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A New Approach to Evaluate and Reduce Uncertainty of Model-Based Biodiversity Projections for Conservation Policy Formulation

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Bonnie J E Myers, Sarah R Weiskopf, Alexey N Shiklomanov, Simon Ferrier, Ensheng Weng, Kimberly A Casey, Mike Harfoot, Stephen T Jackson, Allison K Leidner, Timothy M Lenton, Gordon Luikart, Hiroyuki Matsuda, Nathalie Pettorelli, Isabel M D Rosa, Alex C Ruane, Gabriel B Senay, Shawn P Serbin, Derek P Tittensor, T Douglas Beard, A New Approach to Evaluate and Reduce Uncertainty of Model-Based Biodiversity Projections for Conservation Policy Formulation, BioScience, Volume 71, Issue 12, December 2021, Pages 1261–1273, https://doi.org/10.1093/biosci/biab094

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Abstract (from Bioscience): Biodiversity projections with uncertainty estimates under different climate, land-use, and policy scenarios are essential to setting and achieving international targets to mitigate biodiversity loss. Evaluating and improving biodiversity predictions to better inform policy decisions remains a central conservation goal and challenge. A comprehensive strategy to evaluate and reduce uncertainty of model outputs against observed measurements and multiple models would help to produce more robust biodiversity predictions. We propose an approach that integrates biodiversity models and emerging remote sensing and in-situ data streams to evaluate and reduce uncertainty with the goal of improving policy-relevant biodiversity [...]

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  • National CASC
  • National and Regional Climate Adaptation Science Centers

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citationTypeJournal Article
journalBioScience
parts
typeVolume
value71
typeIssue
value12
typeDOI
value10.1093/biosci/biab094

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