Global‐scale impacts of nitrogen deposition on tree carbon sequestration in tropical,temperate, and boreal forests: A meta‐analysis

Elevated nitrogen (N) deposition may increase net primary productivity in N‐limited terrestrial ecosystems and thus enhance the terrestrial carbon (C) sink. To assess the magnitude of this N‐induced C sink, we performed a meta‐analysis on data from forest fertilization experiments to estimate N‐induced C sequestration in aboveground tree woody biomass, a stable C pool with long turnover times. Our results show that boreal and temperate forests responded strongly to N addition and sequestered on average an additional 14 and 13 kg C per kg N in aboveground woody biomass, respectively. Tropical forests, however, did not respond significantly to N addition. The common hypothesis that tropical forests do not respond to N because they are phosphorus‐limited could not be confirmed, as we found no significant response to phosphorus addition in tropical forests. Across climate zones, we found that young forests responded more strongly to N addition, which is important as many previous meta‐analyses of N addition experiments rely heavily on data from experiments on seedlings and young trees. Furthermore, the C–N response (defined as additional mass unit of C sequestered per additional mass unit of N addition) was affected by forest productivity, experimental N addition rate, and rate of ambient N deposition. The estimated C–N responses from our meta‐analysis were generally lower that those derived with stoichiometric scaling, dynamic global vegetation models, and forest growth inventories along N deposition gradients. We estimated N‐induced global C sequestration in tree aboveground woody biomass by multiplying the C–N responses obtained from the meta‐analysis with N deposition estimates per biome. We thus derived an N‐induced global C sink of about 177 (112–243) Tg C/year in aboveground and belowground woody biomass, which would account for about 12% of the forest biomass C sink (1,400 Tg C/year).     

Structural characteristics and aboveground biomass of old‐growth spruce–fir stands in the eastern Carpathian mountains,Ukraine

Abstract

Temperate old‐growth forests are known to have ecological characteristics distinct from younger forests, but these have been poorly described for the remaining old‐growth Picea abies–Abies alba forests in the eastern Carpathian mountains. In addition, recent studies suggest that old‐growth forests may be more significant carbon sinks than previously recognized. This has stimulated interest in quantifying aboveground carbon stocks in primary forest systems. We investigated the structural attributes and aboveground biomass in two remnant old‐growth spruce–fir stands and compared these against a primary (never logged) mature reference stand. Our sites were located in the Gorgany Nature Reserve in western Ukraine. Overstory data were collected using variable radius plots; coarse woody debris was sampled along line intercept transects. Differences among sites were assessed using non‐parametric statistical analyses. Goodness‐of‐fit tests were used to evaluate the form of diameter distributions. The results strongly supported the hypothesis that old‐growth temperate spruce–fir forests have greater structural complexity compared to mature forests, including higher densities of large trees, more complex horizontal structure, and elevated aboveground biomass. The late‐successional sites we sampled exhibited rotated sigmoid diameter distributions; these may reflect natural disturbance dynamics. Old‐growth Carpathian spruce–fir forests store on average approximately 155–165 Mg ha^?1 of carbon in aboveground tree parts alone. This is approximately 50% higher than mature stands. Given the scarcity of primary spruce–fir forests in the Carpathian region, remaining stands have high conservation value, both as habitat for late‐successional species and as carbon storage reservoirs.     

Conventional intensive logging promotes loss of organic carbon from the mineral soil

There are few data, but diametrically opposed opinions, about the impacts of forest logging on soil organic carbon (SOC). Reviews and research articles conclude either that there is no effect, or show contradictory effects. Given that SOC is a substantial store of potential greenhouse gasses and forest logging and harvesting is routine, resolution is important. We review forest logging SOC studies and provide an overarching conceptual explanation for their findings. The literature can be separated into short‐term empirical studies, longer‐term empirical studies and long‐term modelling. All modelling that includes major aboveground and belowground biomass pools shows a long‐term (i.e. ≥300 years) decrease in SOC when a primary forest is logged and then subjected to harvesting cycles. The empirical longer‐term studies indicate likewise. With successive harvests the net emission accumulates but is only statistically perceptible after centuries. Short‐term SOC flux varies around zero. The long‐term drop in SOC in the mineral soil is driven by the biomass drop from the primary forest level but takes time to adjust to the new temporal average biomass. We show agreement between secondary forest SOC stocks derived purely from biomass information and stocks derived from complex forest harvest modelling. Thus, conclusions that conventional harvests do not deplete SOC in the mineral soil have been a function of their short time frames. Forest managers, climate change modellers and environmental policymakers need to assume a long‐term net transfer of SOC from the mineral soil to the atmosphere when primary forests are logged and then undergo harvest cycles. However, from a greenhouse accounting perspective, forest SOC is not the entire story. Forest wood products that ultimately reach landfill, and some portion of which produces some soil‐like material there rather than in the forest, could possibly help attenuate the forest SOC emission by adding to a carbon pool in landfill.     

Tree diversity,composition, forest structure and aboveground biomass dynamics after single and repeated fire in a Bornean rain forest

Forest fires remain a devastating phenomenon in the tropics that not only affect forest structure and biodiversity, but also contribute significantly to atmospheric CO2. Fire used to be extremely rare in tropical forests, leaving ample time for forests to regenerate to pre-fire conditions. In recent decades, however, tropical forest fires occur more frequently and at larger spatial scales than they used to. We studied forest structure, tree species diversity, tree species composition, and aboveground biomass during the first 7 years since fire in unburned, once burned and twice burned forest of eastern Borneo to determine the rate of recovery of these forests. We paid special attention to changes in the tree species composition during burned forest regeneration because we expect the long-term recovery of aboveground biomass and ecosystem functions in burned forests to largely depend on the successful regeneration of the pre-fire, heavy-wood, species composition. We found that forest structure (canopy openness, leaf area index, herb cover, and stem density) is strongly affected by fire but shows quick recovery. However, species composition shows no or limited recovery and aboveground biomass, which is greatly reduced by fire, continues to be low or decline up to 7 years after fire. Consequently, large amounts of the C released to the atmosphere by fire will not be recaptured by the burned forest ecosystem in the near future. We also observed that repeated fire, with an inter-fire interval of 15 years, does not necessarily lead to a huge deterioration in the regeneration potential of tropical forest. We conclude that burned forests are valuable and should be conserved and that long-term monitoring programs in secondary forests are necessary to determine their recovery rates, especially in relation to aboveground biomass accumulation.     

Simulating the effects of harvest and biofuel production on the forest system carbon balance of the Midwest,USA

Forests of the Midwestern United States are an important source of fiber for the wood and paper products industries. Scientists, land managers, and policy makers are interested in using woody biomass and/or harvest residue for biofuel feedstocks. However, the effects of increased biomass removal for biofuel production on forest production and forest system carbon balance remain uncertain. We modeled the carbon (C) cycle of the forest system by dividing it into two distinct components: (1) biological (net ecosystem production, net primary production, autotrophic and heterotrophic respiration, vegetation, and soil C content) and (2) industrial (harvest operations and transportation, production, use, and disposal of major wood products including biofuel and associated C emissions). We modeled available woody biomass feedstock and whole‐system carbon balance of 220 000 km² of temperate forests in the Upper Midwest, USA by coupling an ecosystem process model to a collection of greenhouse gas life‐cycle inventory models and simulating seven forest harvest scenarios in the biological ecosystem and three biofuel production scenarios in the industrial system for 50 years. The forest system was a carbon sink (118 g C m^?2 yr^?1) under current management practices and forest product production rates. However, the system became a C source when harvest area was doubled and biofuel production replaced traditional forest products. Total carbon stores in the vegetation and soil increased by 5–10% under low‐intensity management scenarios and current management, but decreased up to 3% under high‐intensity harvest regimes. Increasing harvest residue removal during harvest had more modest effects on forest system C balance and total biomass removal than increasing the rate of clear‐cut harvests or area harvested. Net forest system C balance was significantly, and negatively correlated (R² = 0.67) with biomass harvested, illustrating the trade‐offs between increased C uptake by forests and utilization of woody biomass for biofuel feedstock.     

The spatial distribution of forest biomass in the Brazilian Amazon: a comparison of estimates

The amount of carbon released to the atmosphere as a result of deforestation is determined, in part, by the amount of carbon held in the biomass of the forests converted to other uses. Uncertainty in forest biomass is responsible for much of the uncertainty in current estimates of the flux of carbon from land‐use change. In the present contribution several estimates of forest biomass are compared for the Brazilian Amazon, based on spatial interpolations of direct measurements, relationships to climatic variables, and remote sensing data. Three questions were posed: First, do the methods yield similar estimates? Second, do they yield similar spatial patterns of distribution of biomass? And, third, what factors need most attention if we are to predict more accurately the distribution of forest biomass over large areas? The answer to the first two questions is that estimates of biomass for Brazil's Amazonian forests (including dead and belowground biomass) vary by more than a factor of two, from a low of 39 PgC to a high of 93 PgC. Furthermore, the estimates disagree as to the regions of high and low biomass. The lack of agreement among estimates confirms the need for reliable determination of aboveground biomass over large areas. Potential methods include direct measurement of biomass through forest inventories with improved allometric regression equations, dynamic modelling of forest recovery following observed stand‐replacing disturbances, and estimation of aboveground biomass from airborne or satellite‐based instruments sensitive to the vertical structure plant canopies.     

Mapping the biomass of Bornean tropical rain forest from remotely sensed data

The biomass and biomass dynamics of forests are major uncertainties in our understanding of tropical environments. Remote sensing is often the only practical means of acquiring information on forest biomass but has not always been used successfully. Here the conventional approaches to the estimation of forest biomass from remotely sensed data were evaluated relative to techniques based on the application of artificial neural networks. Together these approaches were used to estimate and map the biomass of tropical forests in north‐eastern Borneo from Landsat TM data. The neural networks were found to be particularly suited to the application. A basic multi‐layer perceptron network, for example, provided estimates of biomass that were strongly correlated with those measured in the field (r = 0.80). Moreover, these estimates were more strongly correlated with biomass than those derived from 230 conventional vegetation indices, including the widely used normalized difference vegetation index (NDVI).     

Water availability drives aboveground biomass and bird richness in forest restoration plantings to achieve carbon and biodiversity cobenefits

To combat global warming and biodiversity loss, we require effective forest restoration that encourages recovery of species diversity and ecosystem function to deliver essential ecosystem services, such as biomass accumulation. Further, understanding how and where to undertake restoration to achieve carbon sequestration and biodiversity conservation would provide an opportunity to finance ecosystem restoration under carbon markets. We surveyed 30 native mixed‐species plantings in subtropical forests and woodlands in Australia and used structural equation modeling to determine vegetation, soil, and climate variables most likely driving aboveground biomass accrual and bird richness and investigate the relationships between plant diversity, aboveground biomass accrual, and bird diversity. We focussed on woodland and forest‐dependent birds, and functional groups at risk of decline (insectivorous, understorey‐nesting, and small‐bodied birds). We found that mean moisture availability strongly limits aboveground biomass accrual and bird richness in restoration plantings, indicating potential synergies in choosing sites for carbon and biodiversity purposes. Counter to theory, woody plant richness was a poor direct predictor of aboveground biomass accrual, but was indirectly related via significant, positive effects of stand density. We also found no direct relationship between aboveground biomass accrual and bird richness, likely because of the strong effects of moisture availability on both variables. Instead, moisture availability and patch size strongly and positively influenced the richness of woodland and forest‐dependent birds. For understorey‐nesting birds, however, shrub cover and patch size predicted richness. Stand age or area of native vegetation surrounding the patch did not influence bird richness. Our results suggest that in subtropical biomes, planting larger patches to higher densities, ideally using a diversity of trees and shrubs (characteristics of ecological plantings) in more mesic locations will enhance the provision of carbon and biodiversity cobenefits. Further, ecological plantings will aid the rapid recovery of woodland and forest bird richness, with comparable aboveground biomass accrual to less diverse forestry plantations.     

Biodiversity and climate determine the functioning of Neotropical forests

Aim

Tropical forests account for a quarter of the global carbon storage and a third of the terrestrial productivity. Few studies have teased apart the relative importance of environmental factors and forest attributes for ecosystem functioning, especially for the tropics. This study aims to relate aboveground biomass (AGB) and biomass dynamics (i.e., net biomass productivity and its underlying demographic drivers: biomass recruitment, growth and mortality) to forest attributes (tree diversity, community‐mean traits and stand basal area) and environmental conditions (water availability, soil fertility and disturbance).

Location

Neotropics.

Methods

We used data from 26 sites, 201 1‐ha plots and >92,000 trees distributed across the Neotropics. We quantified for each site water availability and soil total exchangeable bases and for each plot three key community‐weighted mean functional traits that are important for biomass stocks and productivity. We used structural equation models to test the hypothesis that all drivers have independent, positive effects on biomass stocks and dynamics.

Results

Of the relationships analysed, vegetation attributes were more frequently associated significantly with biomass stocks and dynamics than environmental conditions (in 67 vs. 33% of the relationships). High climatic water availability increased biomass growth and stocks, light disturbance increased biomass growth, and soil bases had no effect. Rarefied tree species richness had consistent positive relationships with biomass stocks and dynamics, probably because of niche complementarity, but was not related to net biomass productivity. Community‐mean traits were good predictors of biomass stocks and dynamics.

Main conclusions

Water availability has a strong positive effect on biomass stocks and growth, and a future predicted increase in (atmospheric) drought might, therefore, potentially reduce carbon storage. Forest attributes, including species diversity and community‐weighted mean traits, have independent and important relationships with AGB stocks, dynamics and ecosystem functioning, not only in relatively simple temperate systems, but also in structurally complex hyper‐diverse tropical forests.     

Monitoring individual tree‐based change with airborne lidar

Understanding the carbon flux of forests is critical for constraining the global carbon cycle and managing forests to mitigate climate change. Monitoring forest growth and mortality rates is critical to this effort, but has been limited in the past, with estimates relying primarily on field surveys. Advances in remote sensing enable the potential to monitor tree growth and mortality across landscapes. This work presents an approach to measure tree growth and loss using multidate lidar campaigns in a high‐biomass forest in California, USA. Individual tree crowns were delineated in 2008 and again in 2013 using a 3D crown segmentation algorithm, with derived heights and crown radii extracted and used to estimate individual tree aboveground biomass. Tree growth, loss, and aboveground biomass were analyzed with respect to tree height and crown radius. Both tree growth and loss rates decrease with increasing tree height, following the expectation that trees slow in growth rate as they age. Additionally, our aboveground biomass analysis suggests that, while the system is a net source of aboveground carbon, these carbon dynamics are governed by size class with the largest sources coming from the loss of a relatively small number of large individuals. This study demonstrates that monitoring individual tree‐based growth and loss can be conducted with multidate airborne lidar, but these methods remain relatively immature. Disparities between lidar acquisitions were particularly difficult to overcome and decreased the sample of trees analyzed for growth rate in this study to 21% of the full number of delineated crowns. However, this study illuminates the potential of airborne remote sensing for ecologically meaningful forest monitoring at an individual tree level. As methods continue to improve, airborne multidate lidar will enable a richer understanding of the drivers of tree growth, loss, and aboveground carbon flux.     

Improving predictions of tropical forest response to climate change through integration of field studies and ecosystem modeling

Tropical forests play a critical role in carbon and water cycles at a global scale. Rapid climate change is anticipated in tropical regions over the coming decades and, under a warmer and drier climate, tropical forests are likely to be net sources of carbon rather than sinks. However, our understanding of tropical forest response and feedback to climate change is very limited. Efforts to model climate change impacts on carbon fluxes in tropical forests have not reached a consensus. Here, we use the Ecosystem Demography model (ED2) to predict carbon fluxes of a Puerto Rican tropical forest under realistic climate change scenarios. We parameterized ED2 with species‐specific tree physiological data using the Predictive Ecosystem Analyzer workflow and projected the fate of this ecosystem under five future climate scenarios. The model successfully captured interannual variability in the dynamics of this tropical forest. Model predictions closely followed observed values across a wide range of metrics including aboveground biomass, tree diameter growth, tree size class distributions, and leaf area index. Under a future warming and drying climate scenario, the model predicted reductions in carbon storage and tree growth, together with large shifts in forest community composition and structure. Such rapid changes in climate led the forest to transition from a sink to a source of carbon. Growth respiration and root allocation parameters were responsible for the highest fraction of predictive uncertainty in modeled biomass, highlighting the need to target these processes in future data collection. Our study is the first effort to rely on Bayesian model calibration and synthesis to elucidate the key physiological parameters that drive uncertainty in tropical forests responses to climatic change. We propose a new path forward for model‐data synthesis that can substantially reduce uncertainty in our ability to model tropical forest responses to future climate.     

Big‐sized trees overrule remaining trees' attributes and species richness as determinants of aboveground biomass in tropical forests

Large‐diameter, tall‐stature, and big‐crown trees are the main stand structures of forests, generally contributing a large fraction of aboveground biomass, and hence play an important role in climate change mitigation strategies. Here, we hypothesized that the effects of large‐diameter, tall‐stature, and big‐crown trees overrule the effects of species richness and remaining trees attributes on aboveground biomass in tropical forests (i.e., we term the “big‐sized trees hypothesis”). Specifically, we assessed the importance of: (a) the “top 1% big‐sized trees effect” relative to species richness; (b) the “99% remaining trees effect” relative to species richness; and (c) the “top 1% big‐sized trees effect” relative to the “99% remaining trees effect” and species richness on aboveground biomass. Using environmental factor and forest inventory datasets from 712 tropical forest plots in Hainan Island of southern China, we tested several structural equation models for disentangling the relative effects of big‐sized trees, remaining trees attributes, and species richness on aboveground biomass, while considering for the full (indirect effects only) and partial (direct and indirect effects) mediation effects of climatic and soil conditions, as well as interactions between species richness and trees attributes. We found that top 1% big‐sized trees attributes strongly increased aboveground biomass (i.e., explained 55%–70% of the accounted variation) compared to species richness (2%–18%) and 99% remaining trees attributes (6%–10%). In addition, species richness increased aboveground biomass indirectly via increasing big‐sized trees but via decreasing remaining trees. Hence, we show that the “big‐sized trees effect” overrides the effects of remaining trees attributes and species richness on aboveground biomass in tropical forests. This study also indicates that big‐sized trees may be more susceptible to atmospheric drought. We argue that the effects of big‐sized trees on species richness and aboveground biomass should be tested for better understanding of the ecological mechanisms underlying forest functioning.     

Mineral soil carbon fluxes in forests and implications for carbon balance assessments

Forest carbon cycles play an important role in efforts to understand and mitigate climate change. Large amounts of carbon (C) are stored in deep mineral forest soils, but are often not considered in accounting for global C fluxes because mineral soil C is commonly thought to be relatively stable. We explore C fluxes associated with forest management practices by examining existing data on forest C fluxes in the northeastern US. Our findings demonstrate that mineral soil C can play an important role in C emissions, especially when considering intensive forest management practices. Such practices are known to cause a high aboveground C flux to the atmosphere, but there is evidence that they can also promote comparably high and long‐term belowground C fluxes. If these additional fluxes are widespread in forests, recommendations for increased reliance on forest biomass may need to be reevaluated. Furthermore, existing protocols for the monitoring of forest C often ignore mineral soil C due to lack of data. Forest C analyses will be incomplete until this problem is resolved.     

亚热带典型森林地上和地下凋落物输入对土壤新老有机碳动态平衡的影响

凋落物是森林土壤有机碳(SOC)形成、稳定和周转的重要影响因子。目前针对亚热带不同类型森林地上和地下凋落物对新SOC累积和老SOC输出动态平衡的影响仍不清楚。本研究以中亚热带常绿阔叶天然林、马尾松人工林和杉木人工林为对象,基于C3/C4植物-土壤置换试验,利用稳定同位素¹³C示踪方法开展3年野外定位试验,分析了森林地上、地下凋落物输入对SOC周转的影响。结果表明: 森林类型、凋落物处理和时间均能显著影响SOC含量、土壤δ¹³C值、新SOC和老SOC含量,且存在显著的森林类型×凋落物处理交互效应。地上和地下凋落物输入均能显著提高SOC含量和净增量,与杉木人工林相比,天然林SOC对凋落物输入的响应更敏感。凋落物输入显著降低了土壤δ¹³C值,且天然林、马尾松人工林土壤δ¹³C显著低于杉木人工林。在马尾松人工林,地下凋落物处理的新SOC含量显著高于地上凋落物;在天然林和马尾松人工林,地下凋落物输入处理的老SOC含量显著低于地上凋落物处理。此外,地上凋落物归还量和地下根生物量与SOC含量和净增量呈显著正相关,而地下根凋落物量和C/N与新SOC含量呈显著正相关。森林地下凋落物比地上凋落物输入对SOC周转的影响更重要,且不同森林凋落物输入对SOC的影响存在差异性。本研究可为揭示亚热带典型森林土壤有机碳库的形成和可持续管理提供依据。     

Environmental correlates of tree biomass, basal area, wood specific gravity and stem density gradients in Borneo's tropical forests

Aim Tropical forests have been recognized as important global carbon sinks and sources. However, many uncertainties about the spatial distribution of live tree above‐ground biomass (AGB) remain, mostly due to limited availability of AGB field data. Recent studies in the Amazon have already shown the importance of large sample size for accurate AGB gradient analysis. Here we use a large stem density, basal area, community wood density and AGB dataset to study and explain their spatial patterns in an Asian tropical forest. Location Borneo, Southeast Asia. Methods We combined stem density, basal area, community wood density and AGB data from 83 locations in Borneo with an environmental database containing elevation, climate and soil variables. The Akaike information criterion was used to select models and environmental variables that best explained the observed values of stem density, basal area, community wood density and AGB. These models were used to extrapolate these parameters across Borneo. Results We found that wood density, stem density, basal area and AGB respond significantly, but differentially, to the environment. AGB was only correlated with basal area, but not with stem density and community wood specific gravity. Main conclusions Unlike results from Amazonian forests, soil fertility was an important positive correlate for AGB in Borneo while community wood density, which is a main driver of AGB in the Neotropics, did not correlate with AGB in Borneo. Also, Borneo's average AGB of 457.1 Mg ha^?1 was c. 60% higher than the Amazonian average of 288.6 Mg ha^?1. We find evidence that this difference might be partly explained by the high density of large wind‐dispersed Dipterocarpaceae in Borneo, which need to be tall and emergent to disperse their seeds. Our results emphasize the importance of Bornean forests as carbon sinks and sources due to their high carbon storage capacity.     

Allometric constraints and competition enable the simulation of size structure and carbon fluxes in a dynamic vegetation model of tropical forests (LM3PPA‐TV)

Tropical forests are a key determinant of the functioning of the Earth system, but remain a major source of uncertainty in carbon cycle models and climate change projections. In this study, we present an updated land model (LM3PPA‐TV) to improve the representation of tropical forest structure and dynamics in Earth system models (ESMs). The development and parameterization of LM3PPA‐TV drew on extensive datasets on tropical tree traits and long‐term field censuses from Barro Colorado Island (BCI), Panama. The model defines a new plant functional type (PFT) based on the characteristics of shade‐tolerant, tropical tree species, implements a new growth allocation scheme based on realistic tree allometries, incorporates hydraulic constraints on biomass accumulation, and features a new compartment for tree branches and branch fall dynamics. Simulation experiments reproduced observed diurnal and seasonal patterns in stand‐level carbon and water fluxes, as well as mean canopy and understory tree growth rates, tree size distributions, and stand‐level biomass on BCI. Simulations at multiple sites captured considerable variation in biomass and size structure across the tropical forest biome, including observed responses to precipitation and temperature. Model experiments suggested a major role of water limitation in controlling geographic variation forest biomass and structure. However, the failure to simulate tropical forests under extreme conditions and the systematic underestimation of forest biomass in Paleotropical locations highlighted the need to incorporate variation in hydraulic traits and multiple PFTs that capture the distinct floristic composition across tropical domains. The continued pressure on tropical forests from global change demands models which are able to simulate alternative successional pathways and their pace to recovery. LM3PPA‐TV provides a tool to investigate geographic variation in tropical forests and a benchmark to continue improving the representation of tropical forests dynamics and their carbon storage potential in ESMs.     

Long‐term recovery of the functional community assembly and carbon pools in an African tropical forest succession

On the African continent, the population is expected to expand fourfold in the next century, which will increasingly impact the global carbon cycle and biodiversity conservation. Therefore, it is of vital importance to understand how carbon stocks and community assembly recover after slash‐and‐burn events in tropical second growth forests. We inventoried a chronosequence of 15 1‐ha plots in lowland tropical forest of the central Congo Basin and evaluated changes in aboveground and soil organic carbon stocks and in tree species diversity, functional composition, and community‐weighted functional traits with succession. We aimed to track long‐term recovery trajectories of species and carbon stocks in secondary forests, comparing 5 to 200 + year old secondary forest with reference primary forest. Along the successional gradient, the functional composition followed a trajectory from resource acquisition to resource conservation, except for nitrogen‐related leaf traits. Despite a fast, initial recovery of species diversity and functional composition, there were still important structural and carbon stock differences between old growth secondary and pristine forest, which suggests that a full recovery of secondary forests might take much longer than currently shown. As such, the aboveground carbon stocks of 200 + year old forest were only 57% of those in the pristine reference forest, which suggests a slow recovery of aboveground carbon stocks, although more research is needed to confirm this observation. The results of this study highlight the need for more in‐depth studies on forest recovery in Central Africa, to gain insight into the processes that control biodiversity and carbon stock recovery.     

Disentangling stand and environmental correlates of aboveground biomass in Amazonian forests

Tropical forests contain an important proportion of the carbon stored in terrestrial vegetation, but estimated aboveground biomass (AGB) in tropical forests varies two‐fold, with little consensus on the relative importance of climate, soil and forest structure in explaining spatial patterns. Here, we present analyses from a plot network designed to examine differences among contrasting forest habitats (terra firme, seasonally flooded, and white‐sand forests) that span the gradient of climate and soil conditions of the Amazon basin. We installed 0.5‐ha plots in 74 sites representing the three lowland forest habitats in both Loreto, Peru and French Guiana, and we integrated data describing climate, soil physical and chemical characteristics and stand variables, including local measures of wood specific gravity (WSG). We use a hierarchical model to separate the contributions of stand variables from climate and soil variables in explaining spatial variation in AGB. AGB differed among both habitats and regions, varying from 78 Mg ha^?1 in white‐sand forest in Peru to 605 Mg ha^?1 in terra firme clay forest of French Guiana. Stand variables including tree size and basal area, and to a lesser extent WSG, were strong predictors of spatial variation in AGB. In contrast, soil and climate variables explained little overall variation in AGB, though they did co‐vary to a limited extent with stand parameters that explained AGB. Our results suggest that positive feedbacks in forest structure and turnover control AGB in Amazonian forests, with richer soils (Peruvian terra firme and all seasonally flooded habitats) supporting smaller trees with lower wood density and moderate soils (French Guianan terra firme) supporting many larger trees with high wood density. The weak direct relationships we observed between soil and climate variables and AGB suggest that the most appropriate approaches to landscape scale modeling of AGB in the Amazon would be based on remote sensing methods to map stand structure.     

Tree allometry and improved estimation of carbon stocks and balance in tropical forests

Tropical forests hold large stores of carbon, yet uncertainty remains regarding their quantitative contribution to the global carbon cycle. One approach to quantifying carbon biomass stores consists in inferring changes from long-term forest inventory plots. Regression models are used to convert inventory data into an estimate of aboveground biomass (AGB). We provide a critical reassessment of the quality and the robustness of these models across tropical forest types, using a large dataset of 2,410 trees ≥ 5 cm diameter, directly harvested in 27 study sites across the tropics. Proportional relationships between aboveground biomass and the product of wood density, trunk cross-sectional area, and total height are constructed. We also develop a regression model involving wood density and stem diameter only. Our models were tested for secondary and old-growth forests, for dry, moist and wet forests, for lowland and montane forests, and for mangrove forests. The most important predictors of AGB of a tree were, in decreasing order of importance, its trunk diameter, wood specific gravity, total height, and forest type (dry, moist, or wet). Overestimates prevailed, giving a bias of 0.5–6.5% when errors were averaged across all stands. Our regression models can be used reliably to predict aboveground tree biomass across a broad range of tropical forests. Because they are based on an unprecedented dataset, these models should improve the quality of tropical biomass estimates, and bring consensus about the contribution of the tropical forest biome and tropical deforestation to the global carbon cycle. Electronic Supplementary Material Supplementary material is available for this article at     

Soil charcoal as long‐term pyrogenic carbon storage in Amazonian seasonal forests

Forest fires (paleo + modern) have caused charcoal particles to accumulate in the soil vertical profile in Amazonia. This forest compartment is a long‐term carbon reservoir with an important role in global carbon balance. Estimates of stocks remain uncertain in forests that have not been altered by deforestation but that have been impacted by understory fires and selective logging. We estimated the stock of pyrogenic carbon derived from charcoal accumulated in the soil profile of seasonal forest fragments impacted by fire and selective logging in the northern portion of Brazilian Amazonia. Sixty‐nine soil cores to 1‐m depth were collected in 12 forest fragments of different sizes. Charcoal stocks averaged 3.45 ± 2.17 Mg ha^?1 (2.24 ± 1.41 Mg C ha^?1). Pyrogenic carbon was not directly related to the size of the forest fragments. This carbon is equivalent to 1.40% (0.25% to 4.04%) of the carbon stocked in aboveground live tree biomass in these fragments. The vertical distribution of pyrogenic carbon indicates an exponential model, where the 0–30 cm depth range has 60% of the total stored. The total area of Brazil's Amazonian seasonal forests and ecotones not altered by deforestation implies 65–286 Tg of pyrogenic carbon accumulated along the soil vertical profile. This is 1.2–2.3 times the total amount of residual pyrogenic carbon formed by biomass burning worldwide in 1 year. Our analysis suggests that the accumulated charcoal in the soil vertical profile in Amazonian forests is a substantial pyrogenic carbon pool that needs to be considered in global carbon models.