Abstract: Tropical forests are known for their high diversity. Yet, forest patches do occur in the tropics where a single tree species is dominant. Such “monodominant” forests are known from all of the main tropical regions. For Amazonia, we sampled the occurrence of monodominance in a massive, basin-wide database of forest-inventory plots from the Amazon Tree Diversity Network (ATDN). Utilizing a simple defining metric of at least half of the trees over 10cm diameter belonging to one species, we found only a few occurrences of monodominance in Amazonia, and the phenomenon was not significantly linked to previously hypothesized life history traits such wood density, seed mass, ectomycorrhizal associations, or Rhizobium nodulation. In our analysis, coppicing (the formation of sprouts at the base of the tree or on roots) was the only trait significantly linked to monodominance. While at specific locales coppicing or ectomycorrhizal associations may confer a considerable advantage to a tree species and lead to its monodominance, very few species have these traits. Mining of the ATDN dataset suggests that monodominance is quite rare in Amazonia, and may be linked primarily to edaphic factors.

Abstract: Environmental DNA (eDNA) metabarcoding is a promising tool to estimate aquatic biodiversity. It is based on the capture of DNA from a water sample. The sampled water volume, a crucial aspect for efficient species detection, has been empirically variable (ranging from few centiliters to tens of liters). This results in a high variability of sampling effort across studies, making comparisons difficult and raising uncertainties about the completeness of eDNA inventories. Our aim was to determine the sampling effort (filtered water volume) needed to get optimal inventories of fish assemblages in species-rich tropical streams and rivers using eDNA. Ten DNA replicates were collected in six Guianese sites (3 streams and 3 rivers), resulting in sampling efforts ranging from 17 to 340 liters of water. We show that sampling 34 liters of water detected more than 64% of the expected fish fauna and permitted to distinguish the fauna between sites and between ecosystem types (stream versus rivers). Above 68 liters, the number of detected species per site increased slightly, with a detection rate higher than 71%. Increasing sampling effort up to 340 liters provided little additional information, testifying that filtering 34 to 68 liters is sufficient to inventory most of the fauna in highly diverse tropical aquatic ecosystems. © 2019, The Author(s).

Abstract: Soil fauna is a key control of the decomposition rate of leaf litter, yet its interactions with litter quality and the soil environment remain elusive. We conducted a litter decomposition experiment across different topographic levels within the landscape replicated in two rainforest sites providing natural gradients in soil fertility to test the hypothesis that low nutrient availability in litter and soil increases the strength of fauna control over litter decomposition. We crossed these data with a large dataset of 44 variables characterizing the biotic and abiotic microenvironment of each sampling point and found that microbe-driven carbon (C) and nitrogen (N) losses from leaf litter were 10.1 and 17.9% lower, respectively, in the nutrient-poorest site, but this among-site difference was equalized when meso- and macrofauna had access to the litterbags. Further, on average, soil fauna enhanced the rate of litter decomposition by 22.6%, and this contribution consistently increased as nutrient availability in the microenvironment declined. Our results indicate that nutrient scarcity increases the importance of soil fauna on C and N cycling in tropical rainforests. Further, soil fauna is able to equalize differences in microbial decomposition potential, thus buffering to a remarkable extent nutrient shortages at an ecosystem level.

Abstract: We developed nuclear and chloroplastic single nucleotide polymorphism (SNP) and INDEL (insertion/deletion) markers using restriction associated DNA sequencing (RADSeq) and low coverage MiSeq genome sequencing to set up a genetic tracking method of the geographical origin of Hymenaea sp. From two initial sets of 358 and 32 loci used to genotype at least 94 individuals, a final set of 75 nSNPs, 50 cpSNPs and 6 INDELs identifying significant population structure was developed. © 2018, Springer Nature B.V.

Abstract: Despite the lowtree diversity and scarcity of the understory vegetation, the high morphological plasticity of mangrove trees induces, at the stand level, a very large variability of forest structures that need to be mapped for assessing the functioning of such complex ecosystems. Fully constrained linear spectral unmixing (FCLSU) of very high spatial resolution (VHSR) multispectral images was tested to fine-scale map mangrove zonations in terms of horizontal variation of forest structure. The study was carried out on three Pleiades-1A satellite images covering French island territories located in the Atlantic, Indian, and Pacific Oceans, namely Guadeloupe, Mayotte, and New Caledonia archipelagos. In each image, FCLSU was trained from the delineation of areas exclusively related to four components including either pure vegetation, soil (ferns included), water, or shadows. It was then applied to the whole mangrove cover imaged for each island and yielded the respective contributions of those four components for each image pixel. On the forest stand scale, the results interestingly indicated a close correlation between FCLSU-derived vegetation fractions and canopy closure estimated from hemispherical photographs R 2 = 0.95) and a weak relation with the Normalized Difference Vegetation Index (R 2 = 0.29). Classification of these fractions also offered the opportunity to detect and map horizontal patterns of mangrove structure in a given site. K-means classifications of fraction indeed showed a global view of mangrove structure organization in the three sites, complementary to the outputs obtained from spectral data analysis. Our findings suggest that the pixel intensity decomposition applied to VHSR multispectral satellite images can be a simple but valuable approach for (i) mangrove canopy monitoring and (ii) mangrove forest structure analysis in the perspective of assessing mangrove dynamics and productivity. As with Lidar-based surveys, these potential new mapping capabilities deserve further physically based interpretation of sunlight scattering mechanisms within forest canopy. © 2019 by the authors.