Choosing cost-effective locations for conservation fences in the local landscape
Michael Bode A E , Karl E. C. Brennan B , Keith Morris C , Neil Burrows D and Neville Hague B
+ Author Affiliations
- Author Affiliations
A ARC Centre of Excellence for Environmental Decisions, School of Botany, University of Melbourne, Vic. 3010, Australia.
B Goldfields Region, Department of Environment & Conservation, PO Box 10173, Kalgoorlie, WA 6430, Australia.
C Science Division, Department of Environment & Conservation, PO Box 51 Wanneroo, WA 6946, Australia.
D Science Division, Department of Environment & Conservation, Locked Bag 104, Bently Delivery Centre, WA 6983, Australia.
E Corresponding author. Email: mbode@unimelb.edu.au
Wildlife Research 39(3) 192-201 https://doi.org/10.1071/WR11106
Submitted: 21 June 2011 Accepted: 12 January 2012 Published: 5 April 2012
Abstract
Context: Exclosure fences are widely used to reintroduce locally extinct animals. These fences function either as permanent landscape-scale areas free from most predators, or as small-scale temporary acclimatisation areas for newly translocated individuals to be ‘soft released’ into the wider landscape. Existing research can help managers identify the best design for their exclosure fence, but there are currently no methods available to help identify the optimal location for these exclosures in the local landscape (e.g. within a property).
Aims: We outline a flexible decision-support tool that can help managers choose the best location for a proposed exclosure fence. We applied this method to choose the site of a predator-exclusion fence within the proposed Lorna Glen (Matuwa) Conservation Park in the rangelands of central Western Australia.
Methods: The decision was subject to a set of economic, ecological and political constraints that were applied sequentially. The final exclosure fence location, chosen from among those sites that satisfied the constraints, optimised conservation outcomes by maximising the area enclosed.
Key results: From a prohibitively large set of potential exclosure locations, the series of constraints reduced the number of candidates down to 32. When ranked by the total area enclosed, one exclosure location was clearly superior.
Conclusions: By describing the decision-making process explicitly and quantitatively, and systematically considering each of the candidate solutions, our approach identifies an efficient exclosure fence location via a repeatable and transparent process.
Implications: The construction of an exclusion fence is an expensive management option, and therefore needs to convincingly demonstrate a high expected return-on-investment. A systematic approach for choosing the location of an exclosure fence provides managers with a decision that can be justified to funding sources and stakeholders.
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