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Modeling with uncertain science: estimating mitigation credits from abating lead poisoning in Golden Eagles.

Challenges arise when renewable energy development triggers "no net loss" policies for protected species, such as where wind energy facilities affect Golden Eagles in the western United States. When established mitigation approaches are insufficient to fully avoid or offset losses, conservation goal... Full description

Journal Title: Ecological applications : a publication of the Ecological Society of America September 2015, Vol.25(6), pp.1518-1533
Main Author: Fitts Cochrane, Jean
Other Authors: Lonsdorf, Eric , Allison, Taber D , Sanders-Reed, Carol A
Format: Electronic Article Electronic Article
Language: English
Subjects:
ID: ISSN: 1051-0761
Link: http://search.proquest.com/docview/1732595494/?pq-origsite=primo
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recordid: proquest1732595494
title: Modeling with uncertain science: estimating mitigation credits from abating lead poisoning in Golden Eagles.
format: Article
creator:
  • Fitts Cochrane, Jean
  • Lonsdorf, Eric
  • Allison, Taber D
  • Sanders-Reed, Carol A
subjects:
  • Animals–Toxicity
  • Computer Simulation–Toxicity
  • Eagles–Veterinary
  • Environmental Monitoring–Veterinary
  • Environmental Pollutants–Veterinary
  • Lead–Veterinary
  • Lead Poisoning–Veterinary
  • Models, Biological–Veterinary
  • Uncertainty–Veterinary
  • Environmental Pollutants
  • Lead
ispartof: Ecological applications : a publication of the Ecological Society of America, September 2015, Vol.25(6), pp.1518-1533
description: Challenges arise when renewable energy development triggers "no net loss" policies for protected species, such as where wind energy facilities affect Golden Eagles in the western United States. When established mitigation approaches are insufficient to fully avoid or offset losses, conservation goals may still be achievable through experimental implementation of unproven mitigation methods provided they are analyzed within a framework that deals transparently and rigorously with uncertainty. We developed an approach to quantify and analyze compensatory mitigation that (1) relies on expert opinion elicited in a thoughtful and structured process to design the analysis (models) and supplement available data, (2) builds computational models as hypotheses about cause–effect relationships, (3) represents scientific uncertainty in stochastic model simulations, (4) provides probabilistic predictions of "relative" mortality with and without mitigation, (5) presents results in clear formats useful to applying risk management preferences (regulatory standards) and selecting strategies and levels of mitigation for immediate action, and (6) defines predictive parameters in units that could be monitored effectively, to support experimental adaptive management and reduction in uncertainty. We illustrate the approach with a case study characterized by high uncertainty about underlying biological processes and high conservation interest: estimating the quantitative effects of voluntary strategies to abate lead poisoning in Golden Eagles in Wyoming due to ingestion of spent game hunting ammunition.
language: eng
source:
identifier: ISSN: 1051-0761
fulltext: fulltext
issn:
  • 10510761
  • 1051-0761
url: Link


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titleModeling with uncertain science: estimating mitigation credits from abating lead poisoning in Golden Eagles.
creatorFitts Cochrane, Jean ; Lonsdorf, Eric ; Allison, Taber D ; Sanders-Reed, Carol A
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identifierISSN: 1051-0761
subjectAnimals–Toxicity ; Computer Simulation–Toxicity ; Eagles–Veterinary ; Environmental Monitoring–Veterinary ; Environmental Pollutants–Veterinary ; Lead–Veterinary ; Lead Poisoning–Veterinary ; Models, Biological–Veterinary ; Uncertainty–Veterinary ; Environmental Pollutants ; Lead
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descriptionChallenges arise when renewable energy development triggers "no net loss" policies for protected species, such as where wind energy facilities affect Golden Eagles in the western United States. When established mitigation approaches are insufficient to fully avoid or offset losses, conservation goals may still be achievable through experimental implementation of unproven mitigation methods provided they are analyzed within a framework that deals transparently and rigorously with uncertainty. We developed an approach to quantify and analyze compensatory mitigation that (1) relies on expert opinion elicited in a thoughtful and structured process to design the analysis (models) and supplement available data, (2) builds computational models as hypotheses about cause–effect relationships, (3) represents scientific uncertainty in stochastic model simulations, (4) provides probabilistic predictions of "relative" mortality with and without mitigation, (5) presents results in clear formats useful to applying risk management preferences (regulatory standards) and selecting strategies and levels of mitigation for immediate action, and (6) defines predictive parameters in units that could be monitored effectively, to support experimental adaptive management and reduction in uncertainty. We illustrate the approach with a case study characterized by high uncertainty about underlying biological processes and high conservation interest: estimating the quantitative effects of voluntary strategies to abate lead poisoning in Golden Eagles in Wyoming due to ingestion of spent game hunting ammunition.
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