Strategic Planning for Species Conservation: A Handbook - IUCN

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Strategic Planning for Species Conservation is often the only way to evaluate management approaches intended to prevent rare but catastrophic events (see example in Box 8.2). Modelling can also explore the range of possible or likely outcomes that can arise from one or more uncertain and often interacting processes (see example in Box 8.3). Box 8.2 An example of the use of PVA modeling to evaluate alternative management approaches: disease risks to island foxes. Epidemic disease was known to be a threat to the Critically Endangered island fox since one subspecies had experienced a massive population crash associated with an outbreak of infection with canine distemper virus (Timm et al. 2000). In developing a recovery plan for island foxes under the US Endangered Species Act, two potential approaches to the management of epidemic disease were considered (USFWS in prep): (a) intensive monitoring to detect outbreaks, with vaccination and quarantine; or (b) pre-emptive vaccination of a small proportion of the population as had been proposed for other endangered canids (Haydon, Laurenson and Sillero-Zubiri 2002; Vial et al. 2006). However, experimentation was impossible since disease epidemics occur very rarely, and the existence of only one wild population of each island subspecies would effectively preclude replicated trials. The two approaches were therefore simulated within wellparameterised PVA models (Doak and Bakker unpubl. data); this indicated that, given the small size of the islands, it would be essentially impossible to detect and respond to an epidemic before infection had spread through the population, whereas pre-emptive vaccination could be expected to substantially reduce the risk of disease-associated extinction. The latter approach was therefore adopted by land managers responsible for island fox conservation, after captive trials had confirmed that vaccination conferred no ill effects (Swarts 2006; Timm et al. 2002). Another area of Action in which mathematical modelling – particularly statistical modelling – is extremely useful is in the design of surveys and monitoring programmes. Estimates of population sizes, and trends in population size, are often considered critical for evaluating the outcomes of entire conservation programmes, as well as for measuring the effectiveness of particular Actions. However, the most appropriate methods vary greatly according to circumstances. General methodologies are available (see, for example, Buckland et al. 2001; Legg and Nagy 2006; MacKenzie et al. 2005; Shrader-Frechette and McCoy 1993; Williams, Nichols and Conroy 2002), but further modelling may be valuable for tailoring methods for particular species or circumstances (see, for instance, Barnes 2002; Karanth and Nichols 2002; Plumptre 2000; Sims et al. 2006; Taylor and Gerrodette 1993). 8.4 Monitoring the effectiveness of Actions: indicators of success The implementation of any management approach should be combined with monitoring of its effectiveness, as this allows refinement of successful approaches and abandonment of unsuccessful ones. Such monitoring is especially important for novel approaches which have not been fully evaluated for a particular species or set of circumstances. In many SCSs, monitoring of wildlife populations will be recommended as its own discrete Action, or set of Actions; such monitoring will be needed to determine whether progress has been made towards achieving the agreed Goals. 69
Box 8.3 An example of the use of PVA modelling to evaluate alternative management approaches: oil field development in habitat of the greater sage grouse. 70 8. Actions In the state of Colorado, USA, extraction of petroleum and natural gas was identified as a primary threat to the greater sage grouse, primarily through the disruption of grouse lek sites and direct mortality of individuals. PVA modelling was used to evaluate the demographic impact of developing gas fields and, after careful validation and sensitivity analysis, to explore the likely consequences of different ways of conducting such development (Schnurr et al. 2006). PVA models were developed initially in a workshop setting, with direct involvement of representatives from the State’s petroleum industry as well as representatives from the State’s wildlife management authority. This diverse participation in the process, even by those largely unfamiliar with the techniques of PVA, was key to the success of the overall effort. Detailed hypotheses concerning the relationship between petroleum extraction and sage grouse demography were created, and mitigation of these extraction activities was defined by altering the relative duration of high-intensity development of the gas field, and/or the length of time taken to achieve the transition from gas field development to production (Figure 8.1). Analysis of alternative mitigation strategies suggested that the critical variable was the duration of high-intensity development (Figure 8.2). This information was used to recommend management actions designed to minimize the impact of oil-field development in greater sage grouse habitat – if development were to proceed at all. Figure 8.1 Alternative scenarios concerning the impact of oil field development on sage grouse mortality (Adopting different development scenarios is assumed to influence the magnitude and duration of mortality effects.) Figure 8.2 Projections of average sage grouse population size under the scenarios of oil field development depicted in Figure 8.1, based on PVA modeling Source: Both Figures are adapted from Schnurr et al. 2006
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