Retaliatory killing, motivated by depredation of domestic animals by large carnivores, has had a significant impact on wild predators’ populations. In Brazil, pumas and jaguars are the most persecuted species, so it is important to analyse the spatial patterns of depredation risk of livestock. We aimed to identify the hotspots of depredation risk by these two felids in Brazil, as well as the most important variables that determine the risk at the biome scale. We generated spatial models of livestock depredation using a database of depredation records, anthropogenic, topographic and vegetation variables, and ecological niche models. We used six algorithms to generate spatial risk models of depredation and selected those with the best performance, for inclusion in a consensus model, for each biome. Finally, we overlapped the areas of high depredation risk by both felids, so that areas considered as hotspots are those in which there is a high risk that livestock will be preyed by pumas or jaguars. Approximately 17% of the area of the biomes analysed for puma had high depredation risk, and 18% in the case of jaguar. The hotspots encompassed 6.5% of the included biomes’ area. The variables associated with the high depredation risk were different between species and biomes. Depredation risk by pumas was primarily associated with anthropogenic variables, whereas a combination of anthropogenic variables and vegetation types increased depredation risk by jaguar. Biome‐scale analysis, coupled with the availability of reliable data and the implementation of statistically robust methods, provides information specifically on the areas of highest risk and the conditions that contribute to it.

Agkistrodon bilineatus is a viperid snake with a broad geographic range in Mexico and Central America. Because this species has potent venom and is categorized as Near Threatened on the Red List of Threatened Species of the International Union for Conservation of Nature, understanding its habitat associations and distribution will contribute to both human health and conservation decisions internationally. Based on a comprehensive review of literature and museum records, in addition to our fieldwork, we built the first distribution model for A. bilineatus. Our presence-only consensus model exclusively incorporated contemporary records for the species (from 1980 to 2022, n = 36). The variables that contributed most strongly to the consensus model were: (a) distance to deciduous broadleaf forest, (b) human population density, (c) elevation, (d) precipitation of the wettest quarter, and (e) percentage of herbaceous cover. Of the high-probability distribution area for A. bilineatus predicted by the model, 72.9 % is in Mexico, 12.7 % in Honduras, 9.1 % in Guatemala and 5.2 % in El Salvador. Of the A. bilineatus historical records (those pre-1980), 92.3 % (36/39) were within the high-probability area predicted by the model, indicating either strong model performance or overprediction. Included in our modelling effort were the first two records for A. bilineatus from the State of Mexico, which increases the number of reptile species to 102 in this State. We briefly discuss the implications of our work for human medical treatment and improved conservation assessments for this species, which experiences many environmental threats.

A variety of ecosystems can be found on the eastern flank of the Peruvian Andean-Amazonian piedmont. Amongst these, seasonally flooded forests (which include many peatlands) have attracted scientific attention because of the ecosystem services they provide. Our research was conducted in the Tingana flooded forests situated in the Alto Mayo Valley, San Martin (Peru). The canopies and branches of phorophytes (epiphyte-bearing plants) located within fourteen 20 × 20 m plots at two study sites were accessed using climbing equipment, and 107 epiphytic species were recorded. The epiphyte genera with the highest diversity were Epidendrum (15 species), Asplenium (7 species), Anthurium (6 species) and Peperomia (5 species), and the phorophyte with the highest epiphyte diversity was Ficus trigona. The richness estimators (Chao1 and ACE) accounted for > 75.3 % of the species present, with Stratum III being the most abundant and diverse. Demographic studies will be needed to comprehend the potential consequences of climate change for the epiphyte communities of flooded forests as they recover from disturbance.