Learn about some of the ways Gap Analysis is being applied.
Five Valleys Land Trust
GAP initiated a project with the Five Valleys Land Trust (FVLT) to demonstrate the application of GAP data to conservation activities. The Trust needed to identify priority areas for conservation in their large service area. FVLT’s service area stretches the length of five major river valleys in Western Montana — from the western border of the state, east to Butte and from the Lost Trail Pass in the south to Lincoln and Polson in the north.
GAP provided FVLT with a summary of the land cover types protected by their holdings as well as a summary of land cover in their service area. Knowing the percent of each ecological system’s available habitat that was already protected in the Northwest provided FVLT with context for landscape-level planning. The least protected ecological systems in the service area were mapped, with areas administered by other entities (Federal, State, other NGO, etc) removed, to determine potential priority areas for future conservation. The FLVT will evaluate these areas further using other conservation drivers from their Strategic Conservation Plan. They believe GAP data will add validity to their projects, and provide a greater ecological context, which will increase opportunities for conservation and fundraising.
Charting Sin Nombre Virus Infections in Deer Mice
Environmental data from remote sensing and geographic information system maps were tested as possible indicators of Sin Nombre virus (SNV) infections in deer mouse (Peromyscus maniculatus) populations in the Walker River Basin, Nevada and California. Deer mice from 144 field sites were tested for the presence of SNV infections. Remote sensing and geographic information systems data were used to characterize the vegetation type and density, elevation, slope, and hydrologic features of each field site. The data retroactively predicted infection status of deer mice with up to 80% accuracy. If models of SNV temporal dynamics can be integrated with baseline spatial models, human risk for infection may be assessed with reasonable accuracy.
The Result
It should be possible to estimate the frequency (if not the specific timing) of new infections as a function of a site’s local environment. Additionally, extended longitudinal studies could identify typical infection trajectories of sites based on their environmental characteristics or demographic profiles of their host populations. When combined, these approaches should advance our ability to quantify and predict disease dynamics and human risk.
Analyzing Wildlife Movement Corridors in Montana Using GIS
In this project, researchers delineated landscape routes offering the best chance of success for wildlife moving among the three large core protected areas in the Northern Rockies — the Salmon-Selway, Northern Continental Divide, and Greater Yellowstone Ecosystems. Using ARC/GRID and Montana Gap Analysis data, they derived habitat suitability models for three umbrella species, which were combined with road density information to create kilometer-scale cost surfaces of movement.
For each of the three species — grizzly bear, elk, and cougar — analysts performed a least.cost.path analysis to locate broad potential corridor routes. From this first approximation they identified probable movement routes and as well as critical barriers, bottlenecks, and filters where corridor routes intersected with high.risk habitat. This analysis is being used to identify priority areas for wildlife management to improve the connectivity between the core protected ecosystems in the Northern Rockies.
Reference
Walker, R., and L. Craighead, Least-Cost-Path Corridor Analysis: Analyzing Wildlife Movement Corridors in Montana Using GIS, Proceedings of the 1997 ESRI User’s conference.
Predicting the Risk of Lyme Disease: Habitat Suitability for Ixodes scapularis in the North Central United States
The purpose of this study was to determine the distribution of I. scapularis in the upper Midwest based on data from Wisconsin, northern Illinois, and the Upper Peninsula of Michigan, and to explain the environmental factors that facilitate or inhibit the establishment of I. scapularis. Wisconsin GAP land cover data was one of several land cover data sets used to a develop a land cover classification map against which tick sitings could be analyzed.
Sites with ticks were identified. Ticks were collected at a total of 138 sites. Small animals were live-trapped, examined for ticks, and released. Sites were ranked from 0 (no ticks) to 3 (a high density of ticks). Soil samples were collected at each site, as was data about vegetation, leaf litter thickness, slope, and compass direction. Sites were classified by forest type, and their locations were recorded using GPS.
The database containing the above data was overlaid in a GIS onto a digitized land cover coverage. A discriminate model was created, results were used to create a risk map.
The study concluded that this model could be used to help determine the risk of acquiring Lyme disease and other diseases transmitted by I. scapularis by predicting which locations may be currently infested with the tick. It can also be used to assess whether habitats that are currently non-endemic for I. scapularis would have the necessary combination of environmental factors to allow new populations of I. scapularis to become established. The model can thus be continuously refined based on findings from new areas. The risk of Lyme disease transmission could be predicted in areas capable of sustaining I. scapularis populations if ticks harboring B. burgdorferi are introduced by migrating deer or birds. The results obtained from these field studies can also form the basis for controlled experimental studies under field and laboratory conditions to further elucidate the preferred microenvironment of I. scapularis (3) .
Identifying Big Game Migration Corridors in Wyoming
Given that disruption of migration can reduce the size and viability of big game herds, natural resource managers are increasingly focused on maintaining the quality of migration corridors. Because resources for land and wildlife management are limited, managers need to know which corridors are at risk from disturbances. The study presented here is intended to help identify areas of the state where migration corridors are most at risk.
Digital maps of migration corridors for huntable populations of seven big game species in Wyoming (bighorn sheep, elk, moose, mountain goats, mule deer, pronghorn and white-tailed deer) were prepared using hard-copy data supplied by the Wyoming Game and Fish Department. The original data are based mainly on the expert opinions of Wyoming Game and Fish Department biologists along with a small fraction of data from studies of radio-collared animals in various parts of the state.
The mapped migration corridors were then overlaid on a map showing the relative level of protection from development for different land management categories produced by the Wyoming Gap Analysis Project. These maps can be used to highlight general regions that encompass clusters of relatively threatened migration corridors. Combined with more precise data, they could help direct specific, on-the-ground, planning.
State Wildlife Action Plans
In 2005, each state and U.S. territory completed a plan to evaluate its wildlife conservation needs and outline its conservation priorities. These State Wildlife Action Plans (SWAPs) contain information on Species of Greatest Conservation Need (SGCN), critical habitat, threats to wildlife species and habitats, research needs, necessary actions, and conservation strategies. Together they provide a blueprint for national conservation efforts. These plans were mandated by the Federal government, and they must be updated by 2015.
Use of GAP in original (2005) State Wildlife Action Plans
In the first round of State Wildlife Action Plan development, GAP land cover and vertebrate species habitat distribution maps were important data sets. A survey of SWAP coordinators showed that twenty-two states relied heavily on GAP land cover data. While vegetation classifications were used by 33 percent of respondents, and predicted vertebrate species habitat distribution maps were used by 25 percent of respondents, aquatic species data, land stewardship, land ownership, species richness data, species lists, and habitat descriptions were also important.
The top priority identified in the SWAPs was a need for more research on species. With its new regional and national data, GAP will continue to provide vital information for state wildlife action plans.
Learn about some of the ways Gap Analysis is being applied.
Five Valleys Land Trust
GAP initiated a project with the Five Valleys Land Trust (FVLT) to demonstrate the application of GAP data to conservation activities. The Trust needed to identify priority areas for conservation in their large service area. FVLT’s service area stretches the length of five major river valleys in Western Montana — from the western border of the state, east to Butte and from the Lost Trail Pass in the south to Lincoln and Polson in the north.
GAP provided FVLT with a summary of the land cover types protected by their holdings as well as a summary of land cover in their service area. Knowing the percent of each ecological system’s available habitat that was already protected in the Northwest provided FVLT with context for landscape-level planning. The least protected ecological systems in the service area were mapped, with areas administered by other entities (Federal, State, other NGO, etc) removed, to determine potential priority areas for future conservation. The FLVT will evaluate these areas further using other conservation drivers from their Strategic Conservation Plan. They believe GAP data will add validity to their projects, and provide a greater ecological context, which will increase opportunities for conservation and fundraising.
Charting Sin Nombre Virus Infections in Deer Mice
Environmental data from remote sensing and geographic information system maps were tested as possible indicators of Sin Nombre virus (SNV) infections in deer mouse (Peromyscus maniculatus) populations in the Walker River Basin, Nevada and California. Deer mice from 144 field sites were tested for the presence of SNV infections. Remote sensing and geographic information systems data were used to characterize the vegetation type and density, elevation, slope, and hydrologic features of each field site. The data retroactively predicted infection status of deer mice with up to 80% accuracy. If models of SNV temporal dynamics can be integrated with baseline spatial models, human risk for infection may be assessed with reasonable accuracy.
The Result
It should be possible to estimate the frequency (if not the specific timing) of new infections as a function of a site’s local environment. Additionally, extended longitudinal studies could identify typical infection trajectories of sites based on their environmental characteristics or demographic profiles of their host populations. When combined, these approaches should advance our ability to quantify and predict disease dynamics and human risk.
Analyzing Wildlife Movement Corridors in Montana Using GIS
In this project, researchers delineated landscape routes offering the best chance of success for wildlife moving among the three large core protected areas in the Northern Rockies — the Salmon-Selway, Northern Continental Divide, and Greater Yellowstone Ecosystems. Using ARC/GRID and Montana Gap Analysis data, they derived habitat suitability models for three umbrella species, which were combined with road density information to create kilometer-scale cost surfaces of movement.
For each of the three species — grizzly bear, elk, and cougar — analysts performed a least.cost.path analysis to locate broad potential corridor routes. From this first approximation they identified probable movement routes and as well as critical barriers, bottlenecks, and filters where corridor routes intersected with high.risk habitat. This analysis is being used to identify priority areas for wildlife management to improve the connectivity between the core protected ecosystems in the Northern Rockies.
Reference
Walker, R., and L. Craighead, Least-Cost-Path Corridor Analysis: Analyzing Wildlife Movement Corridors in Montana Using GIS, Proceedings of the 1997 ESRI User’s conference.
Predicting the Risk of Lyme Disease: Habitat Suitability for Ixodes scapularis in the North Central United States
The purpose of this study was to determine the distribution of I. scapularis in the upper Midwest based on data from Wisconsin, northern Illinois, and the Upper Peninsula of Michigan, and to explain the environmental factors that facilitate or inhibit the establishment of I. scapularis. Wisconsin GAP land cover data was one of several land cover data sets used to a develop a land cover classification map against which tick sitings could be analyzed.
Sites with ticks were identified. Ticks were collected at a total of 138 sites. Small animals were live-trapped, examined for ticks, and released. Sites were ranked from 0 (no ticks) to 3 (a high density of ticks). Soil samples were collected at each site, as was data about vegetation, leaf litter thickness, slope, and compass direction. Sites were classified by forest type, and their locations were recorded using GPS.
The database containing the above data was overlaid in a GIS onto a digitized land cover coverage. A discriminate model was created, results were used to create a risk map.
The study concluded that this model could be used to help determine the risk of acquiring Lyme disease and other diseases transmitted by I. scapularis by predicting which locations may be currently infested with the tick. It can also be used to assess whether habitats that are currently non-endemic for I. scapularis would have the necessary combination of environmental factors to allow new populations of I. scapularis to become established. The model can thus be continuously refined based on findings from new areas. The risk of Lyme disease transmission could be predicted in areas capable of sustaining I. scapularis populations if ticks harboring B. burgdorferi are introduced by migrating deer or birds. The results obtained from these field studies can also form the basis for controlled experimental studies under field and laboratory conditions to further elucidate the preferred microenvironment of I. scapularis (3) .
Identifying Big Game Migration Corridors in Wyoming
Given that disruption of migration can reduce the size and viability of big game herds, natural resource managers are increasingly focused on maintaining the quality of migration corridors. Because resources for land and wildlife management are limited, managers need to know which corridors are at risk from disturbances. The study presented here is intended to help identify areas of the state where migration corridors are most at risk.
Digital maps of migration corridors for huntable populations of seven big game species in Wyoming (bighorn sheep, elk, moose, mountain goats, mule deer, pronghorn and white-tailed deer) were prepared using hard-copy data supplied by the Wyoming Game and Fish Department. The original data are based mainly on the expert opinions of Wyoming Game and Fish Department biologists along with a small fraction of data from studies of radio-collared animals in various parts of the state.
The mapped migration corridors were then overlaid on a map showing the relative level of protection from development for different land management categories produced by the Wyoming Gap Analysis Project. These maps can be used to highlight general regions that encompass clusters of relatively threatened migration corridors. Combined with more precise data, they could help direct specific, on-the-ground, planning.
State Wildlife Action Plans
In 2005, each state and U.S. territory completed a plan to evaluate its wildlife conservation needs and outline its conservation priorities. These State Wildlife Action Plans (SWAPs) contain information on Species of Greatest Conservation Need (SGCN), critical habitat, threats to wildlife species and habitats, research needs, necessary actions, and conservation strategies. Together they provide a blueprint for national conservation efforts. These plans were mandated by the Federal government, and they must be updated by 2015.
Use of GAP in original (2005) State Wildlife Action Plans
In the first round of State Wildlife Action Plan development, GAP land cover and vertebrate species habitat distribution maps were important data sets. A survey of SWAP coordinators showed that twenty-two states relied heavily on GAP land cover data. While vegetation classifications were used by 33 percent of respondents, and predicted vertebrate species habitat distribution maps were used by 25 percent of respondents, aquatic species data, land stewardship, land ownership, species richness data, species lists, and habitat descriptions were also important.
The top priority identified in the SWAPs was a need for more research on species. With its new regional and national data, GAP will continue to provide vital information for state wildlife action plans.