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Analogies for a No-Analog World: Tackling Uncertainties in Reintroduction Planning
ElizabethS Forbes1, Peter S Alagona2, Andrea J Adams3
1Department of Ecology, Evolution, and Marine Biology, University of California, Santa Barbara, Santa Barbara, CA 93106-9620, USA.
Trends in Ecology & Evolution
|May 18, 2020
Summary
Species reintroductions face uncertainty, particularly in degraded habitats. Using historical and geographic comparisons can improve habitat suitability assessments for species proposed for reintroduction, like the California grizzly.
Area of Science:
- Conservation biology
- Wildlife management
- Ecological restoration
Background:
- Species reintroductions are crucial for conservation but carry significant uncertainty.
- Highly altered landscapes present unique challenges for reintroduction success.
- Assessing habitat suitability is a critical step in planning reintroductions.
Purpose of the Study:
- To explore how historical, geographic, and taxonomic analogies can reduce uncertainty in species reintroductions.
- To provide a framework for evaluating potential reintroduction sites using analog data.
- To apply this approach to the proposed reintroduction of the California grizzly.
Main Methods:
- Reviewing historical data on species distributions and habitat use.
- Analyzing geographic and ecological similarities between current and historical habitats.
- Utilizing taxonomic relatedness to infer habitat requirements and potential success.
Main Results:
- Analogical reasoning can effectively inform habitat suitability assessments.
- Historical and geographic data provide valuable proxies for predicting reintroduction outcomes.
- The approach helps identify suitable areas for the California grizzly reintroduction.
Conclusions:
- Analog-based assessments are a valuable tool for mitigating reintroduction uncertainty.
- This method enhances the scientific basis for conservation decisions in challenging environments.
- The California grizzly reintroduction can benefit from this evidence-based approach.
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