A WPS Based Biogeography Tool for QGIS

Session Type: 
Tech Session
Presenter(s): 
Jeffery Cavner, Natural History Museum, University of Kansas
Species presence/absence matrices (PAMs) are an important data representation structure in biogeography used to test ecological and evolutionary hypotheses about the properties of species diversity on large geographic scales. PAMs logically link the known biological diversity of geographic areas with the range sizes and properties of their constituent species.
 
Construction of PAMs can be an extremely time consuming data management task when using a heterogeneous collection of GIS tools and statistical packages each with a required learning curve. Packages such as Ecosim and R do not present researchers with intuitive methods for working with these matrices and can be computationally slow when used with large data sets representing hundreds or thousands of species.
 
We use PyWPS, a Python implementation of the Web Processing Service standard to expose spatial and statistical algorithms for generating PAMs of species data, as well as to create species and range indices and null hypothesis data computational input for these indices. Species data based on current and predicted distribution model outputs based on climate scenario data populate the PAMs. A QGIS Python plug-in is used as a client to WPS services that process the species data and perform the matrix calculations in order to build range diversity plots by species and by geographic site. Range diversity plots are then linked in QGIS allowing for ‘brushing’ of datasets by species or location across phylogenetic tree data space and geographic data space, respectively.
 
By employing WPS services with an established and extensible open source GIS platform we provide intuitive, efficient and data rich biogeography tools for formulating biogeographical hypotheses and for simultaneously analyzing and visualizing species ranges and geospatial biological diversity patterns through range-diversity plots.  This web service and thick client architecture will transform current research practices of PAM assembly and advance biodiversity research and education of the global impacts of climate change on biological species and communities.

 

Speaker Bio: 

Jeff Cavner is a software developer for the Bioinformatics Department for the Biodiversity Institute at the Natural History Museum, University of Kansas.

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