Present address: School of Environment, The University of Auckland, Private Bag 92019, Auckland 1142, New Zealand
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Python based GIS tools for landscape genetics: visualising genetic relatedness and measuring landscape connectivity
Article first published online: 8 JUL 2010
DOI: 10.1111/j.2041-210X.2010.00048.x
© 2010 The Author. Methods in Ecology and Evolution © 2010 British Ecological Society
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How to Cite
Etherington, T. R. (2011), Python based GIS tools for landscape genetics: visualising genetic relatedness and measuring landscape connectivity. Methods in Ecology and Evolution, 2: 52–55. doi: 10.1111/j.2041-210X.2010.00048.x
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Present address: School of Environment, The University of Auckland, Private Bag 92019, Auckland 1142, New Zealand
Publication History
- Issue published online: 3 FEB 2011
- Article first published online: 8 JUL 2010
- Received 21 April 2010; accepted 02 June 2010Handling Editor: Robert P. Freckleton
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Keywords:
- ArcGIS;
- geographic information system;
- least-cost modelling;
- Python
Summary
1. 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.
2. To help address this, a series of Python script based GIS tools have been developed for use in landscape genetics studies.
3. 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.
4. 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.