Global Forest Ecosystems Research Articles

The Responses of Forest Fine Root Biomass/Necromass Ratio to Environmental Factors Depend on Mycorrhizal Type and Latitudinal Region

AbstractFine root (≤2 mm in diameter) biomass/necromass (B/N) ratio, representing many dynamic key root parameters, can serve as a powerful measure of root vitality. Based on a global synthesis of fine root biomass and necromass in forest ecosystems, we describe a framework for recognizing responses of B/N ratio to biotic (e.g., mycorrhizal type) and abiotic (e.g., latitudinal region) characteristics. Arbuscular mycorrhiza (AM) and ectomycorrhiza (ECM) forests had similar average B/N ratios (3.28 versus 3.23). AM forest B/N ratio decreased with increasing altitude, stand density, tree age, and soil carbon/nitrogen ratio (C/N) but increased with soil pH. In contrast, ECM forest B/N ratio increased with increasing mean annual precipitation (MAP), altitude, and stand density but decreased with tree age. The average B/N ratio was higher in temperate forests (4.39) than in tropical (2.97) and boreal forests (2.40). The B/N ratio was relatively stable in temperate forests irrespective of changes in biotic and abiotic factors. In tropical forest, the B/N ratio was sensitive to mean annual temperature, altitude, soil C/N ratio, and pH, whereas in boreal forests, it was more sensitive to MAP, stand density, and tree age. The late‐successional forest B/N ratio was closely aligned with biotic and abiotic factors. Our analysis revealed that the relationships of B/N ratio with climate, topography, edaphic, and stand characteristics were dependent on mycorrhizal types and latitudinal regions. These findings provide a basis for large‐scale prediction of fine root dynamics and for better understanding of belowground processes of global forest ecosystems in a changing world.

Global patterns of dead fine root stocks in forest ecosystems

AbstractAimDead fine roots are crucial components of the carbon cycle in global forest ecosystems. Despite their importance, knowledge concerning geographical patterns of dead fine root pools (necromass) and factors influencing their dynamics remain scarce across the globe.LocationGlobal.MethodsWe analysed 136 published case studies covering 169 forest sites located throughout the world to identify broad patterns of necromass and biomass (living fine root pools) and to determine the responses to climate, edaphic gradients and stand properties.ResultsW‐shaped pattern of forest necromass with latitude, from the Southern Hemisphere via the equator to the Northern Hemisphere, was observed. Specifically, more necromass was found at both low (tropical forests) and high latitudes (boreal forests), whereas less necromass was found at mid latitudes (temperate forests), which is in line with patterns of carbon stocks in soils at the global scale. Broad‐leaf forests had greater necromass than needle‐leaf forests, and fine root necromass of the two forest types showed opposing trends in response to shifts in mean annual precipitation and different sensitivities to changes in mean annual temperature and edaphic properties (e.g. soil carbon/nitrogen ratio and pH). Necromass increased with soil organic layer thickness and stand age for both forest types.Main conclusionsThe hemispheric symmetrical necromass distribution is likely determined by changes in environmental conditions across latitudes. Different responses of dead fine roots in broad‐leaf and needle‐leaf forests may be caused by their distinct allocation and accumulation of carbon in relation to climate and to edaphic and forest characteristics at the global scale. Our results have important implications for accurate quantification and modelling of forest ecosystem carbon stocks and cycles and for assessments of their sensitivity and stability in a changing climate.

Pattern and control of biomass allocation across global forest ecosystems.

The underground part of a tree is an important carbon sink in forest ecosystems. Understanding biomass allocation between the below‐ and aboveground parts (root:shoot ratios) is necessary for estimation of the underground biomass and carbon pool. Nevertheless, large‐scale biomass allocation patterns and their control mechanisms are not well identified. In this study, a large database of global forests at the community level was compiled to investigate the root:shoot ratios and their responses to environmental factors. The results indicated that both the aboveground biomass (AGB) and belowground biomass (BGB) of the forests in China (medians 73.0 Mg/ha and 17.0 Mg/ha, respectively) were lower than those worldwide (medians 120.3 Mg/ha and 27.7 Mg/ha, respectively). The root:shoot ratios of the forests in China (median = 0.23), however, were not significantly different from other forests worldwide (median = 0.24). In general, the allocation of biomass between the belowground and aboveground parts was determined mainly by the inherent allometry of the plant but also by environmental factors. In this study, most correlations between root:shoot ratios and environmental factors (development parameter, climate, altitude, and soil) were weak but significant (p < .01). The allometric model agreed with the trends observed in this study and effectively estimated BGB based on AGB across the entire database.

What is the evidence for the contribution of forests to poverty alleviation? A systematic map protocol

BackgroundForests provide an essential resource that support the livelihoods of an estimated 20% of the global population. Forests are thought to serve in three primary roles to support livelihoods: subsistence, safety nets, and pathways to prosperity. While we have a working understanding of how poor people depend on forests in individual sites and countries, much of this evidence is dispersed and not easily accessible. Thus, while the importance of forest ecosystems and resources to contribute to poverty alleviation has been increasingly emphasized in international policies, conservation and development initiatives and investments—the strength of evidence to support how forests can affect poverty outcomes is still unclear. This study takes a systematic mapping approach to scope, identify and describe studies that measure the effect of forest-based activities on poverty outcomes at local and regional scales. This effort builds upon an existing systematic map on linkages between conservation and human well-being in order to make this process more efficient. We will conduct a refined and updated search strategy pertinent to forests-poverty linkages to glean additional evidence from studies outside the scope of the original map. Results of this study can be used for informing conservation and development policy and practices in global forest ecosystems and highlight evidence gaps where future primary studies and systematic reviews can add value.MethodsWe build upon the search strategy outlined in McKinnon et al. (Environ Evid 1–25, 2016) and expand our search to cover a total of 7 bibliographic databases, 15 organizational websites, 8 existing systematic reviews and maps, and evidence gap maps, and solicit key informants. All searches will be conducted in English and encompass all nations. Search results will be screened at title, abstract, and full text levels, recording both the number of excluded articles and reasons for exclusion. Full text assessment will be conducted on all included article and extracted data will be reported in a narrative review that will summarize trends in the evidence, report any knowledge gaps and gluts, and provide insight for policy, practice and future research. The data from this systematic map will be made available as well, through an open access, searchable data portal and visualization tool.

Soil nitrate accumulation explains the nonlinear responses of soil CO2 and CH4 fluxes to nitrogen addition in a temperate needle-broadleaved mixed forest

The responses of soil-atmosphere carbon (C) exchange fluxes to growing atmospheric nitrogen (N) deposition are controversial, leading to large uncertainty in the estimated C sink of global forest ecosystems experiencing substantial N inputs. However, it is challenging to quantify critical load of N input for the alteration of the soil C fluxes, and what factors controlled the changes in soil CO2 and CH4 fluxes under N enrichment. Nine levels of urea addition experiment (0, 10, 20, 40, 60, 80, 100, 120, 140kgNha−1yr−1) were conducted in the needle-broadleaved mixed forest in Changbai Mountain, Northeast China. Soil CO2 and CH4 fluxes were monitored weekly using the static chamber and gas chromatograph technique. Environmental variables (soil temperature and moisture in the 0–10cm depth) and dissolved N (NH4+-N, NO3−-N, total dissolved N (TDN), and dissolved organic N (DON)) in the organic layer and the 0–10cm mineral soil layer were simultaneously measured. High rates of N addition (≥60kgNha−1 yr−1) significantly increased soil NO3−-N contents in the organic layer and the mineral layer by 120%-180% and 56.4%-84.6%, respectively. However, N application did not lead to a significant accumulation of soil NH4+-N contents in the two soil layers except for a few treatments. N addition at a low rate of 10kgNha−1 yr−1 significantly stimulated, whereas high rate of N addition (140kgNha−1yr−1) significantly inhibited soil CO2 emission and CH4 uptake. Significant negative relationships were observed between changes in soil CO2 emission and CH4 uptake and changes in soil NO3−-N and moisture contents under N enrichment. These results suggest that soil nitrification and NO3−-N accumulation could be important regulators of soil CO2 emission and CH4 uptake in the temperate needle-broadleaved mixed forest. The nonlinear responses to exogenous N inputs and the critical level of N in terms of soil C fluxes should be considered in the ecological process models and ecosystem management.

Detection of water abundance in Baluran National Park with landsat satellite imagery analysis

Indonesia is one of the mega-biodiversity countries that have a great responsibility in maintaining the balance of the global climate and forest ecosystems. Drought causes shifting of ecosystems causing disturbances on animal life leading to death of species. Alongside fires in the savanna, drought is a recurrent problem in the park, which occurs every year. This study aims to detect the abundance of water by using satellite imagery in Baluran National Park (BNP). The research analyzed using Landsat satellite imagery ETM7 + in 1999 and 2010 and three (3) main factors that have great potential abundance of water, are: (1) plant density (GI = Greenness Index), (2) soil moisture (WI = Wetness Index), and (3) soil conditions (SBI = Soil Brightness Index). Three factors are summed and divided by three to get 5 levels of water abundance: 1) Very abundant, 2) Abundant, 3) Medium, 4) Few, and 5) Very little. The results showed that the abundance of water decreased between 1999 and 2010 for moderate conditions from 85% to 38%, if the abundance of low water (slightly) increased from 15% to 60%. The level of accuracy of the abundance of water in the field of more than 80% is exactly 91%. The extreme drought conditions will be very dangerous for the survival of flora and fauna in Baluran National Park that are in desperate need of water and potentially in danger of a fire. Construction of water reservoirs and water supply continuously using a water tank in the dry season is very necessary in the Baluran National Park.

Evaluating carbon fluxes of global forest ecosystems by using an individual tree-based model FORCCHN

The carbon budget of forest ecosystems, an important component of the terrestrial carbon cycle, needs to be accurately quantified and predicted by ecological models. As a preamble to apply the model to estimate global carbon uptake by forest ecosystems, we used the CO2 flux measurements from 37 forest eddy-covariance sites to examine the individual tree-based FORCCHN model's performance globally. In these initial tests, the FORCCHN model simulated gross primary production (GPP), ecosystem respiration (ER) and net ecosystem production (NEP) with correlations of 0.72, 0.70 and 0.53, respectively, across all forest biomes. The model underestimated GPP and slightly overestimated ER across most of the eddy-covariance sites. An underestimation of NEP arose primarily from the lower GPP estimates. Model performance was better in capturing both the temporal changes and magnitude of carbon fluxes in deciduous broadleaf forest than in evergreen broadleaf forest, and it performed less well for sites in Mediterranean climate. We then applied the model to estimate the carbon fluxes of forest ecosystems on global scale over 1982–2011. This application of FORCCHN gave a total GPP of 59.41±5.67 and an ER of 57.21±5.32PgCyr−1 for global forest ecosystems during 1982–2011. The forest ecosystems over this same period contributed a large carbon storage, with total NEP being 2.20±0.64PgCyr−1. These values are comparable to and reinforce estimates reported in other studies. This analysis highlights individual tree-based model FORCCHN could be used to evaluate carbon fluxes of forest ecosystems on global scale.

Enhanced accumulation and storage of mercury on subtropical evergreen forest floor: Implications on mercury budget in global forest ecosystems

AbstractForest ecosystems play an important role in the global cycling of mercury (Hg). In this study, we characterized the Hg cycling at a remote evergreen broadleaf (EB) forest site in southwest China (Mount Ailao). The annual Hg input via litterfall is estimated to be 75.0 ± 24.2 µg m−2 yr−1 at Mount Ailao. Such a quantity is up to 1 order of magnitude greater than those observed at remote temperate/boreal (T/B) forest sites. Production of litter biomass is found to be the most influential factor causing the high Hg input to the EB forest. Given their large areal coverage, Hg deposition through litterfall in EB forests is appropriately 9 ± 5 Mg yr−1 in China and 1086 ± 775 Mg yr−1 globally. The observed wet Hg deposition at Mount Ailao is 4.9 ± 4.5 µg m−2 yr−1, falling in the lower range of those observed at 49 T/B forest sites in North America and Europe. Given the data, the Hg deposition flux through litterfall is approximately 15 times higher than the wet Hg deposition at Mount Ailao. Steady Hg accumulation in decomposing litter biomass and Hg uptake from the environment were observed during 25 months of litter decomposition. The size of the Hg pool in the organic horizon of EB forest floors is estimated to be up to 2–10 times the typical pool size in T/B forests. This study highlights the importance of EB forest ecosystems in global Hg cycling, which requires further assessment when more data become available in tropical forests.

Assessment of Global Mercury Deposition through Litterfall

There is a large uncertainty in the estimate of global dry deposition of atmospheric mercury (Hg). Hg deposition through litterfall represents an important input to terrestrial forest ecosystems via cumulative uptake of atmospheric Hg (most Hg(0)) to foliage. In this study, we estimate the quantity of global Hg deposition through litterfall using statistical modeling (Monte Carlo simulation) of published data sets of litterfall biomass production, tree density, and Hg concentration in litter samples. On the basis of the model results, the global annual Hg deposition through litterfall is estimated to be 1180 ± 710 Mg yr(-1), more than two times greater than the estimate by GEOS-Chem. Spatial distribution of Hg deposition through litterfall suggests that deposition flux decreases spatially from tropical to temperate and boreal regions. Approximately 70% of global Hg(0) dry deposition occurs in the tropical and subtropical regions. A major source of uncertainty in this study is the heterogeneous geospatial distribution of available data. More observational data in regions (Southeast Asia, Africa, and South America) where few data sets exist will greatly improve the accuracy of the current estimate. Given that the quantity of global Hg deposition via litterfall is typically 2-6 times higher than Hg(0) evasion from forest floor, global forest ecosystems represent a strong Hg(0) sink.

Mapping Global Forest Aboveground Biomass with Spaceborne LiDAR, Optical Imagery, and Forest Inventory Data

As a large carbon pool, global forest ecosystems are a critical component of the global carbon cycle. Accurate estimations of global forest aboveground biomass (AGB) can improve the understanding of global carbon dynamics and help to quantify anthropogenic carbon emissions. Light detection and ranging (LiDAR) techniques have been proven that can accurately capture both horizontal and vertical forest structures and increase the accuracy of forest AGB estimation. In this study, we mapped the global forest AGB density at a 1-km resolution through the integration of ground inventory data, optical imagery, Geoscience Laser Altimeter System/Ice, Cloud, and Land Elevation Satellite data, climate surfaces, and topographic data. Over 4000 ground inventory records were collected from published literatures to train the forest AGB estimation model and validate the resulting global forest AGB product. Our wall-to-wall global forest AGB map showed that the global forest AGB density was 210.09 Mg/ha on average, with a standard deviation of 109.31 Mg/ha. At the continental level, Africa (333.34 ± 63.80 Mg/ha) and South America (301.68 ± 67.43 Mg/ha) had higher AGB density. The AGB density in Asia, North America and Europe were 172.28 ± 94.75, 166.48 ± 84.97, and 132.97 ± 50.70 Mg/ha, respectively. The wall-to-wall forest AGB map was evaluated at plot level using independent plot measurements. The adjusted coefficient of determination (R2) and root-mean-square error (RMSE) between our predicted results and the validation plots were 0.56 and 87.53 Mg/ha, respectively. At the ecological zone level, the R2 and RMSE between our map and Intergovernmental Panel on Climate Change suggested values were 0.56 and 101.21 Mg/ha, respectively. Moreover, a comprehensive comparison was also conducted between our forest AGB map and other published regional AGB products. Overall, our forest AGB map showed good agreements with these regional AGB products, but some of the regional AGB products tended to underestimate forest AGB density.

Optimization and evaluation of key photosynthesis parameters in forest ecosystems based on FLUXNET data and VPM model.

Gross primary productivity (GPP) plays an important role in global carbon cycle. Vegetation maximum light use efficiency (Δmax) is the key parameter for GPP simulation of terrestrial ecosystem. Based on the vegetation photosynthesis model (VPM) and the eddy covariance flux data at 40 stations from FLUXNET (179 site-years of data), we identified the key model parameters influencing the simulation of GPP with VPM through one-at-a-time (OAT) method. The cross validation method was employed to optimize the key model parameters and evaluate the model perfor-mance for global forest ecosystems. The results showed that the prediction of GPP was mostly affec-ted by Δmax, maximum temperature for photosynthesis (Tmax), and optimum temperature for photosynthesis (Topt). There were distinguishable differences for the key optimized parameters among different forest ecosystems. The optimized Δmax ranged from 0.05 to 0.08 μmol CO2·μmol-1 PAR (evergreen broad-leaved forest>evergreen coniferous forest>mixed forest>deciduous broad-leaved forest). The optimized Tmax ranged from 38 to 48 ℃,while Topt ranged from 18 to 22 ℃. With the optimized key parameters based on ecosystem types, the VPM was able to simulate the seasonal and inter-annual variations of GPP in four forest ecosystems.

Global patterns and predictors of stem CO2 efflux in forest ecosystems.

Stem CO2 efflux (ES) plays an important role in the carbon balance of forest ecosystems. However, its primary controls at the global scale are poorly understood and observation-based global estimates are lacking. We synthesized data from 121 published studies across global forest ecosystems and examined the relationships between annual ES and biotic and abiotic factors at individual, biome, and global scales, and developed a global gridded estimate of annual ES . We tested the following hypotheses: (1) Leaf area index (LAI) will be highly correlated with annual ES at biome and global scales; (2) there will be parallel patterns in stem and root CO2 effluxes (RA) in all forests; (3) annual ES will decline with forest age; and (4) LAI coupled with mean annual temperature (MAT) and mean annual precipitation (MAP) will be sufficient to predict annual ES across forests in different regions. Positive linear relationships were found between ES and LAI, as well as gross primary production (GPP), net primary production (NPP), wood NPP, soil CO2 efflux (RS), and RA . Annual ES was correlated with RA in temperate forests after controlling for GPP and MAT, suggesting other additional factors contributed to the relationship. Annual ES tended to decrease with stand age. Leaf area index, MAT and MAP, predicted 74% of variation in ES at global scales. Our statistical model estimated a global annual ES of 6.7 ± 1.1 Pg C yr(-1) over the period of 2000-2012 with little interannual variability. Modeled mean annual ES was 71 ± 43, 270 ± 103, and 420 ± 134 g C m(2) yr(-1) for boreal, temperate, and tropical forests, respectively. We recommend that future studies report ES at a standardized constant temperature, incorporate more manipulative treatments, such as fertilization and drought, and whenever possible, simultaneously measure both aboveground and belowground CO2 fluxes.

Spatial distribution of forest aboveground biomass in China: Estimation through combination of spaceborne lidar, optical imagery, and forest inventory data

The global forest ecosystem, which acts as a large carbon sink, plays an important role in modeling the global carbon balance. An accurate estimation of the total forest carbon stock in the aboveground biomass (AGB) is therefore necessary for improving our understanding of carbon dynamics, especially against the background of global climate change. The forest area of China is among the top five globally. However, because of limitations in forest AGB mapping methods and the availability of ground inventory data, there is still a lack in the nationwide wall-to-wall forest AGB estimation map for China. In this study, we collected over 8000 ground inventory records from published literatures, and developed an AGB mapping method using a combination of these ground inventory data, Geoscience Laser Altimeter System (GLAS)/Ice, Cloud, and Land Elevation Satellite (ICESat) data, optical imagery, climate surfaces, and topographic data. An uncertainty field model was introduced into the forest AGB mapping procedure to minimize the influence of plot location uncertainty. Our nationwide wall-to-wall forest AGB mapping results show that the forest AGB density in China is 120 Mg/ha on average, with a standard deviation of 61 Mg/ha. Evaluation with an independent ground inventory dataset showed that our proposed method can accurately map wall-to-wall forest AGB across a large landscape. The adjusted coefficient of determination ( R 2 ) and root-mean-square error between our predicted results and the validation dataset were 0.75 and 42.39 Mg/ha, respectively. This new method and the resulting nationwide wall-to-wall forest AGB map will help to improve the accuracy of carbon dynamic predictions in China. • Developed an AGB mapping method through the combination of multi-source data sets • Introduced a model to minimize the influence of plot locality uncertainty • Collected over 8000 ground inventory data across China from the literature • Mapped the wall-to-wall forest AGB of China ( R 2 = 0.75, RMSE = 42.39 Mg/ha)

Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests

AbstractSoil carbon dynamics of terrestrial ecosystems play a significant role in the global carbon cycle. Microbial‐based decomposition models have seen much growth recently for quantifying this role, yet dormancy as a common strategy used by microorganisms has not usually been represented and tested in these models against field observations. Here we developed an explicit microbial‐enzyme decomposition model and examined model performance with and without representation of microbial dormancy at six temperate forest sites of different forest types. We then extrapolated the model to global temperate forest ecosystems to investigate biogeochemical controls on soil heterotrophic respiration and microbial dormancy dynamics at different temporal‐spatial scales. The dormancy model consistently produced better match with field‐observed heterotrophic soil CO2 efflux (RH) than the no dormancy model. Our regional modeling results further indicated that models with dormancy were able to produce more realistic magnitude of microbial biomass (&lt;2% of soil organic carbon) and soil RH (7.5 ± 2.4 Pg C yr−1). Spatial correlation analysis showed that soil organic carbon content was the dominating factor (correlation coefficient = 0.4–0.6) in the simulated spatial pattern of soil RH with both models. In contrast to strong temporal and local controls of soil temperature and moisture on microbial dormancy, our modeling results showed that soil carbon‐to‐nitrogen ratio (C:N) was a major regulating factor at regional scales (correlation coefficient = −0.43 to −0.58), indicating scale‐dependent biogeochemical controls on microbial dynamics. Our findings suggest that incorporating microbial dormancy could improve the realism of microbial‐based decomposition models and enhance the integration of soil experiments and mechanistically based modeling.

Gross primary production of global forest ecosystems has been overestimated.

Coverage rate, a critical variable for gridded forest area, has been neglected by previous studies in estimating the annual gross primary production (GPP) of global forest ecosystems. In this study, we investigated to what extent the coverage rate could impact forest GPP estimates from 1982 to 2011. Here we show that the traditional calculation without considering the coverage rate globally overestimated the forest gross carbon dioxide uptake by approximately 8.7%, with a value of 5.12 ± 0.23 Pg C yr−1, which is equivalent to 48% of the annual emissions from anthropogenic activities in 2012. Actually, the global annual GPP of forest ecosystems is approximately 53.71 ± 4.83 Pg C yr−1 for the past 30 years by taking the coverage rate into account. Accordingly, we argue that forest annual GPP calculated by previous studies has been overestimated due to the exaggerated forest area, and therefore, coverage rate may be a required factor to further quantify the global carbon cycle.

New insights into mechanisms driving carbon allocation in tropical forests.

The proportion of carbon allocated to wood production is an important determinant of the carbon sink strength of global forest ecosystems. Understanding the mechanisms controlling wood production and its responses to environmental drivers is essential for parameterization of global vegetation models and to accurately predict future responses of tropical forests in terms of carbon sequestration. Here, we synthesize data from 105 pantropical old-growth rainforests to investigate environmental controls on the partitioning of net primary production to wood production (%WP) using structural equation modeling. Our results reveal that %WP is governed by two independent pathways of direct and indirect environmental controls. While temperature and soil phosphorus availability indirectly affected %WP via increasing productivity, precipitation and dry season length both directly increased %WP via tradeoffs along the plant economics spectrum. We provide new insights into the mechanisms driving %WP, allowing us to conclude that projected climate change could enhance %WP in less productive tropical forests, thus increasing carbon sequestration in montane forests, but adversely affecting lowland forests.

Challenges in developing a computationally efficient plant physiological height-class-structured forest model

Ongoing and future climate change may be of sufficient magnitude to significantly impact global forest ecosystems. In order to anticipate the potential range of changes to forests in the future and to better understand the development and state of forest ecosystems at present, a variety of forest ecosystem models of varying complexity have been developed over the past 40 years. While most of these models focus on representing either forest demographics including age and height structure, or forest biogeochemistry including plant physiology and ecosystem carbon cycling, it is increasingly seen as crucial that forest ecosystem models include equally good representations of both. However, only few models currently include detailed representations of both biogeochemistry and demographics, and those mostly have high computational demands. Here, we present TreeM-LPJ, a first step towards a new, computationally efficient forest dynamics model. We combine the height-class scheme of the forest landscape model TreeMig with the biogeochemistry of the dynamic global vegetation model LPJ-GUESS. The resulting model is able to simulate forest growth by considering vertical spatial variability without stochastic functions, considerably reducing computational demand. Discretization errors are kept small by using a numerical algorithm that extrapolates growth success in height, and thereby dynamically updates the state variables of the trees in the different height classes. We demonstrate TreeM-LPJ in an application on a transect in the central Swiss Alps where we show results from the new model compare favorably with the more complex LPJ-GUESS. TreeM-LPJ provides a combination of biological detail and computational efficiency that can serve as a useful basis for large-scale vegetation modeling.

Allometric constraints on, and trade-offs in, belowground carbon allocation and their control of soil respiration across global forest ecosystems.

To fully understand how soil respiration is partitioned among its component fluxes and responds to climate, it is essential to relate it to belowground carbon allocation, the ultimate carbon source for soil respiration. This remains one of the largest gaps in knowledge of terrestrial carbon cycling. Here, we synthesize data on gross and net primary production and their components, and soil respiration and its components, from a global forest database, to determine mechanisms governing belowground carbon allocation and their relationship with soil respiration partitioning and soil respiration responses to climatic factors across global forest ecosystems. Our results revealed that there are three independent mechanisms controlling belowground carbon allocation and which influence soil respiration and its partitioning: an allometric constraint; a fine-root production vs. root respiration trade-off; and an above- vs. belowground trade-off in plant carbon. Global patterns in soil respiration and its partitioning are constrained primarily by the allometric allocation, which explains some of the previously ambiguous results reported in the literature. Responses of soil respiration and its components to mean annual temperature, precipitation, and nitrogen deposition can be mediated by changes in belowground carbon allocation. Soil respiration responds to mean annual temperature overwhelmingly through an increasing belowground carbon input as a result of extending total day length of growing season, but not by temperature-driven acceleration of soil carbon decomposition, which argues against the possibility of a strong positive feedback between global warming and soil carbon loss. Different nitrogen loads can trigger distinct belowground carbon allocation mechanisms, which are responsible for different responses of soil respiration to nitrogen addition that have been observed. These results provide new insights into belowground carbon allocation, partitioning of soil respiration, and its responses to climate in forest ecosystems and are, therefore, valuable for terrestrial carbon simulations and projections.

Regional patterns of (15)N natural abundance in forest ecosystems along a large transect in eastern China.

The regional determining factors underlying inter- and intra-site variation of 15N natural abundance in foliage, O horizon and mineral soil were investigated in eastern China.15N natural abundance values for these forest ecosystems were in the middle of the range of values previously found for global forest ecosystems. In contrast to commonly reported global patterns, temperate forest ecosystems were significantly more15N-enriched than tropical forest ecosystems, and foliage δ15N was negatively correlated with increasing mean annual temperature and net soil N mineralisation in eastern China. Tight N cycling in forest ecosystems and the use of atmospheric N deposition by trees might underlie the δ15N distribution patterns in eastern China. The existence of mycorrhizal fungi and root distribution profiles in the soil may also influence the15N natural abundance patterns in forest ecosystems of eastern China.

Forest soil autotrophic and heterotrophic respiration under different mycorrhizal strategies and their responses to temperature and precipitation

Mycorrhizal symbiosis between plant roots and mycorrhizal fungi are almost ubiquitous. These interactions contribute a largely to soil autotrophic respiration (RA), influence soil heterotrophic respiration (RH) and respond strongly to such climatic changes as temperature and precipitation. The aim of the present study was to explore how variation of temperature and precipitation influence RA and RH in global forest ecosystems that are classified by the mycorrhizal type of the dominant plants. The results show slight variation for RA and significant change for RH among different mycorrhizal strategy types. In forests with predominating arbuscular mycorrhiza (AM) the RA and RH are trifling higher than in non-AM type forests. The responses of RA and RH to temperature and precipitation were highly variable among different mycorrhizal strategies. For example, the changes of RA and RH are more dependent on precipitation than temperature in AM-forest, and temperature accounted more for their variations in forests of the other three mycorrhizal types. As far as we know, this study was the first to evaluate the influence of different mycorrhizal strategies on forest RA and RH and their response to temperature and precipitation.