Temperature explains global variation in biomass among humid old‐growth forests

Aim To develop and test a simple climate‐based ecophysiological model of above‐ground biomass – an approach that can be applied directly to predicting the effects of climate change on forest carbon stores. Location Humid lowland forests world‐wide. Methods We developed a new approach to modelling the aboveground biomass of old‐growth forest (AGB_max) based on the influences of temperature on gross primary productivity (GPP) and what we call total maintenance cost (TMC), which includes autotrophic respiration as well as leaf, stem and other plant construction required to maintain biomass. We parameterized the models with measured carbon fluxes and tested them by comparing predicted AGB_max with measured AGB for another 109 old‐growth sites. Results Our models explained 57% of the variation in GPP across 95 sites and 79% of the variation in TMC across 17 sites. According to the best‐fit models, the ratio of GPP to maintenance cost per unit biomass (MCB) peaks at 16.5 °C, indicating that this is the air temperature leading to the highest possible AGB_max when temperatures are constant. Seasonal temperature variation generally reduces predicted AGB_max, and thus maritime temperate climates are predicted to have the highest AGB_max. The shift in temperatures from temperate maritime to tropical climates increases MCB more than GPP, and thus decreases AGB_max. Overall, our model explains exactly 50% of the variation in AGB among humid lowland old‐growth forests. Main conclusions Temperature plays an important role in explaining global variation in biomass among humid lowland old‐growth forests, a role that can be understood in terms of the dual effects of temperature on GPP and TMC. Our simple model captures these influences, and could be an important tool for predicting the effects of climate change on forest carbon stores.     

Interactions between Canopy Structure and Herbaceous Biomass along Environmental Gradients in Moist Forest and Dry Miombo Woodland of Tanzania

We have limited understanding of how tropical canopy foliage varies along environmental gradients, and how this may in turn affect forest processes and functions. Here, we analyse the relationships between canopy leaf area index (LAI) and above ground herbaceous biomass (AGB_H) along environmental gradients in a moist forest and miombo woodland in Tanzania. We recorded canopy structure and herbaceous biomass in 100 permanent vegetation plots (20 m × 40 m), stratified by elevation. We quantified tree species richness, evenness, Shannon diversity and predominant height as measures of structural variability, and disturbance (tree stumps), soil nutrients and elevation as indicators of environmental variability. Moist forest and miombo woodland differed substantially with respect to nearly all variables tested. Both structural and environmental variables were found to affect LAI and AGB_H, the latter being additionally dependent on LAI in moist forest but not in miombo, where other factors are limiting. Combining structural and environmental predictors yielded the most powerful models. In moist forest, they explained 76% and 25% of deviance in LAI and AGB_H, respectively. In miombo woodland, they explained 82% and 45% of deviance in LAI and AGB_H. In moist forest, LAI increased non-linearly with predominant height and linearly with tree richness, and decreased with soil nitrogen except under high disturbance. Miombo woodland LAI increased linearly with stem density, soil phosphorous and nitrogen, and decreased linearly with tree species evenness. AGB_H in moist forest decreased with LAI at lower elevations whilst increasing slightly at higher elevations. AGB_H in miombo woodland increased linearly with soil nitrogen and soil pH. Overall, moist forest plots had denser canopies and lower AGB_H compared with miombo plots. Further field studies are encouraged, to disentangle the direct influence of LAI on AGB_H from complex interrelationships between stand structure, environmental gradients and disturbance in African forests and woodlands.     

An integrated pan‐tropical biomass map using multiple reference datasets

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.     

Spatial heterogeneity and carbon contribution of aboveground biomass of moso bamboo by using geostatistical theory

Moso bamboo extensively distributes in southeast and south Asia, and plays an important role in global carbon budget. However, its spatial distribution and heterogeneity are poorly understood. This research uses geostatistics theory to examine the spatial heterogeneity of aboveground biomass (AGB) of moso bamboo, and uses a point kriging interpolation method to estimate and map its spatial distribution. Results showed that (1) spatial heterogeneity and spatial pattern of moso bamboo’s AGB can be revealed by an exponential semivariance model. The analysis of the model structure indicating that the AGB spatial heterogeneity is mainly composed of spatial autocorrelation components, and spatial autocorrelation range is from 360 to 41,220 m; (2) kriging standard deviation map showing the level of the model errors indicates that the AGB spatial distribution by point kriging interpolation method is reliable; (3) the average AGB of moso bamboo in Anji County is 44.228 Mg hm⁻², and carbon density is 20.297 Mg C hm⁻². The total AGB of moso bamboo accounts for 16.97% of the total forest-stand biomass in Zhejiang province. The total carbon storage of moso bamboo in China is 68.3993 Tg C, accounting for 1.6286% of the total forest carbon storage. This implies the important contribution of moso bamboo in regional or national carbon budget.     

Deadwood stocks increase with selective logging and large tree frequency in Gabon

Deadwood is a major component of aboveground biomass (AGB) in tropical forests and is important as habitat and for nutrient cycling and carbon storage. With deforestation and degradation taking place throughout the tropics, improved understanding of the magnitude and spatial variation in deadwood is vital for the development of regional and global carbon budgets. However, this potentially important carbon pool is poorly quantified in Afrotropical forests and the regional drivers of deadwood stocks are unknown. In the first large‐scale study of deadwood in Central Africa, we quantified stocks in 47 forest sites across Gabon and evaluated the effects of disturbance (logging), forest structure variables (live AGB, wood density, abundance of large trees), and abiotic variables (temperature, precipitation, seasonality). Average deadwood stocks (measured as necromass, the biomass of deadwood) were 65 Mg ha^?1 or 23% of live AGB. Deadwood stocks varied spatially with disturbance and forest structure, but not abiotic variables. Deadwood stocks increased significantly with logging (+38 Mg ha^?1) and the abundance of large trees (+2.4 Mg ha^?1 for every tree >60 cm dbh). Gabon holds 0.74 Pg C, or 21% of total aboveground carbon in deadwood, a threefold increase over previous estimates. Importantly, deadwood densities in Gabon are comparable to those in the Neotropics and respond similarly to logging, but represent a lower proportion of live AGB (median of 18% in Gabon compared to 26% in the Neotropics). In forest carbon accounting, necromass is often assumed to be a constant proportion (9%) of biomass, but in humid tropical forests this ratio varies from 2% in undisturbed forest to 300% in logged forest. Because logging significantly increases the deadwood carbon pool, estimates of tropical forest carbon should at a minimum use different ratios for logged (mean of 30%) and unlogged forests (mean of 18%).     

Optimal climate for large trees at high elevations drives patterns of biomass in remote forests of Papua New Guinea

Our ability to model global carbon fluxes depends on understanding how terrestrial carbon stocks respond to varying environmental conditions. Tropical forests contain the bulk of the biosphere's carbon. However, there is a lack of consensus as to how gradients in environmental conditions affect tropical forest carbon. Papua New Guinea (PNG) lies within one of the largest areas of contiguous tropical forest and is characterized by environmental gradients driven by altitude; yet, the region has been grossly understudied. Here, we present the first field assessment of aboveground biomass (AGB) across three main forest types of PNG using 193 plots stratified across 3,100‐m elevation gradient. Unexpectedly, AGB had no direct relationship to rainfall, temperature, soil, or topography. Instead, natural disturbances explained most variation in AGB. While large trees (diameter at breast height > 50 cm) drove altitudinal patterns of AGB, resulting in a major peak in AGB (2,200–3,100 m) and some of the most carbon‐rich forests at these altitudes anywhere. Large trees were correlated to a set of climatic variables following a hump‐shaped curve. The set of “optimal” climatic conditions found in montane cloud forests is similar to that of maritime temperate areas that harbor the largest trees in the world: high ratio of precipitation to evapotranspiration (2.8), moderate mean annual temperature (13.7°C), and low intra‐annual temperature range (7.5°C). At extreme altitudes (2,800–3,100 m), where tree diversity elsewhere is usually low and large trees are generally rare or absent, specimens from 18 families had girths >70 cm diameter and maximum heights 20–41 m. These findings indicate that simple AGB‐climate‐edaphic models may not be suitable for estimating carbon storage in forests where optimal climate niches exist. Our study, conducted in a very remote area, suggests that tropical montane forests may contain greater AGB than previously thought and the importance of securing their future under a changing climate is therefore enhanced.     

Evaluation of the terrestrial carbon cycle, future plant geography and climate-carbon cycle feedbacks using five Dynamic Global Vegetation Models (DGVMs)

This study tests the ability of five Dynamic Global Vegetation Models (DGVMs), forced with observed climatology and atmospheric CO₂, to model the contemporary global carbon cycle. The DGVMs are also coupled to a fast ‘climate analogue model’, based on the Hadley Centre General Circulation Model (GCM), and run into the future for four Special Report Emission Scenarios (SRES): A1FI, A2, B1, B2. Results show that all DGVMs are consistent with the contemporary global land carbon budget. Under the more extreme projections of future environmental change, the responses of the DGVMs diverge markedly. In particular, large uncertainties are associated with the response of tropical vegetation to drought and boreal ecosystems to elevated temperatures and changing soil moisture status. The DGVMs show more divergence in their response to regional changes in climate than to increases in atmospheric CO₂ content. All models simulate a release of land carbon in response to climate, when physiological effects of elevated atmospheric CO₂ on plant production are not considered, implying a positive terrestrial climate‐carbon cycle feedback. All DGVMs simulate a reduction in global net primary production (NPP) and a decrease in soil residence time in the tropics and extra‐tropics in response to future climate. When both counteracting effects of climate and atmospheric CO₂ on ecosystem function are considered, all the DGVMs simulate cumulative net land carbon uptake over the 21st century for the four SRES emission scenarios. However, for the most extreme A1FI emissions scenario, three out of five DGVMs simulate an annual net source of CO₂ from the land to the atmosphere in the final decades of the 21st century. For this scenario, cumulative land uptake differs by 494 Pg C among DGVMs over the 21st century. This uncertainty is equivalent to over 50 years of anthropogenic emissions at current levels.     

森林生物量遥感降尺度研究

森林生物量是评价全球碳氧平衡、气候变化的重要指标。目前已有基于星载激光雷达数据的全球森林生物量产品,但空间分辨率较低,不能很好地满足小区域森林调查和动态监测的需要。针对这一现状,以美国马里兰州两个森林分布状况不同的区域为研究区,基于CMS(Carbon Monitoring System)30 m分辨率和GEOCARBON 1 km分辨率森林地上生物量产品以及TM等数据源,通过升尺度模拟低分辨率生物量数据和直接使用低分辨率产品两种方式,分别尝试建立了多光谱地表参数和低分辨率森林地上生物量之间的统计关系,以此作为降尺度模型实现了森林地上生物量空间分辨率从1 km到30 m的转换,并对降尺度结果进行精度评价和误差分析。结果表明:模拟数据降尺度后的30 m分辨率森林地上生物量空间分布和CMS森林地上生物量分布状况大致相同,RMSE=59.2—65.5 Mg/hm~2,相关系数约为0.7;其降尺度结果优于GEOCARBON产品直接降尺度结果RMSE=75.3—79.9 Mg/hm~2;相较于线性模型,非线性模型能更好地呈现森林地上生物量和地表参数间的关系;总体上,降尺度生物量呈现高值区低估,低值区高估的现象。     

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     

Above-ground biomass estimation using airborne discrete-return and full-waveform LiDAR data in a coniferous forest

The estimation of forest aboveground biomass (AGB) is critical for quantifying carbon stocks and essential for evaluating global carbon cycle. Many previous studies have estimated forest AGB using airborne discrete-return Light Detection and Ranging (LiDAR) data, while fewer studies predicted forest AGB using airborne full-waveform LiDAR data. The objective of this work was to evaluate the utility of airborne discrete-return and full-waveform LiDAR data in estimating forest AGB. To fulfill the objective, airborne discrete-return LiDAR-derived metrics (DR-metrics), full-waveform LiDAR-derived metrics (FW-metrics) and structure parameters (combining height metrics and canopy cover) were used to estimate forest AGB. Additionally, the combined use of DR- and FW-metrics through a nonlinear way was also evaluated for AGB estimation in a coniferous forest in Dayekou, Gansu province of China. Results indicated that both height metrics derived from discrete-return and full-waveform LiDAR data were stronger predictors of forest AGB compared with other LiDAR-derived metrics. Canopy cover derived from discrete-return LiDAR data was not sensitive to forest AGB, while canopy cover estimated by full-waveform LiDAR data (CC_WF) showed moderate correlation with forest AGB. Structure parameters derived from full-waveform LiDAR data, such as H75_FW * CC_FW, were closely related to forest AGB. In contrast, structure parameters derived from discrete-return LiDAR data were not suitable for estimating forest AGB due to the less sensitivity of canopy cover CC_DR2 to forest AGB. This research also concluded that the synergistic use of DR- and FW-metrics can provide better AGB estimates in coniferous forest.     

Aggravated phosphorus limitation on biomass production under increasing nitrogen loading: a meta‐analysis

Nitrogen (N) and phosphorus (P), either individually or in combination, have been demonstrated to limit biomass production in terrestrial ecosystems. Field studies have been extensively synthesized to assess global patterns of N impacts on terrestrial ecosystem processes. However, to our knowledge, no synthesis has been done so far to reveal global patterns of P impacts on terrestrial ecosystems, especially under different nitrogen (N) levels. Here, we conducted a meta‐analysis of impacts of P addition, either alone or with N addition, on aboveground (AGB) and belowground biomass production (BGB), plant and soil P concentrations, and N : P ratio in terrestrial ecosystems. Overall, our meta‐analysis quantitatively confirmed existing notions: (i) colimitation of N and P on biomass production and (ii) more P limitation in tropical forest than other ecosystems. More importantly, our analysis revealed new findings: (i) P limitation on biomass production was aggravated by N enrichment and (ii) plant P concentration was a better indicator of P limitation than soil P availability. Specifically, P addition increased AGB and BGB by 34% and 13%, respectively. The effect size of P addition on biomass production was larger in tropical forest than grassland, wetland, and tundra and varied with P fertilizer forms, P addition rates, or experimental durations. The P‐induced increase in biomass production and plant P concentration was larger under elevated than ambient N. Our findings suggest that the global limitation of P on biomass production will become severer under increasing N fertilizer and deposition in the future.     

Above-ground biomass and vegetation attributes in the forest-savannah mosaic of Togo,West Africa

Despite the increasing interest in the role of African savannah and woodlands on the global carbon cycle, little is known about the above-ground biomass (AGB) and the factors affecting it in these ecosystems in West Africa. We estimated AGB in different vegetation types of a forest–savannah mosaic in Togo, and we investigated the relationship between AGB, structural and diversity attributes. We also assessed the effects of using the ≥5 or ≥10 cm diameter threshold on AGB estimates. We sampled tree diameter, height and species of all trees ≥5 cm diameter following standardised protocols in 160 plots of 50 × 20 m (50 × 10 m for riparian). Above-ground biomass (AGB) (all trees ≥5 cm diameter) ranged from 6.2 Mg/ha in shrub savannah to 292 Mg/ha in riparian forest and showed significant differences between vegetation types. Differences in AGB were related to structural attributes, with little influence of diversity attributes. The effects of minimum tree diameter size (5 or 10 cm) on AGB estimates were negligible. At a landscape level, closed-canopy and open forests stored important quantities of carbon. We highlight the importance of the forest–savannah mosaic as a large carbon pool, which could be released if converted to another land cover type.     

Aboveground biomass increments over 26 years (1993–2019) in an old-growth cool-temperate forest in northern Japan

Assessing long-term changes in the biomass of old-growth forests with consideration of climate effects is essential for understanding forest ecosystem functions under a changing climate. Long-term biomass changes are the result of accumulated short-term changes, which can be affected by endogenous processes such as gap filling in small-scale canopy openings. Here, we used 26 years (1993–2019) of repeated tree census data in an old-growth, cool-temperate, mixed deciduous forest that contains three topographic units (riparian, denuded slope, and terrace) in northern Japan to document decadal changes in aboveground biomass (AGB) and their processes in relation to endogenous processes and climatic factors. AGB increased steadily over the 26 years in all topographic units, but different tree species contributed to the increase among the topographic units. AGB gain within each topographic unit exceeded AGB loss via tree mortality in most of the measurement periods despite substantial temporal variation in AGB loss. At the local scale, variations in AGB gain were partially explained by compensating growth of trees around canopy gaps. Climate affected the local-scale AGB gain: the gain was larger in the measurement periods with higher mean air temperature during the current summer but smaller in those with higher mean air temperature during the previous autumn, synchronously in all topographic units. The influences of decadal summer and autumn warming on AGB growth appeared to be counteracting, suggesting that the observed steady AGB increase in KRRF is not fully explained by the warming. Future studies should consider global and regional environmental factors such as elevated CO₂ concentrations and nitrogen deposition, and include cool-temperate forests with a broader temperature range to improve our understanding on biomass accumulation in this type of forests under climate change.

     

Forest biomass stocks and dynamics across the subtropical Andes

Forest biomass plays an important role in the global carbon cycle. Therefore, understanding the factors that control forest biomass stocks and dynamics is a key challenge in the context of global change. We analyzed data from 60 forest plots in the subtropical Andes (22–27.5° S and 300–2300 m asl) to describe patterns and identify drivers of aboveground biomass (AGB) stocks and dynamics. We found that AGB stocks remained roughly constant with elevation due to compensating changes in basal area (which increased with elevation) and plot‐mean wood specific gravity (which decreased with elevation). AGB gain and loss rates both decreased with elevation and were explained mainly by temperature and rainfall (positive effects on both AGB gains and losses). AGB gain was also correlated with forest‐use history and weakly correlated with forest structure. Mean annual temperature and rainfall showed minor effects on AGB stocks and AGB change (gains minus losses) over recent decades. Although AGB change was only weakly correlated with climate variables, increases in AGB gains and losses with increasing rainfall—together with observed increases in rainfall in the subtropical Andes—suggest that these forests may become increasingly dynamic in the future. Abstract in Spanish is available with online material     

The global relationship between forest productivity and biomass

Aim  We aim to determine the empirical relationship between above-ground forest productivity and biomass. There are theoretical reasons to assume a relationship between forest structure and function, as both may be influenced by similar ecological factors such as moisture supply. Also, dynamic global vegetation model simulations imply that any increase in forest productivity driven by climate change will result in increases in biomass and therefore carbon storage. However, few studies have explored the strength and form of the relationship between forest productivity and biomass, whether in space or time.
Location Global scale.
Methods  We collated a large data set of above-ground biomass (AGB) and above-ground net primary productivity (ANPP) and tested the extent to which spatial variation in forest biomass across the Earth can be predicted from forest productivity.
Results  The global ANPP–AGB relationship differs fundamentally from the strongly positive, linear relationship reported in earlier analyses, which mostly lacked tropical sites. AGB begins to peak at c . 15–20 Mg ha⁻¹ year⁻¹ ANPP, plateaus at ANPP > 20–25 Mg ha⁻¹ year⁻¹, and may actually decline at higher levels of production.
Main conclusions  High turnover rates in high-productivity forests may limit AGB by promoting the dominance of species with a low wood density. Predicted increases in ANPP will not necessarily favour increases in forest carbon storage, especially if changes in productivity are accompanied by compositional shifts.     

Environmental and Biotic Controls over Aboveground Biomass Throughout a Tropical Rain Forest

The environmental and biotic factors affecting spatial variation in canopy three-dimensional (3-D) structure and aboveground tree biomass (AGB) are poorly understood in tropical rain forests. We combined field measurements and airborne light detection and ranging (lidar) to quantify 3-D structure and AGB across a 5,016 ha rain forest reserve on the northeastern flank of Mauna Kea volcano, Hawaii Island. We compared AGB among native stands dominated by Metrosideros polymorpha found along a 600–1800 m elevation/climate gradient, and on three substrate-age classes of 5, 20, and 65 kyr. We also analyzed how alien tree invasion, canopy species dominance and topographic relief influence AGB levels. Canopy vertical profiles derived from lidar measurements were strong predictors (r ² = 0.78) of AGB across sites and species. Mean AGB ranged from 48 to 363 Mg ha⁻¹ in native forest stands. Increasing elevation corresponded to a 53–84% decrease in AGB levels, depending upon substrate age. Holding climate constant, changes in substrate age from 5 to 65 kyr corresponded to a 23–53% decline in biomass. Invasion by Psidium cattleianum and Ficus rubiginosa trees resulted in a 19–38% decrease in AGB, with these carbon losses mediated by substrate age. In contrast, the spread of former plantation tree species Fraxinus uhdei corresponded to a 7- to 10-fold increase in biomass. The effects of topographic relief at both local and regional scales were evident in the AGB maps, with poorly drained terrain harboring 76% lower biomass than forests on well-drained relief. Our results quantify the absolute and relative importance of environmental factors controlling spatial variation in tree biomass across a rain forest landscape, and highlight the rapid changes in carbon storage incurred following biological invasion. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users. Author Contributions  GPA and RFH conceived of or designed the study. GPA, RFH, TAV, DEK, and TKB performed research and analyzed data. GPA, RFH, DEK, and TKB contributed new methods or models. GPA wrote the article.     

Large uncertainty in carbon uptake potential of land‐based climate‐change mitigation efforts

Most climate mitigation scenarios involve negative emissions, especially those that aim to limit global temperature increase to 2°C or less. However, the carbon uptake potential in land‐based climate change mitigation efforts is highly uncertain. Here, we address this uncertainty by using two land‐based mitigation scenarios from two land‐use models (IMAGE and MAgPIE) as input to four dynamic global vegetation models (DGVMs; LPJ‐GUESS, ORCHIDEE, JULES, LPJmL). Each of the four combinations of land‐use models and mitigation scenarios aimed for a cumulative carbon uptake of ~130 GtC by the end of the century, achieved either via the cultivation of bioenergy crops combined with carbon capture and storage (BECCS) or avoided deforestation and afforestation (ADAFF). Results suggest large uncertainty in simulated future land demand and carbon uptake rates, depending on the assumptions related to land use and land management in the models. Total cumulative carbon uptake in the DGVMs is highly variable across mitigation scenarios, ranging between 19 and 130 GtC by year 2099. Only one out of the 16 combinations of mitigation scenarios and DGVMs achieves an equivalent or higher carbon uptake than achieved in the land‐use models. The large differences in carbon uptake between the DGVMs and their discrepancy against the carbon uptake in IMAGE and MAgPIE are mainly due to different model assumptions regarding bioenergy crop yields and due to the simulation of soil carbon response to land‐use change. Differences between land‐use models and DGVMs regarding forest biomass and the rate of forest regrowth also have an impact, albeit smaller, on the results. Given the low confidence in simulated carbon uptake for a given land‐based mitigation scenario, and that negative emissions simulated by the DGVMs are typically lower than assumed in scenarios consistent with the 2°C target, relying on negative emissions to mitigate climate change is a highly uncertain strategy.     

Damage to living trees contributes to almost half of the biomass losses in tropical forests

Accurate estimates of forest biomass stocks and fluxes are needed to quantify global carbon budgets and assess the response of forests to climate change. However, most forest inventories consider tree mortality as the only aboveground biomass (AGB) loss without accounting for losses via damage to living trees: branchfall, trunk breakage, and wood decay. Here, we use ~151,000 annual records of tree survival and structural completeness to compare AGB loss via damage to living trees to total AGB loss (mortality + damage) in seven tropical forests widely distributed across environmental conditions. We find that 42% (3.62 Mg ha⁻¹ year⁻¹; 95% confidence interval [CI] 2.36–5.25) of total AGB loss (8.72 Mg ha⁻¹ year⁻¹; CI 5.57–12.86) is due to damage to living trees. Total AGB loss was highly variable among forests, but these differences were mainly caused by site variability in damage-related AGB losses rather than by mortality-related AGB losses. We show that conventional forest inventories overestimate stand-level AGB stocks by 4% (1%–17% range across forests) because assume structurally complete trees, underestimate total AGB loss by 29% (6%–57% range across forests) due to overlooked damage-related AGB losses, and overestimate AGB loss via mortality by 22% (7%–80% range across forests) because of the assumption that trees are undamaged before dying. Our results indicate that forest carbon fluxes are higher than previously thought. Damage on living trees is an underappreciated component of the forest carbon cycle that is likely to become even more important as the frequency and severity of forest disturbances increase.     

Effects of endogenous and exogenous processes on aboveground biomass stocks and dynamics in Andean forests

Tropical forests are paramount in regulating the global carbon cycle due to the storage of large amounts of carbon in their biomass. Using repeat censuses of permanent plots located at 15 sites in the Andes Mountains of northwest Colombia, we evaluate: (1) the relationship between aboveground biomass (AGB) stocks, AGB dynamics (mortality, productivity, and net change), and changes in temperature across a ca. 3000-m elevational gradient (≈?16.1 °C); (2) how AGB mortality and AGB productivity interact to determine net AGB change; and (3) the extent to which either fine-grain (0.04-ha) or coarse-grain (1-ha) processes determine the AGB dynamics of these forests. We did not find a significant relationship between elevation/temperature and biomass stocks. The net AGB sequestered each year by these forests (2.21?±?0.51 Mg ha^?1 year^?1), equivalent to approximately 1.09% of initial AGB, was primarily determined by tree growth. Both forest structural properties and global warming influenced AGB mortality and net change. AGB productivity increases with greater inequality of tree sizes, a pattern characteristic of forest patches recovering from disturbances. Overall, we find that global warming is triggering directional changes in species composition by thermophilization via increased tree mortality of species in the lower portions of their thermal ranges and that the inclusion of small-scale forest structural changes can effectively account for endogenous processes such as changes in forest structure. The inclusion of fine-grain processes in assessments of AGB dynamics could provide additional insights about the effects that ongoing climate change has on the functioning of tropical montane forests.     

Effects of soil C:N:P stoichiometry on biomass allocation in the alpine and arid steppe systems

Soil nutrients strongly influence biomass allocation. However, few studies have examined patterns induced by soil C:N:P stoichiometry in alpine and arid ecosystems. Samples were collected from 44 sites with similar elevation along the 220‐km transect at spatial intervals of 5 km along the northern Tibetan Plateau. Aboveground biomass (AGB) levels were measured by cutting a sward in each plot. Belowground biomass (BGB) levels were collected from soil pits in a block of 1 m × 1 m in actual root depth. We observed significant decreases in AGB and BGB levels but increases in the BGB:AGB ratio with increases in latitude. Although soil is characterized by structural complexity and spatial heterogeneity, we observed remarkably consistent C:N:P ratios within the cryic aridisols. We observed significant nonlinear relationships between the soil N:P and BGB:AGB ratios. The critical N:P ratio in soils was measured at approximately 2.0, above which the probability of BGB:AGB response to nutrient availability is small. These findings serve as interesting contributions to the global data pool on arid plant stoichiometry, given the previously limited knowledge regarding high‐altitude regions.