Tropical forests with a low human population and absence of large-scale deforestation provide unique opportunities to study successful conservation strategies, which should be based on adequate monitoring tools. This study explored the conservation status of a large predator, the jaguar, considered an indicator of the maintenance of how well ecological processes are maintained. We implemented an original integrative approach, exploring successive ecosystem status proxies, from habitats and responses to threats of predators and their prey, to canopy structure and forest biomass. Niche modeling allowed identification of more suitable habitats, significantly related to canopy height and forest biomass. Capture/recapture methods showed that jaguar density was higher in habitats identified as more suitable by the niche model. Surveys of ungulates, large rodents and birds also showed higher density where jaguars were more abundant. Although jaguar density does not allow early detection of overall vertebrate community collapse, a decrease in the abundance of large terrestrial birds was noted as good first evidence of disturbance. The most promising tool comes from easily acquired LiDAR data and radar images: a decrease in canopy roughness was closely associated with the disturbance of forests and associated decreasing vertebrate biomass. This mixed approach, focusing on an apex predator, ecological modeling and remote-sensing information, not only helps detect early population declines in large mammals, but is also useful to discuss the relevance of large predators as indicators and the efficiency of conservation measures. It can also be easily extrapolated and adapted in a timely manner, since important open-source data are increasingly available and relevant for large-scale and real-time monitoring of biodiversity.

Species Distribution Models (SDMs) have become increasingly useful for conservation issues. Initially designed to predict distributions of species from incomplete datasets, SDMs may also identify environmental conditions associated with higher occurrences and abundances of widely distributed taxa. Using sighting records of 15 widely distributed mammals from French Guiana, including primates, carnivores, rodents and ungulates, we used three SDMs-based on (i) entropy, (ii) genetic algorithm, (iii) Mahalanobis distance-to investigate relationships between species occurrence and predictive variables such as vegetation, biogeographic units, climate, and disturbance index. Maximal entropy procedures resulted in more accurate projected conditions: the accuracy of the predicted distributions was higher than 90% in nine species among the 15 tested, and predicted occurrences were correlated to fieldmeasured abundances for nine species. The Genetic algorithm implemented with GARP had lower accuracy, with predicted occurrences correlated to abundances for three species only. Finally, Mahalanobis distance had a much lower performance and failed to find any correlation between occurrences and abundances. In the case of MaxEnt modelling, since map projection summarized more appropriate environmental conditions and identified areas likely to act as sources and/or corridors, we propose to use those appropriate environmental conditions as a proxy of conductance for landscape connectivity planning. We provide evidence here that SDMs can identify not only more suitable environmental conditions, but also areas hosting higher abundances for a large set of species with key ecological roles. Further management applications of this environmental suitability index could help in designing corridors between protected areas.

Abstract. A molecular screening of wild-caught rodents was conducted in French Guiana, South America to identify hosts of the hantavirus Maripa described in 2008 in a hantavirus pulmonary syndrome (HPS) case. Over a 9-year period, 418 echimyids and murids were captured. Viral RNA was detected in two sigmodontine rodents, Oligoryzomys fulvescens and Zygodontomys brevicauda, trapped close to the house of a second HPS case that occurred in 2009 and an O. fulvescens close to the fourth HPS case identified in 2013. Sequences from the rodents had 96% and 97% nucleotide identity (fragment of S and M segments, respectively) with the sequence of the first human HPS case. Phylogenetic reconstructions based on the complete sequence of the S segment show that Maripa virus is closely related to Rio Mamore hantavirus. Using environmental descriptors of trapping sites, including vegetation, landscape units, rain, and human disturbance, a maximal entropy-based species distribution model allowed for identification of areas of higher predicted occurrence of the two rodents, where emergence risks of Maripa virus are expected to be higher.Hantaviruses (Bunyaviridae) are distributed worldwide.

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