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This is the final version. Available from Springer via the DOI in this record. ; Data used in this manuscript will be made available on a public repository upon publication ; Purpose: The tropical phosphorus cycle and its relation to soil phosphorus (P) availability are a major uncertainty in projections of forest productivity. In highly weathered soils with low P concentrations, plant and microbial communities depend on abiotic and biotic processes to acquire P. We explored the seasonality and relative importance of drivers controlling the fluctuation of common P pools via processes such as litter production and decomposition, and soil phosphatase activity. Methods: We analyzed intra-annual variation of tropical soil phosphorus pools using a modified Hedley sequential fractionation scheme. In addition, we measured litterfall, the mobilization of P from litter and soil extracellular phosphatase enzyme activity and tested their relation to fluctuations in P- fractions. Results: Our results showed clear patterns of seasonal variability of soil P fractions during the year. We found that modeled P released during litter decomposition was positively related to change in organic P fractions, while net change in organic P fractions was negatively related to phosphatase activities in the top 5 cm. Conclusion: We conclude that input of P by litter decomposition and potential soil extracellular phosphatase activity are the two main factors related to seasonal soil P fluctuations, and therefore the P economy in P impoverished soils. Organic soil P followed a clear seasonal pattern, indicating tight cycling of the nutrient, while reinforcing the importance of studying soil P as an integrated dynamic system in a tropical forest context. ; Brazilian Ministry of Science, Technology, Innovation and Communications ; Brazil's Coordination for the Improvement of Higher Education Personnel (CAPES) ; Brazil's Coordination for the Improvement of Higher Education Personnel (CAPES) ; Amazonas Research Foundation (FAPEAM) ; Brazilian National Council for Scientific and Technological Development (CNPq) ; AmazonFACE ; European Union's Horizon 2020 ; CAPES-INPA

This is the final version. Available on open access from Springer via the DOI in this record ; Purpose Large parts of the Amazon rainforest grow on weathered soils depleted in phosphorus and rock-derived cations. We tested the hypothesis that in this ecosystem, fine roots stimulate decomposition and nutrient release from leaf litter biochemically by releasing enzymes, and by exuding labile carbon stimulating microbial decomposers. Methods We monitored leaf litter decomposition in a Central Amazon tropical rainforest, where fine roots were either present or excluded, over 188 days and added labile carbon substrates (glucose and citric acid) in a fully factorial design. We tracked litter mass loss, remaining carbon, nitrogen, phosphorus and cation concentrations, extracellular enzyme activity and microbial carbon and nutrient concentrations. Results Fine root presence did not affect litter mass loss but significantly increased the loss of phosphorus and cations from leaf litter. In the presence of fine roots, acid phosphatase activity was 43.2% higher, while neither microbial stoichiometry, nor extracellular enzyme activities targeting carbon- and nitrogen-containing compounds changed. Glucose additions increased phosphorus loss from litter when fine roots were present, and enhanced phosphatase activity in root exclusions. Citric acid additions reduced litter mass loss, microbial biomass nitrogen and phosphorus, regardless of fine root presence or exclusion. Conclusions We conclude that plant roots release significant amounts of acid phosphatases into the litter layer and mobilize phosphorus without affecting litter mass loss. Our results further indicate that added labile carbon inputs (i.e. glucose) can stimulate acid phosphatase production by microbial decomposers, highlighting the potential importance of plant-microbial feedbacks in tropical forest ecosystems. ; Inter-American Development Bank ; Brazilian Ministry of Science, Technology, Innovation and Communications ; Brazil's Coordination for the Improvement of Higher Education Personnel (CAPES) ; Amazonas Research Foundation (FAPEAM) ; European Research Council (ERC) ; European Union Horizon 2020 ; Natural Environment Research Council (NERC) ; DFG ; FAPESP grant

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

This is the peer reviewed version of the following article: Honorio Coronado, E. N., Dexter, K. G., Pennington, R. T., Chave, J., Lewis, S. L., Alexiades, M. N., Alvarez, E., Alves de Oliveira, A., Amaral, I. L., Araujo-Murakami, A., Arets, E. J. M. M., Aymard, G. A., Baraloto, C., Bonal, D., Brienen, R., Cerón, C., Cornejo Valverde, F., Di Fiore, A., Farfan-Rios, W., Feldpausch, T. R., Higuchi, N., Huamantupa-Chuquimaco, I., Laurance, S. G., Laurance, W. F., López-Gonzalez, G., Marimon, B. S., Marimon-Junior, B. H., Monteagudo Mendoza, A., Neill, D., Palacios Cuenca, W., Peñuela Mora, M. C., Pitman, N. C. A., Prieto, A., Quesada, C. A., Ramirez Angulo, H., Rudas, A., Ruschel, A. R., Salinas Revilla, N., Salomão, R. P., Segalin de Andrade, A., Silman, M. R., Spironello, W., ter Steege, H., Terborgh, J., Toledo, M., Valenzuela Gamarra, L., Vieira, I. C. G., Vilanova Torre, E., Vos, V., Phillips, O. L. (2015), Phylogenetic diversity of Amazonian tree communities. Diversity and Distributions, 21: 1295–1307. doi:10.1111/ddi.12357, which has been published in final form at 10.1111/ddi.12357 ; Aim: To examine variation in the phylogenetic diversity (PD) of tree communities across geographical and environmental gradients in Amazonia. Location: Two hundred and eighty-three c. 1 ha forest inventory plots from across Amazonia. Methods: We evaluated PD as the total phylogenetic branch length across species in each plot (PDss), the mean pairwise phylogenetic distance between species (MPD), the mean nearest taxon distance (MNTD) and their equivalents standardized for species richness (ses.PDss, ses.MPD, ses.MNTD). We compared PD of tree communities growing (1) on substrates of varying geological age; and (2) in environments with varying ecophysiological barriers to growth and survival. Results: PDss is strongly positively correlated with species richness (SR), whereas MNTD has a negative correlation. Communities on geologically young- and intermediate-aged substrates (western and central Amazonia respectively) have the highest SR, and therefore the highest PDss and the lowest MNTD. We find that the youngest and oldest substrates (the latter on the Brazilian and Guiana Shields) have the highest ses.PDss and ses.MNTD. MPD and ses.MPD are strongly correlated with how evenly taxa are distributed among the three principal angiosperm clades and are both highest in western Amazonia. Meanwhile, seasonally dry tropical forest (SDTF) and forests on white sands have low PD, as evaluated by any metric. Main conclusions: High ses.PDss and ses.MNTD reflect greater lineage diversity in communities. We suggest that high ses.PDss and ses.MNTD in western Amazonia results from its favourable, easy-to-colonize environment, whereas high values in the Brazilian and Guianan Shields may be due to accumulation of lineages over a longer period of time. White-sand forests and SDTF are dominated by close relatives from fewer lineages, perhaps reflecting ecophysiological barriers that are difficult to surmount evolutionarily. Because MPD and ses.MPD do not reflect lineage diversity per se, we suggest that PDss, ses.PDss and ses.MNTD may be the most useful diversity metrics for setting large-scale conservation priorities. ; FINCyT - PhD studentship ; School of Geography of the University of Leeds ; Royal Botanic Garden Edinburgh ; Natural Environment Research Council (NERC) ; Gordon and Betty Moore Foundation ; European Union's Seventh Framework Programme ; ERC ; CNPq/PELD ; NSF - Fellowship

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

© 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

Tropical forests are global centres of biodiversity and carbon storage. Many tropical countries aspire to protect forest to fulfil biodiversity and climate mitigation policy targets, but the conservation strategies needed to achieve these two functions depend critically on the tropical forest tree diversity-carbon storage relationship. Assessing this relationship is challenging due to the scarcity of inventories where carbon stocks in aboveground biomass and species identifications have been simultaneously and robustly quantified. Here, we compile a unique pan-tropical dataset of 360 plots located in structurally intact old-growth closed-canopy forest, surveyed using standardised methods, allowing a multi-scale evaluation of diversity-carbon relationships in tropical forests. Diversity-carbon relationships among all plots at 1 ha scale across the tropics are absent, and within continents are either weak (Asia) or absent (Amazonia, Africa). A weak positive relationship is detectable within 1 ha plots, indicating that diversity effects in tropical forests may be scale dependent. The absence of clear diversity-carbon relationships at scales relevant to conservation planning means that carbon-centred conservation strategies will inevitably miss many high diversity ecosystems. As tropical forests can have any combination of tree diversity and carbon stocks both require explicit consideration when optimising policies to manage tropical carbon and biodiversity. ; This paper is a product of the RAINFOR, AfriTRON and T-FORCES networks, for which we are hugely indebted to hundreds of institutions, field assistants and local communities across many countries that have hosted fieldwork. The three networks have been supported by a European Research Council (ERC) grant ("T-FORCES" - 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'), and Natural Environment Research Council (NERC) Urgency Grants and NERC Consortium Grants 'AMAZONICA' (NE/F005806/1) and 'TROBIT' (NE/D005590/1), 'BIO-RED' (NE/N012542/1) and a NERC New Investigators Grant, the Royal Society, the Centre for International Forestry (CIFOR) and Gabon's National Parks Agency (ANPN). 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. J.T. was supported by a NERC PhD Studentship with CASE sponsorship from UNEP-WCMC. 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 (T-FORCES) and a Phillip Leverhulme Prize. O.L.P. is supported by an ERC Advanced Grant (T-FORCES) and a Royal Society Wolfson Research Merit Award. L.F.B. was supported by a NERC studentship and RGS-IBG Henrietta Hutton Grant. We thank the National Council for Science and Technology Development of Brazil (CNPq) for support to Project Cerrado/Amazonia Transition (PELD/403725/2012-7), Project Phytogeography of Amazonia/Cerrado Transition (CNPq/PPBio/457602/2012-0) and Productivity Grant to B.S.M and B.H.M-J. Funding for plots in the Udzungwa Mountains (Tanzania) was obtained from the Leverhulme Trust under the Valuing the Arc project. We thank the ANPN (Gabon), WCS-Congo and WCS-DR Congo, Marien Ngouabi University and the University of Kisangani for logistical support in Africa, and the Tropenbos Kalimantan project (ITCI plots) and WWF (KUB plots) for providing data from Asia. This study is contribution number 706 to the Technical Series (TS) of the BDFFP – (INPA-STRI). For assistance with access to datasets we thank Adriana Prieto, Agustín Rudas, Alejandro Araujo-Murakami, Alexander G. Parada Gutierrez, Anand Roopsind, Atila Alves de Oliveira, Claudinei Oliveira dos Santos, C. E. Timothy Paine, David Neill, Eliana Jimenez-Rojas, Freddy Ramirez Arevalo, Hannsjoerg Woell, Iêda Leão do Amaral, Irina Mendoza Polo, Isau Huamantupa-Chuquimaco, Julien Engel, Kathryn Jeffery, Luzmila Arroyo, Michael D. Swaine, Nallaret Davila Cardozo, Natalino Silva, Nigel C. A. Pitman, Niro Higuchi, Raquel Thomas, Renske van Ek, Richard Condit, Rodolfo Vasquez Martinez, Timothy J. Killeen, Walter A. Palacios, Wendeson Castro. We thank Georgina Mace and Jon Lloyd for comments on the manuscript. We thank our deceased colleagues, Samuel Almeida, Kwaku Duah, Alwyn Gentry, and Sandra Patiño, for their invaluable contributions to this work and our wider understanding of tropical forest ecology.

Open Acess journal ; While Amazonian forests are extraordinarily diverse, the abundance of trees is skewed strongly towards relatively few 'hyperdominant' species. In addition to their diversity, Amazonian trees are a key component of the global carbon cycle, assimilating and storing more carbon than any other ecosystem on Earth. Here we ask, using a unique data set of 530 forest plots, if the functions of storing and producing woody carbon are concentrated in a small number of tree species, whether the most abundant species also dominate carbon cycling, and whether dominant species are characterized by specific functional traits. We find that dominance of forest function is even more concentrated in a few species than is dominance of tree abundance, with only ≈1% of Amazon tree species responsible for 50% of carbon storage and productivity. Although those species that contribute most to biomass and productivity are often abundant, species maximum size is also influential, while the identity and ranking of dominant species varies by function and by region. ; Gordon and Betty Moore Foundation ; European Union Seventh Framework Programme ; ERC ; Natural Environment Research Council ; PRONEX—FAPEAM/CNPq ; Hidroveg FAPESP/FAPEAM ; Universal/CNPq ; INCT-CENBAM ; Fitogeografia da Transição Amazônia/Cerrado CNPq ; Transição Amazônia/Cerrado ; French ANR - Investissement d'Avenir grants ; CNPq ; Royal Society - Wolfson Research Merit Award ; Dutch Ministry of Economic Affairs