Actual and Potential Use of Population Viability Analyses in Recovery of Plant Species Listed under the U.S. Endangered Species Act

Use of population viability analyses (PVAs) in endangered species recovery planning has been met with both support and criticism. Previous reviews promote use of PVA for setting scientifically based, measurable, and objective recovery criteria and recommend improvements to increase the framework's utility. However, others have questioned the value of PVA models for setting recovery criteria and assert that PVAs are more appropriate for understanding relative trade‐offs between alternative management actions. We reviewed 258 final recovery plans for 642 plants listed under the U.S. Endangered Species Act to determine the number of plans that used or recommended PVA in recovery planning. We also reviewed 223 publications that describe plant PVAs to assess how these models were designed and whether those designs reflected previous recommendations for improvement of PVAs. Twenty‐four percent of listed species had recovery plans that used or recommended PVA. In publications, the typical model was a matrix population model parameterized with ≤5 years of demographic data that did not consider stochasticity, genetics, density dependence, seed banks, vegetative reproduction, dormancy, threats, or management strategies. Population growth rates for different populations of the same species or for the same population at different points in time were often statistically different or varied by >10%. Therefore, PVAs parameterized with underlying vital rates that vary to this degree may not accurately predict recovery objectives across a species’ entire distribution or over longer time scales. We assert that PVA, although an important tool as part of an adaptive‐management program, can help to determine quantitative recovery criteria only if more long‐term data sets that capture spatiotemporal variability in vital rates become available. Lacking this, there is a strong need for viable and comprehensive methods for determining quantitative, science‐based recovery criteria for endangered species with minimal data availability. Uso Actual y Potencial del Análisis de Viabilidad Poblacional para la Recuperación de Especies de Plantas Enlistadas en el Acta de Especies En Peligro de E.U.A     

Using global sensitivity analysis of demographic models for ecological impact assessment

Population viability analysis (PVA) is widely used to assess population‐level impacts of environmental changes on species. When combined with sensitivity analysis, PVA yields insights into the effects of parameter and model structure uncertainty. This helps researchers prioritize efforts for further data collection so that model improvements are efficient and helps managers prioritize conservation and management actions. Usually, sensitivity is analyzed by varying one input parameter at a time and observing the influence that variation has over model outcomes. This approach does not account for interactions among parameters. Global sensitivity analysis (GSA) overcomes this limitation by varying several model inputs simultaneously. Then, regression techniques allow measuring the importance of input‐parameter uncertainties. In many conservation applications, the goal of demographic modeling is to assess how different scenarios of impact or management cause changes in a population. This is challenging because the uncertainty of input‐parameter values can be confounded with the effect of impacts and management actions. We developed a GSA method that separates model outcome uncertainty resulting from parameter uncertainty from that resulting from projected ecological impacts or simulated management actions, effectively separating the 2 main questions that sensitivity analysis asks. We applied this method to assess the effects of predicted sea‐level rise on Snowy Plover (Charadrius nivosus). A relatively small number of replicate models (approximately 100) resulted in consistent measures of variable importance when not trying to separate the effects of ecological impacts from parameter uncertainty. However, many more replicate models (approximately 500) were required to separate these effects. These differences are important to consider when using demographic models to estimate ecological impacts of management actions.     

The Sensitivity of Population Viability Analysis to Uncertainty about Habitat Requirements: Implications for the Management of the Endangered Southern Brown Bandicoot

Abstract:  Whenever population viability analysis (PVA) models are built to help guide decisions about the management of rare and threatened species, an important component of model building is the specification of a habitat model describing how a species is related to landscape or bioclimatic variables. Model-selection uncertainty may arise because there is often a great deal of ambiguity about which habitat model structure best approximates the true underlying biological processes. The standard approach to incorporate habitat models into PVA is to assume the best habitat model is correct, ignoring habitat-model uncertainty and alternative model structures that may lead to quantitatively different conclusions and management recommendations. Here we provide the first detailed examination of the influence of habitat-model uncertainty on the ranking of management scenarios from a PVA model. We evaluated and ranked 6 management scenarios for the endangered southern brown bandicoot ( Isoodon obesulus ) with PVA models, each derived from plausible competing habitat models developed with logistic regression. The ranking of management scenarios was sensitive to the choice of the habitat model used in PVA predictions. Our results demonstrate the need to incorporate methods into PVA that better account for model uncertainty and highlight the sensitivity of PVA to decisions made during model building. We recommend that researchers search for and consider a range of habitat models when undertaking model-based decision making and suggest that routine sensitivity analyses should be expanded to include an analysis of the impact of habitat-model uncertainty and assumptions.     

Using empirical models of species colonization under multiple threatening processes to identify complementary threat‐mitigation strategies

Approaches to prioritize conservation actions are gaining popularity. However, limited empirical evidence exists on which species might benefit most from threat mitigation and on what combination of threats, if mitigated simultaneously, would result in the best outcomes for biodiversity. We devised a way to prioritize threat mitigation at a regional scale with empirical evidence based on predicted changes to population dynamics—information that is lacking in most threat‐management prioritization frameworks that rely on expert elicitation. We used dynamic occupancy models to investigate the effects of multiple threats (tree cover, grazing, and presence of an hyperaggressive competitor, the Noisy Miner (Manorina melanocephala) on bird‐population dynamics in an endangered woodland community in southeastern Australia. The 3 threatening processes had different effects on different species. We used predicted patch‐colonization probabilities to estimate the benefit to each species of removing one or more threats. We then determined the complementary set of threat‐mitigation strategies that maximized colonization of all species while ensuring that redundant actions with little benefit were avoided. The single action that resulted in the highest colonization was increasing tree cover, which increased patch colonization by 5% and 11% on average across all species and for declining species, respectively. Combining Noisy Miner control with increasing tree cover increased species colonization by 10% and 19% on average for all species and for declining species respectively, and was a higher priority than changing grazing regimes. Guidance for prioritizing threat mitigation is critical in the face of cumulative threatening processes. By incorporating population dynamics in prioritization of threat management, our approach helps ensure funding is not wasted on ineffective management programs that target the wrong threats or species.     

Detecting Extinction Risk from Climate Change by IUCN Red List Criteria

Anthropogenic climate change is a key threat to global biodiversity. To inform strategic actions aimed at conserving biodiversity as climate changes, conservation planners need early warning of the risks faced by different species. The IUCN Red List criteria for threatened species are widely acknowledged as useful risk assessment tools for informing conservation under constraints imposed by limited data. However, doubts have been expressed about the ability of the criteria to detect risks imposed by potentially slow‐acting threats such as climate change, particularly because criteria addressing rates of population decline are assessed over time scales as short as 10 years. We used spatially explicit stochastic population models and dynamic species distribution models projected to future climates to determine how long before extinction a species would become eligible for listing as threatened based on the IUCN Red List criteria. We focused on a short‐lived frog species (Assa darlingtoni) chosen specifically to represent potential weaknesses in the criteria to allow detailed consideration of the analytical issues and to develop an approach for wider application. The criteria were more sensitive to climate change than previously anticipated; lead times between initial listing in a threatened category and predicted extinction varied from 40 to 80 years, depending on data availability. We attributed this sensitivity primarily to the ensemble properties of the criteria that assess contrasting symptoms of extinction risk. Nevertheless, we recommend the robustness of the criteria warrants further investigation across species with contrasting life histories and patterns of decline. The adequacy of these lead times for early warning depends on practicalities of environmental policy and management, bureaucratic or political inertia, and the anticipated species response times to management actions. Detección del Riesgo de Extinción a partir del Cambio Climático por medio del Criterio de la Lista Roja de la UICNKeith et al.     

Inferring the nature of anthropogenic threats from long‐term abundance records

Diagnosing the processes that threaten species persistence is critical for recovery planning and risk forecasting. Dominant threats are typically inferred by experts on the basis of a patchwork of informal methods. Transparent, quantitative diagnostic tools would contribute much‐needed consistency, objectivity, and rigor to the process of diagnosing anthropogenic threats. Long‐term census records, available for an increasingly large and diverse set of taxa, may exhibit characteristic signatures of specific threatening processes and thereby provide information for threat diagnosis. We developed a flexible Bayesian framework for diagnosing threats on the basis of long‐term census records and diverse ancillary sources of information. We tested this framework with simulated data from artificial populations subjected to varying degrees of exploitation and habitat loss and several real‐world abundance time series for which threatening processes are relatively well understood: bluefin tuna (Thunnus maccoyii) and Atlantic cod (Gadus morhua) (exploitation) and Red Grouse (Lagopus lagopus scotica) and Eurasian Skylark (Alauda arvensis) (habitat loss). Our method correctly identified the process driving population decline for over 90% of time series simulated under moderate to severe threat scenarios. Successful identification of threats approached 100% for severe exploitation and habitat loss scenarios. Our method identified threats less successfully when threatening processes were weak and when populations were simultaneously affected by multiple threats. Our method selected the presumed true threat model for all real‐world case studies, although results were somewhat ambiguous in the case of the Eurasian Skylark. In the latter case, incorporation of an ancillary source of information (records of land‐use change) increased the weight assigned to the presumed true model from 70% to 92%, illustrating the value of the proposed framework in bringing diverse sources of information into a common rigorous framework. Ultimately, our framework may greatly assist conservation organizations in documenting threatening processes and planning species recovery. Inferencia la Naturaleza de las Amenazas Antropogénicas para los Registros de Abundancia a Largo Plazo     

Critically evaluating best management practices for preventing freshwater turtle extinctions

Ex situ conservation tools, such as captive breeding for reintroduction, are considered a last resort to recover threatened or endangered species, but they may also help reduce anthropogenic threats where it is difficult or impossible to address them directly. Headstarting, or captive rearing of eggs or neonate animals for subsequent release into the wild, is controversial because it treats only a symptom of a larger conservation problem; however, it may provide a mechanism to address multiple threats, particularly near population centers. We conducted a population viability analysis of Australia's most widespread freshwater turtle, Chelodina longicollis, to determine the effect of adult roadkill (death by collision with motor vehicles), which is increasing, and reduced recruitment through nest predation from introduced European red foxes (Vulpes vulpes). We also modeled management scenarios to test the effectiveness of headstarting, fox management, and measures to reduce mortality on roads. Only scenarios with headstarting from source populations eliminated all risks of extinction and allowed population growth. Small increases in adult mortality (2%) had the greatest effect on population growth and extinction risk. Where threats simultaneously affected other life‐history stages (e.g., recruitment), eliminating harvest pressures on adult females alone did not eliminate the risk of population extinction. In our models, one source population could supply enough hatchlings annually to supplement 25 other similar‐sized populations such that extinction was avoided. Based on our results, we believe headstarting should be a primary tool for managing freshwater turtles for which threats affect multiple life‐history stages. We advocate the creation of source populations for managing freshwater turtles that are greatly threatened at multiple life‐history stages, such as depredation of eggs by invasive species and adult mortality via roadkill.     

Assessing the likely effectiveness of multispecies management for imperiled desert fishes with niche overlap analysis

A critical decision in species conservation is whether to target individual species or a complex of ecologically similar species. Management of multispecies complexes is likely to be most effective when species share similar distributions, threats, and response to threats. We used niche overlap analysis to assess ecological similarity of 3 sensitive desert fish species currently managed as an ecological complex. We measured the amount of shared distribution of multiple habitat and life history parameters between each pair of species. Habitat use and multiple life history parameters, including maximum body length, spawning temperature, and longevity, differed significantly among the 3 species. The differences in habitat use and life history parameters among the species suggest they are likely to respond differently to similar threats and that most management actions will not benefit all 3 species equally. Habitat restoration, frequency of stream dewatering, non‐native species control, and management efforts in tributaries versus main stem rivers are all likely to impact each of the species differently. Our results demonstrate that niche overlap analysis provides a powerful tool for assessing the likely effectiveness of multispecies versus single‐species conservation plans. Evaluación de la Posible Efectividad del Manejo Multi‐Especie paraPeces de Desierto en Peligro Mediante el Análisis de Traslape de Nichos     

Incorporating Climate and Ocean Change into Extinction Risk Assessments for 82 Coral Species

Many marine invertebrate species facing potential extinction have uncertain taxonomies and poorly known demographic and ecological traits. Uncertainties are compounded when potential extinction drivers are climate and ocean changes whose effects on even widespread and abundant species are only partially understood. The U.S. Endangered Species Act mandates conservation management decisions founded on the extinction risk to species based on the best available science at the time of consideration—requiring prompt action rather than awaiting better information. We developed an expert‐opinion threat‐based approach that entails a structured voting system to assess extinction risk from climate and ocean changes and other threats to 82 coral species for which population status and threat response information was limited. Such methods are urgently needed because constrained budgets and manpower will continue to hinder the availability of desired data for many potentially vulnerable marine species. Significant species‐specific information gaps and uncertainties precluded quantitative assessments of habitat loss or population declines and necessitated increased reliance on demographic characteristics and threat vulnerabilities at genus or family levels. Adapting some methods (e.g., a structured voting system) used during other assessments and developing some new approaches (e.g., integrated assessment of threats and demographic characteristics), we rated the importance of threats contributing to coral extinction risk and assessed those threats against population status and trend information to evaluate each species’ extinction risk over the 21st century. This qualitative assessment resulted in a ranking with an uncertainty range for each species according to their estimated likelihood of extinction. We offer guidance on approaches for future biological extinction risk assessments, especially in cases of data‐limited species likely to be affected by global‐scale threats. Incorporación del Cambio Climático y Oceánico en Estudios de Riesgo de Extinción para 82 Especies de Coral     

Dependence of the Endangered Black‐Capped Vireo on Sustained Cowbird Management

Conservation‐reliant species depend on active management, even after surpassing recovery goals, for protection from persistent threats. Required management may include control of another species, habitat maintenance, or artificial recruitment. Sometimes, it can be difficult to determine whether sustained management is required. We used nonspatial stochastic population projection matrix simulation and a spatially explicit population model to estimate the effects of parasitism by a brood parasite, the Brown‐headed Cowbird (Moluthrus ater), on a population of endangered Black‐capped Vireos (Vireo atricapilla). We simulated parasitism as a percentage of breeding vireo pairs experiencing decreased fecundity due to cowbirds. We estimated maximum sustainable parasitism (i.e., highest percentage of parasitized vireo breeding pairs for which population growth is ≥1) with the nonspatial model under multiple scenarios designed to assess sensitivity to assumptions about population growth rate, demographic effects of parasitism, and spatial distribution of parasitism. We then used the spatially explicit model to estimate cumulative probabilities of the population falling below the population recovery target of 1000 breeding pairs for a range of parasitism rates under multiple scenarios. We constructed our models from data on vireos collected on the Fort Hood Military Reservation, Texas (U.S.A.). Estimates of maximum sustainable parasitism rates ranged from 9–12% in scenarios with a low (6%) vireo population growth rate to 49–60% in scenarios with a high (24%) growth rate. Sustained parasitism above 45–85%, depending on the scenario, would likely result in the Fort Hood Vireo population dropping below its recovery goal within the next 25 years. These estimates suggest that vireos, although tolerant of low parasitism rates, are a conservation‐reliant species dependent on cowbird management. Dependencia de Vireo atricapilla, Especie en Peligro, hacia el Manejo Sostenido de Moluthurs ater     

Using Population Viability Criteria to Assess Strategies to Minimize Disease Threats for an Endangered Carnivore

Outbreaks of infectious disease represent serious threats to the viability of many vertebrate populations, but few studies have included quantitative evaluations of alternative approaches to the management of disease. The most prevalent management approach is monitoring for and rapid response to an epizootic. An alternative is vaccination of a subset of the free‐living population (i.e., a “vaccinated core”) such that some individuals are partially or fully immune in the event of an epizootic. We developed a simulation model describing epizootic dynamics, which we then embedded in a demographic simulation to assess these alternative approaches to managing rabies epizootics in the island fox (Urocyon littoralis), a species composed of only 6 small populations on the California Channel Islands. Although the monitor and respond approach was superior to the vaccinated‐core approach for some transmission models and parameter values, this type of reactive management did not protect the population from rabies under many disease‐transmission assumptions. In contrast, a logistically feasible program of prophylactic vaccination for part of the wild population yielded low extinction probabilities across all likely disease‐transmission scenarios, even with recurrent disease introductions. Our use of a single metric of successful management—probability of extreme endangerment (i.e., quasi extinction)—to compare very different management approaches allowed an objective assessment of alternative strategies for controlling the threats posed by infectious disease outbreaks. Utilización de Criterios de Viabilidad Poblacional para Evaluar Estrategias para Minimizar Amenazas de Enfermedades para un Carnívoro en Peligro     

Fire Management,Managed Relocation,and Land Conservation Options for Long‐Lived Obligate Seeding Plants under Global Changes in Climate,Urbanization, and Fire Regime

Most species face multiple anthropogenic disruptions. Few studies have quantified the cumulative influence of multiple threats on species of conservation concern, and far fewer have quantified the potential relative value of multiple conservation interventions in light of these threats. We linked spatial distribution and population viability models to explore conservation interventions under projected climate change, urbanization, and changes in fire regime on a long‐lived obligate seeding plant species sensitive to high fire frequencies, a dominant plant functional type in many fire‐prone ecosystems, including the biodiversity hotspots of Mediterranean‐type ecosystems. First, we investigated the relative risk of population decline for plant populations in landscapes with and without land protection under an existing habitat conservation plan. Second, we modeled the effectiveness of relocating both seedlings and seeds from a large patch with predicted declines in habitat area to 2 unoccupied recipient patches with increasing habitat area under 2 projected climate change scenarios. Finally, we modeled 8 fire return intervals (FRIs) approximating the outcomes of different management strategies that effectively control fire frequency. Invariably, long‐lived obligate seeding populations remained viable only when FRIs were maintained at or above a minimum level. Land conservation and seedling relocation efforts lessened the impact of climate change and land‐use change on obligate seeding populations to differing degrees depending on the climate change scenario, but neither of these efforts was as generally effective as frequent translocation of seeds. While none of the modeled strategies fully compensated for the effects of land‐use and climate change, an integrative approach managing multiple threats may diminish population declines for species in complex landscapes. Conservation plans designed to mitigate the impacts of a single threat are likely to fail if additional threats are ignored. Manejo de Incendios, Reubicación Administrada y Opciones de Conservación de Suelo para Plantas de Vida Larga con Sembrado Obligado bajo los Cambios Globales en el Clima, la Urbanización y el Régimen de Incendios     

Integrated models to support multiobjective ecological restoration decisions

Many objectives motivate ecological restoration, including improving vegetation condition, increasing the range and abundance of threatened species, and improving species richness and diversity. Although models have been used to examine the outcomes of ecological restoration, few researchers have attempted to develop models to account for multiple, potentially competing objectives. We developed a combined state‐and‐transition, species‐distribution model to predict the effects of restoration actions on vegetation condition and extent, bird diversity, and the distribution of several bird species in southeastern Australian woodlands. The actions reflected several management objectives. We then validated the models against an independent data set and investigated how the best management decision might change when objectives were valued differently. We also used model results to identify effective restoration options for vegetation and bird species under a constrained budget. In the examples we evaluated, no one action (improving vegetation condition and extent, increasing bird diversity, or increasing the probability of occurrence for threatened species) provided the best outcome across all objectives. In agricultural lands, the optimal management actions for promoting the occurrence of the Brown Treecreeper (Climacteris picumnus), an iconic threatened species, resulted in little improvement in the extent of the vegetation and a high probability of decreased vegetation condition. This result highlights that the best management action in any situation depends on how much the different objectives are valued. In our example scenario, no management or weed control were most likely to be the best management options to satisfy multiple restoration objectives. Our approach to exploring trade‐offs in management outcomes through integrated modeling and structured decision‐support approaches has wide application for situations in which trade‐offs exist between competing conservation objectives.     

Rapid assessment of management options for promoting stock rebuilding in data-poor species under climate change

The development of species recovery plans requires considering likely outcomes of different management interventions, but the complicating effects of climate change are rarely evaluated. We examined how qualitative network models (QNMs) can be deployed to support decision making when data, time, and funding limitations restrict use of more demanding quantitative methods. We used QNMs to evaluate management interventions intended to promote the rebuilding of a collapsed stock of blue king crab (Paralithodes platypus) (BKC) around the Pribilof Islands (eastern Bering Sea) to determine how their potential efficacy may change under climate change. Based on stakeholder input and a literature review, we constructed a QNM that described the life cycle of BKC, key ecological interactions, potential climate-change impacts, relative interaction strengths, and uncertainty in terms of interaction strengths and link presence. We performed sensitivity analyses to identify key sources of prediction uncertainty. Under a scenario of no climate change, predicted increases in BKC were reliable only when stock enhancement was implemented in a BKC hatchery-program scenario. However, when climate change was accounted for, the intervention could not counteract its adverse impacts, which had an overall negative effect on BKC. The remaining management scenarios related to changes in fishing effort on BKC predators. For those scenarios, BKC outcomes were unreliable, but climate change further decreased the probability of observing recovery. Including information on relative interaction strengths increased the likelihood of predicting positive outcomes for BKC approximately 5–50% under the management scenarios. The largest gains in prediction precision will be made by reducing uncertainty associated with ecological interactions between adult BKC and red king crab (Paralithodes camtschaticus). Qualitative network models are useful options when data are limited, but they remain underutilized in conservation.     

Monitoring,imperfect detection,and risk optimization of a Tasmanian devil insurance population

Most species are imperfectly detected during biological surveys, which creates uncertainty around their abundance or presence at a given location. Decision makers managing threatened or pest species are regularly faced with this uncertainty. Wildlife diseases can drive species to extinction; thus, managing species with disease is an important part of conservation. Devil facial tumor disease (DFTD) is one such disease that led to the listing of the Tasmanian devil (Sarcophilus harrisii) as endangered. Managers aim to maintain devils in the wild by establishing disease‐free insurance populations at isolated sites. Often a resident DFTD‐affected population must first be removed. In a successful collaboration between decision scientists and wildlife managers, we used an accessible population model to inform monitoring decisions and facilitate the establishment of an insurance population of devils on Forestier Peninsula. We used a Bayesian catch‐effort model to estimate population size of a diseased population from removal and camera trap data. We also analyzed the costs and benefits of declaring the area disease‐free prior to reintroduction and establishment of a healthy insurance population. After the monitoring session in May–June 2015, the probability that all devils had been successfully removed was close to 1, even when we accounted for a possible introduction of a devil to the site. Given this high probability and the baseline cost of declaring population absence prematurely, we found it was not cost‐effective to carry out any additional monitoring before introducing the insurance population. Considering these results within the broader context of Tasmanian devil management, managers ultimately decided to implement an additional monitoring session before the introduction. This was a conservative decision that accounted for uncertainty in model estimates and for the broader nonmonetary costs of mistakenly declaring the area disease‐free.     

Scaling range sizes to threats for robust predictions of risks to biodiversity

Assessments of risk to biodiversity often rely on spatial distributions of species and ecosystems. Range‐size metrics used extensively in these assessments, such as area of occupancy (AOO), are sensitive to measurement scale, prompting proposals to measure them at finer scales or at different scales based on the shape of the distribution or ecological characteristics of the biota. Despite its dominant role in red‐list assessments for decades, appropriate spatial scales of AOO for predicting risks of species’ extinction or ecosystem collapse remain untested and contentious. There are no quantitative evaluations of the scale‐sensitivity of AOO as a predictor of risks, the relationship between optimal AOO scale and threat scale, or the effect of grid uncertainty. We used stochastic simulation models to explore risks to ecosystems and species with clustered, dispersed, and linear distribution patterns subject to regimes of threat events with different frequency and spatial extent. Area of occupancy was an accurate predictor of risk (0.81<|r|<0.98) and performed optimally when measured with grid cells 0.1–1.0 times the largest plausible area threatened by an event. Contrary to previous assertions, estimates of AOO at these relatively coarse scales were better predictors of risk than finer‐scale estimates of AOO (e.g., when measurement cells are <1% of the area of the largest threat). The optimal scale depended on the spatial scales of threats more than the shape or size of biotic distributions. Although we found appreciable potential for grid‐measurement errors, current IUCN guidelines for estimating AOO neutralize geometric uncertainty and incorporate effective scaling procedures for assessing risks posed by landscape‐scale threats to species and ecosystems.     

Application of multiple-population viability analysis to evaluate species recovery alternatives

Population viability analysis (PVA) is a powerful conservation tool, but it remains impractical for many species, particularly species with multiple, broadly distributed populations for which collecting suitable data can be challenging. A recently developed method of multiple-population viability analysis (MPVA), however, addresses many limitations of traditional PVA. We built on previous development of MPVA for Lahontan cutthroat trout (LCT) (Oncorhynchus clarkii henshawi), a species listed under the U.S. Endangered Species Act, that is distributed broadly across habitat fragments in the Great Basin (U.S.A.). We simulated potential management scenarios and assessed their effects on population sizes and extinction risks in 211 streams, where LCT exist or may be reintroduced. Conservation populations (those managed for recovery) tended to have lower extinction risks than nonconservation populations (mean = 19.8% vs. 52.7%), but not always. Active management or reprioritization may be warranted in some cases. Eliminating non-native trout had a strong positive effect on overall carrying capacities for LCT populations but often did not translate into lower extinction risks unless simulations also reduced associated stochasticity (to the mean for populations without non-native trout). Sixty fish or 5–10 fish/km was the minimum reintroduction number and density, respectively, that provided near-maximum reintroduction success. This modeling framework provided crucial insights and empirical justification for conservation planning and specific adaptive management actions for this threatened species. More broadly, MPVA is applicable to a wide range of species exhibiting geographic rarity and limited availability of abundance data and greatly extends the potential use of empirical PVA for conservation assessment and planning.     

A Matrix‐Calibrated Species‐Area Model for Predicting Biodiversity Losses Due to Land‐Use Change

Abstract: Application of island biogeography theory to prediction of species extinctions resulting from habitat loss is based on the assumption that the transformed landscape matrix is completely inhospitable to the taxa considered, despite evidence demonstrating the nontrivial influence of matrix on populations within habitat remnants. The island biogeography paradigm therefore needs refining to account for specific responses of taxa to the area of habitat “islands” and to the quality of the surrounding matrix. We incorporated matrix effects into island theory by partitioning the slope (z value) of species–area relationships into two components: γ, a constant, and σ, a measure of taxon‐specific responses to each component of a heterogeneous matrix. We used our matrix‐calibrated model to predict extinction and endangerment of bird species resulting from land‐use change in 20 biodiversity hotspots and compared these predictions with observed numbers of extinct and threatened bird species. We repeated this analysis with the conventional species–area model and the countryside species–area model, considering alternative z values of 0.35 (island) or 0.22 (continental). We evaluated the relative strength of support for each of the five candidate models with Akaike's information criterion (AIC). The matrix‐calibrated model had the highest AIC weight (w_i = 89.21%), which means the weight of evidence in support of this model was the optimal model given the set of candidate models and the data. In addition to being a valuable heuristic tool for assessing extinction risk, our matrix‐calibrated model also allows quantitative assessment of biodiversity benefits (and trade‐offs) of land‐management options in human‐dominated landscapes. Given that processes of secondary regeneration have become more widespread across tropical regions and are predicted to increase, our matrix‐calibrated model will be increasingly appropriate for practical conservation in tropical landscapes.     

Metrics for quantifying how much different threats contribute to red lists of species and ecosystems

Red lists are a crucial tool for the management of threatened species and ecosystems. Among the information red lists provide, the threats affecting the listed species or ecosystem, such as pollution or hunting, are of special relevance. This information can be used to quantify the relative contribution of different threat factors to biodiversity loss by disaggregating the cumulative extinction risk across species into components that can be attributed to certain threats. We devised and compared 3 metrics that accomplish this and may be used as indicators. The first metric calculates the portion of the temporal change in red list index (RLI) values that is caused by each threat. The second metric attributes the deviation of an RLI value from its reference value to different threats. The third metric uses extinction probabilities that are inferred from red list categories to estimate the contribution of a threat to the expected loss of species or ecosystems within 50 years. We used data from Norwegian Red Lists to test and evaluate these metrics. The first metric captured only a minor portion of the biodiversity loss caused by threats because it ignores species whose red list category does not change. Management authorities will often be interested in the contribution of a given threat to the total deviation from the optimal state. This was measured by the remaining metrics. The second metric was best suited for comparisons across countries or taxonomic groups. The third metric conveyed the same information but uses numbers of species or ecosystem as its unit, which is likely more intuitive to lay people and may be preferred when communicating with stakeholders or the general public.