Abstract: Closely related tree species that grow in sympatry are abundant in rainforests. However, little is known of the ecoevolutionary processes that govern their niches and local coexistence. We assessed genetic species delimitation in closely related sympatric species belonging to two Neotropical tree species complexes and investigated their genomic adaptation to a fine-scale topographic gradient with associated edaphic and hydrologic features. Combining LiDAR-derived topography, tree inventories, and single nucleotide polymorphisms (SNPs) from gene capture experiments, we explored genome-wide population genetic structure, covariation of environmental variables, and genotype-environment association to assess microgeographic adaptations to topography within the species complexes Symphonia (Clusiaceae), and Eschweilera (Lecythidaceae) with three species per complex and 385 and 257 individuals genotyped, respectively. Within species complexes, closely related tree species had different realized optima for topographic niches defined through the topographic wetness index or the relative elevation, and species displayed genetic signatures of adaptations to these niches. Symphonia species were genetically differentiated along water and nutrient distribution particularly in genes responding to water deprivation, whereas Eschweilera species were genetically differentiated according to soil chemistry. Our results suggest that varied topography represents a powerful driver of processes modulating tropical forest biodiversity with differential adaptations that stabilize local coexistence of closely related tree species.

Abstract: Tropical forests are the most diverse and productive ecosystems on Earth. While better understanding of these forests is critical for our collective future, until quite recently efforts to measure and monitor them have been largely disconnected. Networking is essential to discover the answers to questions that transcend borders and the horizons of funding agencies. Here we show how a global community is responding to the challenges of tropical ecosystem research with diverse teams measuring forests tree-by-tree in thousands of long-term plots. We review the major scientific discoveries of this work and show how this process is changing tropical forest science. Our core approach involves linking long-term grassroots initiatives with standardized protocols and data management to generate robust scaled-up results. By connecting tropical researchers and elevating their status, our Social Research Network model recognises the key role of the data originator in scientific discovery. Conceived in 1999 with RAINFOR (South America), our permanent plot networks have been adapted to Africa (AfriTRON) and Southeast Asia (T-FORCES) and widely emulated worldwide. Now these multiple initiatives are integrated via ForestPlots.net cyber-infrastructure, linking colleagues from 54 countries across 24 plot networks. Collectively these are transforming understanding of tropical forests and their biospheric role. Together we have discovered how, where and why forest carbon and biodiversity are responding to climate change, and how they feedback on it. This long-term pan-tropical collaboration has revealed a large long-term carbon sink and its trends, as well as making clear which drivers are most important, which forest processes are affected, where they are changing, what the lags are, and the likely future responses of tropical forests as the climate continues to change. By leveraging a remarkably old technology, plot networks are sparking a very modern revolution in tropical forest science. In the future, humanity can benefit greatly by nurturing the grassroots communities now collectively capable of generating unique, long-term understanding of Earth's most precious forests.

Abstract: Tropical forests are generally considered to stand upon nutrient-poor soils, but soil nutrient concentrations and availabilities can vary greatly at local scale due to topographic effects on erosion and water drainage. In this study we physically and chemically characterised the soils of 12 study plots situated along a catena with a shallow slope in a tropical rainforest in French Guiana both during the wet and the dry season to evaluate seasonal differences. Soils along the catena were all Acrisols, but differed strongly in their water drainage flux. Over time, this differential drainage has led to differences in soil texture and mineral composition, affecting the adsorption of various nutrients, most importantly phosphorus. The more clayey soils situated on the slope of the catena had higher total concentrations of carbon, nitrogen, phosphorus and several micronutrients, while extractable nutrient concentrations were highest in the sandiest soils situated at the bottom of the catena. We found that carbon, nitrogen and extractable nutrients all varied seasonally, especially in the surface soil layer. These results are interesting because they show that, even at the local scale, small differences in topography can lead to large heterogeneity in nutrient concentrations, which can have large impacts on plant and microbial community organisation at the landscape level.

Abstract: The leaf economics spectrum1,2 and the global spectrum of plant forms and functions3 revealed fundamental axes of variation in plant traits, which represent different ecological strategies that are shaped by the evolutionary development of plant species2. Ecosystem functions depend on environmental conditions and the traits of species that comprise the ecological communities4. However, the axes of variation of ecosystem functions are largely unknown, which limits our understanding of how ecosystems respond as a whole to anthropogenic drivers, climate and environmental variability4,5. Here we derive a set of ecosystem functions6 from a dataset of surface gas exchange measurements across major terrestrial biomes. We find that most of the variability within ecosystem functions (71.8%) is captured by three key axes. The first axis reflects maximum ecosystem productivity and is mostly explained by vegetation structure. The second axis reflects ecosystem water-use strategies and is jointly explained by variation in vegetation height and climate. The third axis, which represents ecosystem carbon-use efficiency, features a gradient related to aridity, and is explained primarily by variation in vegetation structure. We show that two state-of-the-art land surface models reproduce the first and most important axis of ecosystem functions. However, the models tend to simulate more strongly correlated functions than those observed, which limits their ability to accurately predict the full range o

Abstract: Tropical forests disappear rapidly because of deforestation, yet they have the potential to regrow naturally on abandoned lands. We analyze how 12 forest attributes recover during secondary succession and how their recovery is interrelated using 77 sites across the tropics. Tropical forests are highly resilient to low-intensity land use; after 20 years, forest attributes attain 78% (33 to 100%) of their old-growth values. Recovery to 90% of old-growth values is fastest for soil (<1 decade) and plant functioning (<2.5 decades), intermediate for structure and species diversity (2.5 to 6 decades), and slowest for biomass and species composition (>12 decades). Network analysis shows three independent clusters of attribute recovery, related to structure, species diversity, and species composition. Secondary forests should be embraced as a low-cost, natural solution for ecosystem restoration, climate change mitigation, and biodiversity conservation.