Building a better baseline to estimate 160 years of avian population change and create historically informed conservation targets

Globally, anthropogenic land-cover change has been dramatic over the last few centuries and is frequently invoked as a major cause of wildlife population declines. Baseline data currently used to assess population trends, however, began well after major changes to the landscape. In the United States and Canada, breeding bird population trends are assessed by the North American Breeding Bird Survey, which began in the 1960s. Estimates of distribution and abundance prior to major habitat alteration would add historical perspective to contemporary trends and allow for historically based conservation targets. We used a hindcasting framework to estimate change in distribution and abundance of 7 bird species in the Willamette Valley, Oregon (United States). After reconciling classification schemes of current and 1850s reconstructed land cover, we used multiscale species distribution models and hierarchical distance sampling models to predict spatially explicit densities in the modern and historical landscapes. We estimated that since the 1850s, White-breasted Nuthatch (Sitta carolinensis) and Western Meadowlark (Sturnella neglecta) populations, 2 species sensitive to fragmentation of oak woodlands and grasslands, declined by 93% and 97%, respectively. Five other species we estimated nearly stable or increasing populations, despite steep regional declines since the 1960s. Based on these estimates, we developed historically based conservation targets for amount of habitat, population, and density for each species. Hindcasted reconstructions provide historical perspective for assessing contemporary trends and allow for historically based conservation targets that can inform current management.     

Use of standardized methods to improve extinction-risk classification

Standardized classification methods based on quantifiable risk metrics are critical for evaluating extinction threats because they increase objectivity, consistency, and transparency of listing decisions. Yet, in the United States, neither federal nor state agencies use standardized methods for listing species for legal protection, which could put listing decisions at odds with the magnitude of the risk. We used a recently developed set of quantitative risk metrics for California herpetofauna as a case study to highlight discrepancies in listing decisions made without standardized methods. We also combined such quantitative metrics with classification tree analysis to attempt to increase the transparency of previous listing decisions by identifying the criteria that had inherently been given the most weight. Federally listed herpetofauna in California scored significantly higher on the risk-metric spectrum than those not federally listed, whereas state-listed species did not score any higher than species that were not state listed. Based on classification trees, state endemism was the most important predictor of listing status at the state level and distribution trend (decline in a species’ range size) and population trend (decline in a species’ abundance at localized sites) were the most important predictors at the federal level. Our results emphasize the need for governing bodies to adopt standardized methods for assessing conservation risk that are based on quantitative criteria. Such methods allow decision makers to identify criteria inherently given the most weight in determining listing status, thus increasing the transparency of previous listing decisions, and produce an unbiased comparison of conservation threat across all species to promote consistency, efficiency, and effectiveness of the listing process.     

Optimizing conservation in species-specific agricultural landscapes

Recovery of grassland birds in agricultural landscapes is a global imperative. Agricultural landscapes are complex, and the value of resource patches may vary substantially among species. The spatial extent at which landscape features affect populations (i.e., scale of effect) may also differ among species. There is a need for regional-scale conservation planning that considers landscape-scale and species-specific responses of grassland birds to environmental change. We developed a spatially explicit approach to optimizing grassland conservation in the context of species-specific landscapes and prioritization of species recovery and applied it to a conservation program in Kentucky (USA). We used a hierarchical distance-sampling model with an embedded scale of effect predictor to estimate the relationship between landscape structure and abundance of eastern meadowlarks (Sturnella magna), field sparrows (Spizella pusilla), and northern bobwhites (Colinus virginianus). We used a novel spatially explicit optimization procedure rooted in multi-attribute utility theory to design alternative conservation strategies (e.g., prioritize only northern bobwhite recovery or assign equal weight to each species’ recovery). Eastern meadowlarks and field sparrows were more likely to respond to landscape-scale resource patch adjacencies than landscape-scale patch densities. Northern bobwhite responded to both landscape-scale resource patch adjacencies and densities and responded strongly to increased grassland density. Effects of landscape features on local abundance decreased as distance increased and had negligible influence at 0.8 km for eastern meadowlarks (0.7–1.2 km 95% Bayesian credibility intervals [BCI]), 2.5 km for field sparrows (1.5–5.8 km 95% BCI), and 8.4 km for bobwhite (6.4–26 km 95% BCI). Northern bobwhites were predicted to benefit greatly from future grassland conservation regardless of conservation priorities, but eastern meadowlark and field sparrow were not. Our results suggest similar species can respond differently to broad-scale conservation practices because of species-specific, distance-dependent relationships with landscape structure. Our framework is quantitative, conceptually simple, customizable, and predictive and can be used to optimize conservation in heterogeneous ecosystems while considering landscape-scale processes and explicit prioritization of species recovery.     

Estimation of spatiotemporal trends in bat abundance from mortality data collected at wind turbines

Renewable energy sources, such as wind energy, are essential tools for reducing the causes of climate change, but wind turbines can pose a collision risk for bats. To date, the population-level effects of wind-related mortality have been estimated for only 1 bat species. To estimate temporal trends in bat abundance, we considered wind turbines as opportunistic sampling tools for flying bats (analogous to fishing nets), where catch per unit effort (carcass abundance per monitored turbine) is a proxy for aerial abundance of bats, after accounting for seasonal variation in activity. We used a large, standardized data set of records of bat carcasses from 594 turbines in southern Ontario, Canada, and corrected these data to account for surveyor efficiency and scavenger removal. We used Bayesian hierarchical models to estimate temporal trends in aerial abundance of bats and to explore the effect of spatial factors, including landscape features associated with bat habitat (e.g., wetlands, croplands, and forested lands), on the number of mortalities for each species. The models showed a rapid decline in the abundance of 4 species in our study area; declines in capture of carcasses over 7 years ranged from 65% (big brown bat [Eptesicus fuscus]) to 91% (silver-haired bat [Lasionycteris noctivagans]). Estimated declines were independent of the effects of mitigation (increasing wind speed at which turbines begin to generate electricity from 3.5 to 5.5 m/s), which significantly reduced but did not eliminate bat mortality. Late-summer mortality of hoary (Lasiurus cinereus), eastern red (Lasiurus borealis), and silver-haired bats was predicted by woodlot cover, and mortality of big brown bats decreased with increasing elevation. These landscape predictors of bat mortality can inform the siting of future wind energy operations. Our most important result is the apparent decline in abundance of four common species of bat in the airspace, which requires further investigation.     

Assigning trend-based conservation status despite high uncertainty

Estimates of temporal trends in species’ occupancy are essential for conservation policy and planning, but limitations to the data and models often result in very high trend uncertainty. A critical source of uncertainty that degrades scientific credibility is that caused by disagreement among studies or models. Modelers are aware of this uncertainty but usually only partially estimate it and communicate it to decision makers. At the same time, there is growing awareness that full disclosure of uncertainty is critical for effective translation of science into policies and plans. But what are the most effective approaches to estimating uncertainty and communicating uncertainty to decision makers? We explored how alternative approaches to estimating and communicating uncertainty of species trends could affect decisions concerning conservation status of freshwater fishes. We used ensemble models to propagate trend uncertainty within and among models and communicated this uncertainty with categorical distributions of trend direction and magnitude. All approaches were designed to fit an established decision-making system used to assign species conservation status by the New Zealand government. Our results showed how approaches that failed to fully disclose uncertainty, while simplifying the information presented, could hamper species conservation or lead to ineffective decisions. We recommend an approach that was recently used effectively to communicate trend uncertainty to a panel responsible for setting the conservation status of New Zealand's freshwater fishes.     

A critical appraisal of population viability analysis

Population viability analysis (PVA) is useful in management of imperiled species. Applications range from research design, threat assessment, and development of management frameworks. Given the importance of PVAs, it is essential that they be rigorous and adhere to widely accepted guidelines; however, the quality of published PVAs is rarely assessed. We evaluated the quality of 160 PVAs of 144 species of birds and mammals published in peer-reviewed journals from 1990 to 2017. We hypothesized that PVA quality would be lower with generic programs than with custom-built programs; be higher for those developed for imperiled species; change over time; and be higher for those published in journals with high impact factors (IFs). Each included study was evaluated based on answers to an evaluation framework containing 32 questions reflecting whether and to what extent the PVA study adhered to published PVA guidelines or contained important PVA components. All measures of PVA quality were generally lower for studies based on generic programs. Conservation status of the species did not affect any measure of PVA quality, but PVAs published in high IF journals were of higher quality. Quality generally declined over time, suggesting the quantitative literacy of PVA practitioners has not increased over time or that PVAs developed by unskilled users are being published in peer-reviewed journals. Only 18.1% of studies were of high quality (score >75%), which is troubling because poor-quality PVAs could misinform conservation decisions. We call for increased scrutiny of PVAs by journal editors and reviewers. Our evaluation framework can be used for this purpose. Because poor-quality PVAs continue to be published, we recommend caution while using PVA results in conservation decision making without thoroughly assessing the PVA quality.     

Predicting Recovery Criteria for Threatened and Endangered Plant Species on the Basis of Past Abundances and Biological Traits

Recovery plans for species listed under the U.S. Endangered Species Act are required to specify measurable criteria that can be used to determine when the species can be delisted. For the 642 listed endangered and threatened plant species that have recovery plans, we applied recursive partitioning methods to test whether the number of individuals or populations required for delisting can be predicted on the basis of distributional and biological traits, previous abundance at multiple time steps, or a combination of traits and previous abundances. We also tested listing status (threatened or endangered) and the year the recovery plan was written as predictors of recovery criteria. We analyzed separately recovery criteria that were stated as number of populations and as number of individuals (population‐based and individual‐based criteria, respectively). Previous abundances alone were relatively good predictors of population‐based recovery criteria. Fewer populations, but a greater proportion of historically known populations, were required to delist species that had few populations at listing compared with species that had more populations at listing. Previous abundances were also good predictors of individual‐based delisting criteria when models included both abundances and traits. The physiographic division in which the species occur was also a good predictor of individual‐based criteria. Our results suggest managers are relying on previous abundances and patterns of decline as guidelines for setting recovery criteria. This may be justifiable in that previous abundances inform managers of the effects of both intrinsic traits and extrinsic threats that interact and determine extinction risk. Predicción de Criterios de Recuperación para Especies de Plantas en Peligro y Amenazadas con Base en Abundancias Pasadas y Atributos Biológicos     

Modeling population effects of the Deepwater Horizon oil spill on a long-lived species

The 2010 Deepwater Horizon (DWH) oil spill exposed common bottlenose dolphins (Tursiops truncatus) in Barataria Bay, Louisiana to heavy oiling that caused increased mortality and chronic disease and impaired reproduction in surviving dolphins. We conducted photographic surveys and veterinary assessments in the decade following the spill. We assigned a prognostic score (good, fair, guarded, poor, or grave) for each dolphin to provide a single integrated indicator of overall health, and we examined temporal trends in prognostic scores. We used expert elicitation to quantify the implications of trends for the proportion of the dolphins that would recover within their lifetime. We integrated expert elicitation, along with other new information, in a population dynamics model to predict the effects of observed health trends on demography. We compared the resulting population trajectory with that predicted under baseline (no spill) conditions. Disease conditions persisted and have recently worsened in dolphins that were presumably exposed to DWH oil: 78% of those assessed in 2018 had a guarded, poor, or grave prognosis. Dolphins born after the spill were in better health. We estimated that the population declined by 45% (95% CI 14–74) relative to baseline and will take 35 years (95% CI 18–67) to recover to 95% of baseline numbers. The sum of annual differences between baseline and injured population sizes (i.e., the lost cetacean years) was 30,993 (95% CI 6607–94,148). The population is currently at a minimum point in its recovery trajectory and is vulnerable to emerging threats, including planned ecosystem restoration efforts that are likely to be detrimental to the dolphins’ survival. Our modeling framework demonstrates an approach for integrating different sources and types of data, highlights the utility of expert elicitation for indeterminable input parameters, and emphasizes the importance of considering and monitoring long-term health of long-lived species subject to environmental disasters. Article impact statement: Oil spills can have long-term consequences for the health of long-lived species; thus, effective restoration and monitoring are needed.     

Speaking across boundaries to explore the potential for interdisciplinarity in ecosystem services knowledge production

Conservation is likely to be most successful if it draws on knowledge from across the natural and social sciences. The ecosystem services concept has been called a boundary object in that it facilitates development of such interdisciplinary knowledge because it offers a common platform for researchers, policy makers, and practitioners. However, a question that remains is to what extent the interdisciplinary knowledge needed is provided by disciplinary diversity within the field. We asked where is knowledge on ecosystem services produced, how interdisciplinary is this knowledge, and which disciplines facilitate the greatest disciplinary integration? We defined interdisciplinarity as the extent to which published research draws on knowledge that crosses disciplinary borders and used citations as a quantitative indicator of communication among disciplines, based on journal classification. We used disciplinary diversity, richness, and heterocitation as measures of interdisciplinarity and betweenness centrality as a measure of disciplinary integration. Our data set contained 22,153 publications on ecosystem services, published from 1983 to 2018. We found that ecosystem services research matured; average yearly output growth was 33.8%, more than the 8–9% growth in scientific output across all fields. Over time, the network clustering coefficient, measuring connectedness of individual disciplines, rose from 0.388 to 0.727, suggesting increased density in the network of citations. Researchers in the field published more articles (3566 in 2018 alone) across more disciplines (77 unique disciplines in 2018). However, this growth was not mirrored by an increase in the diversity (stable at 0.7–0.9) or richness (averaging 0.35 unique disciplines per citation) of citation patterns. Heterocitation scores, or out-of-group citations, for arts, humanities, social sciences, and law ranged from 56% to 64%, which was lower than we expected, although this may serve to protect the integrity of social science disciplines and attract broader engagement from within. Ultimately, a small number of productive disciplines are central to supporting disciplinary integration. However, opportunities exist for conservation practice to draw on a broader field of research, to realize the potential that the diverse body of knowledge of interdisciplinary work offers.     

The dilemma of pest suppression in the conservation of endangered species

In the conservation of endangered species, suppression of a population of one native species to benefit another poses challenges. Examples include predator control and nest parasite reduction. Less obvious is the control of blood-feeding arthropods. We conducted a case study of the effect of native black flies (Simulium spp.) on reintroduced Whooping Cranes (Grus americana). Our intent was to provide a science-driven approach for determining the effects of blood-feeding arthropods on endangered vertebrates and identifying optimal management actions for managers faced with competing objectives. A multiyear experiment demonstrated that black flies reduce nest success in cranes by driving incubating birds off their nests. We used a decision-analytic approach to develop creative management alternatives and evaluate trade-offs among competing objectives. We identified 4 management objectives: establish a self-sustaining crane population, improve crane well-being, maintain native black flies as functional components of the ecosystem, and minimize costs. We next identified potential management alternatives: do nothing, suppress black flies, force crane renesting to occur after the activity period of black flies, relocate releases of cranes, suppress black flies and relocate releases, or force crane renesting and relocate releases. We then developed predictions on constructed scales of 0 (worst-performing alternative) to 1 (best-performing alternative) to indicate how alternative actions performed in terms of management objectives. The optimal action depended on the relative importance of each objective to a decision maker. Only relocating releases was a dominated alternative, indicating that it was not optimal regardless of the relative importance of objectives. A rational decision maker could choose any other management alternative we considered. Recognizing that decisions involve trade-offs that must be weighed by decision makers is crucial to identifying alternatives that best balance multiple management objectives. Given uncertainty about the population dynamics of blood-feeding arthropods, an adaptive management approach could offer substantial benefits.     

Variability in Population Abundance and the Classification of Extinction Risk

Abstract: Classifying species according to their risk of extinction is a common practice and underpins much conservation activity. The reliability of such classifications rests on the accuracy of threat categorizations, but very little is known about the magnitude and types of errors that might be expected. The process of risk classification involves combining information from many sources, and understanding the quality of each source is critical to evaluating the overall status of the species. One common criterion used to classify extinction risk is a decline in abundance. Because abundance is a direct measure of conservation status, counts of individuals are generally the preferred method of evaluating whether populations are declining. Using the thresholds from criterion A of the International Union for Conservation of Nature (IUCN) Red List (critically endangered, decline in abundance of >80% over 10 years or 3 generations; endangered, decline in abundance of 50–80%; vulnerable, decline in abundance of 30–50%; least concern or near threatened, decline in abundance of 0–30%), we assessed 3 methods used to detect declines solely from estimates of abundance: use of just 2 estimates of abundance; use of linear regression on a time series of abundance; and use of state‐space models on a time series of abundance. We generated simulation data from empirical estimates of the typical variability in abundance and assessed the 3 methods for classification errors. The estimates of the proportion of falsely detected declines for linear regression and the state‐space models were low (maximum 3–14%), but 33–75% of small declines (30–50% over 15 years) were not detected. Ignoring uncertainty in estimates of abundance (with just 2 estimates of abundance) allowed more power to detect small declines (95%), but there was a high percentage (50%) of false detections. For all 3 methods, the proportion of declines estimated to be >80% was higher than the true proportion. Use of abundance data to detect species at risk of extinction may either fail to detect initial declines in abundance or have a high error rate.     

Global trends in research output by zoos and aquariums

Zoos and aquaria, often regarded as preservation-cum-entertainment enterprises, are also actors in the effort to curb the biodiversity crisis: raising awareness, supporting conservation, and conducting research. We assessed trends in zoo and aquaria research topics and study organisms over time worldwide. For the zoos and aquaria registered in the Species360's Zoological Information Management System and the World Association of Zoos and Aquariums, we compiled metadata on their research published in the peer-reviewed literature indexed in Scopus and carried out a keyword frequency analysis. The production of scientific papers by zoos increased at a much faster rate than the average accrual of scientific papers in the literature. Evolution of research themes ran parallel to that of biological sciences (e.g., development of molecular genetics or increased awareness about conservation). The focus of 48.5% of zoo-led research was on vertebrates, of which mammal research was 33.7%. Whether zoos are effectively contributing to conservation may still be debatable, but our results highlight their institutional efforts to increase knowledge about the species in their care.     

Using ensemble modeling to predict the impacts of assisted migration on recipient ecosystems

Assisted migration is a controversial conservation measure that aims to protect threatened species by moving part of their population outside its natural range. Although this could save species from extinction, it also introduces a range of risks. The magnitude of the threat to recipient ecosystems has not been investigated quantitatively, despite being the most common criticism leveled at the action. We used an ensemble modeling framework to estimate the risks of assisted migration to existing species within ecosystems. With this approach, we calculated the consequences of an assisted migration project across a very large combination of translocated species and recipient ecosystems. We predicted the probability of a successful assisted migration and the number of local extinctions would result from establishment of the translocated species. Using an ensemble of simulated 15-species recipient ecosystems, we estimated that translocated species will successfully establish in 83% of cases if introduced to stable, high-quality habitats. However, assisted migration projects were estimated to cause an average of 0.6 extinctions and 5% of successful translocations triggered 4 or more local extinctions. Quantifying the impacts to species within recipient ecosystems is critical to help managers weigh the benefits and negative consequences of assisted migration.     

Quantification of Extinction Risk: IUCN's System for Classifying Threatened Species

Abstract: The International Union for Conservation of Nature (IUCN) Red List of Threatened Species was increasingly used during the 1980s to assess the conservation status of species for policy and planning purposes. This use stimulated the development of a new set of quantitative criteria for listing species in the categories of threat: critically endangered, endangered, and vulnerable. These criteria, which were intended to be applicable to all species except microorganisms, were part of a broader system for classifying threatened species and were fully implemented by IUCN in 2000. The system and the criteria have been widely used by conservation practitioners and scientists and now underpin one indicator being used to assess the Convention on Biological Diversity 2010 biodiversity target. We describe the process and the technical background to the IUCN Red List system. The criteria refer to fundamental biological processes underlying population decline and extinction. But given major differences between species, the threatening processes affecting them, and the paucity of knowledge relating to most species, the IUCN system had to be both broad and flexible to be applicable to the majority of described species. The system was designed to measure the symptoms of extinction risk, and uses 5 independent criteria relating to aspects of population loss and decline of range size. A species is assigned to a threat category if it meets the quantitative threshold for at least one criterion. The criteria and the accompanying rules and guidelines used by IUCN are intended to increase the consistency, transparency, and validity of its categorization system, but it necessitates some compromises that affect the applicability of the system and the species lists that result. In particular, choices were made over the assessment of uncertainty, poorly known species, depleted species, population decline, restricted ranges, and rarity; all of these affect the way red lists should be viewed and used. Processes related to priority setting and the development of national red lists need to take account of some assumptions in the formulation of the criteria.     

Factors associated with preemptive conservation under the U.S. Endangered Species Act

In recent decades, there has been an increasing emphasis on proactive efforts to conserve species being considered for listing under the U.S. Endangered Species Act (ESA) before they are listed (i.e., preemptive conservation). These efforts, which depend on voluntary actions by public and private land managers across the species’ range, aim to conserve species while avoiding regulatory costs associated with ESA listing. We collected data for a set of social, economic, environmental, and institutional factors that we hypothesized would influence voluntary decisions to promote or inhibit preemptive conservation of species under consideration for ESA listing. We used logistic regression to estimate the association of these factors with preemptive conservation outcomes based on data for a set of species that entered the ESA listing process and were either officially listed (n = 314) or preemptively conserved (n = 73) from 1996 to 2018. Factors significantly associated with precluded listing due to preemptive conservation included high baseline conservation status, low proportion of private land across the species’ range, small total range size, exposure to specific types of threats, and species’ range extending over several states. These results highlight strategies that can help improve conservation outcomes, such as allocating resources for imperiled species earlier in the listing process, addressing specific threats, and expanding incentives and coordination mechanisms for conservation on private lands.     

Structuring Decisions for Managing Threatened and Endangered Species in a Changing Climate

The management of endangered species under climate change is a challenging and often controversial task that incorporates input from a variety of different environmental, economic, social, and political interests. Yet many listing and recovery decisions for endangered species unfold on an ad hoc basis without reference to decision‐aiding approaches that can improve the quality of management choices. Unlike many treatments of this issue, which consider endangered species management a science‐based problem, we suggest that a clear decision‐making process is equally necessary. In the face of new threats due to climate change, managers’ choices about endangered species require closely linked analyses and deliberations that identify key objectives and develop measurable attributes, generate and compare management alternatives, estimate expected consequences and key sources of uncertainty, and clarify trade‐offs across different dimensions of value. Several recent cases of endangered species conservation decisions illustrate our proposed decision‐focused approach, including Gulf of Maine Atlantic salmon (Salmo salar) recovery framework development, Cultus Lake sockeye salmon (Oncorhynchus nerka) management, and Upper Columbia River white sturgeon (Acipenser transmontanus) recovery planning. Estructuración de Decisiones para Manejar Especies Amenazadas y en Peligro en un Clima Cambiante     

A Bayesian-weighted approach to predicting the number of newly discovered rare species

In natural ecological communities, most species are rare and thus susceptible to extinction. Consequently, the prediction and identification of rare species are of enormous value for conservation purposes. How many newly found species will be rare in the next field survey? We took a Bayesian viewpoint and used observed species abundance information in an ecological sample to develop an accurate way to estimate the number of new rare species (e.g., singletons, doubletons, and tripletons) in an additional unknown sample. A similar method has been developed for incidence-based data sets. Five seminumerical tests (3 abundance cases and 2 incidence cases) showed that our proposed Bayesian-weight estimator accurately predicted the number of new rare species with low relative bias and low relative root mean squared error and, accordingly, high accuracy. Finally, we applied the proposed estimator to 6 conservation-directed empirical data sets (3 abundance cases and 3 incidence cases) and found the prediction of new rare species was quite accurate; the 95% CI covered the true observed value very well in most cases. Our estimator performed similarly to or better than an unweighted estimator derived from Chao et al. and performed consistently better than the naïve unweighted estimator. We recommend our Bayesian-weight estimator for conservation applications, although the unweighted estimator of Chao et al. may be better under some circumstances. We provide an R package RSE (r are s pecies e stimation) at https://github.com/ecomol/RSE for implementation of the estimators.     

Evaluating institutional fit for the conservation of threatened species

Recovery and conservation of threatened species require adequate institutional responses. We tested an approach to systematically identify and measure how an institutional framework acknowledges threats and required responses for the recovery of endangered species. We measured institutional functional fit with a drivers-pressure-state-impacts-response (DPSIR) model integrated with a quantitative text mining method and qualitative analysis of statutory instruments to examine regulatory responses that support the recovery of 2 endangered species native to Australia, the bridled nailtail wallaby (Onychogalea fraenata) and the Eastern Bristlebird (Dasyornis brachypterus). The key components of the DPSIR model were present in the institutional framework at statutory and operational levels, but some institutional gaps remained in the protection and recovery of the Eastern Bristlebird, including feral predator control, weed control, and grazing management in some locations. However, regulatory frameworks varied in their geographic scope and the application and implementation of many instruments remained optional. Quantitative text mining can be used to quickly navigate a large volume of regulatory documents, but challenges remain in selection of terms, queries of co-occurrence, and interpretation of word frequency counts. To inform policy, we recommend that quantitative assessments of institutional fit be complemented with qualitative analysis and interpreted in light of the sociopolitical and institutional context.     

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.     

Difference in the net value of ecological services between natural and artificial forests in China

Land degradation is a global problem that seriously threatens human society. However, in China and elsewhere, ecological restoration still largely relies on a traditional approach that focuses only on ecological factors and ignores socioeconomic factors. To improve the effectiveness of ecological restoration and maximize its economic and ecological benefits, a more efficient approach is needed that provides support for policy development and land management and thereby promotes environmental conservation. We devised a framework for assessing the value of ecosystem services that remain after subtracting costs, such as the opportunity costs, costs of forest protection, and costs for the people who are affected by the program; that is, the net value of ecosystem services (NVES). To understand the difference between the value of a resource and the net value of the ecosystem service it provides, we used data on VES, timber sales, and afforestation costs from China's massive national afforestation programs to calculate the net value of forest ecosystem services in China. Accounting for the abovementioned costs revealed an NVES of ¥6.1 × 10¹² for forests in 2014, which was 35.9% less than the value calculated without accounting for costs. As a result, the NVES associated with afforestation was 55.9% less than the NVES of natural forests. In some regions, NVES was negative because of the huge costs of human-made plantations, high evapotranspiration rates (thus, high water opportunity costs), and low forest survival rates. To maximize the ecological benefits of conservation, it is necessary to account for as many costs as possible so that management decisions can be based on NVES, thereby helping managers choose projects that maximize both economic and ecological benefits.