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: Selective logging in tropical forests is often perceived as a source of forest degradation and carbon emissions. Improved practices, such as reduced-impact logging (RIL), and alternative timber production strategies (e.g. plantations) can drastically change the overall carbon impact of the wood production sector. Assessing the carbon balance of timber production is crucial but highly dependent on methodological approaches, especially regarding system boundaries and temporality. We developed a temporally-explicit and territory scale model of carbon balance calibrated with long-term local data using Bayesian inference. The model accounts for carbon fluxes from selective logging in natural forest, timber plantation, first transformation and avoided emissions through energy substitution. We used it to compare prospective scenarios of development for the wood sector in French Guiana. Results show that intensification of practices, through increased logging intensity conducted with RIL and establishment of timber plantations, are promising development strategies to reduce the carbon emissions of the French-Guianese wood sector, as well as the area needed for wood production and hence the pressure on natural forests. By reducing logging damage by nearly 50%, RIL allows increasing logging intensity in natural forest from 20 m3 ha−1 to 30 m3 ha−1 without affecting the carbon balance. The use of logging byproducts as fuelwood also improved the carbon balance of selective logging, when substituted to fossil fuel. Allocating less than 30 000 ha to plantation would allow producing 200 000 m3 of timber annually, while the same production in natural forest would imply logging more than 400 000 ha over 60 years. Timber plantation should be preferentially established on non-forested lands, as converting natural forests to plantation leads to high carbon emission peak over the first three decades. We recommend a mixed-strategy combining selective logging in natural forests and plantations as a way to improve long-term carbon balance while reducing short-term emissions. This strategy can reduce the pressure on natural forests while mitigating the risks of changing practices and allowing a diversified source of timber for a diversity of uses. It requires adaptation of the wood sector and development of technical guidelines. Research and monitoring efforts are also needed to assess the impacts of changing practices on other ecosystem services, especially biodiversity conservation.

Abstract: Soil in the tropics is high in diversity, and despite the diversity of Borneo’s forest–soil associations, there is a paucity of data on its soil properties. We investigated the differences between three soil types in the Kabili–Sepilok Forest Reserve, Sabah, Malaysia, encompassing the contrasting alluvial, sandstone and heath forest typologies. We examined the distribution of nutrients between soil types and through soil depths, and assessed the extent of spatial autocorrelation in the three soil types. We confirmed the fertility gradient from alluvial to heath forest soil found by others. Soil elemental concentrations declined in deeper horizons with the exception of exchangeable sodium and aluminium that remained constant through alluvial and sandstone soil profiles. Spatial autocorrelation was present in all three soil types and strongest in the sandstone soil. Overall, we show how bedrock, erosion, leaching and topography influence soil properties across this mosaic of soil types and note their importance in influencing tree communities and their ecological functioning.

Abstract: Environmental DNA (eDNA) metabarcoding has emerged as one of the most efficient methods to assess aquatic species presence. While the method can in theory be used to investigate nonaquatic fauna, its development for inventorying semi-aquatic and terrestrial fauna is still at an early stage. Here we investigated the potential of aquatic eDNA metabarcoding for inventorying mammals in Neotropical environments, be they aquatic, semi-aquatic or terrestrial. We collected aquatic eDNA in 96 sites distributed along three Guianese watersheds and compared our inventories to expected species distributions and field observations derived from line transects located throughout French Guiana. Species occurrences and emblematic mammalian fauna richness patterns were consistent with the expected distribution of fauna and our results revealed that aquatic eDNA metabarcoding brings additional data to line transect samples for diurnal nonaquatic (terrestrial and arboreal) species. Aquatic eDNA also provided data on species not detectable in line transect surveys such as semi-aquatic, aquatic and nocturnal terrestrial and arboreal species. Although the application of eDNA to inventory mammals still needs some developments to optimize sampling efficiency, it can now be used as a complement to traditional surveys.

Abstract: Functional traits determine an organism's performance in a given environment and as such determine which organisms will be found where. Species respond to local conditions, but also to larger scale gradients, such as climate. Trait ecology links these responses of species to community composition and species distributions. Yet, we often do not know which environmental gradients are most important in determining community trait composition at either local or biogeographical scales, or their interaction. Here we quantify the relative contribution of local and climatic conditions to the structure and composition of functional traits found within bromeliad invertebrate communities. We conclude that climate explains more variation in invertebrate trait composition within bromeliads than does local conditions. Importantly, climate mediated the response of traits to local conditions; for example, invertebrates with benthic life-history traits increased with bromeliad water volume only under certain precipitation regimes. Our ability to detect this and other patterns hinged on the compilation of multiple fine-grained datasets, allowing us to contrast the effect of climate versus local conditions. We suggest that, in addition to sampling communities at local scales, we need to aggregate studies that span large ranges in climate variation in order to fully understand trait filtering at local, regional and global scales.