School of BioSciences - Research Publications
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ItemOptimal surveillance strategy for invasive species management when surveys stop after detection(WILEY, 2014-05)Invasive species are a cause for concern in natural and economic systems and require both monitoring and management. There is a trade-off between the amount of resources spent on surveying for the species and conducting early management of occupied sites, and the resources that are ultimately spent in delayed management at sites where the species was present but undetected. Previous work addressed this optimal resource allocation problem assuming that surveys continue despite detection until the initially planned survey effort is consumed. However, a more realistic scenario is often that surveys stop after detection (i.e., follow a "removal" sampling design) and then management begins. Such an approach will indicate a different optimal survey design and can be expected to be more efficient. We analyze this case and compare the expected efficiency of invasive species management programs under both survey methods. We also evaluate the impact of mis-specifying the type of sampling approach during the program design phase. We derive analytical expressions that optimize resource allocation between monitoring and management in surveillance programs when surveys stop after detection. We do this under a scenario of unconstrained resources and scenarios where survey budget is constrained. The efficiency of surveillance programs is greater if a "removal survey" design is used, with larger gains obtained when savings from early detection are high, occupancy is high, and survey costs are not much lower than early management costs at a site. Designing a surveillance program disregarding that surveys stop after detection can result in an efficiency loss. Our results help guide the design of future surveillance programs for invasive species. Addressing program design within a decision-theoretic framework can lead to a better use of available resources. We show how species prevalence, its detectability, and the benefits derived from early detection can be considered.
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ItemAdaptive management improves decisions about where to search for invasive species(Elsevier, 2017-08-01)Invasive species managers must decide how best to allocate surveillance and control effort through space. Doing this requires the predicted location of the invasive species, and these predictions come with uncertainty. While optimal surveillance designs have been developed for many invasive species, few have considered uncertainty in species distribution and abundance. Adaptive management has long been recommended for managing natural systems under uncertainty, but has not yet been applied to searching for invasive species. We investigate whether an adaptive management approach can increase the number of individuals found and removed, as compared to a naïve allocation of search effort or “common sense” rules of thumb. We develop a simple illustrative model where search effort must be allocated to maximise plant removals across two sites in which species abundance is unknown. We tested the performance of both passive and active adaptive strategies through simulation. There are substantial benefits to employing an adaptive strategy, although the two forms of adaptive management performed similarly. The optimal active adaptive strategy is complex to calculate, whereas the passive strategy could be calculated for a large number of sites using widely accessible spreadsheet software. We therefore recommend the passive adaptive strategy for achieving approximately the same outcome while being much more practical to implement, facilitating application to much larger and more realistic search problems in a way that is accessible to managers.
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ItemPrioritizing plant eradication targets by re-framing the project prioritization protocol (PPP) for use in biosecurity applications(Springer, 2017-03-01)The eradication of newly detected alien plant species is often prescribed, but rarely successful. Eradication programs fail for many reasons, however, for eradication to remain a cost-efficient management option it is clear that good decisions must be made at the outset. Here we re-frame the project prioritization protocol (PPP), a tool widely used in conservation biology, for use with the metrics typically used by a biosecurity agency. We then use existing methods to estimate the cost-efficiency of eradicating 50 hypothetical species incursions and compare the reduction in weed risk achieved by allocating resources using the PPP framework with the allocation based on risk ranking. By allocating resources to plant eradication programs using the PPP our analysis indicated that it is possible to improve the return on public expenditure by 25% compared to investing based solely on weed risk assessment scores. We also demonstrate how the cost-efficiency of the overall portfolio is influenced by the choice of planning horizon; including the decline in overall portfolio performance that arises when attempting to eradicate individual species too quickly. Finally, we discuss the logistical benefits to a management agency that arise from the use of a generic overarching framework such as the PPP. We believe that the PPP has considerable potential for use in biosecurity and can help focus attention on those species where management can make the biggest difference.
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ItemLearning about colonization when managing metapopulations under an adaptive management framework(WILEY, 2016-01)Adaptive management is a framework for resolving key uncertainties while managing complex ecological systems. Its use has been prominent in fisheries research and wildlife harvesting; however, its application to other areas of environmental management remains somewhat limited. Indeed, adaptive management has not been used to guide and inform metapopulation restoration, despite considerable uncertainty surrounding such actions. In this study, we determined how best to learn about the colonization rate when managing metapopulations under an adaptive management framework. We developed a mainland-island metapopulation model based on the threatened bay checkerspot butterfly (Euphydryas editha bayensis) and assessed three management approaches: adding new patches, adding area to existing patches, and doing nothing. Using stochastic dynamic programming, we found the optimal passive and active adaptive management strategies by monitoring colonization of vacant patches. Under a passive adaptive strategy, increasing patch area was best when the expected colonization rate was below a threshold; otherwise, adding new patches was optimal. Under an active adaptive strategy, it was best to add patches only when we were reasonably confident that the colonization rate was high. This research provides a framework for managing mainland-island metapopulations in the face of uncertainty while learning about the dynamics of these complex systems.
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ItemClassifying animals into ecologically meaningful groups: A case study on woodland birds(ELSEVIER SCI LTD, 2017-10)Ecologists often classify species into binary groupings such as woodland or non-woodland birds. However, each ecologist may apply a different classification, which might impede progress in ecology and conservation by precluding direct comparison between studies. This study describes and tests a method for deriving empirically-based, ecologically-relevant species groups, using Australian woodland birds as a case study. A Bayesian hierarchical model investigates how vegetation and species traits drive birds' preference for woodland vegetation, characterised by low density trees with an open canopy structure. Birds are then classified according to their affinity to areas with high tree cover and woodland vegetation. Interestingly, no traits are strongly associated with species occurrence in woodland habitats, but occurrence in open country and forests differ depending on dispersal ability and foraging habits. Our results suggest that Australian woodland birds may be united by their avoidance of both sparsely-treed and densely-treed habitat, rather than by shared traits.Classifying species according to our groupings provides results consistent with literature on how woodland birds respond to clearing, grazing and urbanisation. Thus, our model is consistent with current ecological understanding regarding woodland birds; it also provides more nuanced inference across ‘closed-woodland’, ‘open-woodland’, ‘forest’ and ‘open country’ groups. We propose that our modelling approach could be used to classify species for other locations and taxa, providing transparent, ecologically-relevant animal groupings.
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ItemConsequences of inconsistently classifying woodland birds(FRONTIERS MEDIA SA, 2015)