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This is an integrated scenario project to the PFLCC line that incorporates updated critical land and water identification project layers with a decision support system for landscape conservation planning in Florida. The scenarios incorporate climate change, urbanization, and policy assumptions into the scenarios.
Refinement of Gopher Tortoise Habitat Identification and Related Land Cover Data. The benefits of this project include: 1) much improved gopher tortoise remote habitat identification that could have a strong influence on potential listing status (with the likelihood that significantly more habitat may be identified); 2) better statewide land cover data regarding scrubby flatwoods and potentially refined mesic flatwoods and dry prairie classifications; and 3) potential spin off benefits regarding better habitat identification for related species such as gopher frogs and other xeric adapted species that might be found in on drier flatwoods and dry prairie sites.Continuation of Water Restoration Analyses. Considerable...
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The primary objective of this project is to develop a short synthesis report assessing 11 habitats, using a variety of ecological indicators. The report will be one tool that the South Atlantic LCC can use to inform decision-makers, stakeholders, and the general public about the health of South Atlantic habitats. To achieve this project, six discrete project tasks have been identified and are outlined in the next section.1) Project start-up and pre-workshop preparation: IAN will carefully review the Conservation Blueprint habitats and the indicators used to assess the health of these habitats. We will become familiar with the thresholds and data analysis that the South Atlantic LCC is using for their project. This...
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Many ecosystem models, particularly those that are “mechanistic” (based on an understanding of processes), are over-parameterized (not identifiable). As a result, model parameters are selected (not estimated using an optimization technique), parametererror/covariance terms become extremely difficult to estimate, and Monte Carlo error propagation does not adequately capture the effect of all uncertain model terms. In those situations, techniques that evolved from Regional (Generalized) Sensitivity Analysis (RSA), such as Generalized Likelihood Uncertainty Estimation (GLUE), Bayes Monte Carlo, and Markov Chain Monte Carlo (MCMC), are preferred techniques for model error propagation. These techniques can be used to...
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The Appalachian LCC is currently engaged in an effort to develop a draft regional conservation plan for the Cooperative using an interactive and iterative spatial prioritization framework. Using available data and modeling approaches that are well supported in the literature, researchers from Clemson University are developing conservation planning models that include site selection, ecological threat assessments, and broad ranging habitat and ecological connectivity analyses.The research team is working closely with designated technical teams from each major region in the Appalachian LCC to offer unique insights and input to help guide the interactive conservation planning process. After each round of feedback,...
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Provision of shade via riparian restoration is a well-established management adaptation strategy to mitigate against temperature increases in streams. Effective use of this strategy depends upon accurately identifying vulnerable, unforested riparian areas in priority coldwater stream habitats. An innovative riparian planting and restoration decision support tool is now available to the conservation community. This user-friendly tool allows managers and decision-makers to rapidly identify and prioritize areas along the banks of rivers, streams, and lakes for restoration, making these ecosystems more resilient to disturbance and future changes in climate.This research developed and implemented a user-friendly web-based...
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The USGS St. Petersburg Coastal and Marine Science Center (USGS St. Pete) processed lidar topographic data in Alaska. Raw lidar data are not in a format that is generally usable by resource managers and scientists for scientific analysis. Converting dense lidar elevation data into a readily usable format without loss of essential information requires specialized processing. Project included processing of lidar data acquired in Summer 2010 along the North Slope of Alaska between Colville River and Hulahula River.
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Over the last 3 years, high-resolution LiDAR elevation data has been acquired for much of the northern coast of Alaska in support of the USGS Coastal and Marine Geology Program’s National Assessment of Shoreline Change project. Because of funding limitations, LiDAR data were not collected over most river deltas and embayments. Subsequent discussions with scientists and managers from both public agencies and private organizations indicated a need and desire to fill the gaps in the coastal elevation data set, specifically over the low-lying deltas and estuaries that provide important habitat for migratory birds and other wildlife. The Arctic LCC provided support to help cover costs associated with acquiring and processing...
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Dozens of species of landbirds, such as warblers, hummingbirds, and orioles, migrate through the Northeastern United States from their summer breeding grounds in the U.S. and Canada to their nonbreeding grounds as far south as South America. During the migration period, birds must find habitat where they can stop, rest and replenish their energy reserves. Conservation efforts are increasingly focused on identifying stopover sites that are important for sustaining migratory landbird populations. This project builds upon prior work by the University of Delaware and USGS to use weather surveillance data and field surveys to map and predict important migratory bird stopover sites. This project was co-funded by through...
map background search result map search result map Synthesis of South Atlantic ecosystem health indicators Regionalized Sensitivity Analysis and related techniques applied to landscape and ecological response models Identifying Important Migratory Landbird Stopover Sites in the Northeast Riparian Restoration Decision Support Tool Interactive Conservation Planning for the Appalachian LCC North Slope Alaska Admiralty Bay LiDAR Alaska LiDAR Data Processing - Colville to Staines River North Slope Alaska Admiralty Bay LiDAR Alaska LiDAR Data Processing - Colville to Staines River Synthesis of South Atlantic ecosystem health indicators Regionalized Sensitivity Analysis and related techniques applied to landscape and ecological response models Riparian Restoration Decision Support Tool Interactive Conservation Planning for the Appalachian LCC Identifying Important Migratory Landbird Stopover Sites in the Northeast