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Integrated use of Geospatial and Biological Data to Predict African Tilapia Invasion

Integrated use of Geospatial and Biological Data to Predict African Tilapia Invasion in Northern Mesoamerica

The goal of Component 4 of IABIN’s Connectivity Program was to integrate geospatial data with biological data to demonstrate an effective approach for utilizing I3N and IABIN specimen databases to create predictive models that anticipate species invasions in freshwater habitats.  African tilapias were selected as a model organism to demonstrate the predictive modeling approach because they are a documented invasive species that is widely distributed through the IABIN program area and of obvious conservation concern.  A modeling system was developed for all of the domestic and international watersheds of Belize including portions of Guatemala, and Mexico.  The modeling system allows a user to draw on 27 specially prepared environmental datasets to predict patterns of habitat vulnerability to tilapia invasion in all of the 36,368 stream segments of the project area.
 
Integrated use of Geospatial and Biological Data to Predict African Tilapia Invasion 

Specific products that will be delivered to IABIN for evaluation and redistribution include:

 

  1. Environmental and Biotic Datasets – New streamline and water body shapefiles and a flow direction grid to match the streamlines; Fully attributed point occurrence shapefiles of tilapia and 76 native fish species; 27 raster layers of watershed and local predictor variables for incorporation into models.

 

  1. A web-accessible predictive modeling system and support documentation–An easy 7-step model creation process is facilitated through the project website, and accompanied by a 54-page detailed tutorial that allows the user recreate the entire modeling process.

 

  1. GIS Themes and Maps – A shapefile of the final tilapia model, and low and high resolution maps of these results.  The shapefile is accompanied by a detailed Technical Report that outlines the entire process used to create the model.

 

All of the datasets, reports, and websites mentioned above will be submitted with full metadata tl IABIN for inclusion in their online and in-house data repositories and catalogues.

 

This project successfully demonstrates a way that geospatial and biodiversity information can be combined to create value-added products that can assist with conservation decision making.  The outputs of species models are accurate high resolution predictions of habitat vulnerability to tilapias that are compellingly visual and easy to interpret.  Specific recommendations are made about how the power of species predictive modeling can be further enhanced through strategic investment by IABIN and its partners.

 

Lead institution:          Belize Foundation for Research and Environmental Education (Belize)

 

Other partners:           El Colegio de la Frontera Sur—ECOSUR (Mexico)

                                   The Nature Conservancy—Guatemala Program (Guatemala)

           The Central America Monitoring and Visualization System—SERVIR

 

Project Cost:             US$133,780

DGF Allocation:          US$49,455

 

 
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