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Abstract: 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. [ABSTRACT FROM AUTHOR]

Within the tropics, the species richness of tree communities is strongly and positively associated with precipitation. Previous research has suggested that this macroecological pattern is driven by the negative effect of water-stress on the physiological processes of most tree species. This implies that the range limits of taxa are defined by their ability to occur under dry conditions, and thus in terms of species distributions predicts a nested pattern of taxa distribution from wet to dry areas. However, this 'dry-tolerance' hypothesis has yet to be adequately tested at large spatial and taxonomic scales. Here, using a dataset of 531 inventory plots of closed canopy forest distributed across the western Neotropics we investigated how precipitation, evaluated both as mean annual precipitation and as the maximum climatological water deficit, influences the distribution of tropical tree species, genera and families. We find that the distributions of tree taxa are indeed nested along precipitation gradients in the western Neotropics. Taxa tolerant to seasonal drought are disproportionally widespread across the precipitation gradient, with most reaching even the wettest climates sampled; however, most taxa analysed are restricted to wet areas. Our results suggest that the 'dry tolerance' hypothesis has broad applicability in the world's most species-rich forests. In addition, the large number of species restricted to wetter conditions strongly indicates that an increased frequency of drought could severely threaten biodiversity in this region. Overall, this study establishes a baseline for exploring how tropical forest tree composition may change in response to current and future environmental changes in this region. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

We combined two existing datasets of vegetation aboveground biomass ( AGB) ( Proceedings of the National Academy of Sciences of the United States of America, 108, 2011, 9899; Nature Climate Change, 2, 2012, 182) into a pan-tropical AGB map at 1-km resolution using an independent reference dataset of field observations and locally calibrated high-resolution biomass maps, harmonized and upscaled to 14 477 1-km AGB estimates. Our data fusion approach uses bias removal and weighted linear averaging that incorporates and spatializes the biomass patterns indicated by the reference data. The method was applied independently in areas (strata) with homogeneous error patterns of the input (Saatchi and Baccini) maps, which were estimated from the reference data and additional covariates. Based on the fused map, we estimated AGB stock for the tropics (23.4 N-23.4 S) of 375 Pg dry mass, 9-18% lower than the Saatchi and Baccini estimates. The fused map also showed differing spatial patterns of AGB over large areas, with higher AGB density in the dense forest areas in the Congo basin, Eastern Amazon and South-East Asia, and lower values in Central America and in most dry vegetation areas of Africa than either of the input maps. The validation exercise, based on 2118 estimates from the reference dataset not used in the fusion process, showed that the fused map had a RMSE 15-21% lower than that of the input maps and, most importantly, nearly unbiased estimates (mean bias 5 Mg dry mass ha−1 vs. 21 and 28 Mg ha−1 for the input maps). The fusion method can be applied at any scale including the policy-relevant national level, where it can provide improved biomass estimates by integrating existing regional biomass maps as input maps and additional, country-specific reference datasets. [ABSTRACT FROM AUTHOR]

Understanding the resilience of moist tropical forests to treefall disturbance events is important for understanding the mechanisms that underlie species coexistence and for predicting the future composition of these ecosystems. Here, we test whether variation in the functional composition of Amazonian forests determines their resilience to disturbance., We studied the legacy of natural treefall disturbance events in four forests across Amazonia that differ substantially in functional composition. We compared the composition and diversity of all free-standing woody stems 2-10 cm diameter in previously disturbed and undisturbed 20 × 20 m subplots within 55, one-hectare, long-term forest inventory plots., Overall, stem number increased following disturbance, and species and functional composition shifted to favour light-wooded, small-seeded taxa. Alpha-diversity increased, but beta-diversity was unaffected by disturbance, in all four forests., Changes in response to disturbance in both functional composition and alpha-diversity were, however, small (2 - 4% depending on the parameter) and similar among forests., Synthesis. This study demonstrates that variation in the functional composition of Amazonian forests does not lead to large differences in the response of these forests to treefall disturbances, and overall, these events have a minor role in maintaining the diversity of these ecosystems. [ABSTRACT FROM AUTHOR]

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: 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 assemblages can be reliably mapped from space. [ABSTRACT FROM AUTHOR]

1. Tropical forest above-ground wood production (AGWP) varies substantially along environmental gradients. Some evidence suggests that AGWP may vary between regions and specifically that Asian forests have particularly high AGWP. However, comparisons across biogeographic regions using standardized methods are lacking, limiting our assessment of pan-tropical variation in AGWP and potential causes. 2. We sampled AGWP in NW Amazon (17 long-term forest plots) and N Borneo (11 plots), both with abundant year-round precipitation. Within each region, forests growing on a broad range of edaphic conditions were sampled using standardized soil and forest measurement techniques. 3. Plot-level AGWP was 49% greater in Borneo than in Amazonia (9.73 ± 0.56 vs. 6.53 ± 0.34 Mg dry mass ha-1 a-1, respectively; regional mean ± 1 SE). AGWP was positively associated with soil fertility (PCA axes, sum of bases and total P). After controlling for the edaphic environment,AGWP remained significantly higher in Bornean plots. Differences in AGWP were largely attributable to differing height-diameter allometry in the two regions and the abundance of large trees in Borneo. This may be explained, in part, by the greater solar radiation in Borneo compared with NWAmazonia. 4. Trees belonging to the dominant SE Asian family, Dipterocarpaceae, gained woody biomass faster than otherwise equivalent, neighbouring non-dipterocarps, implying that the exceptional production of Bornean forests may be driven by floristic elements. This dominant SE Asian family may partition biomass differently or be more efficient at harvesting resources and in converting themto woody biomass. 5. Synthesis. N Bornean forests have much greater AGWP rates than those in NW Amazon when soil conditions and rainfall are controlled for. Greater resource availability and the highly productive dipterocarps may, in combination, explain why Asian forests produce wood half as fast again as comparable forests in the Amazon. Our results also suggest that taxonomic groups differ in their fundamental ability to capture carbon and that different tropical regions may therefore have different carbon uptake capacities due to biogeographic history. [ABSTRACT FROM AUTHOR]

Tropical forests are biologically diverse ecosystems that play important roles in the carbon cycle and maintenance of global biodiversity. Understanding how tropical forests respond to environmental changes is important, as changes in carbon storage can modulate the rate and magnitude of climate change. Applying an ecoinformatics approach for managing long-term forest inventory plot data, where individual trees are tracked over time, facilitates regional and cross-continental forest research to evaluate changes in taxonomic composition, growth, recruitment and mortality rates, and carbon and biomass stocks. We developed ForestPlots.net as a secure, online inventory data repository and to facilitate data management of long-term tropical forest plots to promote scientific collaborations among independent researchers. The key novel features of the database are: (a) a design that efficiently deals with time-series data; (b) data management tools to assess potential errors; and (c) a query library to generate outputs (e.g. biomass and carbon stock changes over time). [ABSTRACT FROM AUTHOR]

Question: How many vegetation plot observations (relevés) are available in electronic databases, how are they geographically distributed, what are their properties and how might they be discovered and located for research and application? Location: Global. Methods: We compiled the Global Index of Vegetation-Plot Databases (GIVD; ), an Internet resource aimed at registering metadata on existing vegetation databases. For inclusion, databases need to (i) contain temporally and spatially explicit species co-occurrence data and (ii) be accessible to the scientific public. This paper summarizes structure and data quality of databases registered in GIVD as of 30 December 2010. Results: On the given date, 132 databases containing more than 2.4 million non-overlapping plots had been registered in GIVD. The majority of these data were in European databases (83 databases, 1.6 million plots), whereas other continents were represented by substantially less (North America 15, Asia 13, Africa nine, South America seven, Australasia two, multi-continental three). The oldest plot observation was 1864, but most plots were recorded after 1970. Most plots reported vegetation on areas of 1 to 1000 m2; some also stored time-series and nested-plot data. Apart from geographic reference (required for inclusion), most frequent information was on altitude (71%), slope aspect and inclination (58%) and land use (38%), but rarely soil properties (<7%). Conclusions: The vegetation plot data in GIVD constitute a major resource for biodiversity research, both through the large number of species occurrence records and storage of species co-occurrence information at a small scale, combined with structural and plot-based environmental data. We identify shortcomings in available data that need to be addressed through sampling under-represented geographic regions, providing better incentives for data collection and sharing, developing user-friendly database exchange standards, as well as tools to analyse and remove confounding effects of sampling biases. The increased availability of data sets conferred by registration in GIVD offers significant opportunities for large-scale studies in community ecology, macroecology and global change research. [ABSTRACT FROM AUTHOR]