Desert pastoralists’ negative and positive effects on rare wildlife in the Gobi

In arid regions of the developing world, pastoralists and livestock commonly inhabit protected areas, resulting in human–wildlife conflict. Conflict is inextricably linked to the ecological processes shaping relationships between pastoralists and native herbivores and carnivores. To elucidate relationships underpinning human–wildlife conflict, we synthesized 15 years of ecological and ethnographic data from Ikh Nart Nature Reserve in Mongolia's Gobi steppe. The density of argali (Ovis ammon), the world's largest wild sheep, at Ikh Nart was among the highest in Mongolia, yet livestock were >90% of ungulate biomass and dogs >90% of large‐carnivore biomass. For argali, pastoral activities decreased food availability, increased mortality from dog predation, and potentially increased disease risk. Isotope analyses indicated that livestock accounted for >50% of the diet of the majority of gray wolves (Canis lupus) and up to 90% of diet in 25% of sampled wolves (n = 8). Livestock composed at least 96% of ungulate prey in the single wolf pack for which we collected species‐specific prey data. Interviews with pastoralists indicated that wolves annually killed 1–4% of Ikh Nart's livestock, and pastoralists killed wolves in retribution. Pastoralists reduced wolf survival by killing them, but their livestock were an abundant food source for wolves. Consequently, wolf density appeared to be largely decoupled from argali density, and pastoralists had indirect effects on argali that could be negative if pastoralists increased wolf density (apparent competition) or positive if pastoralists decreased wolf predation (apparent facilitation). Ikh Nart's argali population was stable despite these threats, but livestock are increasingly dominant numerically and functionally relative to argali. To support both native wildlife and pastoral livelihoods, we suggest training dogs to not kill argali, community insurance against livestock losses to wolves, reintroducing key native prey species to hotspots of human–wolf conflict, and developing incentives for pastoralists to reduce livestock density.     

Empirical Trials of Plant Field Guides

We designed 3 image‐based field guides to tropical forest plant species in Ghana, Grenada, and Cameroon and tested them with 1095 local residents and 20 botanists in the United Kingdom. We compared users’ identification accuracy with different image formats, including drawings, specimen photos, living plant photos, and paintings. We compared users’ accuracy with the guides to their accuracy with only their prior knowledge of the flora. We asked respondents to score each format for usability, beauty, and how much they would pay for it. Prior knowledge of plant names was generally low (<22%). With a few exceptions, identification accuracy did not differ significantly among image formats. In Cameroon, users identifying sterile Cola species achieved 46–56% accuracy across formats; identification was most accurate with living plant photos. Botanists in the United Kingdom accurately identified 82–93% of the same Cameroonian species; identification was most accurate with specimens. In Grenada, users accurately identified 74–82% of plants; drawings yielded significantly less accurate identifications than paintings and photos of living plants. In Ghana, users accurately identified 85% of plants. Digital color photos of living plants ranked high for beauty, usability, and what users would pay. Black and white drawings ranked low. Our results show the potential and limitations of the use of field guides and nonspecialists to identify plants, for example, in conservation applications. We recommend authors of plant field guides use the cheapest or easiest illustration format because image type had limited bearing on accuracy; match the type of illustration to the most likely use of the guide for slight improvements in accuracy; avoid black and white formats unless the audience is experienced at interpreting illustrations or keeping costs low is imperative; discourage false‐positive identifications, which were common; and encourage users to ask an expert or use a herbarium for groups that are difficult to identify. Pruebas Empíricas de Guías de Campo de Plantas Hawthorne, Cable & Marshall     

Developing an interdisciplinary and cross‐sectoral community of practice in the domain of forests and livelihoods

Although significant resources are being spent researching and fostering the relationship between forests and livelihoods to promote mutually beneficial outcomes, critical gaps in understanding persist. A core reason for such gaps is that researchers, practitioners, and policy makers lack the structured space to interact and collaborate, which is essential for effective, interdisciplinary research, practice, and evaluation. Thus, scientific findings, policy recommendations, and measured outcomes have not always been synthesized into deep, systemic understanding; learning from practice and implementation does not easily find its way into scientific analyses, and science often fails to influence policy. Communities of practice (CofPs) are dynamic sociocultural systems that bring people together to share and create knowledge around a common topic of interest. They offer participants a space and structure within which to develop new, systemic approaches to multidimensional problems on a common theme. Uniquely informed by a systems‐thinking perspective and drawing from the scientific and gray literatures and in‐depth interviews with representatives of established CofPs in the natural resource management and development domain, we argue that a well‐designed and adequately funded CofP can facilitate interdisciplinary and cross‐sectoral relationships and knowledge exchange. Well‐designed CofPs integrate a set of core features and processes to enhance individual, collective, and domain outcomes; they set out an initial but evolving purpose, encourage diverse leadership, and promote collective‐identity development. Funding facilitates effective communication strategies (e.g., in person meetings). We urge our colleagues across sectors and disciplines to take advantage of CofPs to advance the domain of forests and livelihoods.     

Arts as a vehicle for community building and post‐disaster development

Use of the arts in international aid is common in an ad hoc form, but it has not been systematically theorised or evaluated. The arts have the potential to be a culturally contextualised and sustainable intervention for adults and children in the aftermath of war or disaster. On the micro level, the arts are a method to enable the retrieval and reprocessing of traumatic memories that are often encoded in images rather than in words. On a macro level, they can help to reconstruct a group narrative of a disaster as well as mobilise people back into control of their lives. This paper researches a long‐term project using arts in Sri Lanka following the civil war and tsunami. A central finding is the need to understand arts within their cultural context, and their usefulness in strengthening the voices and problem‐solving capacities of the victims of the disaster.     

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     

Implications of different population model structures for management of threatened plants

Population viability analysis (PVA) is a reliable tool for ranking management options for a range of species despite parameter uncertainty. No one has yet investigated whether this holds true for model uncertainty for species with complex life histories and for responses to multiple threats. We tested whether a range of model structures yielded similar rankings of management and threat scenarios for 2 plant species with complex postfire responses. We examined 2 contrasting species from different plant functional types: an obligate seeding shrub and a facultative resprouting shrub. We exposed each to altered fire regimes and an additional, species‐specific threat. Long‐term demographic data sets were used to construct an individual‐based model (IBM), a complex stage‐based model, and a simple matrix model that subsumes all life stages into 2 or 3 stages. Agreement across models was good under some scenarios and poor under others. Results from the simple and complex matrix models were more similar to each other than to the IBM. Results were robust across models when dominant threats are considered but were less so for smaller effects. Robustness also broke down as the scenarios deviated from baseline conditions, likely the result of a number of factors related to the complexity of the species’ life history and how it was represented in a model. Although PVA can be an invaluable tool for integrating data and understanding species’ responses to threats and management strategies, this is best achieved in the context of decision support for adaptive management alongside multiple lines of evidence and expert critique of model construction and output.     

Sustainability and comanagement of subsistence hunting in an indigenous reserve in Guyana

Although hunting is a key component of subsistence strategies of many Amazonians, it is also one of the greatest threats to wildlife. Because indigenous reserves comprise over 20% of Amazonia, effective conservation often requires that conservation professionals work closely with indigenous groups to manage resource use. We used hunter‐generated harvesting data in spatially explicit biodemographic models to assess the sustainability of subsistence hunting of indigenous Waiwai in Guyana. We collected data through a hunter self‐monitoring program, systematic follows of hunters, and semistructured interviews. We used these data to predict future densities of 2 indicator species, spider monkeys (Ateles paniscus) and bearded sakis (Chiropotes sagulatus), under different scenarios of human population expansion and changing hunting technology. We used encounter rates from transect surveys and hunter catch‐per‐unit effort (CPUE) to validate model predictions. Paca (Cuniculus paca) (198 /year), Currosaw (Crax alector) (168), and spider monkey (117) were the most frequently harvested species. Predicted densities of spider monkeys were statistically indistinguishable from empirically derived transect data (Kolmogorov–Smirnov D = 0.67, p = 0.759) and CPUE (D = 0.32, p = 1.000), demonstrating the robustness of model predictions. Ateles paniscus and C. sagulatus were predicted to be extirpated from <13% of the Waiwai reserve in 20 years, even under the most intensive hunting scenarios. Our results suggest Waiwai hunting is currently sustainable, primarily due to their low population density and use of bow and arrow. Continual monitoring is necessary, however, particularly if human population increases are accompanied by a switch to shotgun‐only hunting. We suggest that hunter self‐monitoring and biodemographic modeling can be used effectively in a comanagement approach in which indigenous parabiologists continuously provide hunting data that is then used to update model parameters and validate model predictions.     

The difficulties of systematic reviews

The need for robust evidence to support conservation actions has driven the adoption of systematic approaches to research synthesis in ecology. However, applying systematic review to complex or open questions remains challenging, and this task is becoming more difficult as the quantity of scientific literature increases. We drew on the science of linguistics for guidance as to why the process of identifying and sorting information during systematic review remains so labor intensive, and to provide potential solutions. Several linguistic properties of peer‐reviewed corpora—including nonrandom selection of review topics, small‐world properties of semantic networks, and spatiotemporal variation in word meaning—greatly increase the effort needed to complete the systematic review process. Conversely, the resolution of these semantic complexities is a common motivation for narrative reviews, but this process is rarely enacted with the rigor applied during linguistic analysis. Therefore, linguistics provides a unifying framework for understanding some key challenges of systematic review and highlights 2 useful directions for future research. First, in cases where semantic complexity generates barriers to synthesis, ecologists should consider drawing on existing methods—such as natural language processing or the construction of research thesauri and ontologies—that provide tools for mapping and resolving that complexity. These tools could help individual researchers classify research material in a more robust manner and provide valuable guidance for future researchers on that topic. Second, a linguistic perspective highlights that scientific writing is a rich resource worthy of detailed study, an observation that can sometimes be lost during the search for data during systematic review or meta‐analysis. For example, mapping semantic networks can reveal redundancy and complementarity among scientific concepts, leading to new insights and research questions. Consequently, wider adoption of linguistic approaches may facilitate improved rigor and richness in research synthesis.     

Trait‐based prediction of extinction risk of small‐bodied freshwater fishes

Small body size is generally correlated with r‐selected life‐history traits, including early maturation, short‐generation times, and rapid growth rates, that result in high population turnover and a reduced risk of extinction. Unlike other classes of vertebrates, however, small freshwater fishes appear to have an equal or greater risk of extinction than large fishes. We explored whether particular traits explain the International Union for Conservation of Nature (IUCN) Red List conservation status of small‐bodied freshwater fishes from 4 temperate river basins: Murray‐Darling, Australia; Danube, Europe; Mississippi‐Missouri, North America; and the Rio Grande, North America. Twenty‐three ecological and life‐history traits were collated for all 171 freshwater fishes of ≤120 mm total length. We used generalized linear mixed‐effects models to assess which combination of the 23 traits best explained whether a species was threatened or not threatened. We used the best models to predict the probability of 29 unclassified species being listed as threatened. With and without controlling for phylogeny at the family level, small body size—among small‐bodied species—was the most influential trait correlated with threatened species listings. The k‐folds cross‐validation demonstrated that body size and a random effect structure that included family predicted the threat status with an accuracy of 78% (SE 0.5). We identified 10 species likely to be threatened that are not listed as such on the IUCN Red List. Small body size is not a trait that provides universal resistance to extinction, particularly for vertebrates inhabiting environments affected by extreme habitat loss and fragmentation. We hypothesize that this is because small‐bodied species have smaller home ranges, lower dispersal capabilities, and heightened ecological specialization relative to larger vertebrates. Trait data and further model development are needed to predict the IUCN conservation status of the over 11,000 unclassified freshwater fishes, especially those under threat from proposed dam construction in the world's most biodiverse river basins.     

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.