Consensus on Criteria for Potential Areas for Wolf Reintroduction in Mexico

Abstract: Given the conflict with human interests that in many cases results in the extirpation of large carnivores, acceptance of their reintroduction is a considerable challenge. By the 1980s Mexican wolves (Canis lupus) were extinct in the wild. In 1998 a population was reintroduced in the Blue Range Mountains of New Mexico (U.S.A.). Efforts to reintroduce the species in Mexico have been ongoing since the late 1980s. Four teams working independently identified 6 areas in northern Mexico in the historic range of Mexican wolves, where reintroductions could potentially be successful. Each team used different methods and criteria to identify the areas, which makes it difficult to prioritize among these areas. Therefore, members of the different teams worked together to devise criteria for use in identifying priority areas. They identified areas with high, intermediate, and low potential levels of conflict between wolves and humans. Areas with low potential conflict had larger buffers (i.e., distance from human settlement to areas suitable for wolves) around human settlements than high‐ and intermediate‐conflict areas and thus were thought most appropriate for the first reintroduction. High‐conflict areas contained habitat associated with wolf presence, but were closer to human activity. The first reintroduction of Mexican wolves to Mexico occurred in October 2011 in one of the identified low‐conflict areas. The identification of suitable areas for reintroduction represents a crucial step in the process toward the restoration of large carnivores. Choice of the first reintroduction area can determine whether the reintroduction is successful or fails. A failure may preclude future reintroduction efforts in a region or country.     

Developing Metapopulation Connectivity Criteria from Genetic and Habitat Data to Recover the Endangered Mexican Wolf

Restoring connectivity between fragmented populations is an important tool for alleviating genetic threats to endangered species. Yet recovery plans typically lack quantitative criteria for ensuring such population connectivity. We demonstrate how models that integrate habitat, genetic, and demographic data can be used to develop connectivity criteria for the endangered Mexican wolf (Canis lupus baileyi), which is currently being restored to the wild from a captive population descended from 7 founders. We used population viability analysis that incorporated pedigree data to evaluate the relation between connectivity and persistence for a restored Mexican wolf metapopulation of 3 populations of equal size. Decreasing dispersal rates greatly increased extinction risk for small populations (<150–200), especially as dispersal rates dropped below 0.5 genetically effective migrants per generation. We compared observed migration rates in the Northern Rocky Mountains (NRM) wolf metapopulation to 2 habitat‐based effective distance metrics, least‐cost and resistance distance. We then used effective distance between potential primary core populations in a restored Mexican wolf metapopulation to evaluate potential dispersal rates. Although potential connectivity was lower in the Mexican wolf versus the NRM wolf metapopulation, a connectivity rate of >0.5 genetically effective migrants per generation may be achievable via natural dispersal under current landscape conditions. When sufficient data are available, these methods allow planners to move beyond general aspirational connectivity goals or rules of thumb to develop objective and measurable connectivity criteria that more effectively support species recovery. The shift from simple connectivity rules of thumb to species‐specific analyses parallels the previous shift from general minimum‐viable‐population thresholds to detailed viability modeling in endangered species recovery planning. Desarrollo de Criterios de Conectividad Metapoblacional a Partir de Datos Genéticos y de Hábitat para Recuperar al Lobo Mexicano en Peligro de Extinción     

Hunting Effects on Favourable Conservation Status of Highly Inbred Swedish Wolves

The wolf (Canis lupus) is classified as endangered in Sweden by the Swedish Species Information Centre, which is the official authority for threat classification. The present population, which was founded in the early 1980s, descends from 5 individuals. It is isolated and highly inbred, and on average individuals are more related than siblings. Hunts have been used by Swedish authorities during 2010 and 2011 to reduce the population size to its upper tolerable level of 210 wolves. European Union (EU) biodiversity legislation requires all member states to promote a concept called “favourable conservation status” (FCS) for a series of species including the wolf. Swedish national policy stipulates maintenance of viable populations with sufficient levels of genetic variation of all naturally occurring species. Hunting to reduce wolf numbers in Sweden is currently not in line with national and EU policy agreements and will make genetically based FCS criteria less achievable for this species. We suggest that to reach FCS for the wolf in Sweden the following criteria need to be met: (1) a well‐connected, large, subdivided wolf population over Scandinavia, Finland, and the Russian Karelia‐Kola region should be reestablished, (2) genetically effective size (N_e) of this population is in the minimum range of N_e = 500–1000, (3) Sweden harbors a part of this total population that substantially contributes to the total N_e and that is large enough to not be classified as threatened genetically or according to IUCN criteria, and (4) average inbreeding levels in the Swedish population are <0.1. Efectos de la Cacería sobre el Estatus de Conservación Favorable de Lobos Suecos con Endogamia Alta     

A meta‐analysis of studies on attitudes toward bears and wolves across Europe 1976–2012

The ranges of wolves (Canis lupus) and bears (Ursus arctos) across Europe have expanded recently, and it is important to assess public attitudes toward this expansion because responses toward these species vary widely. General attitudes toward an object are good predictors of broad behavioral patterns; thus, attitudes toward wolves and bears can be used as indicators to assess the social foundation for future conservation efforts. However, most attitude surveys toward bears and wolves are limited in scope, both temporally and spatially, and provide only a snapshot of attitudes. To extend the results of individual surveys over a much larger temporal and geographical range so as to identify transnational patterns and changes in attitudes toward bears and wolves over time, we conducted a meta‐analysis. Our analysis included 105 quantitative surveys conducted in 24 countries from 1976 to 2012. Across Europe, people's attitudes were more positive toward bears than wolves. Attitudes toward bears became more positive over time, but attitudes toward wolves seemed to become less favorable the longer people coexisted with them. Younger and more educated people had more positive attitudes toward wolves and bears than people who had experienced damage from these species, and farmers and hunters had less positive attitudes toward wolves than the general public. For bears attitudes among social groups did not differ. To inform conservation of large carnivores, we recommend that standardized longitudinal surveys be established to monitor changes in attitudes over time relative to carnivore population development. Our results emphasize the need for interdisciplinary research in this field and more advanced explanatory models capable of capturing individual and societal responses to changes in large carnivore policy and management.     

Toward accurate and precise estimates of lion density

Reliable estimates of animal density are fundamental to understanding ecological processes and population dynamics. Furthermore, their accuracy is vital to conservation because wildlife authorities rely on estimates to make decisions. However, it is notoriously difficult to accurately estimate density for wide‐ranging carnivores that occur at low densities. In recent years, significant progress has been made in density estimation of Asian carnivores, but the methods have not been widely adapted to African carnivores, such as lions (Panthera leo). Although abundance indices for lions may produce poor inferences, they continue to be used to estimate density and inform management and policy. We used sighting data from a 3‐month survey and adapted a Bayesian spatially explicit capture‐recapture (SECR) model to estimate spatial lion density in the Maasai Mara National Reserve and surrounding conservancies in Kenya. Our unstructured spatial capture‐recapture sampling design incorporated search effort to explicitly estimate detection probability and density on a fine spatial scale, making our approach robust in the context of varying detection probabilities. Overall posterior mean lion density was estimated to be 17.08 (posterior SD 1.310) lions >1 year old/100 km², and the sex ratio was estimated at 2.2 females to 1 male. Our modeling framework and narrow posterior SD demonstrate that SECR methods can produce statistically rigorous and precise estimates of population parameters, and we argue that they should be favored over less reliable abundance indices. Furthermore, our approach is flexible enough to incorporate different data types, which enables robust population estimates over relatively short survey periods in a variety of systems. Trend analyses are essential to guide conservation decisions but are frequently based on surveys of differing reliability. We therefore call for a unified framework to assess lion numbers in key populations to improve management and policy decisions.     

Site‐Occupancy Distribution Modeling to Correct Population‐Trend Estimates Derived from Opportunistic Observations

Abstract: Species’ assessments must frequently be derived from opportunistic observations made by volunteers (i.e., citizen scientists). Interpretation of the resulting data to estimate population trends is plagued with problems, including teasing apart genuine population trends from variations in observation effort. We devised a way to correct for annual variation in effort when estimating trends in occupancy (species distribution) from faunal or floral databases of opportunistic observations. First, for all surveyed sites, detection histories (i.e., strings of detection–nondetection records) are generated. Within‐season replicate surveys provide information on the detectability of an occupied site. Detectability directly represents observation effort; hence, estimating detectablity means correcting for observation effort. Second, site‐occupancy models are applied directly to the detection‐history data set (i.e., without aggregation by site and year) to estimate detectability and species distribution (occupancy, i.e., the true proportion of sites where a species occurs). Site‐occupancy models also provide unbiased estimators of components of distributional change (i.e., colonization and extinction rates). We illustrate our method with data from a large citizen‐science project in Switzerland in which field ornithologists record opportunistic observations. We analyzed data collected on four species: the widespread Kingfisher (Alcedo atthis) and Sparrowhawk (Accipiter nisus) and the scarce Rock Thrush (Monticola saxatilis) and Wallcreeper (Tichodroma muraria). Our method requires that all observed species are recorded. Detectability was <1 and varied over the years. Simulations suggested some robustness, but we advocate recording complete species lists (checklists), rather than recording individual records of single species. The representation of observation effort with its effect on detectability provides a solution to the problem of differences in effort encountered when extracting trend information from haphazard observations. We expect our method is widely applicable for global biodiversity monitoring and modeling of species distributions.     

Spatially Explicit Power Analyses for Occupancy‐Based Monitoring of Wolverine in the U.S. Rocky Mountains

Conservation scientists and resource managers often have to design monitoring programs for species that are rare or patchily distributed across large landscapes. Such programs are frequently expensive and seldom can be conducted by one entity. It is essential that a prospective power analysis be undertaken to ensure stated monitoring goals are feasible. We developed a spatially based simulation program that accounts for natural history, habitat use, and sampling scheme to investigate the power of monitoring protocols to detect trends in population abundance over time with occupancy‐based methods. We analyzed monitoring schemes with different sampling efforts for wolverine (Gulo gulo) populations in 2 areas of the U.S. Rocky Mountains. The relation between occupancy and abundance was nonlinear and depended on landscape, population size, and movement parameters. With current estimates for population size and detection probability in the northern U.S. Rockies, most sampling schemes were only able to detect large declines in abundance in the simulations (i.e., 50% decline over 10 years). For small populations reestablishing in the Southern Rockies, occupancy‐based methods had enough power to detect population trends only when populations were increasing dramatically (e.g., doubling or tripling in 10 years), regardless of sampling effort. In general, increasing the number of cells sampled or the per‐visit detection probability had a much greater effect on power than the number of visits conducted during a survey. Although our results are specific to wolverines, this approach could easily be adapted to other territorial species. Poder de Análisis Espacialmente Explícito para el Monitoreo Basado en Ocupación del Glotón (Gulo gulo) en las Montañas Rocallosas de Estados Unidos     

Setting population targets for mammals using body mass as a predictor of population persistence

Conservation planning and biodiversity assessments need quantitative targets to optimize planning options and assess the adequacy of current species protection. However, targets aiming at persistence require population‐specific data, which limit their use in favor of fixed and nonspecific targets, likely leading to unequal distribution of conservation efforts among species. We devised a method to derive equitable population targets; that is, quantitative targets of population size that ensure equal probabilities of persistence across a set of species and that can be easily inferred from species‐specific traits. In our method, we used models of population dynamics across a range of life‐history traits related to species’ body mass to estimate minimum viable population targets. We applied our method to a range of body masses of mammals, from 2 g to 3825 kg. The minimum viable population targets decreased asymptotically with increasing body mass and were on the same order of magnitude as minimum viable population estimates from species‐ and context‐specific studies. Our approach provides a compromise between pragmatic, nonspecific population targets and detailed context‐specific estimates of population viability for which only limited data are available. It enables a first estimation of species‐specific population targets based on a readily available trait and thus allows setting equitable targets for population persistence in large‐scale and multispecies conservation assessments and planning.     

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.     

A Contemporary Assessment of Change in Humid Tropical Forests

Abstract: In recent decades the rate and geographic extent of land‐use and land‐cover change has increased throughout the world's humid tropical forests. The pan‐tropical geography of forest change is a challenge to assess, and improved estimates of the human footprint in the tropics are critical to understanding potential changes in biodiversity. We combined recently published and new satellite observations, along with images from Google Earth and a literature review, to estimate the contemporary global extent of deforestation, selective logging, and secondary regrowth in humid tropical forests. Roughly 1.4% of the biome was deforested between 2000 and 2005. As of 2005, about half of the humid tropical forest biome contained 50% or less tree cover. Although not directly comparable to deforestation, geographic estimates of selective logging indicate that at least 20% of the humid tropical forest biome was undergoing some level of timber harvesting between 2000 and 2005. Forest recovery estimates are even less certain, but a compilation of available reports suggests that at least 1.2% of the humid tropical forest biome was in some stage of long‐term secondary regrowth in 2000. Nearly 70% of the regrowth reports indicate forest regeneration in hilly, upland, and mountainous environments considered marginal for large‐scale agriculture and ranching. Our estimates of the human footprint are conservative because they do not resolve very small‐scale deforestation, low‐intensity logging, and unreported secondary regrowth, nor do they incorporate other impacts on tropical forest ecosystems, such as fire and hunting. Our results highlight the enormous geographic extent of forest change throughout the humid tropics and the considerable limitations of the science and technology available for such a synthesis.     

Drivers of Seabird Population Recovery on New Zealand Islands after Predator Eradication

Eradication of introduced mammalian predators from islands has become increasingly common, with over 800 successful projects around the world. Historically, introduced predators extirpated or reduced the size of many seabird populations, changing the dynamics of entire island ecosystems. Although the primary outcome of many eradication projects is the restoration of affected seabird populations, natural population responses are rarely documented and mechanisms are poorly understood. We used a generic model of seabird colony growth to identify key predictor variables relevant to recovery or recolonization. We used generalized linear mixed models to test the importance of these variables in driving seabird population responses after predator eradication on islands around New Zealand. The most influential variable affecting recolonization of seabirds around New Zealand was the distance to a source population, with few cases of recolonization without a source population ≤25 km away. Colony growth was most affected by metapopulation status; there was little colony growth in species with a declining status. These characteristics may facilitate the prioritization of newly predator‐free islands for active management. Although we found some evidence documenting natural recovery, generally this topic was understudied. Our results suggest that in order to guide management strategies, more effort should be allocated to monitoring wildlife response after eradication. Conductores de la Recuperación de Poblaciones de Aves Marinas en Islas de Nueva Zelanda después de la Erradicación de Depredadores     

Economics of Grassland Conversion to Cropland in the Prairie Pothole Region

Abstract: Much of the remaining grassland, particularly in North America, is privately owned, and its conversion to cultivated cropland is largely driven by economics. An understanding of why landowners convert grassland to cropland could facilitate more effective design of grassland‐conservation programs. We built an empirical model of land‐use change in the Prairie Pothole Region (north‐central United States) to estimate the probability of grassland conversion to alternative agricultural land uses, including cultivated crops. Conversion was largely driven by landscape characteristics and the economic returns of alternative uses. Our estimate of the probability of grassland conversion to cultivated crops (1.33% on average from 1979 to 1997) was higher than past estimates (0.4%). Our model also predicted that grassland‐conversion probabilities will increase if agricultural commodity prices continue to follow the trends observed from 2001 to 2006 (0.93% probability of grassland conversion to cultivated crops in 2006 to 1.5% in 2011). Thus, nearly 121 million ha (30 million acres) of grassland could be converted by 2011. Conversion probabilities, however, are spatially heterogeneous (range 0.2% to 3%), depending on characteristics of a parcel (e.g., soil quality and economic returns). Grassland parcels with relatively high‐quality land for agricultural production are more likely to be converted to cultivated crops than lower‐quality parcels and are more responsive to changes in the economic returns on alternative agricultural land uses (i.e., conversion probability increases by a larger magnitude for high‐quality parcels when economics returns to alternative uses increase). Our results suggest that grassland conservation programs could be proactively targeted toward high‐risk parcels by anticipating changes in economic returns, such as could occur if a new biofuel processing plant were to be built in an area.     

Geography and Recovery under the U.S. Endangered Species Act

Abstract: The U.S. Endangered Species Act (ESA) defines an endangered species as one “at risk of extinction throughout all or a significant portion of its range.” The prevailing interpretation of this phrase, which focuses exclusively on the overall viability of listed species without regard to their geographic distribution, has led to development of listing and recovery criteria with fundamental conceptual, legal, and practical shortcomings. The ESA's concept of endangerment is broader than the biological concept of extinction risk in that the “esthetic, ecological, educational, historical, recreational, and scientific” values provided by species are not necessarily furthered by a species mere existence, but rather by a species presence across much of its former range. The concept of “significant portion of range” thus implies an additional geographic component to recovery that may enhance viability, but also offers independent benefits that Congress intended the act to achieve. Although the ESA differs from other major endangered‐species protection laws because it acknowledges the distinct contribution of geography to recovery, it resembles the “representation, resiliency, and redundancy” conservation‐planning framework commonly referenced in recovery plans. To address representation, listing and recovery standards should consider not only what proportion of its former range a species inhabits, but the types of habitats a species occupies and the ecological role it plays there. Recovery planning for formerly widely distributed species (e.g., the gray wolf [Canis lupus]) exemplifies how the geographic component implicit in the ESA's definition of endangerment should be considered in determining recovery goals through identification of ecologically significant types or niche variation within the extent of listed species, subspecies, or “distinct population segments.” By linking listing and recovery standards to niche and ecosystem concepts, the concept of ecologically significant type offers a scientific framework that promotes more coherent dialogue concerning the societal decisions surrounding recovery of endangered species.     

Multiscale Factors Affecting Human Attitudes toward Snow Leopards and Wolves

The threat posed by large carnivores to livestock and humans makes peaceful coexistence between them difficult. Effective implementation of conservation laws and policies depends on the attitudes of local residents toward the target species. There are many known correlates of human attitudes toward carnivores, but they have only been assessed at the scale of the individual. Because human societies are organized hierarchically, attitudes are presumably influenced by different factors at different scales of social organization, but this scale dependence has not been examined. We used structured interview surveys to quantitatively assess the attitudes of a Buddhist pastoral community toward snow leopards (Panthera uncia) and wolves (Canis lupus). We interviewed 381 individuals from 24 villages within 6 study sites across the high‐elevation Spiti Valley in the Indian Trans‐Himalaya. We gathered information on key explanatory variables that together captured variation in individual and village‐level socioeconomic factors. We used hierarchical linear models to examine how the effect of these factors on human attitudes changed with the scale of analysis from the individual to the community. Factors significant at the individual level were gender, education, and age of the respondent (for wolves and snow leopards), number of income sources in the family (wolves), agricultural production, and large‐bodied livestock holdings (snow leopards). At the community level, the significant factors included the number of smaller‐bodied herded livestock killed by wolves and mean agricultural production (wolves) and village size and large livestock holdings (snow leopards). Our results show that scaling up from the individual to higher levels of social organization can highlight important factors that influence attitudes of people toward wildlife and toward formal conservation efforts in general. Such scale‐specific information can help managers apply conservation measures at appropriate scales. Our results reiterate the need for conflict management programs to be multipronged. Factores Multi‐Escala que Afectan las Actitudes Humanas hacia Leopardos de las Nieves y Lobos     

Moral dimensions of human–wildlife conflict

Despite increasing support for conservation globally, controversy over specific conservation policies persists among diverse stakeholders. Investigating the links between morals in relation to conservation can help increase understanding about why humans support or oppose policy, especially related to human–wildlife conflict or human conflict over wildlife. Yet the moral dimension of human–wildlife conflict has mostly gone unconsidered and unmeasured; thus, policy and programmatic efforts to reduce controversy may be missing a key part of the equation. We conducted a web‐based survey (n = 1239 respondents) in Michigan (U.S.A.) to investigate cognitive and emotional influences on the value–behavior relationship. Respondents were identified by their interest and involvement in Michigan wolf management. The survey consisted of questions about values, emotions, cognitions, and behaviors relative to wolves in Michigan. We used path analysis to explore whether emotions and cognitions mediated the relationship between value and behavior. Most respondents attributed intrinsic value to wolves (n = 734) and all life (n = 773) and engaged in behaviors that benefited wolf populations and ecosystems regardless of stakeholder group (e.g., environmentalist, farmer). Attributing intrinsic value to wolves was positively related to favorable emotions toward wolves and cognitive assessments that hunting and trapping of wolves is unacceptable. Despite similarities in attribution of intrinsic value, groups differed in emotions and cognitions about wolf hunting. These differences provide a useful way to predict stakeholder behavior. Our findings may inform interventions aimed at increasing support for wolf management policies and positive interactions among stakeholders and wildlife. Leveraging agreement over intrinsic value may foster cooperation among stakeholders and garner support for controversial conservation policy.     

Quantifying population declines based on presence‐only records for red‐list assessments

Accurate trend estimates are necessary for understanding which species are declining and which are most in need of conservation action. Imperfect species detection may result in unreliable trend estimates because this may lead to the overestimation of declines. Because many management decisions are based on population trend estimates, such biases could have severe consequences for conservation policy. We used an occupancy‐modeling framework to estimate detectability and calculate nationwide population trends for 14 Swiss amphibian species both accounting for and ignoring imperfect detection. Through the application of International Union for Conservation of Nature Red List criteria to the different trend estimates, we assessed whether ignoring imperfect detection could affect conservation policy. Imperfect detection occurred for all species and detection varied substantially among species, which led to the overestimation of population declines when detectability was ignored. Consequently, accounting for imperfect detection lowered the red‐list risk category for 5 of the 14 species assessed. We demonstrate that failing to consider species detectability can have serious consequences for species management and that occupancy modeling provides a flexible framework to account for observation bias and improve assessments of conservation status. A problem inherent to most historical records is that they contain presence‐only data from which only relative declines can be estimated. A move toward the routine recording of nonobservation and absence data is essential if conservation practitioners are to move beyond this toward accurate population trend estimation.     

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     

Longitudinal Analysis of Attitudes Toward Wolves

Understanding individual attitudes and how these predict overt opposition to predator conservation or direct, covert action against predators will help to recover and maintain them. Studies of attitudes toward wild animals rely primarily on samples of individuals at a single time point. We examined longitudinal change in individuals’ attitudes toward gray wolves (Canis lupus). In the contiguous United States, amidst persistent controversy and opposition, abundances of gray wolves are at their highest in 60 years. We used mailed surveys to sample 1892 residents of Wisconsin in 2001 or 2004 and then resampled 656 of these individuals who resided in wolf range in 2009. Our study spanned a period of policy shifts and increasing wolf abundance. Over time, the 656 respondents increased agreement with statements reflecting fear of wolves, the belief that wolves compete with hunters for deer (Odocoileus virginianus), and inclination to poach a wolf. Endorsement of lethal control of wolves by the state and public hunting of wolves also increased. Neither the time span over which respondents reported exposure to wolves locally nor self‐reported losses of domestic animals to wolves correlated with changes in attitude. We predict future increases in legal and illegal killing of wolves that may reduce their abundance in Wisconsin unless interventions are implemented to improve attitudes and behavior toward wolves. To assess whether interventions change attitudes, longitudinal studies like ours are needed. Análisis Longitudinal de las Actitudes Hacia Lobos     

Minimizing species extinctions through strategic planning for conservation fencing

Conservation fences are an increasingly common management action, particularly for species threatened by invasive predators. However, unlike many conservation actions, fence networks are expanding in an unsystematic manner, generally as a reaction to local funding opportunities or threats. We conducted a gap analysis of Australia's large predator‐exclusion fence network by examining translocation of Australian mammals relative to their extinction risk. To address gaps identified in species representation, we devised a systematic prioritization method for expanding the conservation fence network that explicitly incorporated population viability analysis and minimized expected species’ extinctions. The approach was applied to New South Wales, Australia, where the state government intends to expand the existing conservation fence network. Existing protection of species in fenced areas was highly uneven; 67% of predator‐sensitive species were unrepresented in the fence network. Our systematic prioritization yielded substantial efficiencies in that it reduced expected number of species extinctions up to 17 times more effectively than ad hoc approaches. The outcome illustrates the importance of governance in coordinating management action when multiple projects have similar objectives and rely on systematic methods rather than expanding networks opportunistically.     

Estimating Sonoran pronghorn abundance and survival with fecal DNA and capture–recapture methods

Population abundance estimates are important for management but can be challenging to determine in low‐density, wide‐ranging, and endangered species, such as Sonoran pronghorn (Antilocapra americana sonoriensis). The Sonoran pronghorn population has been increasing; however, population estimates are currently derived from a biennial aerial count that does not provide survival or recruitment estimates. We identified individuals through noninvasively collected fecal DNA and used robust‐design capture–recapture to estimate abundance and survival for Sonoran pronghorn in the United States from 2013 to 2014. In 2014 we generated separate population estimates for pronghorn gathered near 13 different artificial water holes and for pronghorn not near water holes. The population using artificial water holes had 116 (95% CI 102–131) and 121 individuals (95% CI 112–132) in 2013 and 2014, respectively. For all locations, we estimated there were 144 individuals (95% CI 132–157). Adults had higher annual survival probabilities (0.83, 95% CI 0.69–0.92) than fawns (0.41, 95% CI 0.21–0.65). Our use of targeted noninvasive genetic sampling and capture–recapture with Sonoran pronghorn fecal DNA was an effective method for monitoring a large proportion of the population. Our results provided the first survival estimates for this population in over 2 decades and precise estimates of the population using artificial water holes. Our method could be used for targeted sampling of broadly distributed species in other systems, such as in African savanna ecosystems, where many species congregate at watering sites.