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ZENODO
Software . 2021
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ZENODO
Software . 2021
Data sources: Datacite
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ZENODO
Software . 2021
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Python based GIS tools for landscape genetics: visualising genetic relatedness and measuring landscape connectivity

Authors: Etherington, Thomas R.;

Python based GIS tools for landscape genetics: visualising genetic relatedness and measuring landscape connectivity

Abstract

Landscape genetics is an area of research that can help to understand many spatial ecological processes, but requires significant interdisciplinary collaboration. Use of geographic information system (GIS) software is essential, but requires a degree of customisation that is often beyond the non-specialist. To help address this, a series of Python script based GIS tools have been developed for use in landscape genetics studies. The scripts convert files, visualise genetic relatedness, and measure landscape connectivity using least-cost path analysis. The scripts are housed in an ArcToolbox that is freely available along with the underlying Python code. The Python scripts allow researchers to use more current software, provide the option of further development by the user community, and reduce the amount of time that would be spent developing common solutions. For a full description of the software please refer to following freely available paper: Etherington TR 2011. Python based GIS tools for landscape genetics: visualising genetic relatedness and measuring landscape connectivity. Methods in Ecology and Evolution 2: 52-55 https://doi.org/10.1111/j.2041-210X.2010.00048.x.

{"references": ["Etherington TR 2011. Python based GIS tools for landscape genetics: visualising genetic relatedness and measuring landscape connectivity. Methods in Ecology and Evolution 2: 52-55 https://doi.org/10.1111/j.2041-210X.2010.00048.x."]}

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Keywords

least-cost modelling, geographic information system, landscape genetics, ArcGIS

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
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1
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4