A Framework for Spatial Risk Assessments: Potential Impacts of Nonindigenous Invasive Species on Native Species
Craig R Allen, USGS Nebraska Cooperative Fish & Wildlife Research Unit, University of Nebraska
Alan R Johnson, Clemson University
Leslie Parris, Clemson University
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Many populations of wild animals and plants are declining and face increasing threats from habitat fragmentation and loss as well as exposure to stressors ranging from toxicants to diseases to invasive nonindigenous species. We describe and demonstrate a spatially explicit ecological risk assessment that allows for the incorporation of a broad array of information that may influence the distribution of an invasive species, toxicants, or other stressors, and the incorporation of landscape variables that may influence the spread of a species or substances. The first step in our analyses is to develop species models and quantify spatial overlap between stressor and target organisms. Risk is assessed as the product of spatial overlap and a hazard index based on target species vulnerabilities to the stressor of interest. We illustrate our methods with an example in which the stressor is the ecologically destructive nonindigenous ant, Solenopsis invicta
, and the targets are two declining vertebrate species in the state of South Carolina, USA. A risk approach that focuses on landscapes and that is explicitly spatial is of particular relevance as remaining undeveloped lands become increasingly uncommon and isolated and more important in the management and recovery of species and ecological systems. Effective ecosystem management includes the control of multiple stressors, including invasive species with large impacts, understanding where those impacts may be the most severe, and implementing management strategies to reduce impacts.
declining species; invasive species; nonindigenous species; risk assessment; spatial risk.
Copyright © 2006 by the author(s). Published here under license by The Resilience Alliance. This article is under a Creative Commons Attribution-NonCommercial 4.0 International License. You may share and adapt the work for noncommercial purposes provided the original author and source are credited, you indicate whether any changes were made, and you include a link to the license.