Disturbance Regimes Drive The Diversity of Regional Floristic Pools Across Guianan Rainforest Landscapes.

Disturbances control rainforest dynamics, and, according to the intermediate disturbance hypothesis (IDH), disturbance regime is a key driver of local diversity. Variations in disturbance regimes and their consequences on regional diversity at broad spatiotemporal scales are still poorly understood. Using multidisciplinary large-scale inventories and LiDAR acquisitions, we developed a robust indicator of disturbance regimes based on the frequency of a few early successional and widely distributed pioneer species. We demonstrate at the landscape scale that tree-species diversity and disturbance regimes vary with climate and relief. Significant relationships between the disturbance indicator, tree-species diversity and soil phosphorus content agree with the hypothesis that rainforest diversity is controlled both by disturbance regimes and long-term ecosystem stability. These effects explain the broad-scale patterns of floristic diversity observed between landscapes. In fact, species-rich forests in highlands, which have benefited from long-term stability combined with a moderate and regular regime of local disturbances, contrast with less diversified forests on recently shaped lowlands, which have undergone more recent changes and irregular dynamics. These results suggest that taking the current disturbance regime into account and including geomorphological stratifications in climate-vegetation models may be an effective way to improve the prediction of changes in species diversity under climate change.

Biological traits, rather than environment, shape detection curves of large vertebrates in neotropical rainforests.

Line transect surveys are widely used in Neotropical rainforests to estimate the population abundance of medium- and large-sized vertebrates. The use of indices such as encounter rate has been criticized because the probability of animal detection may fluctuate due to the heterogeneity of environmental conditions among sites. In addition, the morphological and behavioral characteristics (biological traits) of species affect their detectability. In this study, we compared the extent to which environmental conditions and species' biological traits bias abundance estimates in terra firme rainforests in French Guiana. The selected environmental conditions included both physical conditions and forest structure covariates, while the selected biological traits included the morphological and behavioral characteristics of species. We used the distance sampling method to model the detection probability as an explicit function of environmental conditions and biological traits and implemented a model selection process to determine the relative importance of each group of covariates. Biological traits contributed to the variability of animal detectability more than environmental conditions, which had only a marginal effect. Detectability was best for large animals with uniform or disruptive markings that live in groups in the canopy top. Detectability was worst for small, solitary, terrestrial animals with mottled markings. In the terra firme rainforests that represent ~80% of the Amazonia and Guianas regions, our findings support the use of relative indices such as the encounter rate to compare population abundance between sites in species-specific studies. Even though terra firme rainforests may appear similar between regions of Amazonia and the Guianas, comparability must be ensured, especially in forests disturbed by human activity. The detection probability can be used as an indicator of species' vulnerability to hunting and, thus, to the risk of local extinction. Only a few biological trait covariates are required to correctly estimate the detectability of the majority of medium- and large-sized vertebrates. Thus, a biological trait model could be useful in predicting the detection probabilities of rare, uncommon, or localized species for which few data are available to fit the detection function.

Nutrient-cycling mechanisms other than the direct absorption from soil may control forest structure and dynamics in poor Amazonian soils.

Tropical forests store large amounts of biomass despite they generally grow in nutrient-poor soils, suggesting that the role of soil characteristics in the structure and dynamics of tropical forests is complex. We used data for >34 000 trees from several permanent plots in French Guiana to investigate if soil characteristics could predict the structure (tree diameter, density and aboveground biomass), and dynamics (growth, mortality, aboveground wood productivity) of nutrient-poor tropical forests. Most variables did not covary with site-level changes in soil nutrient content, indicating that nutrient-cycling mechanisms other than the direct absorption from soil (e.g. the nutrient uptake from litter, the resorption, or the storage of nutrients in the biomass), may strongly control forest structure and dynamics. Ecosystem-level adaptations to low soil nutrient availability and long-term low levels of disturbance may help to account for the lower productivity and higher accumulation of biomass in nutrient-poor forests compared to nutrient-richer forests.

Maripa hantavirus in French Guiana: phylogenetic position and predicted spatial distribution of rodent hosts.

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.