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We consider optimal conservation strategies for an endangered population. We assume that juvenile survival is affected by unpredictable environmental fluctuation and can be improved by costly conservation effort. The initial population size is not accurately known at the time that the conservation effort level is chosen, but the uncertainty of its estimate can be reduced by a costly monitoring effort. In a previous paper, we analysed the optimal management strategy that minimizes a weighted sum of extinction probability and economic costs when only a single year is considered. Here we examine the case in which the conservation period lasts for several years by dynamic programming with incompletely observed process states. We study the optimal levels of the conservation and the monitoring efforts, and their dependence on the length of the conservation period and other parameters. The main conclusions are: (1) The optimal conservation effort in the first year depends on the accuracy of the information on the population size in the first year, but is almost independent of the accuracy of the information in later years. (2) When the risk of population extinction is small, the optimal conservation effort increases with the uncertainty of the population size. In contrast when the population is endangered, the optimal conservation effort decreases with the uncertainty of the population size. (3) The optimal conservation and monitoring efforts both increase with the length of the conservation period, provided that the population is relatively safe. However, if the population is endangered, both types of effort become smaller when the conservation period increases.

The relative ability of the NOEC (no-observed-effect concentration) and ECx (the effect concentration corresponding to x-percent response) to determine benchmark toxicant concentrations, which are expected to ensure environmental safety, when there are large uncertainties in data was investigated with Monte Carlo simulations. We assumed a hypothetical true concentration-response function, and examined how random fluctuations of responses around the true responses affected the NOEC and ECx values. For assessment of the relative performances of these endpoints, we adopted two criteria: how large uncertainties were allowed for the minimum requirement for safety to be met, and the probability with which the estimated endpoints exceeded the minimum requirement for safety. The results of simulations indicated that, when there were small uncertainties in the data, performance of the NOEC was comparable with or slightly better than the ECx (EC5 and EC10) in providing benchmark concentrations that satisfied the minimum requirement for safety. With larger random variation of data (the coefficient of variation in responses between replicates within treatments or in the control was noticeably larger than 10 percent), the NOEC performed considerably worse than the ECx in terms of the frequency of simulated runs in which the endpoints exceeded the minimum requirement of safety. We conclude that the NOEC is as relevant as the ECx for risk assessment of chemicals under limited situations. [ABSTRACT FROM AUTHOR]

Management of damaging invasive plants is often undertaken by multiple decision makers, each managing only a small part of the invader's population. As weeds can move between properties and re‐infest eradicated sites from unmanaged sources, the dynamics of multiple decision makers plays a significant role in weed prevalence and invasion risk at the landscape scale. We used a spatially explicit agent‐based simulation to determine how individual agent behavior, in concert with weed population ecology, determined weed prevalence. We compared two invasive grass species that differ in ecology, control methods, and costs: Nassella trichotoma (serrated tussock) and Eragrostis curvula (African love grass). The way decision makers reacted to the benefit of management had a large effect on the extent of a weed. If benefits of weed control outweighed the costs, and either net benefit was very large or all agents were very sensitive to net benefits, then agents tended to act synchronously, reducing the pool of infested agents available to spread the weed. As N. trichotoma was more damaging than E. curvula and had more effective control methods, agents chose to manage it more often, which resulted in lower prevalence of N. trichotoma. A relatively low number of agents who were intrinsically less motivated to control weeds led to increased prevalence of both species. This was particularly apparent when long‐distance dispersal meant each infested agent increased the invasion risk for a large portion of the landscape. In this case, a small proportion of land mangers reluctant to control, regardless of costs and benefits, could lead to the whole landscape being infested, even when local control stopped new infestations. Social pressure was important, but only if it was independent of weed prevalence, suggesting that early access to information, and incentives to act on that information, may be crucial in stopping a weed from infesting large areas. The response of our model to both behavioral and ecological parameters was highly nonlinear. This implies that the outcomes of weed management programs that deal with multiple land mangers could be highly variable in both space and through time. [ABSTRACT FROM AUTHOR]

We review and synthesize recent developments in the study of the invasion of communities in heterogeneous environments, considering both the invasibility of the community and impacts to the community. We consider both empirical and theoretical studies. For each of three major kinds of environmental heterogeneity (temporal, spatial and invader-driven), we find evidence that heterogeneity is critical to the invasibility of the community, the rate of spread, and the impacts on the community following invasion. We propose an environmental heterogeneity hypothesis of invasions, whereby heterogeneity both increases invasion success and reduces the impact to native species in the community, because it promotes invasion and coexistence mechanisms that are not possible in homogeneous environments. This hypothesis could help to explain recent findings that diversity is often increased as a result of biological invasions. It could also explain the scale dependence of the diversity–invasibility relationship. Despite the undoubted importance of heterogeneity to the invasion of communities, it has been studied remarkably little and new research is needed that simultaneously considers invasion, environmental heterogeneity and community characteristics. As a young field, there is an unrivalled opportunity for theoreticians and experimenters to work together to build a tractable theory informed by data. [ABSTRACT FROM AUTHOR]