Featured GIS Projects
How does the Southeast region of the U.S. Fish and Wildlife Service use GIS? Check out a curated list of GIS projects below!
Red-cockaded woodpecker geographic variation in habitat from LiDAR
Leveraging the statewide LiDAR data collection in North Carolina, the Raleigh Field Office has been processing the 360 billion points of LiDAR data collected in the eastern 60 counties to generate vegetation metrics such as canopy height and understory vegetation distribution and density. The LiDAR data was processed at a resolution of 20ft ( 6.096m) to give a fine scale look at localized vegetative habitat. Since this data has been collected at a broad geographic scale, it allows for a broader analysis of specieshabitat interaction. This allows one to see the overall vegetative habitat preferences of species , as well as extracting geographic variation in preferences of habitat. Ongoing work involves obtaining species observations from databases such as the Global Biological Information Facility, gbif.org or the North Carolina Natural Heritage Program to compare the locations to the vegetation structure metrics in the immediate vicinity.
Initial results indicate that different canopy structure data sets will be useful in working with our partners to further our understanding of species - habitat interactions for multiple species and improving conservation planning efforts.
South Atlantic LCC Blueprint 2.2
The South Atlantic Conservation Blueprint is a living spatial plan to conserve natural and cultural resources for future generations. It identifies opportunities for shared conservation action in the face of future changes like sea-level rise and urban growth.
The latest update to the Blueprint, Version 2.2, was released in November 2017. The Blueprint is totally data-driven, prioritizing the lands and waters of the South Atlantic based on the current condition of terrestrial, freshwater, marine, and cross-ecosystem indicators. Through a connectivity analysis, the Blueprint also identifies corridors that link coastal and inland areas and span climate gradients. So far, more than 500 people from 150 different organizations have actively participated in developing the Blueprint. The South Atlantic Blueprint also integrates with a broader Southeast-wide plan as part of the Southeast Conservation Adaptation Strategy (SECAS).
The Blueprint has been used in more than thirty different projects, helping members of the cooperative bring national fire resilience funding to the region, compete for coastal wetlands protection grants, provide landscape-scale context for public lands planning, plan for major disasters, and prioritize fish passage efforts. Through a transparent process, a science-based plan, and a user-friendly product, the South Atlantic LCC intends the Blueprint to eventually become a “gold standard” for guiding large landscape conservation.
The Blueprint is available online through two mapping viewers: the Simple Viewer and the Conservation Planning Atlas. The Simple Viewer summarizes Blueprint priorities, indicator status, and supporting information within subwatersheds and marine lease blocks. The Conservation Planning Atlas allows users to overlay additional datasets, view indicator layers, and download Blueprint data.
If you have questions or would like help incorporating the Blueprint into your conservation work, please reach out to Hilary Morris at email@example.com.
Mapping beach mice habitat
Scampering among the dunes on a small barrier island along the northwest coast of Florida, south of Pensacola, is a small, light colored mouse called the Perdido Key beach mouse (Peromyscus polionotus trissyllepsis). Beach mice are a group of Peromyscus that have adapted to making their living in and among the coastal dune systems in Florida and Alabama. In all, there are eight subspecies, of which six are federally listed and one is presumed extinct. According to the 2006 Designation of Critical Habitat Final Rule, loss of habitat and resulting fragmentation is the greatest threat to the subspecies. Furthermore, it states that for the conservation of the subspecies we need to establish large connected tracts of land that provide all the habitat components (primary, secondary, and scrub dunes) necessary for the long-term survival of the species.
To that end we are attempting to map the coastal dune system with respect to the habitat components of beach mice habitat using data and imagery collected by satellites in space (remotely sensed data). Existing land cover data falls short both in resolution (way too course) and in classification (way too general). Therefore, by using data and imagery collected from airplanes (remotely sensed data) our primary goal is to develop a high-resolution habitat map that we can use to help inform and guide conservation actions implemented for the recovery this species. Our secondary goal is to develop a methodology for which we can apply this same process to the other beach mice subspecies ranges and to look at changes in habitat over time, particularly in the wake of tropical storm events.
By employing object-based image analysis (OBIA) on high-resolution aerial imagery we are able to look at the diversity of the coastal dune habitat, defined by the mosaic of sand and vegetation. Defining these objects then allows us to map areas of habitat with similar characteristics of this mosaic. Once the objects are identified they are then classified as primary, secondary or scrub dune habitat based on the characteristics of the pixels of the imagery within each of these objects.
We are also using highly-accurate laser-based, remotely sensed data, known as LiDAR, to help us a create 3-D view (called digital terrain models or DTM) of the coastal dune system. Because we can “see” the dunes in 3-D, we are able to do some really cool things like mapping dune footprints and dune fields; identifying areas that do not get inundated during tropical storm events, etc. All of this put together helps us to get a better understanding of beach mice habitat across the landscape and as a result better address recovery of these species.
Mottled duck decision support tool
The Gulf Coast Joint Venture (GCJV) region provides valuable habitat for wintering and resident waterfowl species. The mottled duck (Anas fulvigula) is a resident species associated with coastal marsh habitat, a habitat that has significantly declined throughout the GCJV. This decline is a result of several factors, some of which include urbanization, subsidence, sea level rise, altered hydrology due to canal and levee construction, and the spread of invasive species. This loss and fragmentation of habitat has raised concerns about the mottled duck population within the GCJV region, specifically the loss of suitable nesting and brood-rearing habitat (Wilson 2007). Strategies to increase mottled duck populations are primarily based on efforts to increase nest success and brood survival. This is primarily done by either preserving or creating landscapes that contain suitable nesting and brood-rearing habitat in the appropriate spatial configuration.
Researchers at Texas A&M, Kingsville, along with GCJV staff, have developed a Decision Support Tool (DST) designed to aid land managers in: (1) identifying currently suitable nesting (grassland) and brood-rearing (non-saline marsh) habitat, (2) areas where grassland establishment would be beneficial for nesting mottled ducks, and (3) areas where wetland enhancement would be beneficial for brood-rearing activities of mottled ducks.
Parameters for identifying suitable nesting habitat included land cover type, size of nesting patch, edge-to-interior ratio of nesting patches, and distance of nesting patch to suitable brood-rearing habitat. Parameters used to identify suitable brood-rearing habitat included wetland type, hydroperiod (the number of years out of 9 years that a habitat patch was inundated), and distance of brood-rearing patch to suitable nesting habitat.
To maximize the biological return from conservation investment, the DST prioritizes both suitable nesting and brood-rearing habitat. This prioritization was based on the density of both suitable nesting and brood-rearing habitat within 1 mile of each habitat type, the distance of each habitat type from the other, and the hydroperiod of a given brood-rearing habitat.