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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 partnering organizations. Typical conservation plans can be created to focus on single or multiple species, and although they may protect a species or groups of species, they may not account for biodiversity or its protection across the given area. We applied an approach that clustered deductive habitat models for terrestrial vertebrates into metrics that serve as surrogates for biodiversity and relate to ecosystem services. In order to evaluate this process, we collaborated with the partnering agencies who are creating a Multi-Species Habitat Conservation Plan in southern California and compared it to the entire Mojave Desert Ecoregion. We focused on total terrestrial vertebrate species richness and taxon groupings representing amphibians, birds, mammals, and reptiles, and two special status species using the Normalized Index of Biodiversity (NIB). The conservation planning area had a lower NIB and was less species rich than the Mojave Desert Ecoregion, but the Mojave River riparian corridor had a higher NIB and was more species-rich, and while taxon analysis varied across the geographies, this pattern generally held. Additionally, we analyzed desert tortoise (Gopherus agassizii) and desert kit fox (Vulpes macrotis arsipus) as umbrella species and determined that both species are associated with increased NIB and large numbers of species for the conservation area. Our process provided the ability to incorporate value-added surrogate information into a formal land use planning process and used a metric, NIB, which allowed comparison of the various planning areas and geographic units. Although this process has been applied to Apple Valley, CA, and other geographies within the U.S., the approach has practical application for other global biodiversity initiatives.
Kenneth Boykin; William Kepner; Alexa McKerrow. Applying Biodiversity Metrics as Surrogates to a Habitat Conservation Plan. Environments 2021, 8, 69 .
AMA StyleKenneth Boykin, William Kepner, Alexa McKerrow. Applying Biodiversity Metrics as Surrogates to a Habitat Conservation Plan. Environments. 2021; 8 (8):69.
Chicago/Turabian StyleKenneth Boykin; William Kepner; Alexa McKerrow. 2021. "Applying Biodiversity Metrics as Surrogates to a Habitat Conservation Plan." Environments 8, no. 8: 69.
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 Existing Vegetation Data Products (2016 Remap) with a legend based on U.S. National Vegetation Classification allowed us to assess the conservation status of plant communities of the U.S. The map legend is based on the Group level of the USNVC, which characterizes the regional differences in plant communities based on dominant and diagnostic plant species. By combining the Group level map with the Protected Areas Database of the United States (PAD-US Ver 2.1), we quantified the representation of each Group. If the mapped vegetation is assumed to be 100% accurate, using the Aichi Biodiversity target (17% land in protection by 2020) we found that 159 of the 265 natural Groups have less than 17% in GAP Status 1 & 2 lands and 216 of the 265 Groups fail to meet a 30% representation target. Only four of the twenty ecoregions have >17% of their extent in Status 1 & 2 lands. Sixteen ecoregions are dominated by Groups that are under-represented. Most ecoregions have many hectares of natural or ruderal vegetation that could contribute to future conservation efforts and this analysis helps identify specific targets and opportunities for conservation across the U.S.
Alexa McKerrow; Anne Davidson; Matthew Rubino; Don Faber-Langendoen; Daryn Dockter. 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. Forests 2021, 12, 864 .
AMA StyleAlexa McKerrow, Anne Davidson, Matthew Rubino, Don Faber-Langendoen, Daryn Dockter. 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. Forests. 2021; 12 (7):864.
Chicago/Turabian StyleAlexa McKerrow; Anne Davidson; Matthew Rubino; Don Faber-Langendoen; Daryn Dockter. 2021. "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." Forests 12, no. 7: 864.
First posted February 23, 2021 Wildland Fire Science ProgramU.S Geological Survey12201 Sunrise Valley DriveReston, VA 20192 Contact Pubs Warehouse 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 with the needs of the fire science stakeholder community–fire, land, natural resource, and emergency managers from Federal, State, Tribal, and community organizations, as well as members of the scientific community. The Strategic Plan is composed of four integrated priorities, each with associated goals and specific strategies for accomplishing the goals: Priority 1: Produce state-of-the-art, actionable fire science; Priority 2: Engage stakeholders in science production and science delivery; Priority 3: Effectively communicate USGS fire science capacity, products, and information to a broad audience; and Priority 4: Enhance USGS organizational structure and advance support for fire science. The priorities of this Strategic Plan define the USGS’s commitment to producing and delivering cutting edge fire science, information, and decision-support tools in support of national, regional, and local priorities and stakeholder needs.
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 Jr.; Alexa J. McKerrow; James R. Meldrum; Edmund B. Molder; Sheila F. Murphy; Birgit Peterson; Geoffrey S. Plumlee; Douglas J. Shinneman; Phillip J. van Mantgem; Alison York. Strategic plan for U.S. Geological Survey wildland fire science, 2021–26. Circular 2021, 1 .
AMA StylePaul 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 Jr., Alexa J. McKerrow, James R. Meldrum, Edmund B. Molder, Sheila F. Murphy, Birgit Peterson, Geoffrey S. Plumlee, Douglas J. Shinneman, Phillip J. van Mantgem, Alison York. Strategic plan for U.S. Geological Survey wildland fire science, 2021–26. Circular. 2021; ():1.
Chicago/Turabian StylePaul 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 Jr.; Alexa J. McKerrow; James R. Meldrum; Edmund B. Molder; Sheila F. Murphy; Birgit Peterson; Geoffrey S. Plumlee; Douglas J. Shinneman; Phillip J. van Mantgem; Alison York. 2021. "Strategic plan for U.S. Geological Survey wildland fire science, 2021–26." Circular , no. : 1.
Aim To assess the effectiveness of protected areas in two catchment scales (local and network) in conserving regionally common fluvial fishes using modelled species distributions. Location Conterminous United States. Methods A total of 150 species were selected that were geographically widespread, abundant, non‐habitat specialists and native within nine large ecoregions. Species distribution models were developed using boosted regression trees, and modelled distributions were assessed for protection status under two alternatives: lands strictly managed for biodiversity (Highly Restricted Use) and those allowing multiple uses (Multiple Use), with protection target levels (i.e., the amount of protected area required for protection) for local and network catchments being developed from ecoregion‐based urban and agricultural land use thresholds from fish responses. Results Overall, less than 2% of fluvial catchments in the conterminous USA are meeting both local and network catchment protection target levels under the Highly Restricted Use alternative, whereas 16% of catchments met protection levels for the Multiple Use alternative, with protection largely concentrated in the western USA. For common native species distributions within ecoregions, only one species had >10% of streams meeting combined local and network catchment protection target levels under the Highly Restricted Use alternative, whereas 50 distributions (~14% of species distribution models) met this level under the Multiple Use alternative. Main conclusions Even for fishes considered widespread and abundant, protection levels are lacking, particularly when considering only lands that are actively managed for biodiversity. Given the increasing intensification of anthropogenic activities and substantial uncertainty associated with climate change, considering the conservation status for all species, including those currently considered common, is warranted.
Arthur R. Cooper; Yinphan Tsang; Dana M. Infante; Wesley M. Daniel; Alexa J. McKerrow; Daniel Wieferich. Protected areas lacking for many common fluvial fishes of the conterminous USA. Diversity and Distributions 2019, 25, 1289 -1303.
AMA StyleArthur R. Cooper, Yinphan Tsang, Dana M. Infante, Wesley M. Daniel, Alexa J. McKerrow, Daniel Wieferich. Protected areas lacking for many common fluvial fishes of the conterminous USA. Diversity and Distributions. 2019; 25 (8):1289-1303.
Chicago/Turabian StyleArthur R. Cooper; Yinphan Tsang; Dana M. Infante; Wesley M. Daniel; Alexa J. McKerrow; Daniel Wieferich. 2019. "Protected areas lacking for many common fluvial fishes of the conterminous USA." Diversity and Distributions 25, no. 8: 1289-1303.
First posted June 4, 2019 Director, Core Science Analytics and SynthesisU.S. Geological SurveyBox 25046, MS-302Denver, CO 80225-0046 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 vertebrate species and the spatial patterns of richness derived from species’ habitat distribution models. We created species’ habitat distribution models for 1,590 species (282 amphibians, 621 birds, 365 mammals, 322 reptiles) and an additional 129 subspecies (2 amphibians, 28 birds, 94 mammals, 5 reptiles) that occur in the conterminous United States. The 1,590 species level models were spatially combined to create the taxa richness maps at a spatial resolution of 30 meters. Based on those maps we identified the maximum species richness for each of the taxa (43 amphibians, 163 birds, 72 mammals, and 54 reptiles) and show variation in richness across the conterminous United States. Because these habitat models remove unsuitable areas within the range of the species, the patterns of richness presented here are different from the coarse-resolution species’ habitat distribution models commonly presented in the literature. These maps provide a new, more spatially refined richness map. In addition, since these models are logically linked to mapped data layers that constitute habitat suitability, this suite of data can provide an intuitive data system for further exploration of biodiversity and implications for change at ecosystem and landscape scales.
Kevin J. Gergely; Kenneth G. Boykin; Alexa J. McKerrow; Matthew J. Rubino; Nathan M. Tarr; Steven G. Williams. Gap Analysis Project (GAP) Terrestrial Vertebrate Species Richness Maps for the Conterminous U.S. Scientific Investigations Report 2019, 1 .
AMA StyleKevin J. Gergely, Kenneth G. Boykin, Alexa J. McKerrow, Matthew J. Rubino, Nathan M. Tarr, Steven G. Williams. Gap Analysis Project (GAP) Terrestrial Vertebrate Species Richness Maps for the Conterminous U.S. Scientific Investigations Report. 2019; ():1.
Chicago/Turabian StyleKevin J. Gergely; Kenneth G. Boykin; Alexa J. McKerrow; Matthew J. Rubino; Nathan M. Tarr; Steven G. Williams. 2019. "Gap Analysis Project (GAP) Terrestrial Vertebrate Species Richness Maps for the Conterminous U.S." Scientific Investigations Report , no. : 1.
Aim Species 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 threshold for hotspot delineation. Location United States. Methods We created range maps and 30‐m and 1‐km resolution habitat maps for terrestrial vertebrates in the United States and generated species richness maps with each dataset. With the richness maps and the GAP Protected Areas Dataset, we created species richness hotspot maps and calculated the proportion of hotspots within protected areas; calculating protection under a range of thresholds for defining hotspots. Our method allowed us to identify the influence of commission errors by comparing hotspot maps. Results Commission errors from coarse spatial grain data and lack of porosity in the range data inflated richness estimates and altered their spatial patterns. Coincidence of hotspots from different data types was low. The 30‐m hotspots were spatially dispersed, and some were very long distances from the hotspots mapped with coarser data. Estimates of protection were low for each of the taxa. The relationship between estimates of hotspot protection and threshold choice was nonlinear and inconsistent among data types (habitat and range) and grain size (30‐m and 1‐km). Main conclusions Coarse mapping methods and grain sizes can introduce commission errors into species distribution data that could result in misidentifications of the regions where hotspots occur and affect estimates of hotspot protection. Hotspot conservation assessments are also sensitive to choice of threshold for hotspot delineation. There is value in developing species distribution maps with high resolution and low rates of commission error for conservation assessments.
Alexa J. McKerrow; Nathan Tarr; Matthew J. Rubino; Steven G. Williams. Patterns of species richness hotspots and estimates of their protection are sensitive to spatial resolution. Diversity and Distributions 2018, 24, 1464 -1477.
AMA StyleAlexa J. McKerrow, Nathan Tarr, Matthew J. Rubino, Steven G. Williams. Patterns of species richness hotspots and estimates of their protection are sensitive to spatial resolution. Diversity and Distributions. 2018; 24 (10):1464-1477.
Chicago/Turabian StyleAlexa J. McKerrow; Nathan Tarr; Matthew J. Rubino; Steven G. Williams. 2018. "Patterns of species richness hotspots and estimates of their protection are sensitive to spatial resolution." Diversity and Distributions 24, no. 10: 1464-1477.
Remotely sensed differenced normalized burn ratios (DNBR) provide an index of fire severity across the footprint of a fire. We asked whether this index was useful for explaining patterns of bird occurrence within fire adapted xeric pine-oak forests of the southern Appalachian Mountains. We evaluated the use of DNBR indices for linking ecosystem process with patterns of bird occurrence. We compared field-based and remotely sensed fire severity indices and used each to develop occupancy models for six bird species to identify patterns of bird occurrence following fire. We identified and sampled 228 points within fires that recently burned within Great Smoky Mountains National Park. We performed avian point counts and field-assessed fire severity at each bird census point. We also used Landsat™ imagery acquired before and after each fire to quantify fire severity using DNBR. We used non-parametric methods to quantify agreement between fire severity indices, and evaluated single season occupancy models incorporating fire severity summarized at different spatial scales. Agreement between field-derived and remotely sensed measures of fire severity was influenced by vegetation type. Although occurrence models using field-derived indices of fire severity outperformed those using DNBR, summarizing DNBR at multiple spatial scales provided additional insights into patterns of occurrence associated with different sized patches of high severity fire. DNBR is useful for linking the effects of fire severity to patterns of bird occurrence, and informing how high severity fire shapes patterns of bird species occurrence on the landscape.
Eli T. Rose; Theodore R. Simons; Rob Klein; Alexa J. McKerrow. Normalized burn ratios link fire severity with patterns of avian occurrence. Landscape Ecology 2016, 31, 1537 -1550.
AMA StyleEli T. Rose, Theodore R. Simons, Rob Klein, Alexa J. McKerrow. Normalized burn ratios link fire severity with patterns of avian occurrence. Landscape Ecology. 2016; 31 (7):1537-1550.
Chicago/Turabian StyleEli T. Rose; Theodore R. Simons; Rob Klein; Alexa J. McKerrow. 2016. "Normalized burn ratios link fire severity with patterns of avian occurrence." Landscape Ecology 31, no. 7: 1537-1550.
Kevin J. Gergely; Alexa McKerrow. Tools and data for meeting America's conservation challenges. General Information Product 2013, 1 .
AMA StyleKevin J. Gergely, Alexa McKerrow. Tools and data for meeting America's conservation challenges. General Information Product. 2013; ():1.
Chicago/Turabian StyleKevin J. Gergely; Alexa McKerrow. 2013. "Tools and data for meeting America's conservation challenges." General Information Product , no. : 1.
Kevin J. Gergely; Alexa McKerrow. Species data: National inventory of range maps and distribution models. Fact Sheet 2013, 1 .
AMA StyleKevin J. Gergely, Alexa McKerrow. Species data: National inventory of range maps and distribution models. Fact Sheet. 2013; ():1.
Chicago/Turabian StyleKevin J. Gergely; Alexa McKerrow. 2013. "Species data: National inventory of range maps and distribution models." Fact Sheet , no. : 1.
Kevin J. Gergely; Alexa McKerrow. PAD-US—National inventory of protected areas. Fact Sheet 2013, 1 .
AMA StyleKevin J. Gergely, Alexa McKerrow. PAD-US—National inventory of protected areas. Fact Sheet. 2013; ():1.
Chicago/Turabian StyleKevin J. Gergely; Alexa McKerrow. 2013. "PAD-US—National inventory of protected areas." Fact Sheet , no. : 1.
The Gap Analysis Program (GAP) produces data and tools that help meet critical national challenges such as biodiversity conservation, renewable energy development, climate change adaptation, and infrastructure investment. The GAP national land cover includes data on the vegetation and land-use patterns of the United States, including Alaska, Hawaii, and Puerto Rico. This national dataset combines land cover data generated by regional GAP projects with Landscape Fire and Resource Management Planning Tools (LANDFIRE) data (http://www.landfire.gov/). LANDFIRE is an interagency vegetation, fire, and fuel characteristics mapping program, sponsored by the U.S. Department of the Interior and the U.S. Department of Agriculture Forest Service.
Kevin J. Gergely; Alexa McKerrow. Terrestrial ecosystems: national inventory of vegetation and land use. Fact Sheet 2013, 1 .
AMA StyleKevin J. Gergely, Alexa McKerrow. Terrestrial ecosystems: national inventory of vegetation and land use. Fact Sheet. 2013; ():1.
Chicago/Turabian StyleKevin J. Gergely; Alexa McKerrow. 2013. "Terrestrial ecosystems: national inventory of vegetation and land use." Fact Sheet , no. : 1.
GAP species range data are coarse representations of the total areal extent a species occupies, in other words the geographic limits within which a species can be found (Morrison and Hall 2002). These data provide the geographic extent within which the USGS Gap Analysis Project delineates areas of suitable habitat for terrestrial vertebrate species in their species' habitat maps. The range maps are created by attributing a vector file derived from the 12-digit Hydrologic Unit Dataset (USDA NRCS 2009). Modifications to that dataset are described here. Attribution of the season range for each species was based on the literature and online sources (See Cross Reference section of the metadata). Attribution for each hydrologic unit within the range included values for origin (native, introduced, reintroduced, vagrant), occurrence (extant, possibly present, potentially present, extirpated), reproductive use (breeding, non-breeding, both) and season (year-round, summer, winter, migratory, vagrant). These species range data provide the biological context within which to build our species distribution models.
Alexa McKerrow. U.S. Geological Survey - Gap Analysis Project Species Range Maps CONUS_2001. 2021, 1 .
AMA StyleAlexa McKerrow. U.S. Geological Survey - Gap Analysis Project Species Range Maps CONUS_2001. . 2021; ():1.
Chicago/Turabian StyleAlexa McKerrow. 2021. "U.S. Geological Survey - Gap Analysis Project Species Range Maps CONUS_2001." , no. : 1.
The U.S. Geological Survey Gap Analysis Program (GAP) National Terrestrial Ecosystems - Ver 3.0 is a 2011 update of the National Gap Analysis Program Land Cover Data - Version 2.2 for the conterminous U.S. The GAP National Terrestrial Ecosystems - Version 3.0 represents a highly thematically detailed land cover map of the U.S. The map legend includes types described by NatureServe's Ecological Systems Classification (Comer et al. 2002) as well as land use classes described in the National Land Cover Dataset 2011 (Homer et al. 2015). These data cover the entire continental U.S. and are a continuous data layer. These raster data have a 30 m x 30 m cell resolution. GAP used the best information available to create the land cover data; however GAP seeks to improve and update these data as new information becomes available.
Anne Davidson; Alexa McKerrow. GAP/LANDFIRE National Terrestrial Ecosystems 2011. 2021, 1 .
AMA StyleAnne Davidson, Alexa McKerrow. GAP/LANDFIRE National Terrestrial Ecosystems 2011. . 2021; ():1.
Chicago/Turabian StyleAnne Davidson; Alexa McKerrow. 2021. "GAP/LANDFIRE National Terrestrial Ecosystems 2011." , no. : 1.
Gap Analysis Project (GAP) habitat maps are predictions of the spatial distribution of suitable environmental and land cover conditions within the United States for individual species. Mapped areas represent places where the environment is suitable for the species to occur (i.e. suitable to support one or more life history requirements for breeding, resting, or foraging), while areas not included in the map are those predicted to be unsuitable for the species. While the actual distributions of many species are likely to be habitat limited, suitable habitat will not always be occupied because of population dynamics and species interactions. Furthermore, these maps correspond to midscale characterizations of landscapes, but individual animals may deem areas to be unsuitable because of presence or absence of fine-scale features and characteristics that are not represented in our models (e.g. snags, vernal pools, shrubby undergrowth). These maps are intended to be used at a 1:100,000 or smaller map scale.
Alexa McKerrow. U.S. Geological Survey - Gap Analysis Project Species Habitat Maps CONUS_2001. 2021, 1 .
AMA StyleAlexa McKerrow. U.S. Geological Survey - Gap Analysis Project Species Habitat Maps CONUS_2001. . 2021; ():1.
Chicago/Turabian StyleAlexa McKerrow. 2021. "U.S. Geological Survey - Gap Analysis Project Species Habitat Maps CONUS_2001." , no. : 1.