Monitoring, imperfect detection, and risk optimization of a Tasmanian devil insurance population

Exploring artificial habitat fragmentation to control invasion by infectious wildlife diseases

One way to reduce the impacts of invading wildlife diseases is setting up fences that would reduce the spread of pathogens by limiting connectivity, similarly to exclusion fences that are commonly used to conserve threatened species against invasive predators. One of the problems with fences is that, while they may have the short-term benefit of impeding the spread of disease, this benefit may be offset by potential long-term ecological costs of fragmentation by fencing. However, managers facing situations where a pathogen has been detected near the habitat of a (highly) vulnerable species may be willing to explore such a trade-off. To aid such exploration quantitatively, we present a series of models trading off the benefits of fragmentation (potential reduction of disease impacts on susceptible individuals) against its costs (both financial and ecological, i.e. reduced viability in the patches created by fragmentation), and exploring the effects of fragmentation on non-target species richness. For all model variants we derive the optimal number of artificial patches. We show that pre-emptive disease fences may have benefits when the risk of disease exceeds the impacts of fragmentation, when fence failure rates are lower than a specific threshold, and when sufficient resources are available to implement optimal solutions. A useful step to initiate planning is to obtain information about the expected number of initial infection events and on the host's extinction threshold with respect to the focal habitat and management duration. Our approach can assist managers to identify whether the trade-offs support the decision to fence and how intensive fragmentation should be.

Importance of species translocations under rapid climate change

Species that cannot adapt or keep pace with a changing climate are likely to need human intervention to shift to more suitable climates. While hundreds of articles mention using translocation as a climate-change adaptation tool, in practice, assisted migration as a conservation action remains rare, especially for animals. This is likely due to concern over introducing species to places where they may become invasive. However, there are other barriers to consider, such as time-frame mismatch, sociopolitical, knowledge and uncertainty barriers to conservationists adopting assisted migration as a go-to strategy. We recommend the following to advance assisted migration as a conservation tool: attempt assisted migrations at small scales, translocate species with little invasion risk, adopt robust monitoring protocols that trigger an active response, and promote political and public support.

Spatial optimization of invasive species control informed by management practices

Optimization of spatial resource allocation is crucial for the successful control of invasive species under a limited budget but requires labor-intensive surveys to estimate population parameters. In this study, we devised a novel framework for the spatially explicit optimization of capture effort allocation using state-space population models from past capture records. We applied it to a control program for invasive snapping turtles to determine effort allocation strategies that minimize the population density over the whole area. We found that spatially heterogeneous density dependence and capture pressure limit the abundance of snapping turtles. Optimal effort allocation effectively improved the control effect, but the degree of improvement varied substantially depending on the total effort. The degree of improvement by the spatial optimization of allocation effort was only 3.21% when the total effort was maintained at the 2016 level. However, when the total effort was increased by two, four, and eight times, spatial optimization resulted in improvements of 4.65%, 8.33%, and 20.35%, respectively. To achieve the management goal for snapping turtles in our study area, increasing the current total effort by more than four times was necessary, in addition to optimizing the spatial effort. The snapping turtle population is expected to reach the target density one year after the optimal management strategy is implemented, and this rapid response can be explained by high population growth rate coupled with density-dependent feedback regulation. Our results demonstrated that combining a state-space model with optimization makes it possible to adaptively improve the management of invasive species and decision-making. The method used in this study, based on removal records from an invasive management program, can be easily applied to monitoring data for wildlife and pest control management using traps in a variety of ecosystems.

Modelling parameter uncertainty reveals bushmeat yields versus survival trade-offs in heavily-hunted duiker Cephalophus spp

Reliably predicting sustainable exploitation levels for many tropical species subject to hunting remains a difficult task, largely because of the inherent uncertainty associated with estimating parameters related to both population dynamics and hunting pressure. Here, we investigate a modelling approach to support decisions in bushmeat management which explicitly considers parameter uncertainty. We apply the approach to duiker Cephalophus spp., assuming either a constant quota-based, or a constant proportional harvesting, strategy. Within each strategy, we evaluate different hunting levels in terms of both average yield and survival probability, over different time horizons. Under quota-based harvesting, considering uncertainty revealed a trade-off between yield and extinction probability that was not evident when ignoring uncertainty. The highest yield was returned by a quota that implied a 40% extinction risk, whereas limiting extinction risk to 10% reduced yield by 50%-70%. By contrast, under proportional harvesting, there was no trade-off between yield and extinction probability. The maximum proportion returned a yield comparable with the maximum possible under quota-based harvesting, but with extinction risk below 10%. However, proportional harvesting can be harder to implement in practice because it depends on an estimate of population size. In both harvesting approaches, predicted yields were highly right-skewed with median yields differing from mean yields, implying that decision outcomes depend on attitude to risk. The analysis shows how an explicit consideration of all available information, including uncertainty, can, as part of a wider process involving multiple stakeholders, help inform harvesting policies.