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<scp>SDM</scp>toolbox: a python‐based <scp>GIS</scp> toolkit for landscape genetic, biogeographic and species distribution model analyses

Jason L. BrownDepartment of Biology Duke University 125 Science Drive Durham NC 27705 USA
2014en
ABI

Аннотация

Summary Species distribution models ( SDM s) are broadly used in ecological and evolutionary studies. Almost all SDM methods require extensive data preparation in a geographic information system ( GIS ) prior to model building. Often, this step is cumbersome and, if not properly done, can lead to poorly parameterized models or in some cases, if too difficult, prevents the realization of SDM s. Further, for many studies, the creation of SDM s is not the final result and the post‐modelling processing can be equally arduous as other steps. SDM toolbox is designed to facilitate many complicated pre‐ and post‐processing steps commonly required for species distribution modelling and other geospatial analyses. SDM toolbox consists of 59 P ython script‐based GIS tools developed and compiled into a single interface. A large set of the tools were created to complement SDM s generated in M axent or to improve the predictive performance of SDM s created in M axent. However, SDM toolbox is not limited to analyses of M axent models, and many tools are also available for additional analyses or general geospatial processing: for example, assessing landscape connectivity of haplotype networks (using least‐cost corridors or least‐cost paths); correcting SDM over‐prediction; quantifying distributional changes between current and future SDM s; or for calculating several biodiversity metrics, such as corrected weighted endemism. SDM toolbox is a free comprehensive python‐based toolbox for macroecology, landscape genetic and evolutionary studies to be used in Arc GIS 10.1 (or higher) with the S patial A nalyst extension. The toolkit simplifies many GIS analyses required for species distribution modelling and other analyses, alleviating the need for repetitive and time‐consuming climate data pre‐processing and post‐ SDM analyses.

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