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Conservation funds are grossly inadequate to address the plight of threatened species. Government and conservation organizations faced with the task of conserving threatened species desperately need simple strategies for allocating limited resources. The academic literature dedicated to systematic priority setting usually recommends ranking species on several criteria, including level of endangerment and metrics of species value such as evolutionary distinctiveness, ecological importance, and social significance. These approaches ignore 2 crucial factors: the cost of management and the likelihood that the management will succeed. These oversights will result in misallocation of scarce conservation resources and possibly unnecessary losses. We devised a project prioritization protocol (PPP) to optimize resource allocation among New Zealand's threatened-species projects, where costs, benefits (including species values), and the likelihood of management success were considered simultaneously. We compared the number of species managed and the expected benefits gained with 5 prioritization criteria: PPP with weightings based on species value; PPP with species weighted equally; management costs; species value; and threat status. We found that the rational use of cost and success information substantially increased the number of species managed, and prioritizing management projects according to species value or threat status in isolation was inefficient and resulted in fewer species managed. In addition, we found a clear trade-off between funding management of a greater number of the most cost-efficient and least risky projects and funding fewer projects to manage the species of higher value. Specifically, 11 of 32 species projects could be funded if projects were weighted by species value compared with 16 projects if projects were not weighted. This highlights the value of a transparent decision-making process, which enables a careful consideration of trade-offs. The use of PPP can substantially improve conservation outcomes for threatened species by increasing efficiency and ensuring transparency of management decisions.

Governments have agreed to expand the global protected area network from 13% to 17% of the world's land surface by 2020 (Aichi target 11) and to prevent the further loss of known threatened species (Aichi target 12). These targets are interdependent, as protected areas can stem biodiversity loss when strategically located and effectively managed. However, the global protected area estate is currently biased toward locations that are cheap to protect and away from important areas for biodiversity. Here we use data on the distribution of protected areas and threatened terrestrial birds, mammals, and amphibians to assess current and possible future coverage of these species under the convention. We discover that 17% of the 4,118 threatened vertebrates are not found in a single protected area and that fully 85% are not adequately covered (i.e., to a level consistent with their likely persistence). Using systematic conservation planning, we show that expanding protected areas to reach 17% coverage by protecting the cheapest land, even if ecoregionally representative, would increase the number of threatened vertebrates covered by only 6%. However, the nonlinear relationship between the cost of acquiring land and species coverage means that fivefold more threatened vertebrates could be adequately covered for only 1.5 times the cost of the cheapest solution, if cost efficiency and threatened vertebrates are both incorporated into protected area decision making. These results are robust to known errors in the vertebrate range maps. The Convention on Biological Diversity targets may stimulate major expansion of the global protected area estate. If this expansion is to secure a future for imperiled species, new protected areas must be sited more strategically than is presently the case.

Effective detection of population trend is crucial for managing threatened species. Little theory exists, however, to assist managers in choosing the most cost-effective monitoring techniques for diagnosing trend. We present a framework for determining the optimal monitoring strategy by simulating a manager collecting data on a declining species, the Chestnut-rumped Hylacola (Hylacola pyrrhopygia parkeri), to determine whether the species should be listed under the IUCN (World Conservation Union) Red List. We compared the efficiencies of two strategies for detecting trend, abundance, and presence-absence surveys, under financial constraints. One might expect the abundance surveys to be superior under all circumstances because more information is collected at each site. Nevertheless, the presence-absence data can be collected at more sites because the surveyor is not obliged to spend a fixed amount of time at each site. The optimal strategy for monitoring was very dependent on the budget available. Under some circumstances, presence-absence surveys outperformed abundance surveys for diagnosing the IUCN Red List categories cost-effectively. Abundance surveys were best if the species was expected to be recorded more than 16 times/year; otherwise, presence-absence surveys were best. The relationship between the strategies we investigated is likely to be relevant for many comparisons of presence-absence or abundance data. Managers of any cryptic or low-density species who hope to maximize their success of estimating trend should find an application for our results.

Various aspects related to the genetic variation in critical traits and localized evolution in response to climate variation are discussed. As an estimate of the potential for evolutionary response to climate warming, evolved change in critical thermal maximum (CTM), an important indicator of thermal performance, is considered for a hypothetical species. It is suggested that evolution is responsive to climate variation and occurs at rate that make it relevant for consideration of current and projected responses to climate change. It is critical to understand when dispersal and other means, such as behavioral plasticity, either cannot or will not provide species with adequate means to avoid population collapse and extinction. It is concluded that evolutionary change will occur concomitantly with changes in climate as well as other environmental changes.

Predicting abundance across a species' distribution is useful for studies of ecology and biodiversity management. Modeling of survey data in relation to environmental variables can be a powerful method for extrapolating abundances across a species' distribution and, consequently, calculating total abundances and ultimately trends. Research in this area has demonstrated that models of abundance are often unstable and produce spurious estimates, and until recently our ability to remove detection error limited the development of accurate models. The N-mixture model accounts for detection and abundance simultaneously and has been a significant advance in abundance modeling. Case studies that have tested these new models have demonstrated success for some species, but doubt remains over the appropriateness of standard N-mixture models for many species. Here we develop the N-mixture model to accomodate zero-inflated data, a common occurrence in ecology, by employing zero-inflated count models. To our knowledge, this is the first application of this method to modeling zero-inflated count data. We use four variants of the N-mixture model (Poisson, zero-inflated Poisson, negative binomial, and zero-inflated negative binomial) to model abundance, occupancy (zero-inflated models only) and detection probability of six birds in South Australia. We assess models by their statistical fit and the ecological realism of the parameter estimates. Specifically, we assess the statistical fit with AIC and assess the ecological realism by comparing the parameter estimates with expected values derived from literature, ecological theory, and expert opinion. We demonstrate that, despite being frequently ranked the \"best model\" according to AIC, the negative binomial variants of the N-mixture often produce ecologically unrealistic parameter estimates. The zero-inflated Poisson variant is preferable to the negative binomial variants of the N-mixture, as it models an ecological mechanism rather than a statistical phenomenon and generates reasonable parameter estimates. Our results emphasize the need to include ecological reasoning when choosing appropriate models and highlight the dangers of modeling statistical properties of the data. We demonstrate that, to obtain ecologically realistic estimates of abundance, occupancy and detection probability, it is essential to understand the sources of variation in the data and then use this information to choose appropriate error distributions.

Many countries rely on formal legislation to protect and plan for the recovery of threatened species. Even though the listing procedures in threatened species legislation are designed to be consistent for all species there is usually a bias in implementing the laws towards charismatic fauna and flora, which leads to uneven allocation of conservation efforts. However, the extent of bias in national threatened species lists is often unknown. Australia is a good example: the list of threatened species under the Environmental Protection and Biological Conservation Act has not been reviewed since 2000, when it was first introduced. We assessed how well this Act represents threatened species across taxonomic groups and threat status, and whether biases exist in the types of species with recovery plans. We found that birds, amphibians and mammals have high levels of threatened species (12–24%) but < 6% of all reptiles and plants and < 0.01% of invertebrates and fish are considered threatened. Similar taxonomic biases are present in the types of species with recovery plans. Although there have been recent improvements in the representation of threatened species with recovery plans across taxonomic groups, there are still major gaps between the predicted and listed numbers of threatened species. Because of biases in the listing and recovery planning processes many threatened species may receive little attention regardless of their potential for recovery: a lost opportunity to achieve the greatest conservation impact possible. The Environmental Protection and Biological Conservation Act in Australia needs reform to rectify these biases.

The acquisition or designation of new protected areas is usually based on criteria for representation of different ecosystems or land-cover classes, and it is unclear how well-threatened species are conserved within protected-area networks. Here, we assessed how Australia's terrestrial protected-area system (89 million ha, 11.6% of the continent) overlaps with the geographic distributions of threatened species and compared this overlap against a model that randomly placed protected areas across the continent and a spatially efficient model that placed protected areas across the continent to maximize threatened species' representation within the protected-area estate. We defined the minimum area needed to conserve each species on the basis of the species' range size. We found that although the current configuration of protected areas met targets for representation of a given percentage of species' ranges better than a random selection of areas, 166 (12.6%) threatened species occurred entirely outside protected areas and target levels of protection were met for only 259 (19.6%) species. Critically endangered species were among those with the least protection; 12 (21.1%) species occurred entirely outside protected areas. Reptiles and plants were the most poorly represented taxonomic groups, and amphibians the best represented. Spatial prioritization analyses revealed that an efficient protected-area system of the same size as the current protected-area system (11.6% of the area of Australia) could meet representation targets for 1272 (93.3%) threatened species. Moreover, the results of these prioritization analyses showed that by protecting 17.8% of Australia, all threatened species could reach target levels of representation, assuming all current protected areas are retained. Although this amount of area theoretically could be protected, existing land uses and the finite resources available for conservation mean land acquisition may not be possible or even effective for the recovery of threatened species. The optimal use of resources must balance acquisition of new protected areas, where processes that threaten native species are mitigated by the change in ownership or on-ground management jurisdiction, and management of threatened species inside and outside the existing protected-area system. La adquisición o designación de áreas protegidas nueves generalmente se basa en criterios para la representación de diferentes ecosistemas o clases de cobertura de suelo, y no es claro que tan bien son conservadas las especies amenazadas en el interior de las redes de áreas protegidas. Aquí evaluamos como se traslapa el sistema de áreas protegidas terrestres de Australia (89 millones ha, 11.6% del continente) con las distribuciones geográficas de especies amenazadas y comparamos ese traslape con un modelo que ubicó áreas protegidas aleatoriamente en el continente y con un modelo espacialmente eficiente que ubicó áreas protegidas en el continente para maximizar la representación de especies amenazadas dentro de las áreas protegidas. Definimos el área mínima necesaria para conservar cada especie con base en el tamaño del área de distribución de la especie. Encontramos que, aunque la configuración actual de las áreas protegidas cumplía mejor con los objetivos de representación de un porcentaje determinado de rangos de distribución de especies que la selección aleatoria de áreas, 166 (12.6%) de las especies amenazadas ocurrieron completamente fuera de las áreas protegidas y los niveles de protección proyectados solo se cumplieron para 259 (19.6%) especies. Especies críticamente amenazadas se encontraron entre las especies con la menor protección; 12 (21.1%) especies ocurrieron completamente fuera de áreas protegidas. Los reptiles y plantas fueron los grupos taxonómicos más pobremente representados, y los anfibios los mejor representados. Los análisis de priorización espacial revelaron que un sistema eficiente de áreas protegidas del mismo tamaños que el sistema actual de áreas protegidas (11.6% del área de Australia) podría alcanzar objetivos de representación para 1272 (93.3%) de especies amenazadas. Más aun, los resultados de esta priorización mostraron que mediante la protección de 17.8% de Australia, todas las especies amenazadas podrían alcanzar niveles deseables de representación, asumiendo que todas las áreas protegidas son retenidas. Aunque esta cantidad de área pudiera ser protegida teóricamente, los usos de suelo actuales y los limitados recursos disponibles para la conservación significan que la adquisición de tierras no será posible ni efectiva para la recuperación de especies amenazadas. El uso óptimo de recursos debe balancear la adquisición de áreas protegidas nuevas, los procesos que amenazan a las especies nativas son mitigados por el cambio en la propiedad o en la jurisdicción de manejo, y el manejo de especies amenazadas dentro y fuera del sistema de áreas protegidas existente.

Conservation outcomes are uncertain. Agencies making decisions about what threat mitigation actions to take to save which species frequently face the dilemma of whether to invest in actions with high probability of success and guaranteed benefits or to choose projects with a greater risk of failure that might provide higher benefits if they succeed. The answer to this dilemma lies in the decision maker's aversion to risk—their unwillingness to accept uncertain outcomes. Little guidance exists on how risk preferences affect conservation investment priorities. Using a prioritization approach based on cost effectiveness, we compared 2 approaches: a conservative probability threshold approach that excludes investment in projects with a risk of management failure greater than a fixed level, and a variance‐discounting heuristic used in economics that explicitly accounts for risk tolerance and the probabilities of management success and failure. We applied both approaches to prioritizing projects for 700 of New Zealand's threatened species across 8303 management actions. Both decision makers’ risk tolerance and our choice of approach to dealing with risk preferences drove the prioritization solution (i.e., the species selected for management). Use of a probability threshold minimized uncertainty, but more expensive projects were selected than with variance discounting, which maximized expected benefits by selecting the management of species with higher extinction risk and higher conservation value. Explicitly incorporating risk preferences within the decision making process reduced the number of species expected to be safe from extinction because lower risk tolerance resulted in more species being excluded from management, but the approach allowed decision makers to choose a level of acceptable risk that fit with their ability to accommodate failure. We argue for transparency in risk tolerance and recommend that decision makers accept risk in an adaptive management framework to maximize benefits and avoid potential extinctions due to inefficient allocation of limited resources.

For some wildlife commodities, rare species are especially sought after. The tendency for rare commodities to be of higher value can fuel their exploitation and as numbers dwindle, the demand can increase. Consequently, this can precipitate these rare species into an overexploitation vortex where they become increasingly rare, valued and exploited until eventual extinction. We focus here on the hobby of collecting stag beetles, to ascertain if the market value of these items is driven by rarity and if, consequently, these species are vulnerable to this overexploitation vortex. Stag beetle collections fuel a large and lucrative market in Japan, involving more than 700 species from all over the world, with over 15 million specimens imported a year. Some particularly valued species fetch more than US$5,000 a piece. We assessed the importance of species rarity as an acquisition criterion in this market using two methods: an Internet online questionnaire responded to by 509 participants and through examining the quantities imported in Japan and prices paid by collectors. We discovered that species rarity is one of the main choice criteria for acquisition by collectors: rare stag beetles are valued more than the common species and, consequently, stag beetles are vulnerable to the anthropogenic Allee effect in this market. Because of the sheer size of the market and the pervasive nature of this rarity paradox, the attraction to rarity equates to a potential extinction threat for many rare stag beetles species.

In many sectors, freedom in capital flow has allowed optimization of investment returns through choosing sites that provide the best value for money. These returns, however, can be compromised in countries where corruption is prevalent. We assessed where the best value for money might be obtained for investment in threatened species that occur at a single site, when taking into account corruption. We found that the influence of corruption on potential investment decisions was outweighed by the likely value for money in terms of pricing parity. Nevertheless global conservation is likely to get best returns in terms of threatened species security by investing in \"honest\" countries than in corrupt ones, particularly those with a high cost of living.