Biodiversity decline is indisputable, and rates of future decline depend on whether threats to species persistence are abated. However, current resources for threatened species management are less than required to stop further decline. Management that abates many threats to many species is necessary, yet decisions about how to do this under resource constraints are inherently complex. My thesis incorporates systematic conservation planning and cost-effectiveness analysis in a decision-support framework for prioritising spatially-explicit management actions for many species across a region. By prioritising action where it is expected to provide the greatest benefit to the most species at least cost, my research advances the thinking on decision support, and contributes to the effort to reduce biodiversity decline.
Using information on threats to species that was compiled by the Queensland, Australia government, my research develops a decision-support process for managing threats to threatened species in a bio-diverse regional-scale management area, the Burnett-Mary Natural Resource Management Region. In my thesis, predicted distributions for 65 threatened species are modelled on co-occurring presence-only species locations and ecologically-meaningful environmental data. Three threats are addressed: invasive red fox predation; too frequent and intense fire; and habitat degradation from overgrazing. Indirect threat maps are made by combining predicted distribution models of species vulnerable to specific threats and are used to identify locations where threat-abating actions are most likely to provide benefit to species. Management action costs are estimated for fox control, on the basis of a roadside baiting strategy; proactive fire management, on the basis of vegetation type and proximity to human structures; and stewardship agreements to reduce grazing, on the basis of foregone agriculture profit. Spatially combining the costs and benefits of threat-abating actions leads to the ability to prioritise cost-effective locations for actions. Within the context of prioritising regional threat management actions, my research examines four topics.
Firstly, an understanding of where species are affected by threats determines where to direct management. Indirect threat maps are made by combining threatened species distribution maps, but are sensitive to map scale in guiding spatially-explicit threat management efforts (Chapter 2). Using fine-scale predicted species distribution models to derive indirect threat maps, instead of general range maps, may lead to better regional management decisions.
Funding limitations for threat management require that choices be made when not everything can be done. Transparent and rigorous decision support is provided by prioritising management ranked on the most, to least, cost-effective actions and locations, and is made accessible when calculated with readily-available spreadsheet and mapping software (Chapter 3). Cost-effective management priorities are determined by combining indirect threat maps that locate which actions benefit species with maps quantifying the cost of action. Priorities depend on how the benefits and costs co-vary across a landscape.
The costs and/or benefits of one management action may depend upon those of another action, which will affect the ranking of conservation actions by their cost-effectiveness (Chapter 4). If actions are dependent and species are secured when only one threat is managed, managing for multiple threats results in poor allocation of resources. Alternatively, focusing on individual threats potentially results in inadequate management and failure of conservation outcomes if species only benefit when all the threats are managed. Considering when management action success depends upon which other actions are undertaken will better protect species from threats and guide spending of limited funding.
Lastly, providing an alternative to basic decision support, more complex methods for conservation planning can be used to meet more comprehensive management goals, but spatial priorities are likely to differ (Chapter 5). When the goal includes explicitly managing for all species and threats, priority locations for actions are different than if prioritising management in species-rich areas. Trade-offs between threatened species management plans are inevitable, but examining the implications of different strategies may lead to better decisions.
My research provides four contributions to conservation research by focusing on decision support for threat management that reduces biodiversity decline. 1) Indirect threat maps, created by combining predicted distribution models of threatened species, indicate where action is needed for managing threats at the regional scale. 2) Decisions about where to manage threats are made by prioritising cost-effective actions and can be determined using accessible and commonly-used software. 3) Failing to consider that the success of management actions is likely to depend on what other actions have been undertaken will result in ineffective spending of limited funding or insufficient management of threats. 4) Both simpler and more complex conservation planning methods assist in choosing where to manage, with which actions, at least cost, but spatial priorities will differ. In summary, my research shows that management priorities can be selected by combining threatened species distributions with the costs of abating threats. Transparently chosen management actions that are efficient in using limited resources may better lead to abating threats to biodiversity.