Effects of positional error on modeling species distributions: a perspective using presettlement land survey records View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2015-01

AUTHORS

Stephen J. Tulowiecki, Chris P. S. Larsen, Yi-Chen Wang

ABSTRACT

Presettlement land survey records (PLSRs) are the records of early land surveys in North America, and contain data regarding vegetation conditions prior to widespread European-American settlement. Researchers have used the data within PLSRs to develop species distribution models (SDMs), in order to generate predictions of the historical distributions of tree species. Despite their value for SDMs, PLSRs contain positional error, which may hinder their usefulness for modeling species distributions at fine spatial resolution. Using data from the Holland Land Company (HLC) township survey (1797–1799 CE) of Western New York, USA, this study examines the positional error associated with different approaches for georeferencing vegetation data within PLSRs. The study then examines the impact of positional error upon the predictive performance of SDMs that utilize PLSRs. Our study indicates that the magnitude of positional error within PLSRs varies with georeferencing approach, and that more accurate georeferencing approaches produce better-performing SDMs. The study also indicates that the effects of positional error upon SDMs vary with the niche characteristics of species. Overall, this study affirms the importance of accurately georeferencing species data prior to developing SDMs, including applications that involve PLSRs. More... »

PAGES

67-85

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11258-014-0417-9

DOI

http://dx.doi.org/10.1007/s11258-014-0417-9

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1041369792


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51 schema:description Presettlement land survey records (PLSRs) are the records of early land surveys in North America, and contain data regarding vegetation conditions prior to widespread European-American settlement. Researchers have used the data within PLSRs to develop species distribution models (SDMs), in order to generate predictions of the historical distributions of tree species. Despite their value for SDMs, PLSRs contain positional error, which may hinder their usefulness for modeling species distributions at fine spatial resolution. Using data from the Holland Land Company (HLC) township survey (1797–1799 CE) of Western New York, USA, this study examines the positional error associated with different approaches for georeferencing vegetation data within PLSRs. The study then examines the impact of positional error upon the predictive performance of SDMs that utilize PLSRs. Our study indicates that the magnitude of positional error within PLSRs varies with georeferencing approach, and that more accurate georeferencing approaches produce better-performing SDMs. The study also indicates that the effects of positional error upon SDMs vary with the niche characteristics of species. Overall, this study affirms the importance of accurately georeferencing species data prior to developing SDMs, including applications that involve PLSRs.
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