Research Contents and Methodology

The forest age can be defined as the time since the last stand-replacement event. Within the local context, it determines the forest successional stage, a fundamental variable for diagnosing the net carbon fluxes in terrestrial ecosystems. To accurately quantify the carbon sink-source strength in these ecosystems and inform adaptation-mitigation strategies, it is essential to be able to infer forest age at high resolution.This study presents an updated version of the MPI-BGC forest age product, featuring global distributions of forest age for 2010, 2017, 2018, and 2020 at 100m spatial resolution. We employed two machine learning approaches, XGBoost and a multi-layer perceptron model, to create data-driven estimates of forest age based on over 40,000 forest inventory plots, biomass, remote-sensing, and climate data. One key innovation of our approach is the incorporation of Landsat-based disturbance history metrics as input variables. Our updated estimates show better precision in identifying old-growth forests and reduce overestimation biases in young forests and underestimation biases in old forests, but not completely. Additionally, we found substantial regional variations related to changes in covariate strength and improvement in the model. Also, we discussed the uncertainty layers, created using model ensembles, that materialize the quantification of methodological uncertainty in the forest age estimates.An analysis of the global distribution of forest age reveals significant variations across the years studied. We also quantified the changes in forest age in regions with high deforestation or forest degradation rates, where younger stands are becoming more prevalent. We discuss the challenges and limitations of using regression-based mapping approaches, including the choice of machine learning algorithm, spatial cross-validation techniques, and the caveats of extrapolation, given data limitations. Our research highlights the complementary biomass-based approaches for determining forest age and underscores the importance of detailed global estimates at high spatial resolutions. Overall, this study advances our understanding of forest age, a key variable for understanding the carbon cycle in terrestrial ecosystems.

Abstract. Soil respiration (Rs) is an important carbon flux in terrestrial ecosystems, and knowledge about this CO2 release process and the drivers involved is a key topic in the context of global change. However, temporal and spatial variability has not been studied extensively in semi-arid systems such as olive groves. In this study, we show a full year of continuous measurements of Rs with six automatic chambers in a fertigated olive grove with bare soil in the Mediterranean accompanied by modeled ecosystem respiration (Reco) estimated by decomposing net ecosystem exchange (NEE) measured using the eddy covariance (EC) technique. To study spatial variability, the automatic chambers were distributed equally under the canopy (Rs Under-Tree) and in the center of the alley (Rs Alley), and the gradient of Rs between both locations was measured in several manual campaigns in addition to angular changes about the olive trees. The results indicate that Rs Under-Tree was 3 times higher than Rs Alley in the annual computations. Higher Rs was found on the southern face, and an exponential decay of Rs was observed until the alley's center was reached. These spatial changes were used to weigh and project Rs onto the ecosystem scale, whose annual balance was 1.6–2.3 times higher than the Reco estimated using EC-derived models. Rs Under-Tree represented 39 % of the Rs of the olive grove. We found values of Q10<1 in the vicinity of the olive tree in the warm period. Outbursts of CO2 emissions associated with precipitation events were detected, especially in the alley, during dry periods and after extended periods without rain, but they were not accurately detected by EC-derived respiration models. We point out an interaction between several effects that vary in time, that are different under the canopy than in the alleys, and that the accepted models for estimating Q10 and Reco do not consider. These results show high spatial and temporal heterogeneity in soil respiration and the factors involved, which must be considered in future works in semi-arid agroecosystems.

Temperature sensitivity (Q10) of ecosystem respiration (ER) is a crucial parameter for predicting the fate of CO2 in terrestrial e cosystems under global warming. Most studies focus their attention in the variation of Q10 in one or two components of ER, but not in the integration or comparison among Q10 in major components of ER. Vertical and seasonal variations in individual components, including leaf respiration, stem respiration and soil respiration, of ER were observed synchronously along the gradient of leaf–stem–soil over a 2 year period in three forest stands dominated by masson pine, loblolly pine and oak, respectively, in a subtropical forest ecosystem of central China. We found that Q10 in individual components of ER increased along the vertical gradient of leaf–stem–soil. The vertical pattern of Q10 in individual components of ER was ascribed to variations of diurnal temperature range (DTR) and activation energy (ΔHa). These results suggest that a vertical pattern of Q10 in individual components of ER along the gradient of leaf–stem–soil should be taken into consideration in process-based models that simulate respiratory carbon flux in terrestrial ecosystems.

Including leaf trait information helps empirical estimation of jmax from vcmax in cool-temperate deciduous forests

Abstract. A simulation model based on satellite observations of monthly vegetation greenness from the Moderate Resolution Imaging Spectroradiometer (MODIS) was used to estimate monthly carbon fluxes in terrestrial ecosystems of Brazilian Amazon and Cerrado regions over the period 2000–2002. The NASA-CASA (Carnegie Ames Stanford Approach) model estimates of annual forest production were used for the first time as the basis to generate a prediction for the standing pool of carbon in above-ground biomass (AGB; g C m−2) for forested areas of the Brazilian Amazon region. Plot-level measurements of the residence time of carbon in wood in Amazon forest from Malhi et al. (2006) were interpolated by inverse distance weighting algorithms and used with CASA to generate a new regional map of AGB. Data from the Brazilian PRODES (Estimativa do Desflorestamento da Amazônia) project were used to map deforested areas. Results show that net primary production (NPP) sinks for carbon varied between 4.25 Pg C yr−1 (1 Pg=1015 g) and 4.34 Pg C for the region and were highest across the eastern and northern Amazon areas, whereas deforestation sources of CO2 flux from decomposition of residual woody debris were higher and less seasonal in the central Amazon than in the eastern and southern areas. Increased woody debris from past deforestation events was predicted to alter the net ecosystem carbon balance of the Amazon region to generate annual CO2 source fluxes at least two times higher than previously predicted by CASA modeling studies. Variations in climate, land cover, and forest burning were predicted to release carbon at rates of 0.5 to 1 Pg C yr−1 from the Brazilian Amazon. When direct deforestation emissions of CO2 from forest burning of between 0.2 and 0.6 Pg C yr−1 in the Legal Amazon are overlooked in regional budgets, the year-to-year variations in this net biome flux may appear to be large, whereas our model results implies net biome fluxes had actually been relatively consistent from year to year during the period 2000–2002. This is the first study to use MODIS data to model all carbon pools (wood, leaf, root) dynamically in simulations of Amazon forest deforestation from clearing and burning of all kinds.

Spatio-temporal drivers of soil and ecosystem carbon fluxes at field scale in an upland grassland in Germany

It is well known that agricultural and forest ecosystems serve as vital carbon sinks in terrestrial ecosystems. Understanding the fundamental processes and mechanisms of ecosystem carbon cycles in face of climate change is critical for quantifying the carbon sinks of terrestrial ecosystems. Ecosystem carbon cycles cannot be separated from water and nitrogen cycles and thus the response and adaptation of carbon-water-nitrogen processes in agricultural and forest ecosystems to climate change demand further studies. This research topic published 10 papers to gain novel insights into the underlying mechanisms and processes of carbon-water-nitrogen interactions in agricultural and forest ecosystems in response to climate change.Litter decomposition is a pivotal biogeochemical process, which profoundly influences carbon and nitrogen cycling in forest and grassland ecosystems. Climatic factors can significantly impact litter decomposition rates, carbon sequestration, and the emissions of greenhouse gases such as CO2 and N2O. Liu et al. conducted a comprehensive meta-analysis of 351 samples from 37 published studies to explore the interactive effects of solar radiation and precipitation on litter decomposition and CO2 emission on a global scale. They found that the solar radiation significantly increased litter decomposition which was dependent on precipitation regimes. Meanwhile, Li et al. investigated the effects of warming and reclamation on N2O emission flux through a long-term manipulative warming experiment on the Qinghai-Tibetan Plateau. Their results demonstrated that reclamation amplified the warming effects on N2O emissions by enhancing soil nitrification and related enzymatic activities in alpine meadows. Additionally, Lin et al. examined the long-term spatiotemporal variations in aboveground carbon sequestration rates in the eastern Tibetan Plateau using a forest landscape model under different climate change scenarios. Their study highlighted the variability in aboveground carbon sequestration rates across various forest types in response to climate warming.The escalating frequency and duration of drought events under climate change have prompted heightened scrutiny of their impacts on temporal and spatial variations in evapotranspiration and water use efficiency. Yang et al. analyzed the inter-annual variations of evapotranspiration with eddy covariance fluxes in an urban forest in Beijing, China, revealing that spring and mid-summer droughts primarily drove inter-annual variations in evapotranspiration due to the reduced stomatal conductance. Furthermore, Xu et al. employed the ensemble empirical mode decomposition method to investigate spatial variations and mechanisms influencing the stability of water use efficiency in China. Their findings explored the role of precipitation and soil moisture in promoting stable water use efficiency, with unstable trends primarily driven by positive or negative reversals. In addition, Jiang et al. presented an in-depth analysis of the impact of seasonal drought on root distribution and water utilization patterns of forests in south China. Their findings highlighted the critical role of deep fine roots in utilizing deep soil water during the dry season, constituting a substantial portion of total water consumption.Leaf photosynthesis, reliant on both photochemical and carboxylation processes, is central to terrestrial carbon fluxes. Accurate estimation of photochemical parameters and maximum carboxylation rates is essential for predicting carbon fluxes of terrestrial ecosystems. The article by Liu et al. found that the inferred values of the photochemical redox parameters varied with leaf macronutrient contents. The work of Li et al. evaluated the relationships between the leaf maximum rate of carboxylation and both leaf Narea and photosynthetic pigments of winter wheat in a farmland ecosystem in China. One of the study’s notable findings was the strongest correlation between leaf Vcmax and leaf Chlarea. Their findings suggest that photosynthetic pigment content serves as a predictor for estimating Vcmax, offering a novel approach for spatially continuous Vcmax estimation and enhancing simulation accuracy in ecological models.In addition to the above articles from field studies, two papers elucidated the mitigated effects of elevated CO2 concentrations on environmental stressors such as drought and nutrient deficiency. Based on manipulative experiment with environmental growth chambers, Chang et al. examined the effects of elevated CO2 concentration and temperature on plant growth and leaf gas exchange of winter wheat along a soil water gradient, and found that elevated CO2 concentration substantially enhanced leaf photosynthesis by about 30% under water deficiency, suggesting the negative impacts of water deficiency on winter wheat might be partially mitigated by elevated CO2 concentration. Li et al. reported findings that the plant growth and leaf photosynthesis of annual ryegrass under phosphorus deficiency were enhanced by elevated CO2 concentration, indicating the impacts of phosphorus deficiency on annual ryegrass may be alleviated by elevated CO2 concentration under climate change.This research topic presents the latest studies on how climate change affects the carbon-water-nitrogen processes of agricultural and forest ecosystems. Meanwhile, this research topic highlights the importance and uncertainty of ecosystem functioning in response to climate change. Therefore, fully exploring the potential mechanisms and processes of agriculture and forests to climate change is pivotal to projecting the potential risk of climate change on global grain yield and forest carbon sequestrations.

In recent years, the evaluation of carbon sources and carbon sinks has become one of the major research topics. The temporal and spatial distribution of carbon flux and some factors that affect carbon flux were analyzed in this paper based on the Net Ecosystem Exchange (NEE) data, which were provided by Greenhouse Gases Observing Satellite (GOSAT) project and FLUXNET project. Then, we found that carbon flux had obvious seasonal variation. It was carbon sink in summer and carbon source in winter. The total amount of carbon flux in July or August was about -1.377 ~ -1.882 gcm-2day-1, and 0.64 gcm-2day-1 in November. The fluctuation of carbon flux in coastal area was stronger than that in inland. Forest areas had stronger carbon storage capacity than that in other vegetation areas, and the flux in forest areas had the largest change. The vegetation coverage was larger, and the carbon storage capacity was stronger.

Diffuse radiation can promote the vegetation photosynthesis. Radiation use efficiency (RUE = GPP/PAR) simulated by Terrestrial Ecosystem Carbon Flux GPP Model (TEC), Vegetation Photosynthesis Model (VPM), Eddy Covariance Light Use Efficiency Model (EC‐LUE), and Diffuse Fraction‐Based Two‐Leaf Terrestrial Ecosystem Carbon Flux Model (DTEC) models were against the measured radiation‐use efficiency (RUE) from FLUXNET under different bins of diffuse photosynthetically active radiation fraction (FDIFFPAR) in this study. Our results showed that the observed RUE increased linearly with FDIFFPAR. The differences of RUE between the first bin and other bin (RUEbin) from two big‐leaf models were underestimated when the FDIFFPAR is higher than 0.5 except in evergreen broadleaf forests and RUEbin from the DTEC model was overestimated when the FDIFFPAR is higher than 0.7. The role of temperature and vapor pressure deficit in the diffuse radiation effects on vegetation photosynthesis was underestimated in EC‐LUE, TEC, VPM. Although many studies applied LUE models to assess the effects of diffuse radiation on vegetation photosynthesis, our results suggested that these models were needed to be improved.

PDF HTML阅读 XML下载 导出引用 引用提醒 不同林龄白桦天然次生林土壤碳通量和有机碳储量 DOI: 10.5846/stxb201403110418 作者: 作者单位: 森林植物生态学教育部重点实验室,森林植物生态学教育部重点实验室,森林植物生态学教育部重点实验室,森林植物生态学教育部重点实验室,森林植物生态学教育部重点实验室 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目(31270494, 31070350); 国家"973"重点基础研究项目发展计划项目(2010CB951301). Soil organic carbon stocks and fluxes in different age stands of secondary Betula platyphylla in Xiaoxing'an Mountain,China Author: Affiliation: Key Laboratory of Forest Plant Ecology, Ministry of Education,,,Key Laboratory of Forest Plant Ecology, Ministry of Education,Key Laboratory of Forest Plant Ecology, Ministry of Education Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:白桦天然次生林是中国东北地区地带性顶极植被类型--阔叶红松林遭到严重干扰破坏后恢复形成的主要天然次生林类型,测定了生长季内不同林龄白桦天然次生林(20、36、82a)的土壤呼吸速率及土壤碳含量。结果表明:土壤呼吸速率的季节变化呈单峰曲线,主要受土壤温度的驱动,土壤10cm处温度可以解释不同林龄白桦林之间土壤呼吸速率86%-92%的变异,土壤呼吸与土壤含水量关系不显著(P>0.05)。随着林龄的增加,生长季内土壤表面CO2通量呈增加的趋势,依次分别为740(20a)、768(36a)和809(82a)gC m- 2 a-1。土壤呼吸的温度敏感性指数Q10亦随林龄的增加呈上升的趋势,依次分别为2.64、2.91和3.35。平均土壤有机碳含量(0-50cm土壤层)和碳密度均随林龄的增加而增加,随土壤深度的增加而减少;其中,随着林龄的增加土壤有机碳含量依次分别为 43.75、47.72和55.96 g/kg,有机碳密度为14.7、18.1和18.7 kg/m2。不同林龄间土壤表面CO2年通量与土壤有机碳密度之间存在显著的正相关关系(P<0.01),但其相关程度因土层而异,其中与0-10cm土层的有机碳密度相关最为密切(R2=0.908)。 Abstract:Soil respiration, known as the second largest componentof carbon dioxide flux between terrestrial ecosystems and the atmosphere, is sensitive to climate, vegetation type as well as forest age. In order to simulate the long-term forest carbon dynamics and its impact on climate system, we need to understand the successional status of carbon dynamics more than learn the responses of forest ecosystems to the changing climate. However, in spite of its significant role in determining the distribution of carbon pools and fluxes in different forest ecosystems, the effect of age on forest carbon fluxes great is uncertain. Soil temperature and soil water content are recognized as the main factors controlling the temporal variation of soil respiration. In this paper, soil carbon dynamic was measured in different age stands of Secondary Betula platyphylla (20a, 36a, 82a) in Xiaoxing'an Mountain, China. Soil respiration measurements were conducted using a LI-6400-09 soil CO2 flux system from May to October in 2008. Besides, We measured soil organic carbon content (g/kg) and bulk density (g/cm3) at four layers across the chronosequence in August 2009. Our specific objectives were to: (1) compare the cumulative soil respiration during the growing season for the different age stands of Secondary Betula platyphylla, (2) quantify soil organic carbon (SOC) contents and SOC density and (3) establish quantitative relationships between soil carbon fluxes and SOC density for the three forest ecosystems. Our results showed that the seasonality of soil respiration was driven mainly by soil temperature with the peak appeared in August, and was roughly consistent with that of soil temperature. Soil temperature at 10 cm could explain 86% -92% of the variation of soil respiration for the 3 different age stands of Secondary Betula platyphylla. And the soil volumetric water content was not significantly correlated with soil respiration rate and it was not a key factor to soil respiration. We fitted site-based models and used continuous measurements of soil temperature to estimate cumulative soil respiration for the growing season of 2008 (days 132-295). Cumulative soil respiration in the growing season was estimated to be 740、768 and 809 C m- 2 a-1 in the 20a, 36a and 82a Betula platyphylla, respectively. Both, cumulative soil respiration and Q10 increased during stand establishment. Q10 was estimated to be 2.64, 2.91and 3.35 in the 20a, 36a and 82a Betula platyphylla, respectively. Both, total soil organic carbon (SOC) contents and SOC density at 0-50 cm increased during stand establishment, but decreased with soil depth. SOC was estimated to be 43.75, 47.72 and 55.96 g/kg for the three forest ecosystems. Meanwhile, the figures were 14.7, 18.1 and 18.7 kg/m2 for SOC density in the 20a, 36a and 82a Betula platyphylla, respectively. Soil surface carbon flux was positively correlated to SOC content (P<0.01), and the significance level of the correlation depended on soil depth, and the soil carbon flux was more positively correlated to SOC concentration at the depth of 0-10 cm(R2=0.908) . 参考文献 相似文献 引证文献

Ecosystem coupling: A unifying framework to understand the functioning and recovery of ecosystems

Litter decomposition is a fundamental biogeochemical process for carbon flux and nutrient cycling in terrestrial ecosystems, yet the global variation in decomposition rates and their covariations with climate and substrate are not fully understood. Here, we synthesized a global dataset of 6,733 independent observations across six continents to illustrate the climatic and substrate controls over litter decomposition. The average decomposition rates of various litter types ranged from 0.74 to 4.01 y-1 across polar to tropics, showing a large geographical span. Litter substrate and climate directly explained 36 and 30% of the variations in decomposition rates, with the carbon-to-nitrogen ratio identified as the best predictor. In the absence of climate variables, litter substrate can effectively explain the variation, while the model's predictive capacity decreased significantly after litter substrate was excluded. Our synthesis highlights that a fundamental constraint on litter substrate leads to predictable global-scale patterns of terrestrial litter decomposition rates. Integrating litter chemistry parameters should be prioritized for parameter optimization in Earth system models.

Understanding aerosol–climate–ecosystem interactions and the implications for terrestrial carbon sink using the Community Earth System Model

&amp;lt;p&amp;gt;Monitoring CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; emissions originating from urban areas has become a necessity to support sustainable urban planning strategies and climate change mitigation efforts. Integrative decision support, where net effects of various emission/sink components are considered and compared, is now an increasingly relevant part of urban planning processes. The current emission inventories rely on indirect approaches that use fuel and electricity consumption statistics for determining CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; emissions. The consistency of such approaches is questionable and they usually neglect the contribution of the biogenic components of the urban carbon cycle (i.e. vegetation, soil). Moreover, their spatial and temporal scales are restricted because consumption statistics are often available in coarse spatial scales (national, provincial/state, municipal) and usually scaled down using proxy data (e.g. population density) to city-scale annual estimates. The diFUME project (https://mcr.unibas.ch/difume/) is developing a methodology for mapping and monitoring the actual urban CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; flux at optimum spatial and temporal scales, meaningful for urban design decisions. The goal is to develop, apply and evaluate independent models, capable to estimate all the different components of the urban carbon cycle (i.e. building emissions, traffic emissions, human metabolism, photosynthetic uptake, plant respiration, soil respiration), combining mainly Eddy Covariance (EC) with Earth Observation (EO) data. EC provides continuous in-situ measurements of CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; flux at the local scale. Processing, analysis and interpretation of urban EC measurements is challenging due to the inherent spatial complexity of CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; source and sink configurations of the urban structure. The diFUME methodology is using multiple EO datasets to achieve multi-scale monitoring of urban cover, morphology and vegetation phenology in order to characterize the urban source/sink configurations and parameterize turbulent flux source area models. Such combination of EC and EO provides enhanced interpretation of the measured CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; flux, analysis of its controlling factors and therefore the potential of fine scale mapping and monitoring. The diFUME methodology is being developed and applied in the city of Basel, exploiting the available long-term database (&amp;gt; 15 years) of urban EC measurements. The first results highlight the potential of EO-derived geospatial data to interpret the complexity of urban EC measurements. Seasonal and land cover related trends in the EC-measured CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; flux are recognized, while the use of environmental, census and mobility datasets are increasing the interpretation capabilities and the modelling potential of the urban CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; flux patterns.&amp;lt;/p&amp;gt;

Terrestrial ecosystems in the southern United States (SUS) have experienced a complex set of changes in climate, atmospheric CO2 concentration, tropospheric ozone (O3), nitrogen (N) deposition, and land-use and land-cover change (LULCC) during the past century. Although each of these factors has received attention for its alterations on ecosystem carbon (C) dynamics, their combined effects and relative contributions are still not well understood. By using the Dynamic Land Ecosystem Model (DLEM) in combination with spatially explicit, long-term historical data series on multiple environmental factors, we examined the century-scale responses of ecosystem C storage and flux to multiple environmental changes in the SUS. The results indicated that multiple environmental changes shifted SUS ecosystems from a C source of 1.20 ± 0.56 Pg (1 Pg = 1015 g) during the period 1895 to 1950, to a C sink of 2.00 ± 0.94 Pg during the period 1951 to 2007. Over the entire period spanning 1895–2007, SUS ecosystems were a net C sink of 0.80 ± 0.38 Pg. The C sink was primarily due to an increase in the vegetation C pool, whereas the soil C pool decreased during the study period. The spatiotemporal changes of C storage were caused by changes in multiple environmental factors. Among the five factors examined (climate, LULCC, N deposition, atmospheric CO2, and tropospheric O3), elevated atmospheric CO2 concentration was the largest contributor to C sequestration, followed by N deposition. LULCC, climate, and tropospheric O3 concentration contributed to C losses during the study period. The SUS ecosystem C sink was largely the result of interactive effects among multiple environmental factors, particularly atmospheric N input and atmospheric CO2.