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This is the final version. Available on open access from European Geosciences Union via the DOI in this record ; Code availability. A model example of SUGAR for a single site and set-up to run at Caxiuanã using output from JULES is available at https://doi.org/10.5281/zenodo.3547613 (Jones, 2019). For further information or code please contact sj326@exeter.ac.uk. ; Accurately representing the response of ecosystems to environmental change in land surface models (LSMs) is crucial to making accurate predictions of future climate. Many LSMs do not correctly capture plant respiration and growth fluxes, particularly in response to extreme climatic events. This is in part due to the unrealistic assumption that total plant carbon expenditure (PCE) is always equal to gross carbon accumulation by photosynthesis. We present and evaluate a simple model of labile carbon storage and utilisation (SUGAR) designed to be integrated into an LSM, which allows simulated plant respiration and growth to vary independent of photosynthesis. SUGAR buffers simulated PCE against seasonal variation in photosynthesis, producing more constant (less variable) predictions of plant growth and respiration relative to an LSM that does not represent labile carbon storage. This allows the model to more accurately capture observed carbon fluxes at a large-scale drought experiment in a tropical moist forest in the Amazon, relative to the Joint UK Land Environment Simulator LSM (JULES). SUGAR is designed to improve the representation of carbon storage in LSMs and provides a simple framework that allows new processes to be integrated as the empirical understanding of carbon storage in plants improves. The study highlights the need for future research into carbon storage and allocation in plants, particularly in response to extreme climate events such as drought. ; Natural Environment Research Council (NERC) ; Newton Fund ; Australian Research Council (ARC) ; Spanish Ministry of Economy and Competitiveness (MINECO) ; Engineering and Physical Sciences Research Council (EPSRC) ; JPL-Caltech President's and Director's Research & Development Fund ; Met Office Hadley Centre Climate Programme ; European Union Horizon 2020

This is the final version. Available on open access from Wiley via the DOI in this record ; Plant traits are increasingly being used to improve prediction of plant function, including plant demography. However, the capability of plant traits to predict demographic rates remains uncertain, particularly in the context of trees experiencing a changing climate. Here we present data combining 17 plant traits associated with plant structure, metabolism and hydraulic status, with measurements of long-term mean, maximum and relative growth rates for 176 trees from the world's longest running tropical forest drought experiment. We demonstrate that plant traits can predict mean annual tree growth rates with moderate explanatory power. However, only combinations of traits associated more directly with plant functional processes, rather than more commonly employed traits like wood density or leaf mass per area, yield the power to predict growth. Critically, we observe a shift from growth being controlled by traits related to carbon cycling (assimilation and respiration) in well-watered trees, to traits relating to plant hydraulic stress in drought-stressed trees. We also demonstrate that even with a very comprehensive set of plant traits and growth data on large numbers of tropical trees, considerable uncertainty remains in directly interpreting the mechanisms through which traits influence performance in tropical forests. ; Conselho Nacional de Desenvolvimento Científico e Tecnológico ; Natural Environment Research Council (NERC) ; Australian Research Council (ARC) ; European Union FP7 ; Fundação de Amparo à Pesquisa do Estado de São Paulo

This is the final version. Available on open access from Wiley via the DOI in this record ; The response of small understory trees to long-term drought is vital in determining the future composition, carbon stocks and dynamics of tropical forests. Long-term drought is, however, also likely to expose understory trees to increased light availability driven by drought-induced mortality. Relatively little is known about the potential for understory trees to adjust their physiology to both decreasing water and increasing light availability. We analysed data on maximum photosynthetic capacity (Jmax , Vcmax ), leaf respiration (Rleaf ), leaf mass per area (LMA), leaf thickness and leaf nitrogen and phosphorus concentrations from 66 small trees across 12 common genera at the world's longest running tropical rainfall exclusion experiment and compared responses to those from 61 surviving canopy trees. Small trees increased Jmax , Vcmax , Rleaf and LMA (71%, 29%, 32%, 15% respectively) in response to the drought treatment, but leaf thickness and leaf nutrient concentrations did not change. Small trees were significantly more responsive than large canopy trees to the drought treatment, suggesting greater phenotypic plasticity and resilience to prolonged drought, although differences among taxa were observed. Our results highlight that small tropical trees have greater capacity to respond to ecosystem level changes and have the potential to regenerate resilient forests following future droughts. This article is protected by copyright. All rights reserved. ; Australian Research Council (ARC) ; Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) ; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior ; European Union FP7‐Amazalert ; Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) ; Microsoft ; Natural Environment Research Council (NERC) ; Royal Society of Biology

This is the final version. Available on open access from Wiley via the DOI in this record ; Data availability statement: Data have been deposited in DRYAD (Rowland et al., 2020), and are available from https://doi.org/10.5061/dryad.vdncjsxs5 ; Whether tropical trees acclimate to long-term drought stress remains unclear. This uncertainty is amplified if drought stress is accompanied by changes in other drivers such as the increases in canopy light exposure that might be induced by tree mortality or other disturbances. Photosynthetic capacity, leaf respiration, non-structural carbohydrate (NSC) storage and stomatal conductance were measured on 162 trees at the world's longest running (15 years) tropical forest drought experiment. We test whether surviving trees have altered strategies for carbon storage and carbon use in the drier and elevated light conditions present following drought-related tree mortality. Relative to control trees, the surviving trees experiencing the drought treatment showed functional responses including: (a) moderately reduced photosynthetic capacity; (b) increased total leaf NSC; and (c) a switch from starch to soluble sugars as the main store of branch NSC. This contrasts with earlier findings at this experiment of no change in photosynthetic capacity or NSC storage. The changes detected here only occurred in the subset of drought-stressed trees with canopies exposed to high radiation and were absent in trees with less-exposed canopies and also in the community average. In contrast to previous results acquired through less intensive species sampling from this experiment, we also observe no species-average drought-induced change in leaf respiration. Our results suggest that long-term responses to drought stress are strongly influenced by a tree's full-canopy light environment and therefore that disturbance-induced changes in stand density and dynamics are likely to substantially impact tropical forest responses to climate change. We also demonstrate that, while challenging, intensive sampling is essential in tropical forests to avoid sampling biases caused by limited taxonomic coverage. A free Plain Language Summary can be found within the Supporting Information of this article. ; Conselho Nacional de Desenvolvimento Científico e Tecnológico ; European Union FP7 ; Natural Environment Research Council (NERC) ; Australian Research Council (ARC) ; FAPESP/Microsoft Research ; Royal Society

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.

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 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