Correlations among Extinction Risks Assessed by Different Systems of Threatened Species Categorization

Abstract:  Many different systems are used to assess levels of threat faced by species. Prominent ones are those used by the World Conservation Union, NatureServe, and the Florida Game and Freshwater Fish Commission (now the Florida Fish and Wildlife Conservation Commission). These systems assign taxa a threat ranking by assessing their demographic and ecological characteristics. These threat rankings support the legislative protection of species and guide the placement of conservation programs in order of priority. It is not known, however, whether these assessment systems rank species in a similar order. To resolve this issue, we assessed 55 mainly vertebrate taxa with widely differing life histories under each of these systems and determined the rank correlations among them. Moderate, significant positive correlations were seen among the threat rankings provided by the three systems (correlations 0.58–0.69). Further, the threat rankings for taxa obtained using these systems were significantly correlated to their rankings based on predicted probability of extinction within 100 years as determined by population viability analysis (correlations 0.28–0.37). The different categorization systems, then, yield related but not identical threat rankings, and these rankings are associated with predicted extinction risk.     

Optimal Allocation of Conservation Resources to Species That May be Extinct

Abstract: Statements of extinction will always be uncertain because of imperfect detection of species in the wild. Two errors can be made when declaring a species extinct. Extinction can be declared prematurely, with a resulting loss of protection and management intervention. Alternatively, limited conservation resources can be wasted attempting to protect a species that no longer exists. Rather than setting an arbitrary level of certainty at which to declare extinction, we argue that the decision must trade off the expected costs of both errors. Optimal decisions depend on the cost of continued intervention, the probability the species is extant, and the estimated value of management (the benefit of management times the value of the species). We illustrated our approach with three examples: the Dodo (Raphus cucullatus), the Ivory‐billed Woodpecker (U.S. subspecies Campephilus principalis principalis), and the mountain pygmy‐possum (Burramys parvus). The dodo was extremely unlikely to be extant, so managing and monitoring for it today would not be cost‐effective unless the value of management was extremely high. The probability the Ivory‐billed woodpecker is extant depended on whether recent controversial sightings were accepted. Without the recent controversial sightings, it was optimal to declare extinction of the species in 1965 at the latest. Accepting the recent controversial sightings, it was optimal to continue monitoring and managing until 2032 at the latest. The mountain pygmy‐possum is currently extant, with a rapidly declining sighting rate. It was optimal to conduct as many as 66 surveys without sighting before declaring the species extinct. The probability of persistence remained high even after many surveys without sighting because it was difficult to determine whether the species was extinct or undetected. If the value of management is high enough, continued intervention can be cost‐effective even if the species is likely to be extinct.     

Disturbance-Response Analysis: a Method for Rapid Assessment of the Threat to Species in Disturbed Areas

Abstract:  We developed a method with which to analyze a specie's response to chronic anthropogenic disturbance (CAD). We regressed density of individuals on the intensity of 3 disturbance agents (human activities, raising livestock, and land degradation) along CAD gradients to determine how much CAD is experienced by a species; whether species are ruderal (achieving maximum densities in disturbed sites); whether density declines as a result of CAD; which disturbance agents are responsible for this reduction; and the number of populations that decline as a result of CAD. We tested the method on 9 threatened Mammillaria species (Cactaceae). Seven species were ruderal. In 4 species, actual disturbance surpassed the CAD intensity in which plants achieved their maximum densities; thus, the density of those 4 species appeared to be declining. For 7 species, some populations were threatened by human activities or livestock, whereas others were favored by them. Land degradation negatively affected all species. Our results allowed us to distinguish 4 groups of species that had similar responses and thus may require different forms of management. Our method provided an estimation of the growth rate (λ) of the studied populations that was significantly correlated with λs obtained from demographic studies. The size structures of populations were consistent with the predictions of the analysis, which suggests our results are consistent and reliable. Disturbance–response analysis provides a basis for management in heavily populated areas, where conservation must be achieved along with development activities that cause CAD. The method provides readily interpretable information, which facilitates participative decision making; the data are rapidly generated, which makes it appropriate when results are required promptly or for assessment of large numbers of species; and it provides a comprehensive perception of how threatened species behave in the real world.     

Transferability of Species Distribution Models: a Functional Habitat Approach for Two Regionally Threatened Butterflies

Abstract:  Numerous models for predicting species distribution have been developed for conservation purposes. Most of them make use of environmental data (e.g., climate, topography, land use) at a coarse grid resolution (often kilometres). Such approaches are useful for conservation policy issues including reserve-network selection. The efficiency of predictive models for species distribution is usually tested on the area for which they were developed. Although highly interesting from the point of view of conservation efficiency, transferability of such models to independent areas is still under debate. We tested the transferability of habitat-based predictive distribution models for two regionally threatened butterflies, the green hairstreak ( Callophrys rubi ) and the grayling ( Hipparchia semele ), within and among three nature reserves in northeastern Belgium. We built predictive models based on spatially detailed maps of area-wide distribution and density of ecological resources. We used resources directly related to ecological functions (host plants, nectar sources, shelter, microclimate) rather than environmental surrogate variables. We obtained models that performed well with few resource variables. All models were transferable—although to different degrees—among the independent areas within the same broad geographical region. We argue that habitat models based on essential functional resources could transfer better in space than models that use indirect environmental variables. Because functional variables can easily be interpreted and even be directly affected by terrain managers, these models can be useful tools to guide species-adapted reserve management.     

Building on IUCN Regional Red Lists to Produce Lists of Species of Conservation Priority: a Model with Irish Bees

Abstract:  A World Conservation Union (IUCN) regional red list is an objective assessment of regional extinction risk and is not the same as a list of conservation priority species. Recent research reveals the widespread, but incorrect, assumption that IUCN Red List categories represent a hierarchical list of priorities for conservation action. We developed a simple eight-step priority-setting process and applied it to the conservation of bees in Ireland. Our model is based on the national red list but also considers the global significance of the national population; the conservation status at global, continental, and regional levels; key biological, economic, and societal factors; and is compatible with existing conservation agreements and legislation. Throughout Ireland, almost one-third of the bee fauna is threatened (30 of 100 species), but our methodology resulted in a reduced list of only 17 priority species. We did not use the priority species list to broadly categorize species to the conservation action required; instead, we indicated the individual action required for all threatened, near-threatened, and data-deficient species on the national red list based on the IUCN's conservation-actions template file. Priority species lists will strongly influence prioritization of conservation actions at national levels, but action should not be exclusive to listed species. In addition, all species on this list will not necessarily require immediate action. Our method is transparent, reproducible, and readily applicable to other taxa and regions.     

Threatened Species and the Potential Loss of Phylogenetic Diversity: Conservation Scenarios Based on Estimated Extinction Probabilities and Phylogenetic Risk Analysis

Abstract: New species conservation strategies, including the EDGE of Existence (EDGE) program, have expanded threatened species assessments by integrating information about species' phylogenetic distinctiveness. Distinctiveness has been measured through simple scores that assign shared credit among species for evolutionary heritage represented by the deeper phylogenetic branches. A species with a high score combined with a high extinction probability receives high priority for conservation efforts. Simple hypothetical scenarios for phylogenetic trees and extinction probabilities demonstrate how such scoring approaches can provide inefficient priorities for conservation. An existing probabilistic framework derived from the phylogenetic diversity measure (PD) properly captures the idea of shared responsibility for the persistence of evolutionary history. It avoids static scores, takes into account the status of close relatives through their extinction probabilities, and allows for the necessary updating of priorities in light of changes in species threat status. A hypothetical phylogenetic tree illustrates how changes in extinction probabilities of one or more species translate into changes in expected PD. The probabilistic PD framework provided a range of strategies that moved beyond expected PD to better consider worst‐case PD losses. In another example, risk aversion gave higher priority to a conservation program that provided a smaller, but less risky, gain in expected PD. The EDGE program could continue to promote a list of top species conservation priorities through application of probabilistic PD and simple estimates of current extinction probability. The list might be a dynamic one, with all the priority scores updated as extinction probabilities change. Results of recent studies suggest that estimation of extinction probabilities derived from the red list criteria linked to changes in species range sizes may provide estimated probabilities for many different species. Probabilistic PD provides a framework for single‐species assessment that is well‐integrated with a broader measurement of impacts on PD owing to climate change and other factors.     

Bayesian Decision Analysis for Evaluating Management Options to Promote Recovery of a Depleted Salmon Population

Abstract:  The endangered population of sockeye salmon (Oncorhynchus nerka) in Cultus Lake, British Columbia, Canada, migrates through commercial fishing areas along with other, much more abundant sockeye salmon populations, but it is not feasible to selectively harvest only the latter, abundant populations. This situation creates controversial trade-offs between recovery actions and economic revenue. We conducted a Bayesian decision analysis to evaluate options for recovery of Cultus Lake sockeye salmon. We used a stochastic population model that included 2 sources of uncertainty that are often omitted from such analyses: structural uncertainty in the magnitude of a potential Allee effect and implementation uncertainty (the deviation between targets and actual outcomes of management actions). Numerous state-dependent, time-independent management actions meet recovery objectives. These actions prescribe limitations on commercial harvest rates as a function of abundance of Cultus Lake sockeye salmon. We also quantified how much reduction in economic value of commercial harvests of the more abundant sockeye salmon populations would be expected for a given increase in the probability of recovery of the Cultus population. Such results illustrate how Bayesian decision analysis can rank options for dealing with conservation risks and can help inform trade-off discussions among decision makers and among groups that have competing objectives.     

Use of surrogate species to cost-effectively prioritize conservation actions

Conservation efforts often focus on umbrella species whose distributions overlap with many other flora and fauna. However, because biodiversity is affected by different threats that are spatially variable, focusing only on the geographic range overlap of species may not be sufficient in allocating the necessary actions needed to efficiently abate threats. We developed a problem-based method for prioritizing conservation actions for umbrella species that maximizes the total number of flora and fauna benefiting from management while considering threats, actions, and costs. We tested our new method by assessing the performance of the Australian federal government's umbrella prioritization list, which identifies 73 umbrella species as priorities for conservation attention. Our results show that the federal government priority list benefits only 6% of all Australia's threatened terrestrial species. This could be increased to benefit nearly half (or 46%) of all threatened terrestrial species for the same budget of AU$550 million/year if more suitable umbrella species were chosen. This results in a 7-fold increase in management efficiency. We believe nations around the world can markedly improve the selection of prioritized umbrella species for conservation action with this transparent, quantitative, and objective prioritization approach.