Literature DB >> 20971548

Improving our legacy: incorporation of adaptive management into state wildlife action plans.

Joseph J Fontaine1.   

Abstract

The loss of biodiversity is a mounting concern, but despite numerous attempts there are few large scale conservation efforts that have proven successful in reversing current declines. Given the challenge of biodiversity conservation, there is a need to develop strategic conservation plans that address species declines even with the inherent uncertainty in managing multiple species in complex environments. In 2002, the State Wildlife Grant program was initiated to fulfill this need, and while not explicitly outlined by Congress follows the fundamental premise of adaptive management, 'Learning by doing'. When action is necessary, but basic biological information and an understanding of appropriate management strategies are lacking, adaptive management enables managers to be proactive in spite of uncertainty. However, regardless of the strengths of adaptive management, the development of an effective adaptive management framework is challenging. In a review of 53 State Wildlife Action Plans, I found a keen awareness by planners that adaptive management was an effective method for addressing biodiversity conservation, but the development and incorporation of explicit adaptive management approaches within each plan remained elusive. Only ~25% of the plans included a framework for how adaptive management would be implemented at the project level within their state. There was, however, considerable support across plans for further development and implementation of adaptive management. By furthering the incorporation of adaptive management principles in conservation plans and explicitly outlining the decision making process, states will be poised to meet the pending challenges to biodiversity conservation. Published by Elsevier Ltd.

Mesh:

Year:  2010        PMID: 20971548     DOI: 10.1016/j.jenvman.2010.10.015

Source DB:  PubMed          Journal:  J Environ Manage        ISSN: 0301-4797            Impact factor:   6.789


  2 in total

1.  Distribution model transferability for a wide-ranging species, the Gray Wolf.

Authors:  M G Gantchoff; D E Beyer; J D Erb; D M MacFarland; D C Norton; B J Roell; J L Price Tack; J L Belant
Journal:  Sci Rep       Date:  2022-08-08       Impact factor: 4.996

2.  AMModels: An R package for storing models, data, and metadata to facilitate adaptive management.

Authors:  Therese M Donovan; Jonathan E Katz
Journal:  PLoS One       Date:  2018-02-28       Impact factor: 3.240

  2 in total

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