We aggregated data on butterfly-host plant associations from existing sources in order to address the following questions: (1) is there a general correlation between host diversity and butterfly species richness?, (2) has the evolution of host plant use followed consistent patterns across butterfly lineages?, (3) what is the common ancestral host plant for all butterfly lineages? The compilation included 44,148 records from 5,152 butterfly species (28.6% of worldwide species of Papilionoidea) and 1,193 genera (66.3%). The overwhelming majority of butterflies use angiosperms as host plants. Fabales is used by most species (1,007 spp.) from all seven butterfly families and most subfamilies, Poales is the second most frequently used order, but is mostly restricted to two species-rich subfamilies: Hesperiinae (56.5% of all Hesperiidae), and Satyrinae (42.6% of all Nymphalidae). We found a significant and strong correlation between host plant diversity and butterfly species richness. A global test for congruence (Parafit test) was sensitive to uncertainty in the butterfly cladogram, and suggests a mixed system with congruent associations between Papilionidae and magnoliids, Hesperiidae and monocots, and the remaining subfamilies with the eudicots (fabids and malvids), but also numerous random associations. The congruent associations are also recovered as the most probable ancestral states in each node using maximum likelihood methods. The shift from basal groups to eudicots appears to be more likely than the other way around, with the only exception being a Satyrine-clade within the Nymphalidae that feed on monocots. Our analysis contributes to the visualization of the complex pattern of interactions at superfamily level and provides a context to discuss the timing of changes in host plant utilization that might have promoted diversification in some butterfly lineages.

Unsustainable harvest is one of the most important threats to biodiversity, and birds are highly impacted, but avian markets remain poorly understood. When species value and corruption/criminality are high, the “parallel trafficking” hypothesis predicts that illegal animal items will move through networks used for other illicit products. Alternatively, when particular demands, logistical skills or access limits trade, “specialized trafficking” hypotheses predict that few, expert actors will control markets. Here, we use social network analysis of trade in an Endangered songbird, the Red Siskin Spinus cucullatus, originating in Venezuela, to examine the generality of the parallel trafficking hypothesis in a setting where corruption/criminality and species value are high. In spite of these circumstances, of 2575 Red Siskin (RS) records compiled from 2010 to 2017, we found just six reports consistent with parallel trafficking. Instead, we discovered an independent network of 15 actor types, and a trade structure consistent with specialized trafficking. Just two intermediary types (national vendors to intermediaries and to consumers) and one consumer type (national breeders) had the highest exposure to the flow of birds, and the most trade connectivity. Use of wild‐caught over captive‐bred birds was high (67% of records), as was use of natural‐phenotype birds over hybrid or mutant‐phenotype birds (65% of records). Geographically, Spain and Venezuela had the highest exposure to the flow of birds, but Brazil and Colombia had the most direct connections with other countries. The unexpected lack of evidence for parallel trafficking suggests that combined flows of illicit products are not inevitable, even in adverse settings. In a context where law enforcement may not be feasible, our results suggest that it may be possible to reduce unsustainable harvest using breeder connectivity in informational campaigns to stimulate peer‐to‐peer interactions and accelerate behavior change.

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Although most often considered independently, subsistence hunting, domestic trade, and international trade as components of illegal wildlife use (IWU) may be spatially correlated. Understanding how and where subsistence and commercial uses may co-occur has important implications for the design and implementation of effective conservation actions. We analyzed patterns in the joint geographical distribution of illegal commercial and subsistence use of multiple wildlife species in Venezuela and evaluated whether available data were sufficient to provide accurate estimates of the magnitude, scope, and detectability of IWU. We compiled records of illegal subsistence hunting and trade from several sources and fitted a random-forest classification model to predict the spatial distribution of IWUs. From 1969 to 2014, 404 species and 8,340,921 specimens were involved in IWU, for a mean extraction rate of 185,354 individuals/year. Birds were the most speciose group involved (248 spp.), but reptiles had the highest extraction rates (126,414 individuals/year vs. 3,133 individuals/year for birds). Eighty-eight percent of international trade records spatially overlapped with domestic trade, especially in the north and along the coast but also in western inland areas. The distribution of domestic trade was broadly distributed along roads, suggesting that domestic trade does not depend on large markets in cities. Seventeen percent of domestic trade records overlapped with subsistence hunting, but the spatial distribution of this overlap covered a much larger area than between commercial uses. Domestic trade seems to respond to demand from rural more than urban communities. Our approach will be useful for understanding how IWU works at national scales in other parts of the world.

A d a S Á n c h e z -M e r c a d o , J o s É R . F e r r e r -P a r i s , E d g a r d Y e r e n a S h a e n a n d h o a G a r c Í a -R a n g e l and K a t h r y n M . R o d r Í g u e z -C l a r k Abstract Worldwide, many large mammals are threatened by poaching. However, understanding the causes of poaching is difficult when both hunter and hunted are elusive. One alternative is to apply regression models to opportunisticallycollected data but doing so without accounting for inherent biases may result in misleading conclusions. To demonstrate a straightforward method to account for such biases, and to guide further research on an elusive Vulnerable species, we visualized spatio-temporal poaching patterns in 844 Andean bear Tremarctos ornatus presence reports from the Cordillera de Mérida, Venezuela. To create maps of poaching risk we fitted two logistic regression models to a subset of 287 precisely georeferenced reports, one ignoring and one including spatial autocorrelation. Whereas the variance explained by both models was low, the second had better fit and predictive ability, and indicated that protected status had a significant positive effect on reducing poaching risk. Poaching risk increased at lower altitudes, where all indicators of human disturbance increased, although there was scant evidence that human-bear conflicts are a major direct trigger of poaching events. Because highest-risk areas were different from areas with most bear reports, we speculate that hunting may be driven by opportunistic encounters, rather than by purposeful searches in highquality bear habitat. Further research comparing risk maps with bear abundance models and data on poaching behaviour will be invaluable for clarifying poaching causes and for identifying management strategies.

Ecological traps occur when rapid environmental change makes organisms' habitat selection cues misleading and leads them to prefer poor quality habitats. Such traps can threaten the persistence of affected populations, so techniques to predict and map potential traps are of great conservation interest. Here we present a novel method for visualizing such traps and their uncertainty at large scales in a natural landscape, by combining a spatially explicit model of anthropogenic threats with one of occurrence probability. We began with poaching and occurrence data for Andean bears in the Cordillera de Mérida, Venezuela, and applied a partitioning procedure to generate 10 replicates of three partially independent data subsets. To the first subset, we fit a previously developed model of poaching probability, while we used the second and third subsets to fit, validate and select the best of four occurrence probability models. We then combined replicates of the poaching probability model with those of the best occurrence probability model to predict the spatial distribution and uncertainty of potential ecological traps. The best occurrence model predicted high probabilities in the center and in the northern parts of Cordillera de Mérida, with variation among replicates in the same areas. Predicted areas of occurrence covered 10 217 ± 2762 km 2 (24%) of the study area. However, more than a third of this area had a high probability of being an ecological trap. Furthermore, these potential ecological traps were next to or within the largest national parks and were surrounded by large areas with high occurrence probability and low poaching probability. Future research should focus on independent verification of potential occupancy and ecological traps, as well as on bear dispersal behavior. In areas where ecological traps are confirmed, targeted education and law enforcement will be most effective, while in confirmed safe harbor areas, increasing connectivity will be equally important. Our approach will be useful to identify potential ecological traps at the landscape level created by hunting and other human activities elsewhere in the world.

The perceptions and attitudes of local communities help understand the social drivers of unsustainable wildlife use and the social acceptability of conservation programs. We evaluated the social context influencing illegal harvesting of the threatened yellow-shouldered Amazon (Amazona barbadensis) and the effectiveness of a longstanding conservation program in the Macanao Peninsula, Margarita Island, Venezuela. We interviewed 496 people from three communities and documented their perceptions about (1) status and the impact of threats to parrot populations, (2) acceptability of the conservation program, and (3) social processes influencing unsustainable parrot use. Approval of the program was high, but it failed to engage communities despite their high conservation awareness and positive attitudes towards the species. People identified unsustainable use as the main threat to parrots, but negative perceptions were limited to selling, not harvesting or keeping. Harvesters with different motivations (keepers, sellers) may occur in Macanao, and social acceptability of both actors may differ. Future efforts will require a stakeholder engagement strategy to manage conflicts and incentives to participation. A better understanding of different categories of harvesters, as well as their motives and role in the illegal trade network would provide insights to the design of a behavior change campaign.