Landscape Analysis
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The U.S. Department of the Interior (DOI) Office of Policy Analysis has invited LANDFIRE, to present a seminar, Foundational All-Lands Data for Improving Decisions in Land Management, on September 10, 2018, in Washington, D.C. as part of their Seminar Series. The presentation is open to the public via webcast; the recorded event will also be posted to the Office of Policy Analysis website.
This webinar gives a brief introduction to multiple LANDFIRE datasets and then explore how two National Forests are working to tweak LANDFIRE data to better meet their needs. We will conclude by sharing resources and ideas that may help you think through modifying LANDFIRE or other similar datasets for your use.
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The interior secretary, Ryan Zinke, recently directed the agencies in his department to work with states and private landowners to minimize development and disturbance in migration corridors and winter ranges used by elk, mule deer and pronghorn antelope.
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The GBLCC Conservation Planning Atlas (CPA) is an important aspect of our effort to engage a landscape focus and best available science toward improving collaboration and maximizing conservation efforts in the Great Basin. Incorporating over 1000 spatial data layers related to conservation of the Great Basin region’s many natural and cultural resources, the CPA provides managers, researchers and planners from state, federal, local, NGO and private partners a valuable suite of tools for collaborative spatial planning. In short, the portal represents a single website to access regional spatial layers, decision support tools, and Great Basin LCC project information and products.
GBLCC’s Geospatial Data Specialist, Eric Jensen will be joined by Conservation Biology Institute’s Kai Henifin to share about the CPA. Together we will dive into navigation of the portal, data, tools and publications available, and the Data Basin suite of collaborative features—such as Groups, sharing and comment threads. Finally, we’ll explore current use cases and share information about how you or your group can leverage the CPA for your own projects and planning.
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In part due to its vegetative strategy, western aspen is host to a large number of insects and diseases. However, only a few are agents of significant impact that can cause or warn of substantial changes in the condition of aspen clones. Environmental conditions, particularly drought stress, also play an integral role in the life cycle of the important insects and diseases of aspen, and regional droughts were the triggering factor in the initiation of the most notable instances of substantial aspen dieback and decline.
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Map additions to the SGI Web App allow users to easily visualize songbird distribution, bolstering multi-species conservation across the American West.
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One of the greatest challenges facing landscape conservation is how to ensure ecosystem-wide conservation goals, such as those articulated in Landscape Conservation Designs, can effectively inform local management plans and actions. Developing feasible conservation goals and useful landscape planning products requires participation by local stakeholders. However, opportunities for these stakeholders to engage in planning processes are often limited. This webinar will examine the role of local stakeholders and human dimensions thinking in transboundary resource conservation. Catherine Doyle-Capitman, Doctoral Candidate at Cornell University, will highlight the role of local stakeholders in bridging the gap between conservation planning and management implementation. She will then present best practice guidance for engaging local stakeholders and integrating social data into landscape conservation decision processes.
The Nature Conservancy used soils data and satellite imagery to map plant communities to a one-meter resolution. They determined that 268 acres in Great Basin National Park is a basin wildrye ecosystem. This ecosystem was identified as the most endangered plant community in the Park through a park-wide watershed analysis and conservation planning assessment process.
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Our results demonstrated that the important predictors from Lidar-derived metrics had a strong correlation with field-measured biomass in the Random Forests (RF) regression models. The Stepwise Multiple Regression (SMR) results were similar but slightly better than RF. Overall, both RF and SMR methods explained more than 74% of the variance in biomass, with the most important Lidar variables being associated with vegetation structure and statistical measures of this structure (e.g., standard deviation of height was a strong predictor of biomass). Using our model results, we developed spatially-explicit Lidar estimates of total and shrub biomass across our study site in the Great Basin, U.S.A., for monitoring and planning in this imperiled ecosystem.
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Models explained much of the variability between predictions and manual measurements, and yet it is expected that future applications could produce even better results by reducing some of the methodological sources of error that we encountered. Our work demonstrates how terrestrial laser scanning (TLS) can be used efficiently to extend manual measurement of vegetation characteristics from small to large plots in grasslands and shrublands, with potential application to other similarly structured ecosystems. Our method shows that vegetation structural characteristics can be modeled without classifying and delineating individual plants, a challenging and time-consuming step common in previous methods applying TLS to vegetation inventory. Improving application of TLS to studies of shrub-steppe ecosystems will serve immediate management needs by enhancing vegetation inventories, environmental modeling studies, and the ability to train broader datasets collected from air and space.