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ABSTRACT
What is meant by sustainability depends on what is sustained and at what level. Sustainable forest management, for example, requires maintenance of a variety of values not the least of which is sustained timber yields (STYs). For the 1 Bha of the world's forests subjected to selective or partial logging, failure to maintain yields can be hidden by regulatory requirements and questionable auditing practices such as increasing the number of commercial species with each harvest, reducing the minimum size at which trees can be harvested and accepting logs of lower quality. For assertions of STY to be credible, clarity is needed about all these issues, as well as about the associated ecological and economic tradeoffs. Lack of clarity about sustainability heightens risks of unsubstantiated claims and unseen losses. STY is possible but often requires cutting cycles that are longer and logging intensities that are lower than prescribed by law, as well as effective use of low-impact logging practices and application of silvicultural treatments to promote timber stock recovery. These departures from business-as-usual practices will lower profit margins but generally benefit biodiversity and ecosystem services.

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).