species Management Research Program, Southwest Biological Science Center, Western Fisheries Research Center, Columbia River Research Laboratory (CRRL)
Science and Products
Aquatic Gap Analysis Vision
The Aquatic Gap Analysis Project (AGAP) works to synthesize existing data and generate new data products to answer complex questions about aquatic species, their habitats and their conservation needs at multiple scales. AGAP is working to build a national data framework that makes data management and sharing efficient.
Species Vision
Our goal is to build species range and predicted habitat maps to support state, regional, and national biodiversity assessments for the conservation status of native vertebrate species and to facilitate the application of this information to land management activities. These data are intended to describe patterns of species geographic location and basic habitat associations.
Land Cover Vision
The goal of the GAP/LANDFIRE National Terrestrial Ecosystems 2011 data is to provide accurate, seamless data on the vegetation and land cover of the United States. The map legend based on NatureServe’s ecological system classification scheme provides detailed information on the vegetation types at a plant community level.
The Gap Analysis Process and Importance
A Gap Analysis consists of mapping three data layers — land cover, predicted distributions of vertebrate species, and a stewardship layer depicting both location and conservation status of protected areas. This data is then assessed to determine how much of a target species’ (plant or animal) habitat is in conserved areas.
Analysis and Visualization of Climate Information to Support USFWS Species Status Assessments
Under the Endangered Species Act, the U.S. Fish and Wildlife Service (USFWS) must evaluate the status of at-risk plants and animals in the U.S. A Species Status Assessment (SSA) is a scientific assessment prepared for each at-risk species to help inform a range of management decisions under the Endangered Species Act. SSA’s are currently needed for more than 350 species, 250 of which are in the So
SERAP: Assessment of Climate and Land Use Change Impacts on Terrestrial Species
Researchers from North Carolina State University and the USGS integrated models of urbanization and vegetation dynamics with the regional climate models to predict vegetation dynamics and assess how landscape change could impact priority species, including North American land birds. This integrated ensemble of models can be used to predict locations where responses to climate change are most lik
SERAP: Modeling of Global and Land Use Change Impacts
The Southeastern United States spans a broad range of physiographic settings and maintains exceptionally high levels of faunal diversity. Unfortunately, many of these ecosystems are increasingly under threat due to rapid human development, and management agencies are increasingly aware of the potential effects that climate change will have on these ecosystems. Natural resource managers and conserv
Southeast Regional Assessment Project (SERAP): Assessing Global Change Impacts on Natural and Human Systems in the Southeast
The Southeastern United States spans a broad range of physiographic settings and maintains exceptionally high levels of faunal diversity. Unfortunately, many of these ecosystems are increasingly under threat due to rapid human development, and management agencies are increasingly aware of the potential effects that climate change will have on these ecosystems. Natural resource managers and conserv
Filter Total Items: 1731
Aquatic Gap Analysis Project (AGAP) Aquatic Species Distribution Modeling on the National Hydrography Dataset Plus Version 2.1
This USGS data release contains products that resulted from aquatic species distribution modeling in the United States on the National Hydrography Dataset Plus Version 2.1. Source data, supporting code and model results are documented in this data release. The file species_model_list.csv provides a list of most recent models for each combination of species, habitat, and region.
U.S. Geological Survey - Gap Analysis Project Species Habitat Richness
The Species Richness Maps included here are based on the Gap Analysis Project (GAP) habitat maps, which are predictions of the spatial distribution of suitable environmental and land cover conditions within the United States for individual species. Individual species habitat distribution models were summed to create the total richness for each vertebrate taxa. The summing process was coded in Pyth
Nelson's Antelope Squirrel (Ammospermophilus nelsoni) mNASQx_CONUS_2001v1 Habitat Map
This dataset represents a species habitat distribution model for Nelson's Antelope Squirrel. These habitat maps are created by applying a deductive habitat model to remotely-sensed data layers within a species' range.
Spotted Owl (Strix occidentalis) bSPOWx_CONUS_2001v1 Habitat Map
This dataset represents a species habitat distribution model for Spotted Owl. These habitat maps are created by applying a deductive habitat model to remotely-sensed data layers within a species' range.
Whip-poor-will (Caprimulgus vociferus) bWPWIx_CONUS_2001v1 Habitat Map
This dataset represents a species habitat distribution model for Whip-poor-will. These habitat maps are created by applying a deductive habitat model to remotely-sensed data layers within a species' range.
Barn Swallow (Hirundo rustica) bBARSx_CONUS_2001v1 Habitat Map
This dataset represents a species habitat distribution model for Barn Swallow. These habitat maps are created by applying a deductive habitat model to remotely-sensed data layers within a species' range.
Brown Creeper (Certhia americana) bBRCRx_CONUS_2001v1 Habitat Map
This dataset represents a species habitat distribution model for Brown Creeper. These habitat maps are created by applying a deductive habitat model to remotely-sensed data layers within a species' range.
Cave Swallow (Petrochelidon fulva) bCASWx_CONUS_2001v1 Habitat Map
This dataset represents a species habitat distribution model for Cave Swallow. These habitat maps are created by applying a deductive habitat model to remotely-sensed data layers within a species' range.
Sonoma Tree Vole (Arborimus pomo) mSTVOx_CONUS_2001v1 Habitat Map
This dataset represents a species habitat distribution model for Sonoma Tree Vole. These habitat maps are created by applying a deductive habitat model to remotely-sensed data layers within a species' range.
Piute Ground Squirrel (Urocitellus mollis) mPGSQx_CONUS_2001v1 Habitat Map
This dataset represents a species habitat distribution model for Piute Ground Squirrel. These habitat maps are created by applying a deductive habitat model to remotely-sensed data layers within a species' range.
Southern Mountain Yellow-legged Frog (Rana muscosa) aSMFRx_CONUS_2001v1 Habitat Map
This dataset represents a species habitat distribution model for Southern Mountain Yellow-legged Frog. These habitat maps are created by applying a deductive habitat model to remotely-sensed data layers within a species' range.
Montane Vole (Microtus montanus) mMOVOx_CONUS_2001v1 Habitat Map
This dataset represents a species habitat distribution model for Montane Vole. These habitat maps are created by applying a deductive habitat model to remotely-sensed data layers within a species' range.
Filter Total Items: 34
Developing fluvial fish species distribution models across the conterminous United States—A framework for management and conservation
This report explains the steps and specific methods used to predict fluvial fish occurrences in their native ranges for the conterminous United States. In this study, boosted regression tree models predict distributions of 271 ecologically important fluvial fish species using relations between fish presence/absence and 22 natural and anthropogenic landscape variables. Models developed for the fres
Authors
Hao Yu, Arthur R. Cooper, Jared Ross, Alexa McKerrow, Daniel J. Wieferich, Dana M. Infante
Methods for evaluating Gap Analysis Project habitat distribution maps with species occurrence data
The National Gap Analysis Project created species habitat distribution models for all terrestrial vertebrates in the United States to support conservation assessments and explore patterns of species richness. Those models link species to specific habitats throughout the range of each species. For most vertebrates, there are not enough occurrence data to drive inductive, range-wide species habitat
Authors
Matthew J. Rubino, Alexa McKerrow, Nathan M. Tarr, Steven G. Williams
Identifying monitoring information needs that support the management of fish in large rivers
Management actions intended to benefit fish in large rivers can directly or indirectly affect multiple ecosystem components. Without consideration of the effects of management on non-target ecosystem components, unintended consequences may limit management efficacy. Monitoring can help clarify the effects of management actions, including on non-target ecosystem components, but only if data are col
Authors
Timothy D. Counihan, Kristen L. Bouska, Shannon K. Brewer, R. B. Jacobson, Andrew F. Casper, Colin G. Chapman, Ian R. Waite, Kenneth R. Sheehan, Mark Pyron, Elise R. Irwin, Karen Riva-Murray, Alexa McKerrow, Jennifer M. Bayer
Applying biodiversity metrics as surrogates to a habitat conservation plan
Unabated urbanization has led to environmental degradation and subsequent biodiversity loss across the globe. As an outcome of unmitigated land use, multi-jurisdictional agencies have developed land use plans that attempt to protect threatened or endangered species across selected areas by which some trade-offs between harm to species and additional conservation approaches are allowed among the pa
Authors
Kenneth G. Boykin, William G. Kepner, Alexa McKerrow
Quantifying the representation of plant communities in the protected areas of the U.S.: An analysis based on the U.S. National Vegetation Classification Groups
Plant communities represent the integration of ecological and biological processes and they serve as an important component for the protection of biological diversity. To measure progress towards protection of ecosystems in the United States for various stated conservation targets we need datasets at the appropriate thematic, spatial, and temporal resolution. The recent release of the LANDFIRE Exi
Authors
Alexa McKerrow, Anne Davidson, Matthew J. Rubino, Don Faber-Langendoen, Daryn (Contractor) Dockter
Refining the coarse filter approach: Using habitat-based species models to identify rarity and vulnerabilities in the protection of U.S. biodiversity
Preserving biodiversity and its many components is a priority of conservation science and how to efficiently allocate resources to preserve healthy populations of as many species, habitats, and ecosystems as possible. We used the U.S. Geological Survey (USGS) Gap Analysis Project (GAP) species models released in 2018, which identify predicted habitats for terrestrial vertebrates in the conterminou
Authors
Anne Davidson, Leah Dunn, Kevin Gergely, Alexa McKerrow, Steven G. Williams, Mackenzie Case
U.S. Geological Survey wildland fire science strategic plan, 2021–26
The U.S. Geological Survey (USGS) Wildland Fire Science Strategic Plan defines critical, core fire science capabilities for understanding fire-related and fire-responsive earth system processes and patterns, and informing management decision making. Developed by USGS fire scientists and executive leadership, and informed by conversations with external stakeholders, the Strategic Plan is aligned wi
Authors
Paul F. Steblein, Rachel A. Loehman, Mark P. Miller, Joseph R. Holomuzki, Suzanna C. Soileau, Matthew L. Brooks, Mia Drane-Maury, Hannah M. Hamilton, Jason W. Kean, Jon E. Keeley, Robert R. Mason,, Alexa McKerrow, James Meldrum, Edmund B. Molder, Sheila F. Murphy, Birgit Peterson, Geoffrey S. Plumlee, Douglas J. Shinneman, Phillip J. van Mantgem, Alison York
By
Ecosystems Mission Area, Natural Hazards Mission Area, Science Synthesis, Analysis and Research Program, Science Analytics and Synthesis (SAS) Program, Alaska Science Center, Earth Resources Observation and Science (EROS) Center , Forest and Rangeland Ecosystem Science Center, Fort Collins Science Center, Geologic Hazards Science Center, Geology, Geophysics, and Geochemistry Science Center, Western Ecological Research Center (WERC), Wildland Fire Science
Gap Analysis Project (GAP) Terrestrial Vertebrate Species Richness Maps for the Conterminous U.S.
The mission of the Gap Analysis Project (GAP) is to support national and regional assessments of the conservation status of vertebrate species and plant communities. This report explains conterminous United States species richness maps created by the U.S. Geological Survey for four major classes in the phylum Chordata: mammals, birds, reptiles, and amphibians. In this work, we focus on terrestrial
Authors
Kevin J. Gergely, Kenneth G. Boykin, Alexa McKerrow, Matthew J. Rubino, Nathan M. Tarr, Steven G. Williams
Protected areas lacking for many common fluvial fishes of the conterminous USA
AimTo assess the effectiveness of protected areas in two catchment scales (local and network) in conserving regionally common fluvial fishes using modelled species distributions.LocationConterminous United States.MethodsA total of 150 species were selected that were geographically widespread, abundant, non‐habitat specialists and native within nine large ecoregions. Species distribution models wer
Authors
Arthur R. Cooper, Yin-Phang Tsang, Dana M. Infante, Wesley M. Daniel, Alexa McKerrow, Daniel J. Wieferich
Patterns of species richness hotspots and estimates of their protection are sensitive to spatial resolution
AimSpecies richness is a measure of biodiversity often used in spatial conservation assessments and mapped by summing species distribution maps. Commission errors inherent those maps influence richness patterns and conservation assessments. We sought to further the understanding of the sensitivity of hotspot delineation methods and conservation assessments to commission errors, and choice of thres
Authors
Alexa McKerrow, Nathan M. Tarr, Matthew J. Rubino, Steven G. Williams
Integrating multiple data sources in species distribution modeling: A framework for data fusion
The last decade has seen a dramatic increase in the use of species distribution models (SDMs) to characterize patterns of species’ occurrence and abundance. Efforts to parameterize SDMs often create a tension between the quality and quantity of data available to fit models. Estimation methods that integrate both standardized and non-standardized data types offer a potential solution to the tradeof
Authors
Krishna Pacifici, Brian J. Reich, David A.W. Miller, Beth Gardner, Glenn E. Stauffer, Susheela Singh, Alexa McKerrow, Jaime A. Collazo
Long-term fish monitoring in large rivers: Utility of “benchmarking” across basins
In business, benchmarking is a widely used practice of comparing your own business processes to those of other comparable companies and incorporating identified best practices to improve performance. Biologists and resource managers designing and conducting monitoring programs for fish in large river systems tend to focus on single river basins or segments of large rivers, missing opportunities to
Authors
David L. Ward, Andrew F. Casper, Timothy D. Counihan, Jennifer M. Bayer, Ian R. Waite, John J. Kosovich, Colin Chapman, Elise R. Irwin, Jennifer S. Sauer, Brian Ickes, Alexa McKerrow
By
Core Science Systems Mission Area, Ecosystems Mission Area, Science Synthesis, Analysis and Research Program, Gap Analysis Project, Science Analytics and Synthesis (SAS) Program, Species Management Research Program, Southwest Biological Science Center, Western Fisheries Research Center, Columbia River Research Laboratory (CRRL)