Restoration of the American Chestnut: a GIS Approach
2019
- 74Usage
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Usage74
- Abstract Views74
Interview Description
Anthropogenic factors have been the causal agents in the decline of tree species globally. From logging and development to disease and poor management, threats to our forests have taken their toll. One species, the American chestnut (Castanea dentata) was once an integral basal tree species in Appalachian forests but was eliminated on the landscape by chestnut blight by the mid 1900’s, and is now functionally extinct. Blight-resistant chestnuts have been created to reintroduce them back into their historical range. Efficient and effective reintroduction will require optimal restoration sites that will maximize planting success. I propose to conduct a large-scale project focusing on site suitability of Kentucky’s US Forest Service lands. Specifically, I will evaluate the degree to which site suitability criteria from literature can predict chestnut locations in both Land Between the Lakes National Recreation Area (LBL) and Daniel Boone National Forest (DBNF). Resulting analyses from remotely sensed data and maps will be used to further refine our knowledge of chestnut reintroduction and determine how land managers can optimize and expedite the reintroduction process across large landscapes. This project will provide a geospatial framework for chestnut reintroduction and improve methodologies for creating future frameworks for other at-risk species. The results of this project thus have the potential to serve as a model for land managers to utilize GIS and remotely sensed data as tools for the restoration of degraded landscapes.
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