Suchergebnisse

Funding Information: The analysis undertaken here was largely funded by the NERC-funded TREMOR project (NE/N004655/1) to D.G., R.J.W.B., E.G. and O.L.P. A.E.-M. was funded by TREMOR and by two ERC awards (T-FORCES 291585, TreeMort 758873). D.G. acknowledges further support from a Newton-funded consortium award (ARBOLES, NE/S011811/1). O.L.P. was supported by an ERC Advanced Grant and a Royal Society Wolfson Research Merit Award. T.A.M.P. was funded by the ERC award TreeMort 758873. This is paper number 47 of the Birmingham Institute of Forest Research. T.R.F., L.E.O.C.A. and O.L.P. were supported by NERC NE/N011570/1. 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 (291585), the Gordon and Betty Moore Foundation (#1656), the European Union's Seventh Framework Programme (282664, AMAZA-LERT) and the Royal Society (CH160091). This is paper #47 of the Birmingham Institute of Forest Research (BIFoR). ; The carbon sink capacity of tropical forests is substantially affected by tree mortality. However, the main drivers of tropical tree death remain largely unknown. Here we present a pan-Amazonian assessment of how and why trees die, analysing over 120,000 trees representing > 3800 species from 189 long-term RAINFOR forest plots. While tree mortality rates vary greatly Amazon-wide, on average trees are as likely to die standing as they are broken or uprooted—modes of death with different ecological consequences. Species-level growth rate is the single most important predictor of tree death in Amazonia, with faster-growing species being at higher risk. Within species, however, the slowest-growing trees are at greatest risk while the effect of tree size varies across the basin. In the driest Amazonian region species-level bioclimatic distributional patterns also predict the risk of death, suggesting that these forests are experiencing climatic conditions beyond their adaptative limits. These results provide not only a holistic pan-Amazonian picture of tree death but large-scale evidence for the overarching importance of the growth–survival trade-off in driving tropical tree mortality. ; Publisher PDF ; Peer reviewed

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 < 5%. Main conclusions: Pantropical biomass maps are widely used by governments and by projects aiming to reduce deforestation using carbon offsets, but may have significant regional biases. Carbon-mapping techniques must be revised to account for the known ecological variation in tree wood density and allometry to create maps suitable for carbon accounting. The use of single relationships between tree canopy height and above-ground biomass inevitably yields large, spatially correlated errors. This presents a significant challenge to both the forest conservation and remote sensing communities, because neither wood density nor species ...