Identifying opportunities for expert-mediated triangulation in monitoring wildlife trade on social media

Wildlife trade has rapidly expanded on social media platforms in recent years, offering an easy means for traders to access international markets. Investigating this trade activity poses a complex challenge to researchers seeking to understand online trade and moderators seeking to disrupt illicit and harmful activity. Current survey methods frequently rely on text-based searches and focus on posts in which the advertisement is explicit. However, such approaches risk overlooking a growing volume of relevant content, particularly outside social media groups. We used posts from pages promoting West African birds for trade as a case study to explore the availability of information for making inferences about trade activity on social media, specifically information indicating that trade activity was occurring or that could be used to infer trade routes. We recorded 400 posts from 12 pages that we inferred either promoted or facilitated wildlife trade, of which 19.7% were explicit advertisements and 23.8% contained taxa-related terms. In the remaining 341 posts, profile information was the most common indicator of trade activity, but a variety of indicators (e.g., images of birds in trade and trade enquiries) were identified across imagery, text, and comments. We identified multiple types of geographical information that could help infer trade routes and thus the likely legality of trade, although most were relatively rare and sometimes contradictory. Our findings suggest that triangulating multiple types of information from within, across, and beyond posts is vital for effectively identifying and interpreting wildlife trade content on social media. Therefore, were commend that expert-mediated triangulation should be integrated in and used alongside automated detection systems and moderating practices of social media companies.     

Estimating the extent and structure of trade in horticultural orchids via social media

The wildlife trade is a lucrative industry involving thousands of animal and plant species. The increasing use of the internet for both legal and illegal wildlife trade is well documented, but there is evidence that trade may be emerging on new online technologies such as social media. Using the orchid trade as a case study, we conducted the first systematic survey of wildlife trade on an international social‐media website. We focused on themed forums (groups), where people with similar interests can interact by uploading images or text (posts) that are visible to other group members. We used social‐network analysis to examine the ties between 150 of these orchid‐themed groups to determine the structure of the network. We found 4 communities of closely linked groups based around shared language. Most trade occurred in a community that consisted of English‐speaking and Southeast Asian groups. In addition to the network analysis, we randomly sampled 30 groups from the whole network to assess the prevalence of trade in cultivated and wild plants. Of 55,805 posts recorded over 12 weeks, 8.9% contained plants for sale, and 22–46% of these posts pertained to wild‐collected orchids. Although total numbers of posts about trade were relatively small, the large proportion of posts advertising wild orchids for sale supports calls for better monitoring of social media for trade in wild‐collected plants.     

Mechanistic understanding of human–wildlife conflict through a novel application of dynamic occupancy models

Crop and livestock depredation by wildlife is a primary driver of human–wildlife conflict, a problem that threatens the coexistence of people and wildlife globally. Understanding mechanisms that underlie depredation patterns holds the key to mitigating conflicts across time and space. However, most studies do not consider imperfect detection and reporting of conflicts, which may lead to incorrect inference regarding its spatiotemporal drivers. We applied dynamic occupancy models to elephant crop depredation data from India between 2005 and 2011 to estimate crop depredation occurrence and model its underlying dynamics as a function of spatiotemporal covariates while accounting for imperfect detection of conflicts. The probability of detecting conflicts was consistently <1.0 and was negatively influenced by distance to roads and elevation gradient, averaging 0.08–0.56 across primary periods (distinct agricultural seasons within each year). The probability of crop depredation occurrence ranged from 0.29 (SE 0.09) to 0.96 (SE 0.04). The probability that sites raided by elephants in primary period t would not be raided in primary period t + 1 varied with elevation gradient in different seasons and was influenced negatively by mean rainfall and village density and positively by distance to forests. Negative effects of rainfall variation and distance to forests best explained variation in the probability that sites not raided by elephants in primary period t would be raided in primary period t + 1. With our novel application of occupancy models, we teased apart the spatiotemporal drivers of conflicts from factors that influence how they are observed, thereby allowing more reliable inference on mechanisms underlying observed conflict patterns. We found that factors associated with increased crop accessibility and availability (e.g., distance to forests and rainfall patterns) were key drivers of elephant crop depredation dynamics. Such an understanding is essential for rigorous prediction of future conflicts, a critical requirement for effective conflict management in the context of increasing human–wildlife interactions.     

Tracing the geographic origin of traded leopard body parts in the indian subcontinent with DNA‐based assignment tests

Illicit trade in wildlife products is rapidly decimating many species across the globe. Such trade is often underestimated for wide‐ranging species until it is too late for the survival of their remaining populations. Policing this trade could be vastly improved if one could reliably determine geographic origins of illegal wildlife products and identify areas where greater enforcement is needed. Using DNA‐based assignment tests (i.e., samples are assigned to geographic locations), we addressed these factors for leopards (Panthera pardus) on the Indian subcontinent. We created geography‐specific allele frequencies from a genetic reference database of 173 leopards across India to infer geographic origins of DNA samples from 40 seized leopard skins. Sensitivity analyses of samples of known geographic origins and assignments of seized skins demonstrated robust assignments for Indian leopards. We found that confiscated pelts seized in small numbers were not necessarily from local leopards. The geographic footprint of large seizures appeared to be bigger than the cumulative footprint of several smaller seizures, indicating widespread leopard poaching across the subcontinent. Our seized samples had male‐biased sex ratios, especially the large seizures. From multiple seized sample assignments, we identified central India as a poaching hotspot for leopards. The techniques we applied can be used to identify origins of seized illegal wildlife products and trade routes at the subcontinent scale and beyond.     

Multimethod,multistate Bayesian hierarchical modeling approach for use in regional monitoring of wolves

In many cases, the first step in large‐carnivore management is to obtain objective, reliable, and cost‐effective estimates of population parameters through procedures that are reproducible over time. However, monitoring predators over large areas is difficult, and the data have a high level of uncertainty. We devised a practical multimethod and multistate modeling approach based on Bayesian hierarchical‐site‐occupancy models that combined multiple survey methods to estimate different population states for use in monitoring large predators at a regional scale. We used wolves (Canis lupus) as our model species and generated reliable estimates of the number of sites with wolf reproduction (presence of pups). We used 2 wolf data sets from Spain (Western Galicia in 2013 and Asturias in 2004) to test the approach. Based on howling surveys, the naïve estimation (i.e., estimate based only on observations) of the number of sites with reproduction was 9 and 25 sites in Western Galicia and Asturias, respectively. Our model showed 33.4 (SD 9.6) and 34.4 (3.9) sites with wolf reproduction, respectively. The number of occupied sites with wolf reproduction was 0.67 (SD 0.19) and 0.76 (0.11), respectively. This approach can be used to design more cost‐effective monitoring programs (i.e., to define the sampling effort needed per site). Our approach should inspire well‐coordinated surveys across multiple administrative borders and populations and lead to improved decision making for management of large carnivores on a landscape level. The use of this Bayesian framework provides a simple way to visualize the degree of uncertainty around population‐parameter estimates and thus provides managers and stakeholders an intuitive approach to interpreting monitoring results. Our approach can be widely applied to large spatial scales in wildlife monitoring where detection probabilities differ between population states and where several methods are being used to estimate different population parameters.     

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.     

Predicting the Spatial Distribution of a Seabird Community to Identify Priority Conservation Areas in the Timor Sea

Understanding spatial and temporal variability in the distribution of species is fundamental to the conservation of marine and terrestrial ecosystems. To support strategic decision making aimed at sustainable management of the oceans, such as the establishment of protected areas for marine wildlife, we identified areas predicted to support multispecies seabird aggregations in the Timor Sea. We developed species distribution models for 21 seabird species based on at‐sea survey observations from 2000–2013 and oceanographic variables (e.g., bathymetry). We applied 4 statistical modeling techniques and combined the results into an ensemble model with robust performance. The ensemble model predicted the probability of seabird occurrence in areas where few or no surveys had been conducted and demonstrated 3 areas of high seabird richness that varied little between seasons. These were located within 150 km of Adele Island, Ashmore Reef, and the Lacepede Islands, 3 of the largest aggregations of breeding seabirds in Australia. Although these breeding islands were foci for high species richness, model performance was greatest for 3 nonbreeding migratory species that would have been overlooked had regional monitoring been restricted to islands. Our results indicate many seabird hotspots in the Timor Sea occur outside existing reserves (e.g., Ashmore Reef Marine Reserve), where shipping, fisheries, and offshore development likely pose a threat to resident and migratory populations. Our results highlight the need to expand marine spatial planning efforts to ensure biodiversity assets are appropriately represented in marine reserves. Correspondingly, our results support the designation of at least 4 new important bird areas, for example, surrounding Adele Island and Ashmore Reef. Pronostico de la Distribución Espacial de una Comunidad de Aves Marinas para Identificar Áreas Prioritarias de Conservación en el Mar de Timor     

Amphibian Commerce as a Likely Source of Pathogen Pollution

Abstract: The commercial trade of wildlife occurs on a global scale. In addition to removing animals from their native populations, this trade may lead to the release and subsequent introduction of nonindigenous species and the pathogens they carry. Emerging infectious diseases, such as chytridiomycosis caused by the chytrid fungus Batrachochytrium dendrobatidis (Bd), and ranaviral disease have spread with global trade in amphibians and are linked to amphibian declines and die‐offs worldwide, which suggests that the commercial trade in amphibians may be a source of pathogen pollution. We screened tiger salamanders involved in the bait trade in the western United States for both ranaviruses and Bd with polymerase chain reaction and used oral reports from bait shops and ranavirus DNA sequences from infected bait salamanders to determine how these animals and their pathogens are moved geographically by commerce. In addition, we conducted 2 surveys of anglers to determine how often tiger salamanders are used as bait and how often they are released into fishing waters by anglers, and organized bait‐shop surveys to determine whether tiger salamanders are released back into the wild after being housed in bait shops. Ranaviruses were detected in the tiger salamander bait trade in Arizona, Colorado, and New Mexico, and Bd was detected in Arizona bait shops. Ranaviruses were spread geographically through the bait trade. All tiger salamanders in the bait trade were collected from the wild, and in general they moved east to west and north to south, bringing with them their multiple ranavirus strains. Finally, 26–73% of anglers used tiger salamanders as fishing bait, 26–67% of anglers released tiger salamanders bought as bait into fishing waters, and 4% of bait shops released tiger salamanders back into the wild after they were housed in shops with infected animals. The tiger salamander bait trade in the western United States is a useful model for understanding the consequences of the unregulated anthropogenic movement of amphibians and their pathogens through trade.     

Measuring the impact of the pet trade on Indonesian birds

The trade in wild animals involves one‐third of the world's bird species and thousands of other vertebrate species. Although a few species are imperiled as a result of the wildlife trade, the lack of field studies makes it difficult to gauge how serious a threat it is to biodiversity. We used data on changes in bird abundances across space and time and information from trapper interviews to evaluate the effects of trapping wild birds for the pet trade in Sumatra, Indonesia. To analyze changes in bird abundance over time, we used data gathered over 14 years of repeated bird surveys in a 900‐ha forest in southern Sumatra. In northern Sumatra, we surveyed birds along a gradient of trapping accessibility, from the edge of roads to 5 km into the forest interior. We interviewed 49 bird trappers in northern Sumatra to learn which species they targeted and how far they went into the forest to trap. We used prices from Sumatran bird markets as a proxy for demand and, therefore, trapping pressure. Market price was a significant predictor of species declines over time in southern Sumatra (e.g., given a market price increase of approximately $50, the log change in abundance per year decreased by 0.06 on average). This result indicates a link between the market‐based pet trade and community‐wide species declines. In northern Sumatra, price and change in abundance were not related to remoteness (distance from the nearest road). However, based on our field surveys, high‐value species were rare or absent across this region. The median maximum distance trappers went into the forest each day was 5.0 km. This suggests that trapping has depleted bird populations across our remoteness gradient. We found that less than half of Sumatra's remaining forests are >5 km from a major road. Our results suggest that trapping for the pet trade threatens birds in Sumatra. Given the popularity of pet birds across Southeast Asia, additional studies are urgently needed to determine the extent and magnitude of the threat posed by the pet trade.     

A guide to using the internet to monitor and quantify the wildlife trade

The unrivaled growth in e-commerce of animals and plants presents an unprecedented opportunity to monitor wildlife trade to inform conservation, biosecurity, and law enforcement. Using the internet to quantify the scale of the wildlife trade (volume and frequency) is a relatively recent and rapidly developing approach that lacks an accessible framework for locating relevant websites and collecting data. We produced an accessible guide for internet-based wildlife trade surveillance. We detailed a repeatable method involving a systematic internet search, with search engines, to locate relevant websites and content. For data collection, we highlight web-scraping technology as an efficient way to collect data in an automated fashion at regularly timed intervals. Our guide is applicable to the multitude of trade-based contexts because researchers can tailor search keywords for specific taxa or derived products and locations of interest. We provide information for working with the diversity of websites used in wildlife trade. For example, to locate relevant content on social media (e.g., posts or groups), each social media platform should be examined individually via the site's internal search engine. A key advantage of using the internet to study wildlife trade is the relative ease of access to an increasing amount of trade-related data. However, not all wildlife trade occurs online and it may occur on unobservable sections of the internet.     

Effects of Private‐Land Use,Livestock Management,and Human Tolerance on Diversity,Distribution, and Abundance of Large African Mammals

Successful conservation of large terrestrial mammals (wildlife) on private lands requires that landowners be empowered to manage wildlife so that benefits outweigh the costs. Laikipia County, Kenya, is predominantly unfenced, and the land uses in the area allow wide‐ranging wildlife to move freely between different management systems on private land. We used camera traps to sample large mammals associated with 4 different management systems (rhinoceros sanctuaries, no livestock; conservancies, intermediate stocking level; fenced ranches, high stocking level; and group ranches, high stocking level, no fencing, pastoralist clan ownership) to examine whether management and stocking levels affect wildlife. We deployed cameras at 522 locations across 8 properties from January 2008 through October 2010 and used the photographs taken during this period to estimate richness, occupancy, and relative abundance of species. Species richness was highest in conservancies and sanctuaries and lowest on fenced and group ranches. Occupancy estimates were, on average, 2 and 5 times higher in sanctuaries and conservancies as on fenced and group ranches, respectively. Nineteen species on fenced ranches and 25 species on group ranches were considered uncommon (occupancy < 0.1). The relative abundance of most species was highest or second highest in sanctuaries and conservancies. Lack of rights to manage and utilize wildlife and uncertain land tenure dampen many owners’ incentives to tolerate wildlife. We suggest national conservation strategies consider landscape‐level approaches to land‐use planning that aim to increase conserved areas by providing landowners with incentives to tolerate wildlife. Possible incentives include improving access to ecotourism benefits, forging agreements to maintain wildlife habitat and corridors, resolving land‐ownership conflicts, restoring degraded rangelands, expanding opportunities for grazing leases, and allowing direct benefits to landowners through wildlife harvesting. Efectos del Uso Privado de Suelo, Manejo de Ganado y la Tolerancia Humana sobre la Diversidad, Distribución y Abundancia de Mamíferos Mayores Africanos     

Wild meat trade over the last 45 years in the Peruvian Amazon

The trade in wild meat is an important economic component of rural people's livelihoods, but it has been perceived to be among the main causes of the decline of wildlife species. Recently, the COVID-19 pandemic has brought to light an additional concern of wildlife markets as a major human-health challenge. We analyzed data from the largest longitudinal monitoring (1973–2018) of the most important urban wild-meat markets in Iquitos, Peru, to examine the trends in and impacts of these markets on people's livelihoods. Over the last 45 years, wild meat sales increased at a rate of 6.4 t/year (SD 2.17), paralleling urban population growth. Wild meat sales were highest in 2018 (442 t), contributing US$2.6 million (0.76%) to the regional gross domestic product. Five species of ungulates and rodents accounted for 88.5% of the amount of biomass traded. Vulnerable and Endangered species represented 7.0% and 0.4% of individuals sold, respectively. Despite growth in sales, the contribution of wild meat to overall urban diet was constant: 1–2%/year of total meat consumed. This result was due to greater availability and higher consumption of cheaper meats (e.g., in 2018, poultry was 45.8% cheaper and was the most consumed meat) coupled with the lack of economic incentives to harvest wild meat species in rural areas. Most wild meat was sold salted or smoked, reducing the likelihood of foodborne diseases. Community-based wildlife management plans and the continued trade bans on primates and threatened taxa may avoid biodiversity loss. Considering the recent COVID-19 pandemic, future management plans should include potential viral hosts and regulation and enforcement of hygiene practices in wild-meat markets.     

Using multilevel spatial models to understand salamander site occupancy patterns after wildfire

Studies of the distribution of elusive forest wildlife have suffered from the confounding of true presence with the uncertainty of detection. Occupancy modeling, which incorporates probabilities of species detection conditional on presence, is an emerging approach for reducing observation bias. However, the current likelihood modeling framework is restrictive for handling unexplained sources of variation in the response that may occur when there are dependence structures such as smaller sampling units that are nested within larger sampling units. We used multilevel Bayesian occupancy modeling to handle dependence structures and to partition sources of variation in occupancy of sites by terrestrial salamanders (family Plethodontidae) within and surrounding an earlier wildfire in western Oregon, USA. Comparison of model fit favored a spatial N-mixture model that accounted for variation in salamander abundance over models that were based on binary detection/non-detection data. Though catch per unit effort was higher in burned areas than unburned, there was strong support that this pattern was due to a higher probability of capture for individuals in burned plots. Within the burn, the odds of capturing an individual given it was present were 2.06 times the odds outside the burn, reflecting reduced complexity of ground cover in the burn. Ther was weak support that true occupancy was lower within the burned area. While the odds of occupancy in the burn were 0.49 times the odds outside the burn among the five species, the magnitude of variation attributed to the burn was small in comparison to variation attributed to other landscape variables and to unexplained, spatially autocorrelated random variation. While ordinary occupancy models may separate the biological pattern of interest from variation in detection probability when all sources of variation are known, the addition of random effects structures for unexplained sources of variation in occupancy and detection probability may often more appropriately represent levels of uncertainty.     

A test of the substitution–habitat hypothesis in amphibians

Most examples that support the substitution‐habitat hypothesis (human‐made habitats act as substitutes of original habitat) deal with birds and mammals. We tested this hypothesis in 14 amphibians by using percentage occupancy as a proxy of habitat quality (i.e., higher occupancy percentages indicate higher quality). We classified water body types as original habitat (no or little human influence) depending on anatomical, behavioral, or physiological adaptations of each amphibian species. Ten species had relatively high probabilities (0.16–0.28) of occurrence in original habitat, moderate probability of occurrence in substitution habitats (0.11–0.14), and low probability of occurrence in refuge habitats (0.05–0.08). Thus, the substitution–habitat hypothesis only partially applies to amphibians because the low occupancy of refuges could be due to the negligible human persecution of this group (indicating good conservation status). However, low occupancy of refuges could also be due to low tolerance of refuge conditions, which could have led to selective extinction or colonization problems due to poor dispersal capabilities. That original habitats had the highest probabilities of occupancy suggests amphibians have a good conservation status in the region. They also appeared highly adaptable to anthropogenic substitution habitats.     

Predictors of occupancy trend across spatial scale

Many explorations of extinction probability have had a global focus, yet it is unclear whether variables that explain the probability of extinction at large spatial extents are the same as those at small spatial extents. Thus, we used nearly annual presence-absence records for the most recent 40 years of a 110-year data set from Palenque, Mexico, an area with ongoing deforestation, to explore which of >200 species of birds have probabilities of extirpation that are likely to increase. We assessed associations between long-term trends in species presence (i.e., detection in a given year) and body size, geographic range size, diet, dependence on forest cover, taxonomy, and ecological specialization. Our response variable was the estimated slope of a weighted logistic regression for each species. We assessed the relative strength of each predictor by means of a model ranking scheme. Several variables associated with high extinction probability at global extents, such as large body size or small geographic range size, were not associated with occurrence of birds over time at our site. Body size was associated with species loss at Palenque, but occurrence trends of both very large and very small species, particularly the latter, have declined, or the species have been extirpated. We found no association between declining occurrence trend and geographic range size, yet decline correlated with whether a species depends on forest (mean occupancy trend =-0.0380, 0.0263, and 0.0186 for, respectively, species with high, intermediate, or low dependence on forest) and with complex combinations of diet and foraging strata (e.g., occurrence of canopy insectivores and terrestrial omnivores has increased, whereas occurrence of mid-level frugivores and terrestrial granivores has decreased). Our findings emphasize that analyses of local areas are necessary to explicate extirpation risk at various spatial extents.     

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     

The perils of flawed science in wildlife trade literature

Despite broad scientific consensus that sustainable use of wildlife can enhance conservation efforts, ethical concerns have led some community groups to oppose use of wild animals. Voicing those concerns is legitimate, but underlying philosophical bias should not influence science-based analysis and interpretation. We argue that philosophical biases are common in the scientific literature on trade in wildlife. The critically important case of bias surrounding the use of reptile leathers for luxury fashion illustrates the problem. Based on analysis of official seizures of fashion products made from wildlife, a recent study inferred that criminal activity (as inferred by noncompliance with regulations) was common and increasing and, hence, that authorities needed to adopt more stringent restrictions on the trade. In fact, the conclusions of that study are artifacts of pseudoreplication (e.g., multiple counts of single violations) and biased sampling (e.g., focus on companies with high rates of error) and run directly opposite to actual patterns in the data. As a proportion of overall trade, rates of noncompliance are exceptionally low (<0.4%), are declining, and result primarily from paper-work errors rather than criminal intent (e.g., such errors are more frequent for goods shipped by government authorities than by the commercial fashion industry). The recommendation by the study authors to prohibit the international trade in wildlife-based fashion products is imperiling a sustainable trade that can benefit biodiversity and people's livelihoods by providing financial incentives for conservation of species and habitats. This example offers a warning of the dangers of basing research on the wildlife trade on ethical or philosophical positions rather than objective evaluations of evidence.     

Human disturbance and shifts in vertebrate community composition in a biodiversity hotspot

Understanding how human modification of the landscape shapes vertebrate community composition is vital to understanding the current status and future trajectory of wildlife. Using a participatory approach, we deployed the largest camera-trap network in Mesoamerica to date to investigate how anthropogenic disturbance shapes the occupancy and co-occurrence of terrestrial vertebrate species in a tropical biodiversity hotspot: the Osa Peninsula, Costa Rica. We estimated species richness in different categories of land protection with rarefaction analysis and estimated the expected occupancy with a joint species distribution model that included covariates for anthropogenic disturbance, land protection, habitat quality, and habitat availability. Areas with the most stringent land-use protections (e.g., Corcovado National Park, 24 species [95% CI 23–25]) harbored significantly more species than unprotected areas (20 species [19.7–20.3]), mainly due to a reduced presence of large-bodied species of conservation concern in unprotected areas (e.g., jaguar Panthera onca and white-lipped peccary Tayassu pecari). Small-bodied generalist species, such as opossums (Didelphidae) and armadillos (Dasypus novemcinctus), in contrast, were more common at disturbed sites, resulting in a significant difference in vertebrate community composition between sites with low and high disturbance. Co-occurrence of species was also mainly associated with response to disturbance. Similar responses to disturbance create two groups of species, those whose site-level occupancy usually increased as anthropogenic disturbance increased and those whose estimated occupancy decreased. The absence of large-bodied species entails an important loss of ecological function in disturbed areas and can hinder forest development and maintenance. Efforts to protect and restore forested landscapes are likely having a positive effect on the abundance of some threatened species. These efforts, however, must be sustained and expanded to increase connectivity and ensure the long-term viability of the wildlife community.     

Understanding implications of consumer behavior for wildlife farming and sustainable wildlife trade

Unsustainable wildlife trade affects biodiversity and the livelihoods of communities dependent upon those resources. Wildlife farming has been proposed to promote sustainable trade, but characterizing markets and understanding consumer behavior remain neglected but essential steps in the design and evaluation of such operations. We used sea turtle trade in the Cayman Islands, where turtles have been farm raised for human consumption for almost 50 years, as a case study to explore consumer preferences toward wild‐sourced (illegal) and farmed (legal) products and potential conservation implications. Combining methods innovatively (including indirect questioning and choice experiments), we conducted a nationwide trade assessment through in‐person interviews from September to December 2014. Households were randomly selected using disproportionate stratified sampling, and responses were weighted based on district population size. We approached 597 individuals, of which 37 (6.2%) refused to participate. Although 30% of households had consumed turtle in the previous 12 months, the purchase and consumption of wild products was rare (e.g., 64–742 resident households consumed wild turtle meat [i.e., 0.3–3.5% of households] but represented a large threat to wild turtles in the area due to their reduced populations). Differences among groups of consumers were marked, as identified through choice experiments, and price and source of product played important roles in their decisions. Despite the long‐term practice of farming turtles, 13.5% of consumers showed a strong preference for wild products, which demonstrates the limitations of wildlife farming as a single tool for sustainable wildlife trade. By using a combination of indirect questioning, choice experiments, and sales data to investigate demand for wildlife products, we obtained insights about consumer behavior that can be used to develop conservation‐demand‐focused initiatives. Lack of data from long‐term social–ecological assessments hinders the evaluation of and learning from wildlife farming. This information is key to understanding under which conditions different interventions (e.g., bans, wildlife farming, social marketing) are likely to succeed.     

Legal ivory trade in a corrupt world and its impact on African elephant populations

Illegal hunting of African elephants (Loxodonta africana) for ivory is causing rapid declines in their populations. Since 2007, illegal ivory trade has more than doubled. African elephants are facing the most serious conservation crisis since 1989, when international trade was banned. One solution proposed is establishment of a controlled legal trade in ivory. High prices for ivory mean that the incentives to obtain large quantities are high, but the quantity of tusks available for trade are biologically constrained. Within that context, effective management of a legal ivory trade would require robust systems to be in place to ensure that ivory from illegally killed elephants cannot be laundered into a legal market. At present, that is not feasible due to corruption among government officials charged with implementing wildlife‐related legislation. With organized criminal enterprises involved along the whole commodity chain, corruption enables the laundering of illegal ivory into legal or potentially legal markets. Poachers and traffickers can rapidly pay their way out of trouble, so the financial incentives to break the law heavily outweigh those of abiding by it. Maintaining reliable permitting systems and leak‐proof chains of custody in this context is challenging, and effective management breaks down. Once illegal ivory has entered the legal trade, it is difficult or impossible for enforcement officers to know what is legal and illegal. Addressing corruption throughout a trade network that permeates countries across the globe will take decades, if it can ever be achieved. That will be too late for wild African elephants at current rates of loss. If we are to conserve remaining wild populations, we must close all markets because, under current levels of corruption, they cannot be controlled in a way that does not provide opportunities for illegal ivory being laundered into legal markets. Comercio Legal de Marfil en un Mundo Corrupto y su Imapacto sobre Poblaciones de Elefantes