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Abstract Using 2.046 botanically-inventoried tree plots across the largest tropical forest on Earth, we mapped tree species-diversity and tree species-richness at 0.1-degree resolution, and investigated drivers for diversity and richness. Using only location, stratified by forest type, as predictor, our spatial model, to the best of our knowledge, provides the most accurate map of tree diversity in Amazonia to date, explaining approximately 70% of the tree diversity and species-richness. Large soil-forest combinations determine a significant percentage of the variation in tree species-richness and tree alpha-diversity in Amazonian forest-plots. We suggest that the size and fragmentation of these systems drive their large-scale diversity patterns and hence local diversity. A model not using location but cumulative water deficit, tree density, and temperature seasonality explains 47% of the tree species-richness in the terra-firme forest in Amazonia. Over large areas across Amazonia, residuals of this relationship are small and poorly spatially structured, suggesting that much of the residual variation may be local. The Guyana Shield area has consistently negative residuals, showing that this area has lower tree species-richness than expected by our models. We provide extensive plot meta-data, including tree density, tree alpha-diversity and tree species-richness results and gridded maps at 0.1-degree resolution.

Abstract In a time of rapid global change, the question of what determines patterns in species abundance distribution remains a priority for understanding the complex dynamics of ecosystems. The constrained maximization of information entropy provides a framework for the understanding of such complex systems dynamics by a quantitative analysis of important constraints via predictions using least biased probability distributions. We apply it to over two thousand hectares of Amazonian tree inventories across seven forest types and thirteen functional traits, representing major global axes of plant strategies. Results show that constraints formed by regional relative abundances of genera explain eight times more of local relative abundances than constraints based on directional selection for specific functional traits, although the latter does show clear signals of environmental dependency. These results provide a quantitative insight by inference from large-scale data using cross-disciplinary methods, furthering our understanding of ecological dynamics.

Functional variations in tropical forests can be determined from remotely sensed forest trait and structural attributes at spatial resolutions relevant to satellite-based observations, according to a coarse resolution analysis of airborne remotely sensed data in Malaysian Borneo.

Global patterns of regional plant diversity are relatively well known, but whether they hold for local communities is debated. This study created multi-grain global maps of alpha diversity for vascular plants to provide a nuanced understanding of plant diversity hotspots and improve predictions of global change effects on biodiversity.

The need to measure, monitor, and understand our living planet is greater than ever. Yet, while many technologies are applied to tackle this need, one developed in the 19th century is transforming tropical ecology. Permanent plots, in which forests are directly sensed tree-by-tree and species-by-species, already provide a global public good. They could make greater contributions still by unlocking our potential to understand future ecological change, as the more that computational and remote technologies are deployed the greater the need to ground them with direct observations and the physical, nature-based skills of those who make them. To achieve this requires building profound connections with forests and disadvantaged communities and sustaining these over time. Many of the greatest needs and opportunities in tropical forest science are therefore not to be found in space or in silico, but in vivo, with the people, places and plots who experience nature directly. These are fundamental to understanding the health, predicting the future, and exploring the potential of Earth’s richest ecosystems. Now is the time to invest in the tropical field research communities who make so much possible.

Abstract Background Many significant ecosystems, including important non-forest woody ecosystems such as the Cerrado (Brazilian savannah), are under threat from climate change, yet our understanding of how increasing temperatures will impact native vegetation remains limited. Temperature manipulation experiments are important tools for investigating such impacts, but are often constrained by access to power supply and limited to low-stature species, juvenile individuals, or heating of target organs, perhaps not fully revealing how entire or mature individuals and ecosystems will react to higher temperatures. Results We present a novel, modified open top chamber design for in situ passive heating of whole individuals up to 2.5 m tall (but easily expandable) in remote field environments with strong solar irradiance. We built multiple whole-tree heating structures (WTHSs) in an area of Cerrado around native woody species Davilla elliptica and Erythroxylum suberosum to test the design and its effects on air temperature and humidity, while also studying the physiological responses of E. suberosum to short-term heating. The WTHSs raised internal air temperature by approximately 2.5 °C above ambient during the daytime. This increased to 3.4 °C between 09:00 and 17:00 local time when thermal impact was greatest, and during which time mean internal temperatures corresponded closely with maximum ambient temperatures. Heating was consistent over time and across WTHSs of variable size and shape, and they had minimal effect on humidity. E. suberosum showed no detectable response of photosynthesis or respiration to short-term experimental heating, but some indication of acclimation to natural temperature changes. Conclusions Our WTHSs produced a consistent and reproducible level of daytime heating in line with mid-range climate predictions for the Cerrado biome by the end of the century. The whole-tree in situ passive heating design is flexible, low-cost, simple to build using commonly available materials, and minimises negative impacts associated with passive chambers. It could be employed to investigate the high temperature responses of many understudied species in a range of complex non-forest environments with sufficient solar irradiance, providing new and important insights into the possible impacts of our changing climate.

Abstract Despite increasing attention for relationships between species richness and ecosystem services, for tropical forests such relationships are still under discussion. Contradicting relationships have been reported concerning carbon stock, while little is known about relationships concerning timber stock and the abundance of non-timber forest product producing plant species (NTFP abundance). Using 151 1-ha plots, we related tree and arborescent palm species richness to carbon stock, timber stock and NTFP abundance across the Guiana Shield, and using 283 1-ha plots, to carbon stock across all of Amazonia. We analysed how environmental heterogeneity influenced these relationships, assessing differences across and within multiple forest types, biogeographic regions and subregions. Species richness showed significant relationships with all three ecosystem services, but relationships differed between forest types and among biogeographical strata. We found that species richness was positively associated to carbon stock in all biogeographical strata. This association became obscured by variation across biogeographical regions at the scale of Amazonia, resembling a Simpson’s paradox. By contrast, species richness was weakly or not significantly related to timber stock and NTFP abundance, suggesting that species richness is not a good predictor for these ecosystem services. Our findings illustrate the importance of environmental stratification in analysing biodiversity-ecosystem services relationships.

Drought and fire reduce productivity and increase tree mortality in tropical forests. Fires also produce pyrogenic carbon (PyC), which persists in situ for centuries to millennia, and represents a legacy of past fires, potentially improving soil fertility and water holding capacity and selecting for the survival and recruitment of certain tree life-history (or successional) strategies. We investigated whether PyC is correlated with physicochemical soil properties, wood density, aboveground carbon (AGC) dynamics and forest resistance to severe drought. To achieve our aim, we used an Amazon-wide, long-term plot network, in forests without known recent fires, integrating site-specific measures of forest dynamics, soil properties and a unique soil PyC concentration database. We found that forests with higher concentrations of soil PyC had both higher soil fertility and lower wood density. Soil PyC was not associated with AGC dynamics in non-drought years. However, during extreme drought events (10% driest years), forests with higher concentrations of soil PyC experienced lower reductions in AGC gains (woody growth and recruitment), with this drought-immunizing effect increasing with drought severity. Forests with a legacy of ancient fires are therefore more likely to continue to grow and recruit under increased drought severity. Forests with high soil PyC concentrations (third quartile) had 3.8% greater AGC gains under mean drought, but 33.7% greater under the most extreme drought than forests with low soil PyC concentrations (first quartile), offsetting losses of up to 0.68 Mg C ha–1yr–1 of AGC under extreme drought events. This suggests that ancient fires have legacy effects on current forest dynamics, by altering soil fertility and favoring tree species capable of continued growth and recruitment during droughts. Therefore, mature forest that experienced fires centuries or millennia ago may have greater resistance to current short-term droughts.

A study using paired 15N tracers shows atmospheric N deposited in oxidized form is more likely retained by trees, while the reduced form is retained in soil. The authors argue that this is a greater contribution of deposited N to the global forest C sink than previously reported.

The Amazon forest represents one of the world’s largest terrestrial carbon reservoirs. Here, we evaluated the role of soil texture, climate, vegetation, and distance to savanna on the distribution and stocks of soil pyrogenic carbon (PyC) in intact forests with no history of recent fire spanning the southern Amazonia forest-Cerrado Zone of Transition (ZOT). In 19 one hectare forest plots, including three Amazonian Dark Earth (ADE, terra preta) sites with high soil PyC, we measured all trees and lianas with diameter ≥ 10 cm and analyzed soil physicochemical properties, including texture and PyC stocks. We quantified PyC stocks as a proportion of total organic carbon using hydrogen pyrolysis. We used multiple linear regression and variance partitioning to determine which variables best explain soil PyC variation. For all forests combined, soil PyC stocks ranged between 0.9 and 6.8 Mg/ha to 30 cm depth (mean 2.3 ± 1.5 Mg/ha) and PyC, on average, represented 4.3% of the total soil organic carbon (SOC). The most parsimonious model (based on AICc) included soil clay content and above-ground biomass (AGB) as the main predictors, explaining 71% of soil PyC variation. After removal of the ADE plots, PyC stocks ranged between 0.9 and 3.8 Mg/ha (mean 1.9 ± 0.8 Mg/ha–1) and PyC continued to represent ∼4% of the total SOC. The most parsimonious models without ADE included AGB and sand as the best predictors, with sand and PyC having an inverse relationship, and sand explaining 65% of the soil PyC variation. Partial regression analysis did not identify any of the components (climatic, environmental, and edaphic), pure or shared, as important in explaining soil PyC variation with or without ADE plots. We observed a substantial amount of soil PyC, even excluding ADE forests; however, contrary to expectations, soil PyC stocks were not higher nearer to the fire-dependent Cerrado than more humid regions of Amazonia. Our findings that soil texture and AGB explain the distribution and amount of soil PyC in ZOT forests will help to improve model estimates of SOC change with further climatic warming.

Phytolith analysis is a well-established archaeobotanical tool, having provided important insights into pre-Columbian crop cultivation and domestication across Amazonia through the Holocene. Yet, its use as a palaeoecological tool is in its infancy in Amazonia and its effectiveness for reconstructing pre-Columbian land-use beyond archaeological sites (i.e., ‘off-site’) has so far received little critical attention. This paper examines both new and previously published soil phytolith data from SW Amazonia to assess the robustness of this proxy for reconstructing pre-Columbian land-use. We conducted the study via off-site soil pits radiating 7.5 km beyond a geoglyph in Acre state, Brazil, and 50 km beyond a ring-ditch in northern Bolivia, spanning the expected gradients in historical land-use intensity. We found that the spatio-temporal patterns in palm phytolith data across our soil-pit transects support the hypothesis that pre-Columbian peoples enriched their forests with palms over several millennia, although phytoliths are limited in their ability to capture small-scale crop cultivation and deforestation. Despite these drawbacks, we conclude that off-site soil phytolith analysis can provide novel insights into pre-Columbian land use, provided it is effectively integrated with other land-use (e.g., charcoal) and archaeological data.

Societal Impact Statement The approach that we take to our science is as important as the questions that we address if we would like our research to inform management. Here, we discuss our experience of using networks of permanent forest inventory plots to support sustainable management and conservation of intact tropical forests. A key conclusion is that to maximize the use of data from such large international networks within policymaking, it is crucial that leadership is widely shared among participants. Such an approach helps to address ethical concerns surrounding international collaborations and also achieves greater policy impact. Summary Long‐term data from permanent forest inventory plots have much to offer the management and conservation of intact tropical forest landscapes. Knowledge of the growth and mortality rates of economically important species, forest carbon balance, and the impact of climate change on forest composition are all central to effective management. However, this information is rarely integrated within the policymaking process. The problem reflects broader issues in using evidence to influence environmental management, and in particular, the need to engage with potential users beyond the collection and publication of high‐quality data. To ensure permanent plot data are used, (a) key “policy windows”—opportunities to integrate data within policy making—need to be identified; (b) long‐term relationships need to be developed between scientists and policy makers and policymaking organizations; and (c) leadership of plot networks needs to be shared among all participants, and particularly between institutions in the global north and those in tropical countries. Addressing these issues will allow permanent plot networks to make tangible contributions to ensuring that intact tropical forest persists over coming decades.

Societal Impact Statement Understanding of tropical forests has been revolutionized by monitoring in permanent plots. Data from global plot networks have transformed our knowledge of forests’ diversity, function, contribution to global biogeochemical cycles, and sensitivity to climate change. Monitoring has thus far been concentrated in rain forests. Despite increasing appreciation of their threatened status, biodiversity, and importance to the global carbon cycle, monitoring in tropical dry forests is still in its infancy. We provide a protocol for permanent monitoring plots in tropical dry forests. Expanding monitoring into dry biomes is critical for overcoming the linked challenges of climate change, land use change, and the biodiversity crisis.

The role of non-structural carbohydrates (NSC) in mediating the impacts of drought in tropical trees is unclear. Here, the authors analyse leaf and branch NSC in 82 Amazon tree species across a Basin-wide precipitation gradient, finding that allocation of leaf NSC to soluble sugars is higher in drier sites and is coupled to tree hydraulic status.

Here, the authors investigate the aboveground carbon sink efficiency of Andean forests. The study shows the high potential of these forests to serve as future carbon refuges, and urges to reduce deforestation and increase restoration.

Fire has a historical role in tropical forests related to past climate and ancient land use spanning the Holocene; however, it is unclear from charcoal records how fire varied at different spatiotemporal scales and what sampling strategies are required to determine fire history and their effects. We evaluated fire variation in structurally intact, terra-firme Amazon forests, by intensive soil charcoal sampling from three replicate soil pits in sites in Guyana and northern and southern Peru. We used radiocarbon (14C) measurement to assess (1) locally, how the timing of fires represented in our sample varied across the surface of forest plots and with soil depth, (2) basin-wide, how the age of fires varies across climate and environmental gradients, and (3) how many samples are appropriate when applying the 14C approach to assess the date of last fire. Considering all 14C dates (n = 33), the most recent fires occurred at a similar time at each of the three sites (median ages: 728–851 cal years BP), indicating that in terms of fire disturbance at least, these forests could be considered old-growth. The number of unique fire events ranged from 1 to 4 per pit and from 4 to 6 per site. Based upon our sampling strategy, the N-Peru site—with the highest annual precipitation—had the most fire events. Median fire return intervals varied from 455 to 2,950 cal years BP among sites. Based on available dates, at least three samples (1 from the top of each of 3 pits) are required for the sampling to have a reasonable likelihood of capturing the most recent fire for forests with no history of a recent fire. The maximum fire return interval for two sites was shorter than the time since the last fire, suggesting that over the past ∼800 years these forests have undergone a longer fire-free period than the past 2,000–3,500 years. Our analysis from terra-firme forest soils helps to improve understanding of changes in fire regime, information necessary to evaluate post-fire legacies on modern vegetation and soil and to calibrate models to predict forest response to fire under climate change.

Abstract We report large-scale estimates of Amazonian gap dynamics using a novel approach with large datasets of airborne light detection and ranging (lidar), including five multi-temporal and 610 single-date lidar datasets. Specifically, we (1) compared the fixed height and relative height methods for gap delineation and established a relationship between static and dynamic gaps (newly created gaps); (2) explored potential environmental/climate drivers explaining gap occurrence using generalized linear models; and (3) cross-related our findings to mortality estimates from 181 field plots. Our findings suggest that static gaps are significantly correlated to dynamic gaps and can inform about structural changes in the forest canopy. Moreover, the relative height outperformed the fixed height method for gap delineation. Well-defined and consistent spatial patterns of dynamic gaps were found over the Amazon, while also revealing the dynamics of areas never sampled in the field. The predominant pattern indicates 20–35% higher gap dynamics at the west and southeast than at the central-east and north. These estimates were notably consistent with field mortality patterns, but they showed 60% lower magnitude likely due to the predominant detection of the broken/uprooted mode of death. While topographic predictors did not explain gap occurrence, the water deficit, soil fertility, forest flooding and degradation were key drivers of gap variability at the regional scale. These findings highlight the importance of lidar in providing opportunities for large-scale gap dynamics and tree mortality monitoring over the Amazon.

Tree mortality has been shown to be the dominant control on carbon storage in Amazon forests, but little is known of how and why Amazon forest trees die. Here the authors analyse a large Amazon-wide dataset, finding that fast-growing species face greater mortality risk, but that slower-growing individuals within a species are more likely to die, regardless of size.

Tree mortality rates and the modes of tree death have recently been extensively investigated in the Amazon. However, efforts to describe these processes have not been well distributed across the basin. No study has yet investigated in depth tree mortality process in the unique low, open, bamboo-dominated forests of southwestern Amazonia, a region with a distinct climate and the epicenter of recent severe drought events. Here, we investigated the leading ways that trees die in the terra-firme forests of the southwestern Brazilian Amazon, to understand whether the dynamics of mortality differ from those recorded in other parts of the basin. Using data from six permanent plots located in southwestern Amazonia, we calculated the mortality rate for three main modes of tree death: standing, broken and uprooted. We thus identified the predominant mode of death over a 14 year period (2002–2016). We found that trees in the southwestern Amazon died mainly standing (325 trees, 0.8% year−1) and broken (362 trees, 0.8% year−1); significantly fewer trees died uprooted (156 trees, 0.4% year−1, equivalent to less than one in five of all trees dying). During the study period, the tree mode of death with the greatest proportion in the region alternated between standing and broken trees. Forest characteristics of the southwestern Amazon, like presence and high density of bamboo culms, and the fact that the region was subject to severe droughts in 2005 and 2010, may be affecting how trees die in southwestern Amazon. The presence of these factors makes the forest dynamics of the southwestern Amazon different from other regions of the Amazon basin.

Different aspects of biodiversity may not necessarily converge in their response to climate change. Here, the authors investigate 25-year shifts in taxonomic, functional and phylogenetic diversity of tropical forests along a spatial climate gradient in West Africa, showing that drier forests are less stable than wetter forests.

Abstract Background Long-term studies of community and population dynamics indicate that abrupt disturbances often catalyse changes in vegetation and carbon stocks. These disturbances include the opening of clearings, rainfall seasonality, and drought, as well as fire and direct human disturbance. Such events may be super-imposed on longer-term trends in disturbance, such as those associated with climate change (heating, drying), as well as resources. Intact neotropical forests have recently experienced increased drought frequency and fire occurrence, on top of pervasive increases in atmospheric CO2 concentrations, but we lack long-term records of responses to such changes especially in the critical transitional areas at the interface of forest and savanna biomes. Here, we present results from 20 years monitoring a valley forest (moist tropical forest outlier) in central Brazil. The forest has experienced multiple drought events and includes plots which have and which have not experienced fire. We focus on how forest structure (stem density and aboveground biomass carbon) and dynamics (stem and biomass mortality and recruitment) have responded to these disturbance regimes. Results Overall, the biomass carbon stock increased due to the growth of the trees already present in the forest, without any increase in the overall number of tree stems. Over time, both recruitment and especially mortality of trees tended to increase, and periods of prolonged drought in particular resulted in increased mortality rates of larger trees. This increased mortality was in turn responsible for a decline in aboveground carbon toward the end of the monitoring period. Conclusion Prolonged droughts influence the mortality of large trees, leading to a decline in aboveground carbon stocks. Here, and in other neotropical forests, recent droughts are capable of shutting down and reversing biomass carbon sinks. These new results add to evidence that anthropogenic climate changes are already adversely impacting tropical forests.

Abstract Mapping forest types and tree species at regional scales to provide information for ecologists and forest managers is a new challenge for the remote sensing community. Here, we assess the potential of a U‐net convolutional network, a recent deep learning algorithm, to identify and segment (1) natural forests and eucalyptus plantations, and (2) an indicator of forest disturbance, the tree species Cecropia hololeuca, in very high resolution images (0.3 m) from the WorldView‐3 satellite in the Brazilian Atlantic rainforest region. The networks for forest types and Cecropia trees were trained with 7611 and 1568 red‐green‐blue (RGB) images, respectively, and their dense labeled masks. Eighty per cent of the images were used for training and 20% for validation. The U‐net network segmented forest types with an overall accuracy >95% and an intersection over union (IoU) of 0.96. For C. hololeuca, the overall accuracy was 97% and the IoU was 0.86. The predictions were produced over a 1600 km2 region using WorldView‐3 RGB bands pan‐sharpened at 0.3 m. Natural and eucalyptus forests compose 79 and 21% of the region's total forest cover (82 250 ha). Cecropia crowns covered 1% of the natural forest canopy. An index to describe the level of disturbance of the natural forest fragments based on the spatial distribution of Cecropia trees was developed. Our work demonstrates how a deep learning algorithm can support applications such as vegetation, tree species distributions and disturbance mapping on a regional scale.

Abstract Various historical processes have been put forth as drivers of patterns in the spatial distribution of Amazonian trees and their population genetic variation. We tested whether five widespread tree species show congruent phylogeographic breaks and similar patterns of demographic expansion, which could be related to proposed Pleistocene refugia or the presence of geological arches in western Amazonia. We sampled Otoba parvifolia/glycycarpa (Myristicaceae), Clarisia biflora, Poulsenia armata, Ficus insipida (all Moraceae), and Jacaratia digitata (Caricaceae) across the western Amazon Basin. Plastid DNA (trnH–psbA; 674 individuals from 34 populations) and nuclear ribosomal internal transcribed spacers (ITS; 214 individuals from 30 populations) were sequenced to assess genetic diversity, genetic differentiation, population genetic structure, and demographic patterns. Overall genetic diversity for both markers varied among species, with higher values in populations of shade‐tolerant species than in pioneer species. Spatial analysis of molecular variance (SAMOVA) identified three genetically differentiated groups for the plastid marker for each species, but the areas of genetic differentiation were not concordant among species. Fewer SAMOVA groups were found for ITS, with no detectable genetic differentiation among populations in pioneers. The lack of spatially congruent phylogeographic breaks across species suggests no common biogeographic history of these Amazonian tree species. The idiosyncratic phylogeographic patterns of species could be due instead to species‐specific responses to geological and climatic changes. Population genetic patterns were similar among species with similar biological features, indicating that the ecological characteristics of species impact large‐scale phylogeography.

Lianas are woody vines, rooted in the soil, and supported physically by trees. Lianas contribute to forest ecosystem functioning globally, but especially in the tropics and subtropics. However, prolific liana growth following heavy disturbance frequently affects subsequent recovery of forest tree diversity, biomass, structure, and function. Understanding this forest liana dynamic, and its sensitivity to climate and anthropogenic forces, is essential for worldwide forest restoration and climate change mitigation. Here, we synthesise the evidence for both positive and negative effects of lianas on forests and propose a framework that outlines the expected global response of forests to disturbance-induced liana proliferation. Emerging evidence suggests that lianas play a major role in both facilitating and delaying forest recovery following disturbance. At low levels of disturbance and/or where environmental conditions favour tree growth, lianas can facilitate forest recovery by protecting trees from extreme weather, fire, weed invasion and herbivory. However, under conditions where lianas proliferate beyond critical thresholds, positive feedbacks are expected to induce and sustain liana-dominated forest states that can endure for decades or even longer. We conceptualise alternative classes of forest recovery response to disturbance and describe measurement and modelling of liana thresholds. We identify four essential challenges for global change science relating to lianas: (1) incorporation of lianas and sapling stems into forest monitoring and tree stand measurements worldwide; (2) long-term experiments to determine variation in liana-tree competition, and potential drivers across forest successional gradients; (3) identification and prediction of liana thresholds and other alternative forest recovery response classes; and (4) dynamic mechanistic modelling of forest recovery to determine regional and global variation within and among different recovery response classes, in relation to variation in potential drivers, liana feedbacks and their interactions. Addressing these challenges will determine the importance of lianas in shaping regional and global forest composition, recovery and dynamics.

Above-ground biomass (AGB) is an essential descriptor of forests, of use in ecological and climate-related research. At tree- and stand-scale, destructive but direct measurements of AGB are replaced with predictions from allometric models characterizing the correlational relationship between AGB, and predictor variables including stem diameter, tree height and wood density. These models are constructed from harvested calibration data, usually via linear regression. Here, we assess systematic error in out-of-sample predictions of AGB introduced during measurement, compilation and modeling of in-sample calibration data. Various conventional bivariate and multivariate models are constructed from open access data of tropical forests. Metadata analysis, fit diagnostics and cross-validation results suggest several model misspecifications: chiefly, unaccounted for inconsistent measurement error in predictor variables between in- and out-of-sample data. Simulations demonstrate conservative inconsistencies can introduce significant bias into tree- and stand-scale AGB predictions. When tree height and wood density are included as predictors, models should be modified to correct for bias. Finally, we explore a fundamental assumption of conventional allometry, that model parameters are independent of tree size. That is, the same model can provide predictions of consistent trueness irrespective of size-class. Most observations in current calibration datasets are from smaller trees, meaning the existence of a size dependency would bias predictions for larger trees. We determine that detecting the absence or presence of a size dependency is currently prevented by model misspecifications and calibration data imbalances. We call for the collection of additional harvest data, specifically under-represented larger trees.

Deforestation carbon emissions from the Brazilian Amazon have declined steeply, but how much drought-induced forest fire emissions add to this process is still unclear. Here the authors show that gross emissions from forest fires are more than half as great as those from deforestation during drought years.

The existence of a pan-tropical forest carbon sink remains uncertain due to the lack of data from Asia. Here, using direct on-the-ground observations, the authors confirm remaining intact forests in Borneo have provided a long-term carbon sink, but carbon net gains are vulnerable to drought and edge effects.

A Correction to this paper has been published: https://doi.org/10.1038/s41467-020-20537-x

Abstract High levels of species diversity hamper current understanding of how tropical forests may respond to environmental change. In the tropics, water availability is a leading driver of the diversity and distribution of tree species, suggesting that many tropical taxa may be physiologically incapable of tolerating dry conditions, and that their distributions along moisture gradients can be used to predict their drought tolerance. While this hypothesis has been explored at local and regional scales, large continental-scale tests are lacking. We investigate whether the relationship between drought-induced mortality and distributions holds continentally by relating experimental and observational data of drought-induced mortality across the Neotropics to the large-scale bioclimatic distributions of 115 tree genera. Across the different experiments, genera affiliated to wetter climatic regimes show higher drought-induced mortality than dry-affiliated ones, even after controlling for phylogenetic relationships. This pattern is stronger for adult trees than for saplings or seedlings, suggesting that the environmental filters exerted by drought impact adult tree survival most strongly. Overall, our analysis of experimental, observational, and bioclimatic data across neotropical forests suggests that increasing moisture-stress is indeed likely to drive significant changes in floristic composition.

Abstract Background Several independent lines of evidence suggest that Amazon forests have provided a significant carbon sink service, and also that the Amazon carbon sink in intact, mature forests may now be threatened as a result of different processes. There has however been no work done to quantify non-land-use-change forest carbon fluxes on a national basis within Amazonia, or to place these national fluxes and their possible changes in the context of the major anthropogenic carbon fluxes in the region. Here we present a first attempt to interpret results from ground-based monitoring of mature forest carbon fluxes in a biogeographically, politically, and temporally differentiated way. Specifically, using results from a large long-term network of forest plots, we estimate the Amazon biomass carbon balance over the last three decades for the different regions and nine nations of Amazonia, and evaluate the magnitude and trajectory of these differentiated balances in relation to major national anthropogenic carbon emissions. Results The sink of carbon into mature forests has been remarkably geographically ubiquitous across Amazonia, being substantial and persistent in each of the five biogeographic regions within Amazonia. Between 1980 and 2010, it has more than mitigated the fossil fuel emissions of every single national economy, except that of Venezuela. For most nations (Bolivia, Colombia, Ecuador, French Guiana, Guyana, Peru, Suriname) the sink has probably additionally mitigated all anthropogenic carbon emissions due to Amazon deforestation and other land use change. While the sink has weakened in some regions since 2000, our analysis suggests that Amazon nations which are able to conserve large areas of natural and semi-natural landscape still contribute globally-significant carbon sequestration. Conclusions Mature forests across all of Amazonia have contributed significantly to mitigating climate change for decades. Yet Amazon nations have not directly benefited from providing this global scale ecosystem service. We suggest that better monitoring and reporting of the carbon fluxes within mature forests, and understanding the drivers of changes in their balance, must become national, as well as international, priorities.

Climate, species composition, and soils are thought to control carbon cycling and forest structure in Amazonian forests. Here, we add a demographics scheme (tree recruitment, growth, and mortality) to a recently developed non-demographic model—the Trait-based Forest Simulator (TFS)—to explore the roles of climate and plant traits in controlling forest productivity and structure. We compared two sites with differing climates (seasonal vs. aseasonal precipitation) and plant traits. Through an initial validation simulation, we assessed whether the model converges on observed forest properties (productivity, demographic and structural variables) using datasets of functional traits, structure, and climate to model the carbon cycle at the two sites. In a second set of simulations, we tested the relative importance of climate and plant traits for forest properties within the TFS framework using the climate from the two sites with hypothetical trait distributions representing two axes of functional variation (“fast” vs. “slow” leaf traits, and high vs. low wood density). The adapted model with demographics reproduced observed variation in gross (GPP) and net (NPP) primary production, and respiration. However, NPP and respiration at the level of plant organs (leaf, stem, and root) were poorly simulated. Mortality and recruitment rates were underestimated. The equilibrium forest structure differed from observations of stem numbers suggesting either that the forests are not currently at equilibrium or that mechanisms are missing from the model. Findings from the second set of simulations demonstrated that differences in productivity were driven by climate, rather than plant traits. Contrary to expectation, varying leaf traits had no influence on GPP. Drivers of simulated forest structure were complex, with a key role for wood density mediated by its link to tree mortality. Modeled mortality and recruitment rates were linked to plant traits alone, drought-related mortality was not accounted for. In future, model development should focus on improving allocation, mortality, organ respiration, simulation of understory trees and adding hydraulic traits. This type of model that incorporates diverse tree strategies, detailed forest structure and realistic physiology is necessary if we are to be able to simulate tropical forest responses to global change scenarios.

Global changes, e.g. global warming, elevated nitrogen deposition, and shifts of precipitation regime, exert a major influence on forests via affecting plant water use efficiency (WUE) and plant nitrogen (N) availability. Large-scale ecological sampling can help us to better understand variation across regions and provide opportunities to investigate the potential impacts of multiple aspects of global change on forest ecosystem responses. Here, we determine the geographical patterns of key isotopic measures of ecosystem function—plant WUE (calculated from foliar δ ^13 C values) and plant N availability (assessed by foliar δ ^15 N values)—across China’s forests covering ∼21 latitude (∼22–43°N) and ∼28 longitude (∼93–121°E) degree, and investigate how a suite of soil, plant, and atmospheric factors regulate them. We found that plant WUE increased but N availability decreased with latitude, while plant WUE and N availability did not vary with longitudinal gradient. Different factors regulate the large-scale patterns in WUE and N availability. The mean annual temperature, atmospheric N deposition, and soil water content exhibit considerable effects on plant WUE over both the north-to-south and east-to-west transects, while the mean annual precipitation, soil potassium content, foliar N, and precipitation seasonality considerably affect the latitudinal patterns of plant N availability. In addition, the east-to-west spatial pattern in plant N availability is associated with the variation in solar radiation. Our results suggest that key forest ecological functions respond to an array of environmental factors, and imply that changes in many different environmental attributes need to be considered in order to successfully assess plant WUE and N availability responses to global changes this century.

Mapping plant species at the regional scale to provide information for ecologists and forest managers is a challenge for the remote sensing community. Here, we use a deep learning algorithm called U-net and very high-resolution multispectral images (0.5 m) from GeoEye satellite to identify, segment and map canopy palms over ∼3000 km 2 of Amazonian forest. The map was used to analyse the spatial distribution of canopy palm trees and its relation to human disturbance and edaphic conditions. The overall accuracy of the map was 95.5% and the F1-score was 0.7. Canopy palm trees covered 6.4% of the forest canopy and were distributed in more than two million patches that can represent one or more individuals. The density of canopy palms is affected by human disturbance. The post-disturbance density in secondary forests seems to be related to the type of disturbance, being higher in abandoned pasture areas and lower in forests that have been cut once and abandoned. Additionally, analysis of palm trees’ distribution shows that their abundance is controlled naturally by local soil water content, avoiding both flooded and waterlogged areas near rivers and dry areas on the top of the hills. They show two preferential habitats, in the low elevation above the large rivers, and in the slope directly below the hill tops. Overall, their distribution over the region indicates a relatively pristine landscape, albeit within a forest that is critically endangered because of its location between two deforestation fronts and because of illegal cutting. New tree species distribution data, such as the map of all adult canopy palms produced in this work, are urgently needed to support Amazon species inventory and to understand their distribution and diversity.

An amendment to this paper has been published and can be accessed via the original article.

In this study we evaluated the floristic composition and changes in stored biomass and dynamics over time in 9 permanent plots monitored by RAINFOR (Amazon Forest Inventory Network) and located in the lowland Amazon rainforest of the Tambopata National Reserve. Data were acquired in the field using the standardized methodology of RAINFOR. The biomass was estimated using the equation for tropical moist forests of Chave et al. (2005). Biomass dynamics were analyzed, in three separated periods from 2003 to 2011. 64 families, 219 genera and 531 species were recorded. The tree floristic composition is very similar in all plots except for one swamp plot, although but it is also evident that two slightly different forest communities exist in the rest of landscape, apparently related to the age of the ancient river terraces in the area. Mortality and recruitment of individuals averaged 2.12 ± 0.52% and 1.92 ± 0.49%, respectively. The turnover rate is 2.02% per year. Aboveground biomass stored in these forests averages 296.2 ± 33.9 t ha-1. The biomass dynamics show a total net gain of 1.96, 1.69 and –1.23 t ha-1 for period respectively. Prior to the drought of 2010 a change in biomass was found 1.88 t ha-1 yr-1 and post drought was -0.18 t ha-1 yr-1 on average, though the difference is not significant. Demographic analysis suggests a dynamic equilibrium in the plots. The negative balance of biomass observed for the period 2008 – 2011 may be due to the drought of 2010, in which half of the monitored plots experienced negative net biomass change due to mortality of individuals selectively affecting the floristic composition.

The original version of this Article contained an error in the third sentence of the abstract and incorrectly read “Here, using long-term plot monitoring records of up to half a century, we find that intact forests in Borneo gained 0.43 Mg C ha−1 year−1 (95% CI 0.14–0.72, mean period 1988–2010) above-ground live biomass”, rather than the correct “Here, using long-term plot monitoring records of up to half a century, we find that intact forests in Borneo gained 0.43 Mg C ha−1 year−1 (95% CI 0.14–0.72, mean period 1988–2010) in above-ground live biomass carbon”. This has now been corrected in both the PDF and HTML versions of the Article.

Logging, including selective and illegal activities, is widespread, affecting the carbon cycle and the biodiversity of tropical forests. However, automated approaches using very high resolution (VHR) satellite data (≤1 m spatial resolution) to accurately track these small-scale human disturbances over large and remote areas are not readily available. The main constraint for performing this type of analysis is the lack of spatially accurate tree-scale validation data. In this study, we assessed the potential of VHR satellite imagery to detect canopy tree loss related to selective logging in closed-canopy tropical forests. To do this, we compared the tree loss detection capability of WorldView-2 and GeoEye-1 satellites with airborne LiDAR, which acquired pre- and post-logging data at the Jamari National Forest in the Brazilian Amazon. We found that logging drove changes in canopy height ranging from −5.6 to −42.2 m, with a mean reduction of −23.5 m. A simple LiDAR height difference threshold of −10 m was enough to map 97% of the logged trees. Compared to LiDAR, tree losses can be detected using VHR satellite imagery and a random forest (RF) model with an average precision of 64%, while mapping 60% of the total tree loss. Tree losses associated with large gap openings or tall trees were more successfully detected. In general, the most important remote sensing metrics for the RF model were standard deviation statistics, especially those extracted from the reflectance of the visible bands (R, G, B), and the shadow fraction. While most small canopy gaps closed within ~2 years, larger gaps could still be observed over a longer time. Nevertheless, the use of annual imagery is advised to reach acceptable detectability. Our study shows that VHR satellite imagery has the potential for monitoring the logging in tropical forests and detecting hotspots of natural disturbance with a low cost at the regional scale.

Abstract Upon publication of the original article [1], the authors noticed that the figure labelling for Fig. 4 in the online version was processed wrong. The top left panel should be panel a, with the panels to its right being b and c. d and e should be the panels on the lower row, and f is correct. The graphs themselves are all correct. It is simply the letter labels that are wrong.

Stocks of dead wood or necromass represent an important portion of biomass and nutrients in tropical forests. The objectives of this study were: 1) to evaluate and compare the necromass of “terra firme” and lowlands forests, (2) to study the relationship between necromass, above-ground biomass and wood density, and (3) to estimate the necromass of the department of Madre de Dios, Peru. Stocks of necromass and above-ground biomass were estimated at three different locations using permanent plots and line intercept transects. The average volume of necromass for the three sites was 72.9 m3 ha-1 with an average weight varying between 24.8 and 30.7 Mg ha-1, depending on the estimations of dead wood density used for the calculations. Terra firme forests had significantly higher stocks of necromass than lowland forests. The amount of necromass was 11% of the total above-ground biomass in Madre de Dios forests. The total stock of carbon stored in dead wood for the entire department of Madre de Dios was estimated to be approximately 100 mega tonnes of carbon. This is ten times more than the annual fossil fuel emissions of Peru between 2000 and 2008. The substantial stocks of necromass emphasize the importance of these types of field studies, considering that this component of tropical forest carbon cannot be detected using other methods such as satellite remote sensing.

The Atlantic rainforest of Brazil is one of the global terrestrial hotspots of biodiversity. Despite having undergone large scale deforestation, forest cover has shown signs of increases in the last decades. Here, to understand the degradation and regeneration history of Atlantic rainforest remnants near São Paulo, we combine a unique dataset of very high resolution images from Worldview-2 and Worldview-3 (0.5 and 0.3m spatial resolution, respectively), georeferenced aerial photographs from 1962 and use a deep learning method called U-net to map (i) the forest cover and changes and (ii) two pioneer tree species, Cecropia hololeuca and Tibouchina pulchra. For Tibouchina pulchra, all the individuals were mapped in February, when the trees undergo mass-flowering with purple and pink blossoms. Additionally, elevation data at 30m spatial resolution from NASA Shuttle Radar Topography Mission (SRTM) and annual mean climate variables (Terraclimate datasets at ∼ 4km of spatial resolution) were used to analyse the forest and species distributions. We found that natural forests are currently more frequently found on south-facing slopes, likely because of geomorphology and past land use, and that Tibouchina is restricted to the wetter part of the region (southern part), which annually receives at least 1600 mm of precipitation. Tibouchina pulchra was found to clearly indicate forest regeneration as almost all individuals were found within or adjacent to forests regrown after 1962. By contrast, Cecropia hololeuca was found to indicate older disturbed forests, with all individuals almost exclusively found in forest fragments already present in 1962. At the regional scale, using the dominance maps of both species, we show that at least 4.3% of the current region's natural forests have regrown after 1962 (Tibouchina dominated, ∼ 4757 ha) and that ∼ 9% of the old natural forests have experienced significant disturbance (Cecropia dominated).