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Estimating historical forest density from land‐survey data: a response to Baker and Williams (2018)Author(s): Carrie R. Levine; Charles V Cogbill; Brandon M. Collins; Andrew J. Larson; James A. Lutz; Malcolm P. North; Christina M. Restaino; Hugh D. Safford; Scott L. Stephens; John J. Battles
Source: Ecological Applications
Publication Series: Scientific Journal (JRNL)
Station: Pacific Southwest Research Station
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DescriptionResearchers throughout the US have used the General Land Office (GLO) surveys of the late 19th and early 20th centuries to estimate historical forest conditions. These surveys were conducted throughout the US and represent a systematic, historical sample of trees across a broad geographic area. The challenge of using GLO survey data is the accurate estimation of density from sparse witness tree data. Levine et al. (2017) tested the accuracy and precision of four plotless density estimators that can be applied to GLO survey sample data, including the Cottam, Pollard, Morisita, and mean harmonic Voronoi density estimators. Baker and Williams (2018) contend that the major conclusions in Levine et al. (2017) are not valid. Based on this new analysis of the data, we confirmed the two main conclusions of Levine with respect to the MHVD.
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CitationLevine, Carrie R.; Cogbill, Charles V.; Collins, Brandon M.; Larson, Andrew J.; Lutz, James A.; North, Malcolm P.; Restaino, Christina M.; Safford, Hugh D.; Stephens, Scott L.; Battles, John J. 2019. Estimating historical forest density from land‐survey data: a response to Baker and Williams (2018). Ecological Applications. 30: 1103. https://doi.org/10.1002/eap.1968.
KeywordsForest, California, density, plotless density estimator, Voronoi-area
- Evaluating a new method for reconstructing forest conditions from General Land Office survey records
- Forests of Illinois, 2017
- Forests of Missouri, 2017
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