County data related to forest dependence and community capitals, 2014-2019

Frey, Gregory E.; Kallayanamitra, Chalisa; Wilkens, Philadelphia; James, Natasha A.

doi:10.2737/rds-2021-0077

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“…All data described in this section were compiled and published in an online, public database [1]. This public database provides data on several variables from public sources, including the information described below, as well as other indicators of community resilience [24].…”

Section: Methodsmentioning

confidence: 99%

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Defining and Measuring Forest Dependence in the United States: Operationalization and Sensitivity Analysis

Frey

Kallayanamitra²,

Wilkens³

et al. 2022

Forests

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This manuscript helps bridge a gap between theoretical work that advocates for a broad view of forest dependence, and empirical work that has focused narrowly on economic measures. Background: Forest dependence has been widely recognized as a valuable concept for understanding human communities’ well-being and vulnerability to shocks and changes. Past theoretical literature has highlighted the importance of recognizing various types of dependence—environmental, economic, and social—yet past empirical literature on the topic in the United States has almost exclusively relied on measures of economic dependence such as employment and earnings from the traditional forest products sector. Objective and Methods: As a first step to bridge the gap between the theoretical and empirical, we reviewed the existing, publicly available, reliable, wall-to-wall data sources to identify alternate proxy measures for forest dependence. Data availability made the analysis feasible only at the county level—the administrative subdivisions of the state—or higher. Results and Conclusions: We created environmental, economic, and social criteria based on threshold levels of the following proxy variables: forest area, earnings, employment, and indigenous population. Using these criteria, we identified 524 counties to be potentially forest-dependent of 3140 total counties in the United States. The largest concentration was in the Pacific Northwest and Southeast regions, and a higher proportion were non-metro counties than metro. Varying the threshold levels significantly changes the number of counties identified but does not alter the overall geographic trends.

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Section: Methodsmentioning

confidence: 99%

“…Data Availability Statement: All data described in the Materials and Methods section have been compiled and published in an online, public database [1].…”

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confidence: 99%