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.     

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.     

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.     

Looking for age-related growth decline in natural forests: unexpected biomass patterns from tree rings and simulated mortality

Forest biomass growth is almost universally assumed to peak early in stand development, near canopy closure, after which it will plateau or decline. The chronosequence and plot remeasurement approaches used to establish the decline pattern suffer from limitations and coarse temporal detail. We combined annual tree ring measurements and mortality models to address two questions: first, how do assumptions about tree growth and mortality influence reconstructions of biomass growth? Second, under what circumstances does biomass production follow the model that peaks early, then declines? We integrated three stochastic mortality models with a census tree-ring data set from eight temperate forest types to reconstruct stand-level biomass increments (in Minnesota, USA). We compared growth patterns among mortality models, forest types and stands. Timing of peak biomass growth varied significantly among mortality models, peaking 20–30 years earlier when mortality was random with respect to tree growth and size, than when mortality favored slow-growing individuals. Random or u-shaped mortality (highest in small or large trees) produced peak growth 25–30 % higher than the surviving tree sample alone. Growth trends for even-aged, monospecific Pinus banksiana or Acer saccharum forests were similar to the early peak and decline expectation. However, we observed continually increasing biomass growth in older, low-productivity forests of Quercus rubra, Fraxinus nigra, and Thuja occidentalis. Tree-ring reconstructions estimated annual changes in live biomass growth and identified more diverse development patterns than previous methods. These detailed, long-term patterns of biomass development are crucial for detecting recent growth responses to global change and modeling future forest dynamics.     

Demographic Drivers of Aboveground Biomass Dynamics During Secondary Succession in Neotropical Dry and Wet Forests

The magnitude of the carbon sink in second-growth forests is expected to vary with successional biomass dynamics resulting from tree growth, recruitment, and mortality, and with the effects of climate on these dynamics. We compare aboveground biomass dynamics of dry and wet Neotropical forests, based on monitoring data gathered over 3–16 years in forests covering the first 25 years of succession. We estimated standing biomass, annual biomass change, and contributions of tree growth, recruitment, and mortality. We also evaluated tree species’ contributions to biomass dynamics. Absolute rates of biomass change were lower in dry forests, 2.3 and 1.9 Mg ha^?1 y^?1, after 5–15 and 15–25 years after abandonment, respectively, than in wet forests, with 4.7 and 6.1 Mg ha^?1 y^?1, in the same age classes. Biomass change was largely driven by tree growth, accounting for at least 48% of biomass change across forest types and age classes. Mortality also contributed strongly to biomass change in wet forests of 5–15 years, whereas its contribution became important later in succession in dry forests. Biomass dynamics tended to be dominated by fewer species in early-successional dry than wet forests, but dominance was strong in both forest types. Overall, our results indicate that biomass dynamics during succession are faster in Neotropical wet than dry forests, with high tree mortality earlier in succession in the wet forests. Long-term monitoring of second-growth tropical forest plots is crucial for improving estimates of annual biomass change, and for enhancing understanding of the underlying mechanisms and demographic drivers.     

Nationally Representative Plot Network Reveals Contrasting Drivers of Net Biomass Change in Secondary and Old-Growth Forests

Uncertainty about the mechanisms driving biomass change at broad spatial scales limits our ability to predict the response of forest biomass storage to global change. Here we use a spatially representative network of 874 forest plots in New Zealand to examine whether commonly hypothesised drivers of forest biomass and biomass change (diversity, disturbance, nutrients and climate) differ between old-growth and secondary forests at a national scale. We calculate biomass stocks and net biomass change for live above-ground biomass, below-ground biomass, deadwood and litter pools. We combine these data with plot-level information on forest type, tree diversity, plant functional traits, climate and disturbance history, and use structural equation models to identify the major drivers of biomass change. Over the period 2002–2014, secondary forest biomass increased by 2.78 (1.68–3.89) Mg ha^?1 y^?1, whereas no significant change was detected in old-growth forests (+0.28; ?0.72 to 1.29 Mg ha^?1 y^?1). The drivers of biomass and biomass change differed between secondary and old-growth forests. Plot-level biomass change of old-growth forest was driven by recent disturbance (large tree mortality within the last decade), whereas biomass change of secondary forest was determined by current biomass and past anthropogenic disturbance. Climate indirectly affected biomass change through its relationship with past anthropogenic disturbance. Our results highlight the importance of disturbance and disturbance history in determining broad-scale patterns of forest biomass change and suggest that explicitly modelling processes driving biomass change within secondary and old-growth forests is essential for predicting future changes in global forest biomass.     

Predicting tree biomass growth in the temperate–boreal ecotone: Is tree size,age, competition,or climate response most important?

As global temperatures rise, variation in annual climate is also changing, with unknown consequences for forest biomes. Growing forests have the ability to capture atmospheric CO₂ and thereby slow rising CO₂ concentrations. Forests’ ongoing ability to sequester C depends on how tree communities respond to changes in climate variation. Much of what we know about tree and forest response to climate variation comes from tree‐ring records. Yet typical tree‐ring datasets and models do not capture the diversity of climate responses that exist within and among trees and species. We address this issue using a model that estimates individual tree response to climate variables while accounting for variation in individuals’ size, age, competitive status, and spatially structured latent covariates. Our model allows for inference about variance within and among species. We quantify how variables influence aboveground biomass growth of individual trees from a representative sample of 15 northern or southern tree species growing in a transition zone between boreal and temperate biomes. Individual trees varied in their growth response to fluctuating mean annual temperature and summer moisture stress. The variation among individuals within a species was wider than mean differences among species. The effects of mean temperature and summer moisture stress interacted, such that warm years produced positive responses to summer moisture availability and cool years produced negative responses. As climate models project significant increases in annual temperatures, growth of species like Acer saccharum, Quercus rubra, and Picea glauca will vary more in response to summer moisture stress than in the past. The magnitude of biomass growth variation in response to annual climate was 92–95% smaller than responses to tree size and age. This means that measuring or predicting the physical structure of current and future forests could tell us more about future C dynamics than growth responses related to climate change alone.     

温度和降水对森林生物量分配的影响研究进展

森林生物量分配策略是全球变化背景下群落保持生产力的重要机制.温度和降水会影响森林生物量的分配格局.文章基于文献分析,总结了增温、低温和降水对森林地上、地下生物量分配的影响机制,以及温度和降水对森林生物量分配的交互作用,并对未来温度和降水影响森林生物量分配的研究进行了展望,提出该领域今后的研究重点为:(1)加强生物量分配...     

Long‐term forest resilience to climate change indicated by mortality,regeneration, and growth in semiarid southern Siberia

Several studies have documented that regional climate warming and the resulting increase in drought stress have triggered increased tree mortality in semiarid forests with unavoidable impacts on regional and global carbon sequestration. Although climate warming is projected to continue into the future, studies examining long‐term resilience of semiarid forests against climate change are limited. In this study, long‐term forest resilience was defined as the capacity of forest recruitment to compensate for losses from mortality. We observed an obvious change in long‐term forest resilience along a local aridity gradient by reconstructing tree growth trend and disturbance history and investigating postdisturbance regeneration in semiarid forests in southern Siberia. In our study, with increased severity of local aridity, forests became vulnerable to drought stress, and regeneration first accelerated and then ceased. Radial growth of trees during 1900–2012 was also relatively stable on the moderately arid site. Furthermore, we found that smaller forest patches always have relatively weaker resilience under the same climatic conditions. Our results imply a relatively higher resilience in arid timberline forest patches than in continuous forests; however, further climate warming and increased drought could possibly cause the disappearance of small forest patches around the arid tree line. This study sheds light on climate change adaptation and provides insight into managing vulnerable semiarid forests.     

Simulating forest ecosystem response to climate warming incorporating spatial effects in north-eastern China

Aim Predictions of ecosystem responses to climate warming are often made using gap models, which are among the most effective tools for assessing the effects of climate change on forest composition and structure. Gap models do not generally account for broad‐scale effects such as the spatial configuration of the simulated forest ecosystems, disturbance, and seed dispersal, which extend beyond the simulation plots and are important under changing climates. In this study we incorporate the broad‐scale spatial effects (spatial configurations of the simulated forest ecosystems, seed dispersal and fire disturbance) in simulating forest responses to climate warming. We chose the Changbai Natural Reserve in China as our study area. Our aim is to reveal the spatial effects in simulating forest responses to climate warming and make new predictions by incorporating these effects in the Changbai Natural Reserve. Location Changbai Natural Reserve, north‐eastern China. Method We used a coupled modelling approach that links a gap model with a spatially explicit landscape model. In our approach, the responses (establishment) of individual species to climate warming are simulated using a gap model (linkages ) that has been utilized previously for making predictions in this region; and the spatial effects are simulated using a landscape model (LANDIS) that incorporates spatial configurations of the simulated forest ecosystems, seed dispersal and fire disturbance. We used the recent predictions of the Canadian Global Coupled Model (CGCM2) for the Changbai Mountain area (4.6 °C average annual temperature increase and little precipitation change). For the area encompassed by the simulation, we examined four major ecosystems distributed continuously from low to high elevations along the northern slope: hardwood forest, mixed Korean pine hardwood forest, spruce‐fir forest, and sub‐alpine forest. Results The dominant effects of climate warming were evident on forest ecosystems in the low and high elevation areas, but not in the mid‐elevation areas. This suggests that the forest ecosystems near the southern and northern ranges of their distributions will have the strongest response to climate warming. In the mid‐elevation areas, environmental controls exerted the dominant influence on the dynamics of these forests (e.g. spruce‐fir) and their resilience to climate warming was suggested by the fact that the fluctuations of species trajectories for these forests under the warming scenario paralleled those under the current climate scenario. Main conclusions With the spatial effects incorporated, the disappearance of tree species in this region due to the climate warming would not be expected within the 300‐year period covered by the simulation. Neither Korean pine nor spruce‐fir was completely replaced by broadleaf species during the simulation period. Even for the sub‐alpine forest, mountain birch did not become extinct under the climate warming scenario, although its occurrence was greatly reduced. However, the decreasing trends characterizing Korean pine, spruce, and fir indicate that in simulations beyond 300 years these species could eventually be replaced by broadleaf tree species. A complete forest transition would take much longer than the time periods predicted by the gap models.     

A climate change‐induced threat to the ecological resilience of a subtropical monsoon evergreen broad‐leaved forest in Southern China

Recent studies have suggested that tropical forests may not be resilient against climate change in the long term, primarily owing to predicted reductions in rainfall and forest productivity, increased tree mortality, and declining forest biomass carbon sinks. These changes will be caused by drought‐induced water stress and ecosystem disturbances. Several recent studies have reported that climate change has increased tree mortality in temperate and boreal forests, or both mortality and recruitment rates in tropical forests. However, no study has yet examined these changes in the subtropical forests that account for the majority of China's forested land. In this study, we describe how the monsoon evergreen broad‐leaved forest has responded to global warming and drought stress using 32 years of data from forest observation plots. Due to an imbalance in mortality and recruitment, and changes in diameter growth rates between larger and smaller trees and among different functional groups, the average DBH of trees and forest biomass have decreased. Sap flow measurements also showed that larger trees were more stressed than smaller trees by the warming and drying environment. As a result, the monsoon evergreen broad‐leaved forest community is undergoing a transition from a forest dominated by a cohort of fewer and larger individuals to a forest dominated by a cohort of more and smaller individuals, with a different species composition, suggesting that subtropical forests are threatened by their lack of resilience against long‐term climate change.     

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     

Linking canopy leaf area and light environments with tree size distributions to explain Amazon forest demography

Forest biophysical structure – the arrangement and frequency of leaves and stems – emerges from growth, mortality and space filling dynamics, and may also influence those dynamics by structuring light environments. To investigate this interaction, we developed models that could use LiDAR remote sensing to link leaf area profiles with tree size distributions, comparing models which did not (metabolic scaling theory) and did allow light to influence this link. We found that a light environment‐to‐structure link was necessary to accurately simulate tree size distributions and canopy structure in two contrasting Amazon forests. Partitioning leaf area profiles into size‐class components, we found that demographic rates were related to variation in light absorption, with mortality increasing relative to growth in higher light, consistent with a light environment feedback to size distributions. Combining LiDAR with models linking forest structure and demography offers a high‐throughput approach to advance theory and investigate climate‐relevant tropical forest change.     

A mechanistic approach for modeling temperature-dependent consumer-resource dynamics

Paramount to our ability to manage and protect biological communities from impending changes in the environment is an understanding of how communities will respond. General mathematical models of community dynamics are often too simplistic to accurately describe this response, partly to retain mathematical tractability and partly for the lack of biologically pleasing functions representing the model/environment interface. We address these problems of tractability and plausibility in community/environment models by incorporating the Boltzmann factor (temperature dependence) in a bioenergetic consumer-resource framework. Our analysis leads to three predictions for the response of consumer-resource systems to increasing mean temperature (warming). First, mathematical extinctions do not occur with warming; however, stable systems may transition into an unstable (cycling) state. Second, there is a decrease in the biomass density of resources with warming. The biomass density of consumers may increase or decrease depending on their proximity to the feasibility (extinction) boundary. Third, consumer biomass density is more sensitive to warming than resource biomass density (with some exceptions). These predictions are in line with many current observations and experiments. The model presented and analyzed here provides an advancement in the testing framework for global change scenarios and hypotheses of latitudinal and elevational species distributions.     

Above-ground forest biomass is not consistently related to wood density in tropical forests

Aim  It is increasingly accepted that the mean wood density of trees within a forest is tightly coupled to above-ground forest biomass. It is unknown, however, if a positive relationship between forest biomass and mean community wood density is a general phenomenon across forests. Understanding spatial variation in biomass as a function of wood density both within and among forests is important for predicting changes in stored carbon in response to global change, and here we evaluated the generality of a positive biomass–wood density relationship within and among six tropical forests.
Location  Costa Rica, Panama, Puerto Rico and Ecuador.
Methods  Individual stem data, including diameter at breast height and spatial position, for six forest dynamics plots were merged with an extensive wood density database. Individual stem biomass values were calculated from these data using published statistical models. Total above ground biomass, total basal area and mean community wood density were also quantified across a range of subcommunity plot sizes within each forest.
Results  Among forests, biomass did not vary with mean community wood density. The relationship between subcommunity biomass and mean wood density within a forest varied from negative to null to positive depending on the size of subcommunities and forest identity. The direction of correlation was determined by the associated total basal area–mean wood density correlation, the slope of which increased strongly with whole forest mean wood density.
Main conclusions  There is no general relationship between forest biomass and wood density, and in some forests, stored carbon is highest where wood density is lowest. Our results suggest that declining wood density, due to global change, will result in decreased or increased stored carbon in forests with high or low mean wood density, respectively.     

Climate-growth relations of congeneric tree species vary across a tropical vegetation gradient in Brazil

Seasonally dry tropical forests are an important global climatic regulator, a main driver of the global carbon sink dynamics and are predicted to suffer future reductions in their productivity due to climate change. Yet, little is known about how interannual climate variability affects tree growth and how climate-growth responses vary across rainfall gradients in these forests. Here we evaluate changes in climate sensitivity of tree growth along an environmental gradient of seasonally dry tropical vegetation types (evergreen forest – savannah – dry forest) in Northeastern Brazil, using congeneric species of two common neotropical genera: Aspidosperma and Handroanthus. We built tree-ring width chronologies for each species × forest type combinations and explored how growth variability correlated with local (precipitation, temperature) and global (the El Niño Southern Oscillation - ENSO) climatic factors. We also assessed how growth sensitivity to climate and the presence of growth deviations varied along the gradient. Precipitation stimulates tree growth and was the main growth-influencing factor across vegetation types. Trees in the dry forest site showed highest growth sensitivity to interannual variation in precipitation. Temperature and ENSO phenomena correlated negatively with growth and sensitivity to both climatic factors were similar across sites. Negative growth deviations were present and found mostly in the dry-forest species. Our results reveal a dominant effect of precipitation on tree growth in seasonally dry tropical forests and suggest that along the gradient, dry forests are the most sensitivity to drought. These forests may therefore be the most vulnerable to the deleterious effects of future climatic changes. These results highlight the importance of understanding the climatic sensitivity of different tropical forests. This understanding is key to predict the carbon dynamics in tropical regions, and sensitivity differences should be considered when prioritizing conservation measures of seasonally dry topical forests.     

Forest Pattern, Fire, and Climatic Change in the Sierra Nevada

In the Sierra Nevada, distributions of forest tree species are largely controlled by the soil-moisture balance. Changes in temperature or precipitation as a result of increased greenhouse gas concentrations could lead to changes in species distributions. In addition, climatic change could increase the frequency and severity of wildfires. We used a forest gap model developed for Sierra Nevada forests to investigate the potential sensitivity of these forests to climatic change, including a changing fire regime. Fuel moisture influences the fire regime and couples fire to climate. Fires are also affected by fuel loads, which accumulate according to forest structure and composition. These model features were used to investigate the complex interactions between climate, fire, and forest dynamics. Eight hypothetical climate-change scenarios were simulated, including two general circulation model (GCM) predictions of a 2 × CO₂ world. The response of forest structure,species composition, and the fire regime to these changes in the climate were examined at four sites across an elevation gradient. Impacts on woody biomass and species composition as a result of climatic change were site specific and depended on the environmental constraints of a site and the environmental tolerances of the tree species simulated. Climatic change altered the fire regime both directly and indirectly. Fire frequency responded directly to climate's influence on fuel moisture, whereas fire extent was affected by changes that occurred in either woody biomass or species composition. The influence of species composition on fuel-bed bulk density was particularly important. Future fires in the Sierra Nevada could be both more frequent and of greater spatial extent if GCM predictions prove true. Received 5 May 1998; accepted 4 November 1998.     

Variation in above‐ground forest biomass across broad climatic gradients

Aim An understanding of the relationship between forest biomass and climate is needed to predict the impacts of climate change on carbon stores. Biomass patterns have been characterized at geographically or climatically restricted scales, making it unclear if biomass is limited by climate in any general way at continental to global scales. Using a dataset spanning multiple climatic regions we evaluate the generality of published biomass–climate correlations. We also combine metabolic theory and hydraulic limits to plant growth to first derive and then test predictions for how forest biomass should vary with maximum individual tree biomass and the ecosystem water deficit. Location Temperate forests and dry, moist and wet tropical forests across North, Central and South America. Methods A forest biomass model was derived from allometric functions and power‐law size distributions. Biomass and climate were correlated using extensive forest plot (276 0.1‐ha plots), wood density and climate datasets. Climate variables included mean annual temperature, annual precipitation, their ratio, precipitation of the driest quarter, potential and actual evapotranspiration, and the ecosystem water deficit. The water deficit uniquely summarizes water balance by integrating water inputs from precipitation with water losses due to solar energy. Results Climate generally explained little variation in forest biomass, and mixed support was found for published biomass–climate relationships. Our theory indicated that maximum individual biomass governs forest biomass and is constrained by water deficit. Indeed, forest biomass was tightly coupled to maximum individual biomass and the upper bound of maximum individual biomass declined steeply with water deficit. Water deficit similarly constrained the upper bound of forest biomass, with most forests below the constraint. Main conclusions The results suggest that: (1) biomass–climate models developed at restricted geographic/climatic scales may not hold at broader scales; (2) maximum individual biomass is strongly related to forest biomass, suggesting that process‐based models should focus on maximum individual biomass; (3) the ecosystem water deficit constrains biomass, but realized biomass often falls below the constraint; such that (4) biomass is not strongly limited by climate in most forests so that forest biomass may not predictably respond to changes in mean climate.     

林木根呼吸及测定方法进展

 森林土壤呼吸的近2/3是由林木根呼吸产生的,林木根呼吸对估计森林C吸存及构建森林生态系统碳动态模型有重要意义,是全球碳循环研究的一个重要组成部分。林木根呼吸包括生长呼吸和维持呼吸,不同森林生态系统林木根呼吸对土壤呼吸的贡献大多在40%～60%范围内,林木根呼吸在生长季节较高而休眠季节较低。测定林木根呼吸的主要方法有排除根法、离体根法、同位素法和原位PVC管气室法,前两者相对简单、成本低,常用于森林生态系统中;同位素法可原位测定根呼吸,对土壤干扰较小,但不易操作,且成本高。根呼吸受土壤温度、根直径大小、根组织N浓度、环境CO2浓度、土壤湿度、养分有效性等因素的影响。今后的研究应集中在以下方面：1）探讨和比较不同条件下测定根呼吸组成（生长呼吸、维持呼吸）的最合适方法;2）加大在野外条件下使用有效方法分离根呼吸和根际微生物呼吸的力度;3）对森林生态系统根呼吸动态进行长期的定位研究;4）进一步加强研究不同气候带,不同森林类型林木根呼吸,并将研究尺度从气室扩大到区域或全球水平;5）加强林木根呼吸对全球变化的响应及机制的研究;6)对林木根呼吸进行多学科合作研究将为全球C循环做出新的贡献。     

Net aboveground biomass declines of four major forest types with forest ageing and climate change in western Canada's boreal forests

Biomass change of the world's forests is critical to the global carbon cycle. Despite storing nearly half of global forest carbon, the boreal biome of diverse forest types and ages is a poorly understood component of the carbon cycle. Using data from 871 permanent plots in the western boreal forest of Canada, we examined net annual aboveground biomass change (ΔAGB) of four major forest types between 1958 and 2011. We found that ΔAGB was higher for deciduous broadleaf (DEC) (1.44 Mg ha^?1 year^?1, 95% Bayesian confidence interval (CI), 1.22–1.68) and early‐successional coniferous forests (ESC) (1.42, CI, 1.30–1.56) than mixed forests (MIX) (0.80, CI, 0.50–1.11) and late‐successional coniferous (LSC) forests (0.62, CI, 0.39–0.88). ΔAGB declined with forest age as well as calendar year. After accounting for the effects of forest age, ΔAGB declined by 0.035, 0.021, 0.032 and 0.069 Mg ha^?1 year^?1 per calendar year in DEC, ESC, MIX and LSC forests, respectively. The ΔAGB declines resulted from increased tree mortality and reduced growth in all forest types except DEC, in which a large biomass loss from mortality was accompanied with a small increase in growth. With every degree of annual temperature increase, ΔAGB decreased by 1.00, 0.20, 0.55 and 1.07 Mg ha^?1 year^?1 in DEC, ESC, MIX and LSC forests, respectively. With every cm decrease of annual climatic moisture availability, ΔAGB decreased 0.030, 0.045 and 0.17 Mg ha^?1 year^?1 in ESC, MIX and LSC forests, but changed little in DEC forests. Our results suggest that persistent warming and decreasing water availability have profound negative effects on forest biomass in the boreal forests of western Canada. Furthermore, our results indicate that forest responses to climate change are strongly dependent on forest composition with late‐successional coniferous forests being most vulnerable to climate changes in terms of aboveground biomass.