Robust conservation decision-making


Autoria(s): McDonald-Madden, E.; Baxter, P. W. J.; Possingham, H. P.
Contribuinte(s)

Ayyub, Bilal

Data(s)

2011

Resumo

Decision-making for conservation is conducted within the margins of limited funding. Furthermore, to allocate these scarce resources we make assumptions about the relationship between management impact and expenditure. The structure of these relationships, however, is rarely known with certainty. We present a summary of work investigating the impact of model uncertainty on robust decision-making in conservation and how this is affected by available conservation funding. We show that achieving robustness in conservation decisions can require a triage approach, and emphasize the need for managers to consider triage not as surrendering but as rational decision making to ensure species persistence in light of the urgency of the conservation problems, uncertainty, and the poor state of conservation funding. We illustrate this theory by a specific application to allocation of funding to reduce poaching impact on the Sumatran tiger Panthera tigris sumatrae in Kerinci Seblat National Park, Indonesia. To conserve our environment, conservation managers must make decisions in the face of substantial uncertainty. Further, they must deal with the fact that limitations in budgets and temporal constraints have led to a lack of knowledge on the systems we are trying to preserve and on the benefits of the actions we have available (Balmford & Cowling 2006). Given this paucity of decision-informing data there is a considerable need to assess the impact of uncertainty on the benefit of management options (Regan et al. 2005). Although models of management impact can improve decision making (e.g.Tenhumberg et al. 2004), they typically rely on assumptions around which there is substantial uncertainty. Ignoring this 'model uncertainty', can lead to inferior decision-making (Regan et al. 2005), and potentially, the loss of the species we are trying to protect. Current methods used in ecology allow model uncertainty to be incorporated into the model selection process (Burnham & Anderson 2002; Link & Barker 2006), but do not enable decision-makers to assess how this uncertainty would change a decision. This is the basis of information-gap decision theory (info-gap); finding strategies most robust to model uncertainty (Ben-Haim 2006). Info-gap has permitted conservation biology to make the leap from recognizing uncertainty to explicitly incorporating severe uncertainty into decision-making. In this paper we present a summary of McDonald-Madden et al (2008a) who use an info-gap framework to address the impact of uncertainty in the functional representations of biological systems on conservation decision-making. Furthermore, we highlight the importance of two key elements limiting conservation decision-making - funding and knowledge - and how they interact to influence the best management strategy for a threatened species. Copyright © ASCE 2011.

Formato

application/pdf

Identificador

http://eprints.qut.edu.au/82407/

Publicador

American Society of Civil Engineers (ASCE)

Relação

http://eprints.qut.edu.au/82407/1/82407.pdf

DOI:10.1061/41170(400)115

McDonald-Madden, E., Baxter, P. W. J., & Possingham, H. P. (2011) Robust conservation decision-making. In Ayyub, Bilal (Ed.) Vulnerability, Uncertainty, and Risk Analysis, Modeling, and Management, American Society of Civil Engineers (ASCE), Hyattsville, Maryland, pp. 945-952.

Direitos

American Society of Civil Engineers (ASCE)

Fonte

School of Earth, Environmental & Biological Sciences; Science & Engineering Faculty

Palavras-Chave #Andersons #Conservation biology #Decision makers #Functional representation #Indonesia #Info-gap #Information-gap #Key elements #Management options #Management strategies #Model Selection #Model uncertainties #National parks #Rational decision making #Scarce resources #Species persistence #Temporal constraints #Threatened species #Conservation #Decision theory #Ecology #Finance #Managers #Parks #Risk analysis #Risk assessment #Uncertainty analysis #Decision making
Tipo

Conference Paper