Evaluating range‐wide habitat use by a target species requires information on species occurrence over broad geographic regions, a process made difficult by species rarity, large spatiotemporal sampling domains and imperfect detection. We address these challenges in an assessment of habitat use for jaguars (Panthera onca) outside protected areas in Central America. Occurrence records were acquired within 12 putative corridors using interviews with knowledgeable corridor residents. We developed a Bayesian hierarchical occupancy model to gain robust inference, allowing for heterogeneity introduced in the sampling process over space and time, using records of jaguar occurrence prone to false positives and false negatives. Probability of false detection of jaguars increased with the number of interviews conducted per unit (from 5.42% to 7.74% given <4 and ≥4 observers per unit). True probability of detection (p = 0.58) increased with the number of days interviewees spent in a survey unit per year. Failing to account for false positives biased predicted habitat use high (c. 1.8×), especially where occurrence records were sparse. Probability of site use by jaguars increased with greater forest cover, prey richness, and distance from human settlements, and decreased with greater agricultural cover, elevation, and distance from protected areas. Site use probabilities averaged 0.15–0.97 by corridor, providing relatively fine‐scale resolution of predicted jaguar occurrence consistent with known patterns of jaguar gene flow across Central America. Model validation, accounting for both false positives and negatives in the observation process, indicated moderate correspondence between model‐predicted observations and actual observations for withheld data (0.65, 95% CRI 0.59–0.71), with sensitivity and specificity rates of 0.69 (0.61–0.77) and 0.59 (0.50–0.68), respectively. These results demonstrate that reliable predictions can be achieved despite the complexity of large‐scale, interview‐based analyses of species occurrence. Synthesis and applications. Our Bayesian hierarchical occupancy model accommodated heterogeneity caused by typical sampling inequities and idiosyncrasies associated with interview data, yielding robust estimates of jaguar habitat use. Our approach is applicable to any wide‐ranging and readily identifiable species and has particular utility for rare species in human‐dominated landscapes where traditional survey techniques (e.g. camera traps) may be impractical.

Human activities such as habitat degradation and fragmentation threaten biodiversity in Neotropical areas. This work proposes an analytical methodology to identify natural areas in Central America with anthropogenic impact, analyzing the presence of antimicrobial resistance genes (ARGs) in accordance with their theoretical relationship with human-related activities. Sixteen ARGs were quantified in feces of different individuals of 13 jaguars (Panthera onca) and 13 pumas (Puma concolor) in three conservation areas in Costa Rica by real-time PCR. At least one ARG was detected in all samples. Of the ARGs encoding tetracycline resistance, the most frequent were tetQ and tetY (85% and 69%, respectively). The sulfonamides (sulI and sulII; 69% each), phenicols (catI and catII; 19% and 54%, respectively), and quinolones (qnrS; 12%) were also detected. The presence of human settlements, livestock farms (pigs, cattle, and poultry), roads, human health centers, flood zones, and rivers were identified within each area to generate an index of human activity. We found no difference between the presence of ARG by roads, agricultural activities, and human settlements (P>0.05). However, tetW showed higher percentages with porcine and bovine farms; both tetY and tetW were more frequent in jaguars than in pumas. Of concern is that many of the most contaminated samples were taken from national parks, such as Braulio Carrillo and Tortuguero, where animals should not have direct contact with humans.

Understanding species-environment relationships at large spatial scales is required for the prioritization of conservation areas and the preservation of landscape connectivity for large carnivores. This endeavour is challenging for jaguars (Panthera onca), given their elusiveness, and the local nature of most jaguar studies, precluding extrapolation to larger areas. We developed an occupancy model using occurrence data of jaguars across five countries of Central America, collected from camera-trap studies of 2-12 months' duration, deployed over an area of 14 112 km 2 from 2005 to 2018. Our occupancy model showed that habitat use of jaguars increased with primary net productivity and distance to human settlements, and decreased with distance to rivers. Detection of the species was related to survey effort and research team identity. Within the jaguar extent of occurrence, 73% was deemed suitable for the species, with 47% of it lying within Jaguar Conservation Units (JCU) and 59% of JCU land being legally protected. Suitable areas were divided into four distinct clusters of continuous habitat shared across country borders. However, large areas of predicted low habitat suitability may constrict connectivity in the region. The reliability of these spatial predictions is indicated by the model validation using an independent dataset (AUC = 0.82; sensitivity = 0.766, specificity = 0.761), and concordance of our results with other studies conducted in the region. Across Central America, we found that human influence has the strongest impact on jaguar habitat use and JCUs are the main reservoirs of habitat. Therefore, conservation actions must focus on preventing habitat loss and mitigating human pressure, particularly within the clusters of continuous areas of high suitability, and on restoring habitat to foster connectivity. The long-term persistence of jaguars in the region will depend on strong international cooperation that secures jaguar populations and their habitat across Central American borders.

Introducción: Existe poca información ecológica sobre el tejón o grisón mayor, Galictis vittata, incluida su distribución geográfica, dieta y hábitat. Objetivo: Informar el primer registro de este tejón capturando un sapo gigante. Métodos: Examinamos imágenes de cámaras-trampa de enero de 2019 a mayo de 2020. Resultados: Obtuvimos una foto de un tejón con el sapo en su hocico, en una finca de palma aceitera junto a un bosque en regeneración en Golfo Dulce, Costa Rica, y supusimos que la depredación fue exitosa. Conclusiones: Este registro representa el primer evento de depredación de R. horribilis por G. vittata, así como el primer registro de este tejón en una finca de palma aceitera en Costa Rica.

RESUMENEn las últimas décadas el coyote (Canis latrans) ha colonizado nuevos hábitats, ampliando su distribución en Centroamérica. En este trabajo reportamos los primeros registros de la especie en la Reserva Forestal Golfo Dulce y el Parque Nacional Corcovado, lo que extiende su distribución en Costa Rica.Palabras clave: Canidae, Carnivora, colonización, Parque Nacional Corcovado, Reserva Forestal Golfo Dulce.ABSTRACTIn the last decades the coyote (Canis latrans) has colonized new habitats, expanding its distribution in Central America. We report the first records of the species in the Golfo Dulce Forest Reserve and Corcovado National Park, increasing is distribution in Costa Rica.Key words: Canidae, Carnivora, colonization, Corcovado National Park, Golfo Dulce Forest Reserve.