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Islands are global hotspots of both biodiversity and extinction. Invasive species are a primary threat, and the majority of islands have been invaded by more than one. Multispecies eradications are essential for conserving the biodiversity of these islands, but experience has shown that eradicating species at the wrong time can be disastrous for endemic species., Managers not only have to decide how to eradicate each invasive species, they need to determine when to target each species, and how to control multiple species with a limited budget. We use dynamic control theory to show that, when resources are limited, species should be eradicated in a particular order (an eradication schedule). We focus on a common invaded island ecosystem motif, where one invasive predator consumes two prey species (one endemic, one invasive), and managers wish to eradicate both invasives while ensuring the persistence of the endemic species. We identify the optimal eradication schedule for this entire class of problem. To illustrate the application of our solution, we also analyse a particular case study from California's Channel Islands., For any island ecosystem that shares this motif, managers should begin by allocating all of their resources towards invasive predator control. Only later should resources be shifted towards controlling the invasive prey. This shift should ideally be gradual, but an abrupt shift is very close to optimal. The Channel Islands case study confirms these findings. Targeting both species simultaneously is substantially suboptimal., We reach the robust conclusion that the same eradication schedule should be applied to any island with this ecosystem motif, even if the ecosystem contains different species to the Channel Islands case study., Synthesis and applications. Although very numerous, the world's invaded island ecosystems could be described by a limited range of invaded ecosystem motifs. By calculating robust optimal eradication schedules for each motif, the approach defined in this study could offer rapid decision-support for a large number of future conservation projects where specific data are scarce. [ABSTRACT FROM AUTHOR]

Agencies charged with nature conservation and protecting built-assets from fire face a policy dilemma because management that protects assets can have adverse impacts on biodiversity. Although conservation is often a policy goal, protecting built-assets usually takes precedence in fire management implementation. To make decisions that can better achieve both objectives, existing trade-offs must first be recognized, and then policies implemented to manage multiple objectives explicitly. We briefly review fire management actions that can conflict with biodiversity conservation. Through this review, we find that common management practices might not appreciably reduce the threat to built-assets but could have a large negative impact on biodiversity. We develop a framework based on decision theory that could be applied to minimize these conflicts. Critical to this approach is (1) the identification of the full range of management options and (2) obtaining data for evaluating the effectiveness of those options for achieving asset protection and conservation goals. This information can be used to compare explicitly the effectiveness of different management choices for conserving species and for protecting assets, given budget constraints. The challenge now is to gather data to quantify these trade-offs so that fire policy and practices can be better aligned with multiple objectives. [ABSTRACT FROM AUTHOR]

Land acquisition is a common approach to biodiversity conservation but is typically subject to property availability on the public market. Consequently, conservation plans are often unable to be implemented as intended. When properties come on the market, conservation agencies must make a choice: purchase immediately, often without a detailed knowledge of its biodiversity value; survey the parcel and accept the risk that it may be removed from the market during this process; or not purchase and hope a better parcel comes on the market at a later date. We describe both an optimal method, using stochastic dynamic programming, and a simple rule of thumb for making such decisions. The solutions to this problem illustrate how optimal conservation is necessarily dynamic and requires explicit consideration of both the time period allowed for implementation and the availability of properties. [ABSTRACT FROM AUTHOR]