Biogeographical and Taxonomic Biases in Tropical Forest Fragmentation Research

Despite several decades of research on the effects of fragmentation and habitat change on biodiversity, there remain strong biases in the geographical regions and taxonomic species studied. The knowledge gaps resulting from these biases are of particular concern if the forests most threatened with modification are also those for which the effects of such change are most poorly understood. To quantify the nature and magnitude of such biases, we conducted a systematic review of the published literature on forest fragmentation in the tropics for the period 1980–2012. Studies included focused on any type of response of single species, communities, or assemblages of any taxonomic group to tropical forest fragmentation and on fragmentation‐related changes to forests. Of the 853 studies we found in the SCOPUS database, 64% were conducted in the Neotropics, 13% in Asia, 10% in the Afrotropics, and 5% in Australasia. Thus, although the Afrotropics is subject to the highest rates of deforestation globally, it was the most disproportionately poorly studied biome. Significant taxonomic biases were identified. Of the taxonomic groups considered, herpetofauna was the least studied in the tropics, particularly in Africa. Research examining patterns of species distribution was by far the most common type (72%), and work focused on ecological processes (28%) was rare in all biomes, but particularly in the Afrotropics and for fauna. We suggest research efforts be directed toward less‐studied biogeographic regions, particularly where the threat of forest fragmentation continues to be high. Increased research investment in the Afrotropics will be important to build knowledge of threats and inform responses in a region where almost no efforts to restore its fragmented landscapes have yet begun and forest protection is arguably most tenuous. Sesgos Biogeográficos y Taxonómicos en la Investigación de la Fragmentación de Bosques Tropicales     

Effects of publication bias on conservation planning

Conservation planners need reliable information on spatial patterns of biodiversity. However, existing data sets are skewed because some ecosystems, taxa, and locations are underrepresented. We determined how many articles have been published in recent decades on the biodiversity of different countries and their constituent provinces. We searched the Web of Science catalogues Science Citation Index (SCI) and Social Science Citation Index (SSCI) for biodiversity-related articles published from 1993 to 2016 that included country and province names. We combined data on research publication frequency with other provincial-scale factors hypothesized to affect the likelihood of research activity (i.e., economic development, human presence, infrastructure, and remoteness). Areas that appeared understudied relative to the biodiversity expected based on site climate likely have been inaccessible to researchers for reasons, notably armed conflict. Geographic publication bias is of most concern in the most remote areas of sub-Saharan Africa and South America. Our provincial-scale model may help compensate for publication biases in conservation planning by revealing the spatial extent of research needs and the low cost of redoing this analysis annually.     

Effects of Road Networks on Bird Populations

Abstract: One potential contributor to the worldwide decline of bird populations is the increasing prevalence of roads, which have several negative effects on birds and other vertebrates. We synthesized the results of studies and reviews that explore the effects of roads on birds with an emphasis on paved roads. The well‐known direct effects of roads on birds include habitat loss and fragmentation, vehicle‐caused mortality, pollution, and poisoning. Nevertheless, indirect effects may exert a greater influence on bird populations. These effects include noise, artificial light, barriers to movement, and edges associated with roads. Moreover, indirect and direct effects may act synergistically to cause decreases in population density and species richness. Of the many effects of roads, it appears that road mortality and traffic noise may have the most substantial effects on birds relative to other effects and taxonomic groups. Potential measures for mitigating the detrimental effects of roads include noise‐reduction strategies and changes to roadway lighting and vegetation and traffic flow. Road networks and traffic volumes are projected to increase in many countries around the world. Increasing habitat loss and fragmentation and predicted species distribution shifts due to climate change are likely to compound the overall effects of roads on birds.     

Meta-analysis of the differential effects of habitat fragmentation and degradation on plant genetic diversity

Genetic diversity is a key factor for population survival and evolution. However, anthropogenic habitat disturbance can erode it, making populations more prone to extinction. Aiming to assess the global effects of habitat disturbance on plant genetic variation, we conducted a meta-analysis based on 92 case studies obtained from published literature. We compared the effects of habitat fragmentation and degradation on plant allelic richness and gene diversity (equivalent to expected heterozygosity) and tested whether such changes are sensitive to different life-forms, life spans, mating systems, and commonness. Anthropogenic disturbance had a negative effect on allelic richness, but not on gene diversity. Habitat fragmentation had a negative effect on genetic variation, whereas habitat degradation had no effect. When we examined the individual effects in fragmented habitats, allelic richness and gene diversity decreased, but this decrease was strongly dependent on certain plant traits. Specifically, common long-lived trees and self-incompatible species were more susceptible to allelic richness loss. Conversely, gene diversity decreased in common short-lived species (herbs) with self-compatible reproduction. In a wider geographical context, tropical plant communities were more sensitive to allelic richness loss, whereas temperate plant communities were more sensitive to gene diversity loss. Our synthesis showed complex responses to habitat disturbance among plant species. In many cases, the absence of effects could be the result of the time elapsed since the disturbance event or reproductive systems favoring self-pollination, but attention must be paid to those plant species that are more susceptible to losing genetic diversity, and appropriate conservation should be actions taken.     

Shifting elasmobranch community assemblage at Cocos Island—an isolated marine protected area

Fishing pressure has increased the extinction risk of many elasmobranch (shark and ray) species. Although many countries have established no‐take marine reserves, a paucity of monitoring data means it is still unclear if reserves are effectively protecting these species. We examined data collected by a small group of divers over the past 21 years at one of the world's oldest marine protected areas (MPAs), Cocos Island National Park, Costa Rica. We used mixed effects models to determine trends in relative abundance, or probability of occurrence, of 12 monitored elasmobranch species while accounting for variation among observers and from abiotic factors. Eight of 12 species declined significantly over the past 2 decades. We documented decreases in relative abundance for 6 species, including the iconic scalloped hammerhead shark (Sphyrna lewini) (?45%), whitetip reef shark (Triaenodon obesus) (?77%), mobula ray (Mobula spp.) (?78%), and manta ray (Manta birostris) (?89%), and decreases in the probability of occurrence for 2 other species. Several of these species have small home ranges and should be better protected by an MPA, which underscores the notion that declines of marine megafauna will continue unabated in MPAs unless there is adequate enforcement effort to control fishing. In addition, probability of occurrence at Cocos Island of tiger (Galeocerdo cuvier), Galapagos (Carcharhinus galapagensis), blacktip (Carcharhinus limbatus), and whale (Rhincodon typus) sharks increased significantly. The effectiveness of MPAs cannot be evaluated by examining single species because population responses can vary depending on life history traits and vulnerability to fishing pressure.     

Research priorities for conservation and natural resource management in Oceania's small‐island developing states

For conservation science to effectively inform management, research must focus on creating the scientific knowledge required to solve conservation problems. We identified research questions that, if answered, would increase the effectiveness of conservation and natural resource management practice and policy in Oceania's small‐island developing states. We asked conservation professionals from academia, governmental, and nongovernmental organizations across the region to propose such questions and then identify which were of high priority in an online survey. We compared the high‐priority questions with research questions identified globally and for other regions. Of 270 questions proposed by respondents, 38 were considered high priority, including: What are the highest priority areas for conservation in the face of increasing resource demand and climate change? How should marine protected areas be networked to account for connectivity and climate change? What are the most effective fisheries management policies that contribute to sustainable coral reef fisheries? High‐priority questions related to the particular challenges of undertaking conservation on small‐island developing states and the need for a research agenda that is responsive to the sociocultural context of Oceania. Research priorities for Oceania relative to elsewhere were broadly similar but differed in specific issues relevant to particular conservation contexts. These differences emphasize the importance of involving local practitioners in the identification of research priorities. Priorities were reasonably well aligned among sectoral groups. Only a few questions were widely considered answered, which may indicate a smaller‐than‐expected knowledge‐action gap. We believe these questions can be used to strengthen research collaborations between scientists and practitioners working to further conservation and natural resource management in this region.     

Identifying key needs for the integration of social–ecological outcomes in arctic wildlife monitoring

For effective monitoring in social–ecological systems to meet needs for biodiversity, science, and humans, desired outcomes must be clearly defined and routes from direct to derived outcomes understood. The Arctic is undergoing rapid climatic, ecological, social, and economic changes and requires effective wildlife monitoring to meet diverse stakeholder needs. To identify stakeholder priorities concerning desired outcomes of arctic wildlife monitoring, we conducted in-depth interviews with 29 arctic scientists, policy and decision makers, and representatives of indigenous organizations and nongovernmental organizations. Using qualitative content analysis, we identified and defined desired outcomes and documented links between outcomes. Using network analysis, we investigated the structure of perceived links between desired outcomes. We identified 18 desired outcomes from monitoring and classified them as either driven by monitoring information, monitoring process, or a combination of both. Highly cited outcomes were make decisions, conserve, detect change, disseminate, and secure food. These reflect key foci of arctic monitoring. Infrequently cited outcomes (e.g., govern) were emerging themes. Three modules comprised our outcome network. The modularity highlighted the low strength of perceived links between outcomes that were primarily information driven or more derived (e.g., detect change, make decisions, conserve, or secure food) and outcomes that were primarily process driven or more derived (e.g., cooperate, learn, educate). The outcomes expand monitoring community and disseminate created connections between these modules. Key desired outcomes are widely applicable to social–ecological systems within and outside the Arctic, particularly those with wildlife subsistence economies. Attributes and motivations associated with outcomes can guide development of integrated monitoring goals for biodiversity conservation and human needs. Our results demonstrated the disconnect between information- and process-driven goals and how expansion of the monitoring community and improved integration of monitoring stakeholders will help connect information- and process-derived outcomes for effective ecosystem stewardship.     

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.     

A spatial approach to combatting wildlife crime

Poaching can have devastating impacts on animal and plant numbers, and in many countries has reached crisis levels, with illegal hunters employing increasingly sophisticated techniques. We used data from an 8‐year study in Savé Valley Conservancy, Zimbabwe, to show how geographic profiling—a mathematical technique originally developed in criminology and recently applied to animal foraging and epidemiology—can be adapted for use in investigations of wildlife crime. The data set contained information on over 10,000 incidents of illegal hunting and the deaths of 6,454 wild animals. We used a subset of data for which the illegal hunters’ identities were known. Our model identified the illegal hunters’ home villages based on the spatial locations of the hunting incidences (e.g., snares). Identification of the villages was improved by manipulating the probability surface inside the conservancy to reflect the fact that although the illegal hunters mostly live outside the conservancy, the majority of hunting occurs inside the conservancy (in criminology terms, commuter crime). These results combined with rigorous simulations showed for the first time how geographic profiling can be combined with GIS data and applied to situations with more complex spatial patterns, for example, where landscape heterogeneity means some parts of the study area are less likely to be used (e.g., aquatic areas for terrestrial animals) or where landscape permeability differs (e.g., forest bats tend not to fly over open areas). More broadly, these results show how geographic profiling can be used to target antipoaching interventions more effectively and more efficiently and to develop management strategies and conservation plans in a range of conservation scenarios.     

Using global sensitivity analysis of demographic models for ecological impact assessment

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