title: Planning for ex situ conservation in the face of uncertainty.
abstract: Ex situ conservation strategies for threatened species often require long-term commitment and financial investment to achieve management objectives. We present a framework that considers the decision to adopt ex situ management for a target species as the end point of several linked decisions. We used a decision tree to intuitively represent the logical sequence of decision making. The first decision is to identify the specific management actions most likely to achieve the fundamental objectives of the recovery plan, with or without the use of ex-situ populations. Once this decision has been made, one decides whether to establish an ex situ population, accounting for the probability of success in the initial phase of the recovery plan, for example, the probability of successful breeding in captivity. Approaching these decisions in the reverse order (attempting to establish an ex situ population before its purpose is clearly defined) can lead to a poor allocation of resources, because it may restrict the range of available decisions in the second stage. We applied our decision framework to the recovery program for the threatened spotted tree frog (Litoria spenceri) of southeastern Australia. Across a range of possible management actions, only those including ex situ management were expected to provide >50% probability of the species' persistence, but these actions cost more than use of in situ alternatives only. The expected benefits of ex situ actions were predicted to be offset by additional uncertainty and stochasticity associated with establishing and maintaining ex situ populations. Naïvely implementing ex situ conservation strategies can lead to inefficient management. Our framework may help managers explicitly evaluate objectives, management options, and the probability of success prior to establishing a captive colony of any given species.
authors: ARC Centre of Excellence for Environmental Decisions, School of BioSciences, University of Melbourne, 3010, Victoria, Australia.
authors: Stefano
authors: S
authors: Canessa
authors: United States Geological Survey, Patuxent Wildlife Research Center, 12100 Beech Forest Road, Laurel, MD 20708, U.S.A.
authors: Sarah J
authors: SJ
authors: Converse
authors: ARC Centre of Excellence for Environmental Decisions, School of BioSciences, University of Melbourne, 3010, Victoria, Australia.|Wildlife Conservation and Science, Zoos Victoria, Parkville, 3052, Victoria, Australia.
authors: Matt
authors: M
authors: West
authors: Arthur Rylah Institute for Environmental Research, Department of Environment and Primary Industries, Heidelberg, 3084, Victoria, Australia.
authors: Nick
authors: N
authors: Clemann
authors: Flora and Fauna Division, NT Department of Land Resource Management, Palmerston, 0831, Northern Territory, Australia.
authors: Graeme
authors: G
authors: Gillespie
authors: Taronga Conservation Society Australia, Mosman, 2088, NSW, Australia.
authors: Michael
authors: M
authors: McFadden
authors: Institute for Conservation Biology and Environmental Management, School of Biological Sciences, University of Wollongong, Wollongong, 2522 NSW, Australia.
authors: Aimee J
authors: AJ
authors: Silla
authors: ARC Centre of Excellence for Environmental Decisions, School of BioSciences, University of Melbourne, 3010, Victoria, Australia.
authors: Kirsten M
authors: KM
authors: Parris
authors: ARC Centre of Excellence for Environmental Decisions, School of BioSciences, University of Melbourne, 3010, Victoria, Australia.
authors: Michael A
authors: MA
authors: McCarthy
mesh_terms: D000818:Animals; D001315:Australia; D003247:Conservation of Natural Resources; D003657:Decision Making; D056727:Endangered Species; D035501:Uncertainty
keywords: captive breeding; cost-effectiveness; datos de expertos; decision tree; expert elicitation; management; manejo; multi-attribute value; reintroducción; reintroduction; rentabilidad; reproducción en cautiverio; valor multi-característico; zoológicos; zoos; árbol de decisiones