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Examining Local Transferability of Predictive Species Distribution Models for Invasive Plants: An Example with Cogongrass (Imperata cylindrica)

Published online by Cambridge University Press:  20 January 2017

Gary N. Ervin  and
D. Christopher Holly
Gary N. Ervin*
Affiliation:
Department of Biological Sciences, Mississippi State University, MS 39762
D. Christopher Holly
Affiliation:
Department of Biological Sciences, Mississippi State University, MS 39762
*
Corresponding author's E-mail: [email protected]
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Abstract

Species distribution modeling is a tool that is gaining widespread use in the projection of future distributions of invasive species and has important potential as a tool for monitoring invasive species spread. However, the transferability of models from one area to another has been inadequately investigated. This study aimed to determine the degree to which species distribution models (SDMs) for cogongrass, developed with distribution data from Mississippi (USA), could be applied to a similar area in neighboring Alabama. Cogongrass distribution data collected in Mississippi were used to train an SDM that was then tested for accuracy and transferability with cogongrass distribution data collected by a forest management company in Alabama. Analyses indicated the SDM had a relatively high predictive ability within the region of the training data but had poor transferability to the Alabama data. Analysis of the Alabama data, via independent SDM development, indicated that predicted cogongrass distribution in Alabama was more strongly correlated with soil variables than was the case in Mississippi, where the SDM was most strongly correlated with tree canopy cover. Results suggest that model transferability is influenced strongly by (1) data collection methods, (2) landscape context of the survey data, and (3) variations in qualitative aspects of environmental data used in model development.

Keywords

Cogongrass, Imperata cylindrica (L.) Beauv. IMPCYEcological modelingenvironmental niche modelsgeospatial soil dataland cover datamaximum entropy models
Type
Research Article
Information
Invasive Plant Science and Management , Volume 4 , Issue 4 , December 2011 , pp. 390 - 401
Copyright
Copyright © Weed Science Society of America 

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Footnotes

Current address: 1154 East Wellsgate Drive, Oxford, MS, 38655

References

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