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Red Flags and Species Endangerment: Meta-analytical Development of Criteria for Assessing Extinction Risk [1]

Principal Investigator(s): 

Robin Waples and Jeffrey Hutchings

Humans now dominate most global ecosystems, with severe consequences for biodiversity. Straightforward guidelines for risk assessment that are broadly applicable across diverse taxa, environments, and regulatory settings are essential for effective conservation of species and populations. We will use an empirically-based approach to developing risk criteria guidelines that takes advantage of large amounts of data for natural populations that have been compiled over the last 1-2 decades. Conceptually, we propose to consider a species ‘endangered’ if it has entered a ‘Red Zone’ characterized by two features:

a) actual risks of extinction rise rapidly, even though they can be difficult to predict quantitatively, and
b) uncertainty about key demographic/evolutionary processes increases exponentially.

The key then is to identify ‘Red Flags,’ or metrics that signal a species/population is in or near the Red Zone. We propose a rather broad interpretation of the Red Zone to include breakdown of key evolutionary processes within populations (e.g., loss of genetic variability, human-induced selection); and ecological interactions between populations (e.g., changes in predator-prey relationships, levels of interspecific competition); as well as the importance of biocomplexity and connectivity in promoting sustainability of interacting groups of populations. The practical usefulness of candidate Red Flag criteria will be tested by applying them to a large number of case studies of species that have been formally considered for federal protection in the US and Canada; and performance of quantitative models to predict probability of entering the Red Zone will be evaluated.

More information [2] about this research project and participants.


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Source URL: http://www.nceas.ucsb.edu/featured/waples

Links:
[1] http://www.nceas.ucsb.edu/featured/waples
[2] http://www.nceas.ucsb.edu/projects/12559