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To achieve global food security, we need to approximately double food production over the coming decades. Conventional agriculture is the mainstream approach to achieving this target but has also caused extensive environmental and social harms. The consensus is that we now need an agriculture that can "multi-functionally" increase food production while simultaneously enhancing social and environmental goals, as committed to in the sustainable development goals (SDGs). Farming also needs to become more resilient to multiple insecurities including climate change, soil degradation, and market unpredictability, all of which reduce sustainability and are likely to exacerbate hunger. Here, we illustrate how agroforestry systems can increase yield while also advancing multiple SDGs, especially for the small developing-world agriculturalists central to the SDG framework. Agroforestry also increases resilience of crops and farm livelihoods, especially among the most vulnerable food producers. However, conventional yield-enhancement strategies have naturally dominated the debate on food production, hindering implementation of more multifunctional alternatives. Governments and institutions now have the opportunity to rebalance agricultural policy and investment toward such multigoal approaches. In doing so, they could achieve important improvements on multiple international commitments around the interlinked themes of food security, climate change, biodiversity conservation, and social well-being.

Fine roots constitute a significant component of the net primary productivity (NPP) of forest ecosystems but are much less studied than aboveground NPP. Comparisons across sites and regions are also hampered by inconsistent methodologies, especially in tropical areas. Here, we present a novel dataset of fine root biomass, productivity, residence time, and allocation in tropical old-growth rainforest sites worldwide, measured using consistent methods, and examine how these variables are related to consistently determined soil and climatic characteristics. Our pantropical dataset spans intensive monitoring plots in lowland (wet, semi-deciduous, and deciduous) and montane tropical forests in South America, Africa, and Southeast Asia (n = 47). Large spatial variation in fine root dynamics was observed across montane and lowland forest types. In lowland forests, we found a strong positive linear relationship between fine root productivity and sand content, this relationship was even stronger when we considered the fractional allocation of total NPP to fine roots, demonstrating that understanding allocation adds explanatory power to understanding fine root productivity and total NPP. Fine root residence time was a function of multiple factors: soil sand content, soil pH, and maximum water deficit, with longest residence times in acidic, sandy, and water-stressed soils. In tropical montane forests, on the other hand, a different set of relationships prevailed, highlighting the very different nature of montane and lowland forest biomes. Root productivity was a strong positive linear function of mean annual temperature, root residence time was a strong positive function of soil nitrogen content in montane forests, and lastly decreasing soil P content increased allocation of productivity to fine roots. In contrast to the lowlands, environmental conditions were a better predictor for fine root productivity than for fractional allocation of total NPP to fine roots, suggesting that root productivity is a particularly strong driver of NPP allocation in tropical mountain regions. © 2021 The Authors. Global Change Biology published by John Wiley & Sons Ltd. ; This study is a product of the Global Ecosystem Monitoring network (GEM), Andes Biodiversity and Ecosystem Research Group (ABERG), Amazon Forest Inventory Network (RAINFOR), Stability of Altered Forest Ecosystem (SAFE), and Instituto de Investigaciones de la Amazonia Peruana (IIAP). WHH was funded by Peruvian FONDECYT/CONCYTEC (grant contract number 213-2015-FONDECYT). The GEM network was supported by a European Research Council Advanced Investigator Grant to YM (GEM-TRAITS: 321131) under the European Union's Seventh Framework Programme (FP7/2007-2013). The field data collection was funded NERC Grants NE/D014174/1 and NE/J022616/1 for in Peru, BALI (NE/K016369/1) for work in Malaysia, the Royal Society-Leverhulme Africa Capacity Building Programme for work in Ghana and Gabon and ESPA-ECOLIMITS (NE/1014705/1) in Ghana and Ethiopia. Plot inventories in South America were supported by funding from the US National Science Foundation Long-Term Research in Environmental Biology program (LTREB; DEB 1754647) and the Gordon and Betty Moore Foundation Andes-Amazon Program. GEM data in Gabon were collected under authorization to YM and supported by the Gabon National Parks Agency. Y.M. is supported by the Jackson Foundation. We would like to acknowledge the GEM team across the tropical regions and countries of Bolivia, Brazil, Ghana, Gabon, Ethiopia, Malaysia, and Peru.

Forest inventory plots are widely used to estimate biomass carbon storage and its change over time. While there has been much debate and exploration of the analytical methods for calculating biomass, the methods used to determine rates of wood production have not been evaluated to the same degree. This affects assessment of ecosystem fluxes and may have wider implications if inventory data are used to parameterise biospheric models, or scaled to large areas in assessments of carbon sequestration. Here we use a dataset of 35 long-term Amazonian forest inventory plots to test different methods of calculating wood production rates. These address potential biases associated with three issues that routinely impact the interpretation of tree measurement data: (1) changes in the point of measurement (POM) of stem diameter as trees grow over time; (2) unequal length of time between censuses; and (3) the treatment of trees that pass the minimum diameter threshold ("recruits"). We derive corrections that control for changing POM height, that account for the unobserved growth of trees that die within census intervals, and that explore different assumptions regarding the growth of recruits during the previous census interval. For our dataset we find that annual aboveground coarse wood production (AGWP; in Mg ha−1 year−1 of dry matter) is underestimated on average by 9.2% if corrections are not made to control for changes in POM height. Failure to control for the length of sampling intervals results in a mean underestimation of 2.7% in annual AGWP in our plots for a mean interval length of 3.6 years. Different methods for treating recruits result in mean differences of up to 8.1% in AGWP. In general, the greater the length of time a plot is sampled for and the greater the time elapsed between censuses, the greater the tendency to underestimate wood production. We recommend that POM changes, census interval length, and the contribution of recruits should all be accounted for when estimating productivity rates, and suggest methods for doing this. ; European Union ; UK Natural Environment Research Council ; Gordon and Betty Moore Foundation ; CASE sponsorship from UNEP-WCMC ; Royal Society University Research Fellowship ; ERC Advanced Grant "Tropical Forests in the Changing Earth System" ; Royal Society Wolfson Research Merit Award

No claim to original US government works New Phytologist © 2018 New Phytologist Trust Tree mortality rates appear to be increasing in moist tropical forests (MTFs) with significant carbon cycle consequences. Here, we review the state of knowledge regarding MTF tree mortality, create a conceptual framework with testable hypotheses regarding the drivers, mechanisms and interactions that may underlie increasing MTF mortality rates, and identify the next steps for improved understanding and reduced prediction. Increasing mortality rates are associated with rising temperature and vapor pressure deficit, liana abundance, drought, wind events, fire and, possibly, CO2 fertilization-induced increases in stand thinning or acceleration of trees reaching larger, more vulnerable heights. The majority of these mortality drivers may kill trees in part through carbon starvation and hydraulic failure. The relative importance of each driver is unknown. High species diversity may buffer MTFs against large-scale mortality events, but recent and expected trends in mortality drivers give reason for concern regarding increasing mortality within MTFs. Models of tropical tree mortality are advancing the representation of hydraulics, carbon and demography, but require more empirical knowledge regarding the most common drivers and their subsequent mechanisms. We outline critical datasets and model developments required to test hypotheses regarding the underlying causes of increasing MTF mortality rates, and improve prediction of future mortality under climate change.

This is the final version. Available on open access from Wiley via the DOI in this record ; Competition among trees is an important driver of community structure and dynamics in tropical forests. Neighboring trees may impact an individual tree's growth rate and probability of mortality, but large-scale geographic and environmental variation in these competitive effects has yet to be evaluated across the tropical forest biome. We quantified effects of competition on tree-level basal area growth and mortality for trees ≥ 10 cm diameter across 151 ~1-ha plots in mature tropical forests in Amazonia and tropical Africa by developing non-linear models that accounted for wood density, tree size and neighborhood crowding. Using these models, we assessed how water availability (i.e., climatic water deficit) and soil fertility influenced the predicted plot-level strength of competition (i.e., the extent to which growth is reduced, or mortality is increased, by competition across all individual trees). On both continents, tree basal area growth decreased with wood density, and increased with tree size. Growth decreased with neighborhood crowding, which suggests that competition is important. Tree mortality decreased with wood density and generally increased with tree size, but was apparently unaffected by neighborhood crowding. Across plots, variation in the plot-level strength of competition was most strongly related to plot basal area (i.e., the sum of the basal area of all trees in a plot), with greater reductions in growth occurring in forests with high basal area, but in Amazonia the strength of competition also varied with plot-level wood density. In Amazonia, the strength of competition increased with water availability because of the greater basal area of wetter forests, but was only weakly related to soil fertility. In Africa, competition was weakly related to soil fertility, and invariant across the shorter water availability gradient. Overall, our results suggest that competition influences the structure and dynamics of tropical forests primarily through effects on individual tree growth rather than mortality, and that the strength of competition largely depends on environment-mediated variation in basal area. ; Gordon and Betty Moore Foundation ; European Union FP7 ; European Research Council (ERC) ; Natural Environment Research Council (NERC) ; Conselho Nacional de Desenvolvimento Científico e Tecnológico of Brazil (CNPq) ; Microsoft Research ; University of Regina ; Royal Society

This is the final version of the article. Available from Wiley via the DOI in this record. ; Quantifying the relationship between tree diameter and height is a key component of efforts to estimate biomass and carbon stocks in tropical forests. Although substantial site-to-site variation in height-diameter allometries has been documented, the time consuming nature of measuring all tree heights in an inventory plot means that most studies do not include height, or else use generic pan-tropical or regional allometric equations to estimate height. Using a pan-tropical dataset of 73 plots where at least 150 trees had in-field ground-based height measurements, we examined how the number of trees sampled affects the performance of locally derived height-diameter allometries, and evaluated the performance of different methods for sampling trees for height measurement. Using cross-validation, we found that allometries constructed with just 20 locally measured values could often predict tree height with lower error than regional or climate-based allometries (mean reduction in prediction error = 0.46 m). The predictive performance of locally derived allometries improved with sample size, but with diminishing returns in performance gains when more than 40 trees were sampled. Estimates of stand-level biomass produced using local allometries to estimate tree height show no over- or under-estimation bias when compared with biomass estimates using field measured heights. We evaluated five strategies to sample trees for height measurement, and found that sampling strategies that included measuring the heights of the ten largest diameter trees in a plot outperformed (in terms of resulting in local height-diameter models with low height prediction error) entirely random or diameter size-class stratified approaches. Our results indicate that even limited sampling of heights can be used to refine height-diameter allometries. We recommend aiming for a conservative threshold of sampling 50 trees per location for height measurement, and including the ten trees with the largest diameter in this sample. ; This paper is a product of the RAINFOR, AfriTRON and T-FORCES networks, for which we are indebted to the hundreds of institutions, field assistants and local communities across many countries that have supported and hosted fieldwork. The three networks have been supported by the Natural Environment Research Council (NERC) Urgency Grants and NERC Consortium Grants "AMAZONICA" (NE/F005806/1), "TROBIT" (NE/D005590/1) and "BIO-RED" (NE/N012542/1), a NERC New Investigators Grant, a European Research Council grant ("Tropical Forests in the Changing Earth System"), the Gordon and Betty Moore Foundation, the David and Lucile Packard Foundation, the European Union's Seventh Framework Programme (283080, "GEOCARBON"; 282664, "AMAZALERT"), the Royal Society and Gabon's National Parks Agency (ANPN). R.J.W.B. is funded by a NERC research fellowship (grant ref: NE/I021160/1). S.L.L. was supported by a Royal Society University Research Fellowship, ERC Advanced Grant and a Phillip Leverhulme Prize. O.L.P. is supported by an ERC Advanced Grant and a Royal Society Wolfson Research Merit Award. L.F.B. was supported by a NERC studentship, RGS-IBG Henrietta Hutton Grant and Royal Society Dudley Stamp Award. R.H. and M.C. were supported through the long-term research development project no. RVO 67985939 and a KBFSC research fellowship (2011, to R.H.). M. Svátek was funded by the Ministry of Education, Youth and Sports of the Czech Republic (grant number INGO II LG15051). We thank Georgia Pickavance for assistance with database curation, and Natacha Nssi Bengone, Sylvester Chenikan, Eric Chezeaux, Armandu Daniels, Jean-Louis Doucet, Kath Jeffery, Edi Mirmanto, Abel Monteagudo-Mendoza, Faustin Mpanya Lukasu, Reuben Nilus, Guido Pardo, Lourens Poorter, Sylvester Tan, Marisol Toledo, Armando Torres-Lezama, John Tshibamba Mukendi, Richard Tshombe, Geertje van der Heijden, Lee White, Hannsjoerg Woell and John Woods, Gabon's National Parks Agency (ANPN), the Forest Development Authority of Liberia and Wildlife Conservation Society-Democratic Republic of Congo for assistance with access to datasets. We thank an anonymous reviewer for constructive comments on this manuscript.

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 ...

This is the final version. Available from the National Academy of Sciences via the DOI in this record. ; The input data and R code are available on ForestPlots (https://doi.org/10.5521/forestplots.net/2021_4). ; The responses of tropical forests to environmental change are critical uncertainties in predicting the future impacts of climate change. The positive phase of the 2015-2016 El Niño Southern Oscillation resulted in unprecedented heat and low precipitation in the tropics with substantial impacts on the global carbon cycle. The role of African tropical forests is uncertain as their responses to short-term drought and temperature anomalies have yet to be determined using on-the-ground measurements. African tropical forests may be particularly sensitive because they exist in relatively dry conditions compared with Amazonian or Asian forests, or they may be more resistant because of an abundance of drought-adapted species. Here, we report responses of structurally intact old-growth lowland tropical forests inventoried within the African Tropical Rainforest Observatory Network (AfriTRON). We use 100 long-term inventory plots from six countries each measured at least twice prior to and once following the 2015-2016 El Niño event. These plots experienced the highest temperatures and driest conditions on record. The record temperature did not significantly reduce carbon gains from tree growth or significantly increase carbon losses from tree mortality, but the record drought did significantly decrease net carbon uptake. Overall, the long-term biomass increase of these forests was reduced due to the El Niño event, but these plots remained a live biomass carbon sink (0.51 ± 0.40 Mg C ha-1 y-1) despite extreme environmental conditions. Our analyses, while limited to African tropical forests, suggest they may be more resistant to climatic extremes than Amazonian and Asian forests. ; Natural Environment Research Council (NERC) ; Natural Environment Research Council (NERC) ; European Research Council (ERC) ; The Royal Society ; Belgian Science Policy Office (BELSPO) ; Belgian Science Policy Office (BELSPO) ; Belgian Science Policy Office (BELSPO) ; Belgian Science Policy Office (BELSPO) ; Flemish Interuniversity Council VLIR-UOS ; Flemish Interuniversity Council VLIR-UOS ; Natural Environment Research Council (NERC) ; The Gordon and Betty Moore Foundation ; European Union ; Natural Environment Research Council (NERC) ; Natural Environment Research Council (NERC) ; Natural Environment Research Council (NERC) ; Gabon's National Parks Agency ; Leverhulme Trust ; The David and Lucile Packard Foundation ; CIFOR

This is the final version of the article. Available from Wiley via the DOI in this record. ; Understanding the processes that determine above-ground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity [woody net primary productivity (NPP)] and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size structure for determining spatial variation in AGB. The relationship between stem mortality rates and AGB varies among different regions of Amazonia, indicating that variation in wood density and height/diameter relationships also influences AGB. In contrast to previous findings, we find that woody NPP is not correlated with stem mortality rates and is weakly positively correlated with AGB. Across the four models, basin-wide average AGB is similar to the mean of the observations. However, the models consistently overestimate woody NPP and poorly represent the spatial patterns of both AGB and woody NPP estimated using plot data. In marked contrast to the observations, DGVMs typically show strong positive relationships between woody NPP and AGB. Resolving these differences will require incorporating forest size structure, mechanistic models of stem mortality and variation in functional composition in DGVMs. ; This paper is a product of the European Union's Seventh Framework Programme AMAZALERT project (282664). The field data used in this study have been generated by the RAINFOR network, which has been supported by a Gordon and Betty Moore Foundation grant, the European Union's Seventh Framework Programme projects 283080, 'GEOCARBON'; and 282664, 'AMAZALERT'; ERC grant 'Tropical Forests in the Changing Earth System'), and Natural Environment Research Council (NERC) Urgency, Consortium and Standard Grants 'AMAZONICA' (NE/F005806/1), 'TROBIT' (NE/D005590/1) and 'Niche Evolution of South American Trees' (NE/I028122/1). Additional data were included from the Tropical Ecology Assessment and Monitoring (TEAM) Network – a collaboration between Conservation International, the Missouri Botanical Garden, the Smithsonian Institution and the Wildlife Conservation Society, and partly funded by these institutions, the Gordon and Betty Moore Foundation, and other donors. Fieldwork was also partially supported by Conselho Nacional de Desenvolvimento Científico e Tecnológico of Brazil (CNPq), project Programa de Pesquisas Ecológicas de Longa Duração (PELD-403725/2012-7). A.R. acknowledges funding from the Helmholtz Alliance 'Remote Sensing and Earth System Dynamics'; L.P., M.P.C. E.A. and M.T. are partially funded by the EU FP7 project 'ROBIN' (283093), with co-funding for E.A. from the Dutch Ministry of Economic Affairs (KB-14-003-030); B.C. [was supported in part by the US DOE (BER) NGEE-Tropics project (subcontract to LANL). O.L.P. is supported by an ERC Advanced Grant and is a Royal Society-Wolfson Research Merit Award holder. P.M. acknowledges support from ARC grant FT110100457 and NERC grants NE/J011002/1, and T.R.B. acknowledges support from a Leverhulme Trust Research Fellowship.

Aim: The accurate mapping of forest carbon stocks is essential for understanding the global carbon cycle, for assessing emissions from deforestation, and for rational land-use planning. Remote sensing (RS) is currently the key tool for this purpose, but RS does not estimate vegetation biomass directly, and thus may miss significant spatial variations in forest structure. We test the stated accuracy of pantropical carbon maps using a large independent field dataset. Location: Tropical forests of the Amazon basin. The permanent archive of the field plot data can be accessed at: http://dx.doi.org/10.5521/FORESTPLOTS.NET/2014_1 Methods: Two recent pantropical RS maps of vegetation carbon are compared to a unique ground-plot dataset, involving tree measurements in 413 large inventory plots located in nine countries. The RS maps were compared directly to field plots, and kriging of the field data was used to allow area-based comparisons. Results: The two RS carbon maps fail to capture the main gradient in Amazon forest carbon detected using 413 ground plots, from the densely wooded tall forests of the north-east, to the light-wooded, shorter forests of the south-west. The differences between plots and RS maps far exceed the uncertainties given in these studies, with whole regions over- or under-estimated by >???25%, whereas regional uncertainties for the maps were reported to be

Understanding the processes that determine aboveground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity (woody NPP) and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size-structure for determining spatial variation in AGB. The relationship between stem mortality rates and AGB varies among different regions of Amazonia, indicating that variation in wood density and height/diameter relationships also influence AGB. In contrast to previous findings, we find that woody NPP is not correlated with stem mortality rates, and is weakly positively correlated with AGB. Across the four models, basin-wide average AGB is similar to the mean of the observations. However, the models consistently overestimate woody NPP, and poorly represent the spatial patterns of both AGB and woody NPP estimated using plot data. In marked contrast to the observations, DGVMs typically show strong positive relationships between woody NPP and AGB. Resolving these differences will require incorporating forest size structure, mechanistic models of stem mortality and variation in functional composition in DGVMs. This article is protected by copyright. All rights reserved. ; This paper is a product of the European Union's Seventh Frame-work Programme AMAZALERT project (282664). The field dataused in this study have been generated by the RAINFOR net-work, which has been supported by a Gordon and Betty MooreFoundation grant, the European Union's Seventh FrameworkProgramme projects 283080, 'GEOCARBON'; and 282664,'AMAZALERT'; ERC grant 'Tropical Forests in the ChangingEarth System'), and Natural Environment Research Council(NERC) Urgency, Consortium and Standard Grants 'AMAZO-NICA' (NE/F005806/1), 'TROBIT' (NE/D005590/1) and 'NicheEvolution of South American Trees' (NE/I028122/1). Additionaldata were included from the Tropical Ecology Assessment andMonitoring (TEAM) Network – a collaboration between Conser-vation International, the Missouri Botanical Garden, the Smith-sonian Institution and the Wildlife Conservation Society, andpartly funded by these institutions, the Gordon and Betty MooreFoundation, and other donors. Fieldwork was also partially sup-ported by Conselho Nacional de Desenvolvimento Cientı´fico eTecnolo´gico of Brazil (CNPq), project Programa de PesquisasEcolo´gicas de Longa Duracßa˜o (PELD-403725/2012-7). A.R.acknowledges funding from the Helmholtz Alliance 'RemoteSensing and Earth System Dynamics'; L.P., M.P.C. E.A. andM.T. are partially funded by the EU FP7 project 'ROBIN'(283093), with co-funding for E.A. from the Dutch Ministry ofEconomic Affairs (KB-14-003-030); B.C. [was supported in partby the US DOE (BER) NGEE-Tropics project (subcontract toLANL). O.L.P. is supported by an ERC Advanced Grant and is aRoyal Society-Wolfson Research Merit Award holder. P.M.acknowledges support from ARC grant FT110100457 and NERCgrants NE/J011002/1, and T.R.B. acknowledges support from aLeverhulme Trust Research Fellowship.

© 2014 The Authors. Global Ecology and Biogeography published by John Wiley & Sons Ltd. ; The accurate mapping of forest carbon stocks is essential for understanding the global carbon cycle, for assessing emissions from deforestation, and for rational land-use planning. Remote sensing (RS) is currently the key tool for this purpose, but RS does not estimate vegetation biomass directly, and thus may miss significant spatial variations in forest structure. We test the stated accuracy of pantropical carbon maps using a large independent field dataset. ; Gordon and Betty Moore Foundation ; European Union's Seventh Framework Programme ; ERC ; NERC ; PRONEX -FAPEAM/CNPq. ; Hidroveg FAPESP/FAPEAM ; Universal/CNPq. ; INCT-CENBAM ; Investissement d'Avenir grants of the French ANR. ; Royal Society Fellowship ; Royal Society Wolfson Research Merit Award

This is the final version. Available on open access from Wiley via the DOI in this record ; Most of the planet's diversity is concentrated in the tropics, which includes many regions undergoing rapid climate change. Yet, while climate-induced biodiversity changes are widely documented elsewhere, few studies have addressed this issue for lowland tropical ecosystems. Here we investigate whether the floristic and functional composition of intact lowland Amazonian forests have been changing by evaluating records from 106 long-term inventory plots spanning 30 years. We analyse three traits that have been hypothesized to respond to different environmental drivers (increase in moisture stress and atmospheric CO2 concentrations): maximum tree size, biogeographic water-deficit affiliation and wood density. Tree communities have become increasingly dominated by large-statured taxa, but to date there has been no detectable change in mean wood density or water deficit affiliation at the community level, despite most forest plots having experienced an intensification of the dry season. However, among newly recruited trees, dry-affiliated genera have become more abundant, while the mortality of wet-affiliated genera has increased in those plots where the dry season has intensified most. Thus, a slow shift to a more dry-affiliated Amazonia is underway, with changes in compositional dynamics (recruits and mortality) consistent with climate-change drivers, but yet to significantly impact whole-community composition. The Amazon observational record suggests that the increase in atmospheric CO2 is driving a shift within tree communities to large-statured species and that climate changes to date will impact forest composition, but long generation times of tropical trees mean that biodiversity change is lagging behind climate change. ; Support for RAINFOR has come from the Natural Environment Research Council (NERC) Urgency Grants and NERC Consortium Grants "AMAZONICA" (NE/F005806/1), "TROBIT" (NE/D005590/1) and "BIO‐RED" (NE/N012542/1), a European Research Council (ERC) grant (T‐FORCES, "Tropical Forests in the Changing Earth System"), the Gordon and Betty Moore Foundation, the European Union's Seventh Framework Programme (282664, "AMAZALERT") and the Royal Society (CH160091). OLP was supported by an ERC Advanced Grant and a Royal Society Wolfson Research Merit Award. KGD was supported by a Leverhulme Trust International Academic Fellowship. This paper is part of the PhD of AE‐M, which was funded by the ERC T‐FORCES grant. AE‐M is currently supported by T‐FORCES and the NERC project "TREMOR" (NE/N004655/1).