Fluxes In Terrestrial Ecosystems Research Articles

Autumnal warming does not change root phenology in two contrasting vegetation types of subarctic tundra

Root phenology is important in controlling carbon and nutrient fluxes in terrestrial ecosystems, yet, remains largely unexplored, especially in the Arctic. We compared below- and aboveground phenology and ending of the growing season in two contrasting vegetation types of subarctic tundra: heath and meadow, and their response to experimental warming in autumn. Root phenology was measured in-situ with minirhizotrons and compared with aboveground phenology assessed with repeat digital photography. The end of the growing season, both below- and aboveground, was similar in meadow and heath and the belowground growing season ended later than aboveground in the two vegetation types. Root growth was higher and less equally distributed over time in meadow compared to heath. The warming treatment increased air and soil temperature by 0.5 °C and slightly increased aboveground greenness, but did not affect root growth or prolong the below- and aboveground growing season in either of the vegetation types. These results imply that vegetation types differ in root dynamics and suggest that other factors than temperature control autumnal root growth in these ecosystems. Further investigations of root phenology will help to identify those drivers, in which including responses of functionally contrasting vegetation types will help to estimate how climate change affects belowground processes and their roles in ecosystem function.

Резервуари і потоки карбону у наземних екосистемах України

Резервуари і потоки карбону у наземних екосистемах України

基于人工神经网络与空间仿真模拟的区域森林碳估算比较——以龙泉市为例

PDF HTML阅读 XML下载 导出引用 引用提醒 基于人工神经网络与空间仿真模拟的区域森林碳估算比较——以龙泉市为例 DOI: 10.5846/stxb201603010352 作者: 作者单位: 浙江农林大学,浙江农林大学 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（30972360，41201563）；浙江农林大学农林碳汇与生态环境修复研究中心预研基金；浙江省林业碳汇与计量创新团队项目（2012R10030-01）；浙江省林学一级重中之重学科学生创新计划项目资助（201515） Comparison of regional forest carbon estimation methods based on back- propagation neural network and spatial simulation: A case study in Longquan County Author: Affiliation: Zhejiang A & F University,Zhejiang A & F University 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:森林是生态系统的重要组成部分，准确估算森林碳储量及其分布对于评价森林生态系统的功能具有重要意义。以龙泉市为研究区，利用2009年99个森林资源清查样地数据和同年度 Landsat TM 影像数据，采用高斯序列协同仿真（SGCS）与BP神经网络方法（BPNN）分别模拟森林地上部分碳密度及其分布，并进行了对比分析。随机将样本数据分成70个建模样本和29个检验样本。通过模型检验，BP神经网络预测值与实测值的相关性达到0.67，相对均方根误差为0.63，空间仿真方法预测值与实测值的相关性为0.68，相对均方根误差为0.63，空间仿真方法预测能力略高于神经网络方法。仿真结果表明，基于BP神经网络模拟的森林碳总量为11042990 Mg，平均碳密度为36.10 Mg/hm2，总体森林碳密度均值高于样地平均值8.82%。基于空间仿真模拟的森林碳总量为11388657 Mg，平均碳密度为37.23 Mg/hm2，总体森林碳密度均值高于样地平均值9.40%。对比分析可知：高斯协同仿真模拟和BP神经网络虽然在碳总量估算值上与抽样数据估计值相近，但两种方法在估测值的频率分布以及研究区碳分布上有较大的差异。与BP神经网络相比，序列高斯协同模拟结果更接近系统抽样样地实测值，全部样地预测值与实测值的相关性达到0.75，在估计区域森林碳空间分布上有明显优势。在碳密度值域与频率分布方面，序列高斯协同模拟结果分布更合理。综上所述，序列高斯协同模拟在森林碳空间估计方面要优于BP神经网络。 Abstract:Quantifying the carbon stocks of forest is critical for understanding the dynamics of carbon fluxes in terrestrial ecosystems and the atmosphere as well as monitoring ecosystem responses to environmental changes. However, due to the lack of methods and data, results of forest carbon estimation from different studies shown large difference, which presents a great uncertainty in the evaluation of forest carbon sink. Different methods can be used to estimate the carbon storage in the same study area, which can be compared with the advantages and disadvantages of each method and provides guidance for forest carbon estimation. On the basis of National Forest Inventory (NFI) data and the Land-sat TM image data collected in Longquan County, Zhejiang Province in 2009, we applied two methods, namely error back-propagation neural network (BPNN) and sequential Gaussian co-simulation (SGCS) to reproduce the distribution of above-ground forest carbon. We randomly divided plots into two sets, a 70-plot set for modeling and a 29-plot set for testing. For the model test, the correlation coefficient of predictive value and the plot data was 0.67 and 0.68 for BPNN and SGCS, respectively. Both of the two methods have the same RRMSE value (0.63). The predictive ability of SGCS was slightly higher than that of BPNN. The estimation results using BPNN showed that the sum of above-ground carbon is 11042990 Mg and the mean carbon density was 36.10 Mg/hm2 which was higher than the average from the sample plots with a relative error of 8.82%. The SGCS showed that the sum of above-ground carbon was 11388657 Mg with a mean carbon density 37.23 Mg/hm2 which was higher than the average from the sample plots with a relative error of 9.4%. Comparative analysis showed the carbon densities estimated using these two methods are both close to that calculated from the NFI data. However, there were some differences between the two methods with respect to the estimation of the frequency distribution and the carbon distribution in the study area. Predictive value of sample plot obtained using the SGCS method was closer to the plot data value than that obtained using the BPNN. And the correlation between predictive value and the plot data was 0.75, which proved that there were obvious advantages in estimating the spatial distribution of forest carbon. In addition, in terms of carbon density range and frequency distribution, SGCS was more reliable. This study further verifies the effectiveness of the SGSC which could provide effective methods for the estimation of regional forest carbon storage. 参考文献 相似文献 引证文献

Role of CO<sub>2</sub>, climate and land use in regulating the seasonal amplitude increase of carbon fluxes in terrestrial ecosystems: a multimodel analysis

Abstract. We examined the net terrestrial carbon flux to the atmosphere (FTA) simulated by nine models from the TRENDY dynamic global vegetation model project for its seasonal cycle and amplitude trend during 1961–2012. While some models exhibit similar phase and amplitude compared to atmospheric inversions, with spring drawdown and autumn rebound, others tend to rebound early in summer. The model ensemble mean underestimates the magnitude of the seasonal cycle by 40 % compared to atmospheric inversions. Global FTA amplitude increase (19 ± 8 %) and its decadal variability from the model ensemble are generally consistent with constraints from surface atmosphere observations. However, models disagree on attribution of this long-term amplitude increase, with factorial experiments attributing 83 ± 56 %, −3 ± 74 and 20 ± 30 % to rising CO2, climate change and land use/cover change, respectively. Seven out of the nine models suggest that CO2 fertilization is the strongest control – with the notable exception of VEGAS, which attributes approximately equally to the three factors. Generally, all models display an enhanced seasonality over the boreal region in response to high-latitude warming, but a negative climate contribution from part of the Northern Hemisphere temperate region, and the net result is a divergence over climate change effect. Six of the nine models show that land use/cover change amplifies the seasonal cycle of global FTA: some are due to forest regrowth, while others are caused by crop expansion or agricultural intensification, as revealed by their divergent spatial patterns. We also discovered a moderate cross-model correlation between FTA amplitude increase and increase in land carbon sink (R2 = 0.61). Our results suggest that models can show similar results in some benchmarks with different underlying mechanisms; therefore, the spatial traits of CO2 fertilization, climate change and land use/cover changes are crucial in determining the right mechanisms in seasonal carbon cycle change as well as mean sink change.

Topographic influences on shoot litter and root decomposition in semiarid hilly grasslands

Topography has strong effects on microclimates; thus may influence the decomposition of organic matter, a key process determines soil nutrient availability and carbon fluxes in terrestrial ecosystems. Yet, little is known if and how topographic factors influence litter decomposition. We studied the effects of slope aspect (south- vs. north-facing slopes) and position (base and middle positions) on plant shoot litter and root decomposition. We analyzed dynamics of litter mass loss in a 442-day period, and soil and vegetation characteristics in a typical semiarid hilly grassland. Our results showed that the decomposition of roots was faster at south-facing than at north-facing sites, which can be explained by the 2°C higher soil temperature at south-facing sites. Decomposition rate of shoot litter were not different between slope aspects. North-facing sites had 76% higher aboveground biomass and 80% higher belowground biomass than those at south-facing sites. Accordingly, plant N and C storages at north-facing sites were 67% and 76% higher than those at south-facing sites, respectively. The smaller plant carbon and nitrogen stocks and the faster root decomposition at south-facing slopes suggest higher proportions of plant C and N are lost from the ecosystem than that at north-facing slopes. This work highlights the necessity of taking slope aspect into account in carbon and nitrogen cycling studies in hilly grasslands.

Evaluation of the Community Land Model simulated carbon and water fluxes against observations over ChinaFLUX sites

The Community Land Model (CLM) is an advanced process-based land surface model that simulates carbon, nitrogen, water vapor and energy exchanges between terrestrial ecosystems and the atmosphere at various spatial and temporal scales. We use observed carbon and water fluxes from five representative Chinese Terrestrial Ecosystem Flux Research Network (ChinaFLUX) eddy covariance tower sites to systematically evaluate the new version CLM4.5 and old version CLM4.0, and to generate insights that may inform future model developments. CLM4.5 underestimates the annual carbon sink at three forest sites and one alpine grassland site but overestimates the carbon sink of a semi-arid grassland site. The annual carbon sink underestimation for the deciduous-dominated forest site results from underestimated daytime carbon sequestration during summer and overestimated nighttime carbon emission during spring and autumn. Compared to CLM4.0, the bias of annual gross primary production (GPP) is reduced by 24% and 28% in CLM4.5 at two subtropical forest sites. However, CLM4.5 still presents a large positive bias in annual GPP. The improvement in net ecosystem exchange (NEE) is limited, although soil respiration bias decreases by 16%–43% at three forest sites. CLM4.5 simulates lower soil water content in the dry season than CLM4.0 at two grassland sites. Drier soils produce a significant drop in the leaf area index and in GPP and an increase in respiration for CLM4.5. The new fire parameterization approach in CLM4.5 causes excessive burning at the Changbaishan forest site, resulting in an unexpected underestimation of NEE, vegetation carbon, and soil organic carbon by 46%, 95%, and 87%, respectively. Overall, our study reveals significant improvements achieved by CLM4.5 compared to CLM4.0, and suggests further developments on the parameterization of seasonal GPP and respiration, which will require a more effective representation of seasonal water conditions and the partitioning of net radiation between sensible and heat fluxes.

Construction and progress of Chinese terrestrial ecosystem carbon, nitrogen and water fluxes coordinated observation

Eddy Covariance technique (EC) achieves the direct measurement on ecosystem carbon, nitrogen and water fluxes, and it provides scientific data for accurately assessing ecosystem functions in mitigating global climate change. This paper briefly reviewed the construction and development of Chinese terrestrial ecosystem flux observation and research network (ChinaFLUX), and systematically introduced the design principle and technology of the terrestrial ecosystem carbon, nitrogen and water fluxes coordinated observation system of ChinaFLUX. In addition, this paper summarized the main progress of ChinaFLUX in the ecosystem carbon, nitrogen and water exchange and environmental controlling mechanisms, the spatial pattern of carbon, nitrogen and water fluxes and biogeographical mechanisms, and the regional terrestrial ecosystem carbon budget assessment. Finally, the prospects and emphases of the terrestrial ecosystem carbon, nitrogen and water fluxes coordinated observation of ChinaFLUX are put forward to provide theoretical references for the development of flux observation and research in China.

Atmospheric CO<sub>2</sub> source and sink patterns over the Indian region

Abstract. In this paper we examine CO2 emission hot spots and sink regions over India as identified from global model simulations during the period 2000–2009. CO2 emission hot spots overlap with locations of densely clustered thermal power plants, coal mines and other industrial and urban centres; CO2 sink regions coincide with the locations of dense forest. Fossil fuel CO2 emissions are compared with two bottom-up inventories: the Regional Emission inventories in ASia (REAS v1.11; 2000–2009) and the Emission Database for Global Atmospheric Research (EDGAR v4.2) (2000–2009). Estimated fossil fuel emissions over the hot spot region are ∼ 500–950 gC m−2 yr−1 as obtained from the global model simulation, EDGAR v4.2 and REAS v1.11 emission inventory. Simulated total fluxes show increasing trends, from 1.39 ± 1.01 % yr−1 (19.8 ± 1.9 TgC yr−1) to 6.7 ± 0.54 % yr−1 (97 ± 12 TgC yr−1) over the hot spot regions and decreasing trends of −0.95 ± 1.51 % yr−1 (−1 ± 2 TgC yr−1) to −5.7 ± 2.89 % yr−1 (−2.3 ± 2 TgC yr−1) over the sink regions. Model-simulated terrestrial ecosystem fluxes show decreasing trends (increasing CO2 uptake) over the sink regions. Decreasing trends in terrestrial ecosystem fluxes imply that forest cover is increasing, which is consistent with India State of Forest Report (2009). Fossil fuel emissions show statistically significant increasing trends in all the data sets considered in this study. Estimated trend in simulated total fluxes over the Indian region is ∼ 4.72 ± 2.25 % yr−1 (25.6 TgC yr−1) which is slightly higher than global growth rate ∼ 3.1 % yr−1 during 2000–2010.

Effects of plant functional group loss on soil biota and net ecosystem exchange: a plant removal experiment in the Mongolian grassland

SummaryThe rapid loss of global biodiversity can greatly affect the functioning of above‐ground components of ecosystems. However, how such biodiversity losses affect below‐ground communities and linkages to soil carbon (C) sequestration is unclear. Here, we describe how losses in plant functional groups (PFGs) affect soil microbial and nematode communities and net ecosystem exchange (NEE) in a 4‐year removal experiment conducted on the Mongolian plateau, the world's largest remaining natural grassland.Our results demonstrated that the biomasses or abundances of most components of the two below‐ground communities (microbes and nematodes) were negatively affected byPFGloss and were positively related to above‐ground plant biomass. The removal of dominantPFGs (perennial bunchgrasses and perennial rhizomatous grasses) reduced the biomass or abundance of below‐ground community components while removal of less dominantPFGs (perennial forbs and annuals/biennials) did not change or increased the biomass or abundance of below‐ground community components.The biomass‐based ratio of fungal to bacterial microbes and the number‐based ratio of fungal‐feeding to bacterial‐feeding nematodes decreased with increasingPFGlosses. Variation partitioning analyses showed that the identity ofPFGs together with above‐ground plant biomass explained most of the total variation in soil microbes and that the identity ofPFGs and above‐ground plant biomass together with nematode food resources explained most of the total variation in soil nematodes. The increase inNEEwithPFGloss was mainly explained by decreases in above‐ground plant biomass and the ratio of fungi to bacteria.Synthesis. The shift of below‐ground communities from a fungal‐based to a bacterial‐based energy channel asPFGrichness decreases indicates that less diverse grassland ecosystems will have lower nutrient retention and hence be more sensitive to land‐use or climate change. The dominant effects of above‐ground plant biomass and below‐ground communities onNEEindicate thatPFGloss resulting from land‐use or climate change has the potential to reduce C sequestration in semi‐arid grassland soils. These findings suggest that predictive models may need to consider the composition of above‐ground and below‐ground communities in order to accurately simulate the dynamics ofCO2fluxes in terrestrial ecosystems.

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

Ecosystem carbon (C) fluxes in terrestrial ecosystems are affected by varying environmental conditions (e.g., soil heterogeneity and weather) and land management. However, the interactions between soil respiration (Rs) and net ecosystem exchange (NEE) and their spatio-temporal dependence on environmental conditions and land management at field scale is not well understood. We performed repeated C flux measurement at 21 sites during the 2013 growing season in a temperate upland grassland in Germany, which was fertilized and cut three times according to the agricultural practice typical of the region. Repeated measurements included determination of NEE, Rs, leaf area index (LAI), meteorological conditions as well as physical and chemical soil properties. Temporal variability of Rs was controlled by air temperature, while LAI influenced the temporal variability of NEE. The three grass cuts reduced LAI and affected NEE markedly. More than 50% of NEE variability was explained by defoliation at field scale. Additionally, soil heterogeneity affected NEE, but to a lower extent (>30%), while Rs remained unaffected. We conclude that grassland management (i.e., repeated defoliation) and soil heterogeneity affects the spatio-temporal variability of NEE at field scale.

Temperature sensitivity of soil respiration in China’s forest ecosystems: Patterns and controls

Soil respiration, one of the most important carbon fluxes in terrestrial ecosystems, is very sensitive to climate change. Understanding the spatial patterns of temperature sensitivity of soil respiration (Q10) and its controlling factors is very important to quantify the climate–carbon cycle feedback at regional scales. In this study, we conducted a synthesis of 74 field measurements on Q10 value across China’s forests. Based on the overall data, the Q10 values ranged from 1.10 to 5.18, with a mean value of 2.51. Moreover, the largest relative frequency of Q10 values was within the range of 2.0–3.0. The Q10 value in China’s forests was significantly and negatively correlated with mean annual temperature and mean annual precipitation. However, the Q10 values increased with latitude and altitude but there was no obvious relationship between Q10 and longitude. There were no significant differences in Q10 among evergreen coniferous forest, coniferous-broadleaved mixed forest, deciduous broadleaved forest and deciduous coniferous forest. However, the Q10 of evergreen broadleaved forest was significantly lower than that of evergreen coniferous forest and deciduous coniferous forest. The findings may advance our understanding on the different environmental controls of Q10 of soil respiration and also improve our ability to predict regional-scale soil carbon flux in a changing world.

Comparison of soil solution sampling techniques to assess metal fluxes from contaminated soil to groundwater.

The unsaturated zone plays a major role in elemental fluxes in terrestrial ecosystems. A representative chemical analysis of soil pore water is required for the interpretation of soil chemical phenomena and particularly to assess Trace Elements (TEs) mobility. This requires an optimal sampling system to avoid modification of the extracted soil water chemistry and allow for an accurate estimation of solute fluxes. In this paper, the chemical composition of soil solutions sampled by Rhizon® samplers connected to a standard syringe was compared to two other types of suction probes (Rhizon® + vacuum tube and Rhizon® + diverted flow system). We investigated the effects of different vacuum application procedures on concentrations of spiked elements (Cr, As, Zn) mixed as powder into the first 20cm of 100-cm columns and non-spiked elements (Ca, Na, Mg) concentrations in two types of columns (SiO2 sand and a mixture of kaolinite + SiO2 sand substrates). Rhizon® was installed at different depths. The metals concentrations showed that (i) in sand, peak concentrations cannot be correctly sampled, thus the flux cannot be estimated, and the errors can easily reach a factor 2; (ii) in sand + clay columns, peak concentrations were larger, indicating that they could be sampled but, due to sorption on clay, it was not possible to compare fluxes at different depths. The different samplers tested were not able to reflect the elemental flux to groundwater and, although the Rhizon® + syringe device was more accurate, the best solution remains to be the use of a lysimeter, whose bottom is kept continuously at a suction close to the one existing in the soil.

Geographical statistical assessments of carbon fluxes in terrestrial ecosystems of China: Results from upscaling network observations

Accurate quantifying the magnitudes and distributions of carbon budgets is helpful for strategies in mitigating global climate change. Based on spatial patterns of carbon fluxes (gross ecosystem productivity (GEP), ecosystem respiration (ER) and net ecosystem productivity (NEP)) and their drivers, we constructed geographical statistical assessment schemes and quantified the magnitudes of carbon fluxes in China. The optimal assessment scheme was then validated with observed eddy covariance data to analyze the spatial distributions of carbon fluxes. Using climate-based geographical statistical assessment schemes, our estimates of GEP, ER and NEP in China during 2000s were 7.51±0.51, 5.82±0.16 and 1.91±0.15PgCyr−1, corresponding to 4.29%–6.80%, 5.65%–6.06% and 9.10%–12.73% of global annual carbon fluxes, respectively. The spatial distributions of GEP, ER and NEP, generated from the optimal scheme, were similar, following a southeast–northwest decreasing gradient. The maximum values for GEP, ER and NEP were 1790, 1300 and 490gCm−2yr−1, respectively, which occurred in Central subtropics and Southern subtropics. Climate-based geographical statistical assessment schemes provided an independent dataset for the regional carbon budget assessment, which can be deemed as the potential carbon fluxes. Meanwhile, most areas in China were potential carbon sink especially Eastern China and the largest potential carbon sink appeared in Central subtropics and Southern subtropics.

Does consideration of water routing affect simulated water and carbon dynamics in terrestrial ecosystems?

Abstract. The cycling of carbon (C) in terrestrial ecosystems is closely coupled with the cycling of water. An important mechanism connecting ecological and hydrological processes in terrestrial ecosystems is lateral flow of water along landscapes. Few studies, however, have examined explicitly how consideration of water routing affects simulated water and C dynamics in terrestrial ecosystems. The objective of this study is to explore how consideration of water routing in a process-based hydro-ecological model affects simulated water and C dynamics. To achieve that end, we rasterized the regional hydro-ecological simulation system (RHESSys) and employed the rasterized RHESSys (R-RHESSys) in a forested watershed. We performed and compared two contrasting simulations, one with and another without water routing. We found that R-RHESSys was able to correctly simulate major hydrological and ecological variables regardless of whether water routing was considered. When water routing was considered, however, soil water table depth and saturation deficit were simulated to be greater and spatially more heterogeneous. As a result, water (evaporation, transpiration, and evapotranspiration) and C (forest productivity, soil autotrophic and heterotrophic respiration) fluxes also were simulated to be spatially more heterogeneous compared to the simulation without water routing. When averaged for the entire watershed, the three simulated water fluxes were greater while C fluxes were smaller under simulation considering water routing compared to that ignoring water routing. In addition, the effects of consideration of water routing on simulated C and water dynamics were more apparent in dry conditions. Overall, the study demonstrated that consideration of water routing enabled R-RHESSys to better capture our preconception of the spatial patterns of water table depth and saturation deficit across the watershed. Because soil moisture is fundamental to the exchange of water and C fluxes among soil, vegetation and the atmosphere, ecosystem and C cycle models therefore need to explicitly represent water routing in order to accurately quantify the magnitude and patterns of water and C fluxes in terrestrial ecosystems.

Climate‐driven uncertainties in modeling terrestrial gross primary production: a site level to global‐scale analysis

We used a land surface model to quantify the causes and extents of biases in terrestrial gross primary production (GPP) due to the use of meteorological reanalysis datasets. We first calibrated the model using meteorology and eddy covariance data from 25 flux tower sites ranging from the tropics to the northern high latitudes and subsequently repeated the site simulations using two reanalysis datasets: NCEP/NCAR and CRUNCEP. The results show that at most sites, the reanalysis-driven GPP bias was significantly positive with respect to the observed meteorology-driven simulations. Notably, the absolute GPP bias was highest at the tropical evergreen tree sites, averaging up to ca. 0.45kgCm(-2) yr(-1) across sites (ca. 15% of site level GPP). At the northern mid-/high-latitude broadleaf deciduous and the needleleaf evergreen tree sites, the corresponding annual GPP biases were up to 20%. For the nontree sites, average annual biases of up to ca. 20-30% were simulated within savanna, grassland, and shrubland vegetation types. At the tree sites, the biases in short-wave radiation and humidity strongly influenced the GPP biases, while the nontree sites were more affected by biases in factors controlling water stress (precipitation, humidity, and air temperature). In this study, we also discuss the influence of seasonal patterns of meteorological biases on GPP. Finally, using model simulations for the global land surface, we discuss the potential impacts of site-level reanalysis-driven biases on the global estimates of GPP. In a broader context, our results can have important consequences on other terrestrial ecosystem fluxes (e.g., net primary production, net ecosystem production, energy/water fluxes) and reservoirs (e.g., soil carbon stocks). In a complementary study (Barman etal., ), we extend the present analysis for latent and sensible heat fluxes, thus consistently integrating the analysis of climate-driven uncertainties in carbon, energy, and water fluxes using a single modeling framework.

CNGI/ChinaFLUX: an IPv6-based Terrestrial Ecosystem Flux Research Network in China

In this manuscript, we introduce the first-step research and development on CNGI/ChinaFLUX, which is supported by CNGI (China Next Generation Internet) Project. From May 2012, we set up an IPv6-based real-time carbon flux observation system in ten sites, based on the Chinese Terrestrial Ecosystem Flux Research Network (ChinaFLUX). The hardware environment construction includes IPv6-based data transmission network platform, data acquisition system, data storage and processing system. The software environment construction includes IPv6-based observation device monitoring system, data storage and management system. Researchers develop a series of research applications in CNGI/ChinaFLUX network.

Convergence between ANPP estimation methods in grasslands — A practical solution to the comparability dilemma

Aboveground net primary production (ANPP) is a key ecosystem characteristic and of fundamental importance for essentially all aspects of matter and energy fluxes in terrestrial ecosystems. Various methods for estimating ANPP are available and despite partial consensus on ‘best practice methods’ important methodological issues remain unresolved: ANPP data obtained with different methods differ in their magnitude, variability and their tendency to over- or underestimate primary production. Paradoxically, despite the large number of published ANPP data, the limited comparability of ANPP estimates across studies de facto leads to a scarcity of ANPP data for assembled large-scale studies. We aimed to overcome these problems by establishing conversion rates between the most commonly used ANPP methods, making the large body of published ANPP data more comparable and thus useful for assembled large-scale studies.Using seasonal biomass dynamics from 89 sites representing various biomes and climata, we established linear conversions for all 21 combinations between the seven most common ANPP estimation algorithms in grass-dominated vegetation. We also checked for confounding effects of environmental factors such as biome and climatic aridity. Aridity was the only factor with a clear influence on ANPP conversions, and in six cases we thus calculated separate relationships for dry and humid environments. In these cases, dryland ANPP was systematically underestimated by the respective methods. As these methods are insensitive to turn-over processes from live to senescent biomass, we assume this underestimation is related to climate-induced differences in biomass turn-over rates, with more arid sites having higher rates.The majority of the resulting 27 conversions had high (pseudo) R2 values (≥0.65; full range: 0.31–0.92), indicating clear linear relationships between most ANPP estimation methods. Given the large size of the dataset and the accuracy of statistical models, we assume that most conversion formulae are generally valid. We classified conversions with respect to their R2 values and their methodological comparability, and concluded that 16 conversions can be fully recommended. For those cases where a recalculation of ANPP on basis of original biomass data is not possible, our conversion formulae offer an easy and practical approach to synchronize ANPP estimates from divergent algorithms and sources.

Modeling evapotranspiration by combing a two-source model, a leaf stomatal model, and a light-use efficiency model

summary Modeling and partitioning ecosystem evapotranspiration (ET) are important in predicting the responses of ecosystem water cycles to global climate change and land use. By incorporating the Ball–Berry stomatal conductance model and a light use efficiency-based gross primary productivity (GPP) model into the Shuttleworth–Wallace model, we developed a new model, SWH, for estimating ET with meteorological data and remote sensing products. Since the new model solved the problem of estimating canopy stomatal conductance, it can be used at sites equipped with meteorological observation systems around the world. Compared with eddy covariance measurements, the SWH model demonstrated satisfactory estimates of ET at a temperate forest and an alpine grassland. Eight meteorological variables and two remote sensing products (i.e., leaf area index, LAI, and enhanced vegetation index, EVI or normalized difference vegetation index, NDVI, or fraction of photosynthetically active radiation, FPAR) are required in our model. This will facilitate estimates of ET and its components, and further elucidate the mechanisms underlying their variations at regional scale. In addition, our model estimates ET and GPP simultaneously, making it convenient to address the coupling of these two key fluxes in terrestrial ecosystems.

The seasonal pattern of soil microbial community structure in mesic low arctic tundra

Soil microorganisms are critical to carbon and nutrient fluxes in terrestrial ecosystems. Understanding the annual pattern of soil microbial community structure and how it corresponds to soil nutrient availability and plant production is a fundamental first step towards being able to predict impacts of environmental change on ecosystem functioning. We investigated the composition, structure and nutrient stoichiometry of the soil microbial community in mesic arctic tundra on 9 sample dates in 6 months from winter to fall using phospholipid fatty acid analysis (PLFA), quantitative polymerase chain reaction (qPCR), epifluorescent microscopy and chloroform-fumigation–extraction (CFE). PLFA analysis indicates that the winter microbial community was fungal-dominated, cold-adapted and associated with high C, N and P in the soil solution and microbial biomass. The microscopy data suggest that both bacteria and fungi were active and growing in soils between −5 °C and 0 °C. A significant shift occurred in the PLFA data, qPCR patterns, microscopy and microbial biogeochemistry after the thaw period, resulting in a distinct community that persisted through our spring, summer and fall sample dates, despite large changes in plant productivity. This shift was characterised by increasing relative abundances of certain bacteria (especially Gram +ves) as well as a decline in fungal biomass, and corresponded with decreasing C, N and P in the soil solution. The summer period of low substrate availability (plant–microbe competition) was associated with microbial indicators of nutritional stress. Overall, our results indicate that tundra microbial communities are clearly differentiated according to the changes in soil nutrient status and environmental conditions that occur between winter and post-thaw, and that those changes reflect functionally important adaptations to those conditions.

Spatial patterns and climate drivers of carbon fluxes in terrestrial ecosystems of China

Understanding the dynamics and underlying mechanism of carbon exchange between terrestrial ecosystems and the atmosphere is one of the key issues in global change research. In this study, we quantified the carbon fluxes in different terrestrial ecosystems in China, and analyzed their spatial variation and environmental drivers based on the long-term observation data of ChinaFLUX sites and the published data from other flux sites in China. The results indicate that gross ecosystem productivity (GEP), ecosystem respiration (ER), and net ecosystem productivity (NEP) of terrestrial ecosystems in China showed a significantly latitudinal pattern, declining linearly with the increase of latitude. However, GEP, ER, and NEP did not present a clear longitudinal pattern. The carbon sink functional areas of terrestrial ecosystems in China were mainly located in the subtropical and temperate forests, coastal wetlands in eastern China, the temperate meadow steppe in the northeast China, and the alpine meadow in eastern edge of Qinghai-Tibetan Plateau. The forest ecosystems had stronger carbon sink than grassland ecosystems. The spatial patterns of GEP and ER in China were mainly determined by mean annual precipitation (MAP) and mean annual temperature (MAT), whereas the spatial variation in NEP was largely explained by MAT. The combined effects of MAT and MAP explained 79%, 62%, and 66% of the spatial variations in GEP, ER, and NEP, respectively. The GEP, ER, and NEP in different ecosystems in China exhibited 'positive coupling correlation' in their spatial patterns. Both ER and NEP were significantly correlated with GEP, with 68% of the per-unit GEP contributed to ER and 29% to NEP. MAT and MAP affected the spatial patterns of ER and NEP mainly by their direct effects on the spatial pattern of GEP.