The growth rate of atmospheric carbon dioxide (CO2) concentrations since industrialization is characterized by large interannual variability, mostly resulting from variability in CO2 uptake by terrestrial ecosystems (typically termed carbon sink). However, the contributions of regional ecosystems to that variability are not well known. Using an ensemble of ecosystem and land-surface models and an empirical observation-based product of global gross primary production, we show that the mean sink, trend, and interannual variability in CO2 uptake by terrestrial ecosystems are dominated by distinct biogeographic regions. Whereas the mean sink is dominated by highly productive lands (mainly tropical forests), the trend and interannual variability of the sink are dominated by semi-arid ecosystems whose carbon balance is strongly associated with circulation-driven variations in both precipitation and temperature. Copyright © 2015, American Association for the Advancement of Science.

通量观测是定量描述土壤-植被-大气间物质循环和能量交换过程的基础。涡度相关技术作为直接测量植被冠层与大气间能量与物质交换通量的技术手段, 已经逐步发展成为国际通用的通量观测标准方法。随着涡度相关技术在全球碳水循环研究中的广泛应用, 长期连续的通量观测正在为准确评价生态系统碳固持能力、水分和能量平衡状况、生态系统对全球气候变化的反馈作用、区域和全球尺度模型的优化与验证、极端事件对生态系统结构与功能影响等方面的研究提供重要数据支撑和机制理解途径。通过站点尺度通量长期动态观测, 明确了不同气候区和植被类型生态系统碳水通量强度基线及其季节与年际变异特征。通过多站点联网观测, 在区域和全球尺度研究生态系统碳通量空间变异特征, 揭示了区域尺度上温度和降水对生态系统碳通量空间格局的生物地理学控制机制。该文概括地介绍了涡度相关技术的基本原理、假设与系统构成, 总结了涡度通量长期联网观测在陆地生态系统碳水通量研究中的主要应用, 并对通量研究发展前景进行了展望。

. The carbon (C) cycling in semiarid and arid areas remains largely unexplored, despite the wide distribution of drylands globally. Rehabilitation practices have been carried out in many desertified areas, but information on the C sequestration capacity of recovering vegetation is still largely lacking. Using the eddy-covariance technique, we measured the net ecosystem CO2 exchange (NEE) over a recovering shrub ecosystem in northwest China throughout 2012 in order to (1) quantify NEE and its components and to (2) examine the dependence of C fluxes on biophysical factors at multiple timescales. The annual budget showed a gross ecosystem productivity (GEP) of 456 g C m−2 yr−1 (with a 90% prediction interval of 449–463 g C m−2 yr−1) and an ecosystem respiration (Re) of 379 g C m−2 yr−1 (with a 90% prediction interval of 370–389 g C m−2 yr−1), resulting in a net C sink of 77 g C m−2 yr−1 (with a 90% prediction interval of 68–87 g C m−2 yr−1). The maximum daily NEE, GEP and Re were −4.7, 6.8 and 3.3 g C m−2 day−1, respectively. Both the maximum C assimilation rate (i.e., at the optimum light intensity) and the quantum yield varied over the growing season, being higher in summer and lower in spring and autumn. At the half-hourly scale, water deficit exerted a major control over daytime NEE, and interacted with other stresses (e.g., heat and photoinhibition) in constraining C fixation by the vegetation. Low soil moisture also reduced the temperature sensitivity of Re (Q10). At the synoptic scale, rain events triggered immediate pulses of C release from the ecosystem, followed by peaks of CO2 uptake 1–2 days later. Over the entire growing season, leaf area index accounted for 45 and 65% of the seasonal variation in NEE and GEP, respectively. There was a linear dependence of daily Re on GEP, with a slope of 0.34. These results highlight the role of abiotic stresses and their alleviation in regulating C cycling in the face of an increasing frequency and intensity of extreme climatic events.\n

Although leaf economics spectrum (LES) has been extensively tested with regional and global datasets, the correlation among functional traits of desert plants remains largely unclear. Moreover, examinations on whether and how leaf and root traits are coordinated have yielded mixed results. We investigated variations in leaf and fine-root traits across 48 species in a desert community of northern China to test the hypotheses that (1) the leaf-trait syndrome of plant species in desert shrublands follows the predictions of the global LES, and is paralleled by a similar root-trait syndrome, (2) functional traits related to nutrient contents and resource uptake are tightly coordinated between leaves and fine roots in desert ecosystems where plant growth is limited primarily by dry and nutrient-poor conditions, and (3) traits as well as their relationships vary among functional groups. Our results partially supported the LES theory. Specific leaf area (SLA) was correlated with leaf tissue density, phosphorus content, and carbon-to-nitrogen ratio, but not with leaf nitrogen content. Specific root length (SRL) was not correlated with other fine-root traits, and fine-root traits were largely independent of each other. Therefore, fine-root traits did not mirror the leaf-trait syndrome. Fine-root nitrogen and phosphorus contents, nitrogen-to-phosphorous ratio, and carbon-to-nitrogen ratio all increased with analogous leaf traits, whereas SRL was not correlated with SLA. After phylogenetic effects were considered, nutrient contents and their ratios still displayed stronger coordination between leaves and fine roots than did SRL and SLA. The overall pattern of trait variations and relationships suggested differentiation among functional groups. Our results suggest that despite the absence of a root-trait syndrome, fine-root functions in the studied desert community were probably coordinated with leaf functions with respect to nutrient allocation and use.

Energy balance studies require knowledge of the heat flux at the soil surface. This flux is determined by summing the heat flux at a reference depth (zr) some centimeters below the surface and the rate of change of heat storage in the soil above zr. The rate of change of heat storage, or heat storage for short (ΔS), is calculated from soil volumetric heat capacity (C) and temperature. The objectives of this study were to determine how choices regarding zr, C measurements, and ΔS calculations all affect the accuracy of ΔS data. Heat transfer theory and data from three field sites were used toward these ends. In some studies, shallow reference depths have been used and ΔS neglected. Our results indicate that when zr is sufficiently deep to permit accurate heat flux measurements, ΔS is too large to neglect. Three methods for determining C were evaluated: soil sampling, the ThetaProbe soil moisture sensor, and heat pulse sensors. When C was determined using all three methods simultaneously, the estimates agreed to within 6% on average; however, the temporal variability of C was best recorded with the automated heat pulse sensors. Three approaches for calculating ΔS were also tested. The common approach of letting C vary in time but neglecting its time derivative caused errors when soil water content was changing. These errors exceeded 200 W m−2 in some cases. The simple approach of assuming a constant C performed similarly. We introduce a third approach that accounts for the time derivative of C and yields the most accurate ΔS data.

. Eddy covariance technique to measure CO2, water and energy fluxes between biosphere and atmosphere is widely spread and used in various regional networks. Currently more than 250 eddy covariance sites are active around the world measuring carbon exchange at high temporal resolution for different biomes and climatic conditions. In this paper a new standardized set of corrections is introduced and the uncertainties associated with these corrections are assessed for eight different forest sites in Europe with a total of 12 yearly datasets. The uncertainties introduced on the two components GPP (Gross Primary Production) and TER (Terrestrial Ecosystem Respiration) are also discussed and a quantitative analysis presented. Through a factorial analysis we find that generally, uncertainties by different corrections are additive without interactions and that the heuristic u*-correction introduces the largest uncertainty. The results show that a standardized data processing is needed for an effective comparison across biomes and for underpinning inter-annual variability. The methodology presented in this paper has also been integrated in the European database of the eddy covariance measurements.

The FLUXNET2015 dataset provides ecosystem-scale data on CO, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.

In this millennium, global drylands face a myriad of problems that present tough research, management, and policy challenges. Recent advances in dryland development, however, together with the integrative approaches of global change and sustainability science, suggest that concerns about land degradation, poverty, safeguarding biodiversity, and protecting the culture of 2.5 billion people can be confronted with renewed optimism. We review recent lessons about the functioning of dryland ecosystems and the livelihood systems of their human residents and introduce a new synthetic framework, the Drylands Development Paradigm (DDP). The DDP, supported by a growing and well-documented set of tools for policy and management action, helps navigate the inherent complexity of desertification and dryland development, identifying and synthesizing those factors important to research, management, and policy communities.

. With the eddy covariance (EC) technique, net fluxes of carbon dioxide (CO2) and other trace gases as well as water and energy fluxes can be measured at the ecosystem level. These flux measurements are a main source for understanding biosphere–atmosphere interactions and feedbacks through cross-site analysis, model–data integration, and upscaling. The raw fluxes measured with the EC technique require extensive and laborious data processing. While there are standard tools1 available in an open-source environment for processing high-frequency (10 or 20 Hz) data into half-hourly quality-checked fluxes, there is a need for more usable and extensible tools for the subsequent post-processing steps. We tackled this need by developing the REddyProc package in the cross-platform language R that provides standard CO2-focused post-processing routines for reading (half-)hourly data from different formats, estimating the u* threshold, as well as gap-filling, flux-partitioning, and visualizing the results. In addition to basic processing, the functions are extensible and allow easier integration in extended analysis than current tools. New features include cross-year processing and a better treatment of uncertainties. A comparison of REddyProc routines with other state-of-the-art tools resulted in no significant differences in monthly and annual fluxes across sites. Lower uncertainty estimates of both u* and resulting gap-filled fluxes by 50 % with the presented tool were achieved by an improved treatment of seasons during the bootstrap analysis. Higher estimates of uncertainty in daytime partitioning (about twice as high) resulted from a better accounting for the uncertainty in estimates of temperature sensitivity of respiration. The provided routines can be easily installed, configured, and used. Hence, the eddy covariance community will benefit from the REddyProc package, allowing easier integration of standard post-processing with extended analysis. 1http://fluxnet.fluxdata.org/2017/10/10/toolbox-a-rolling-list-of-softwarepackages-for-flux-related-data-processing/, last access: 17 August 2018\n

. Climate change severely impacts the grassland carbon cycling by\naltering rates of litter decomposition and soil respiration (Rs),\nespecially in arid areas. However, little is known about the Rs\nresponses to different warming magnitudes and watering pulses in situ in desert\nsteppes. To examine their effects on Rs, we conducted long-term moderate\nwarming (4 years, ∼3 ∘C), short-term acute\nwarming (1 year, ∼4 ∘C) and watering field\nexperiments in a desert grassland of northern China. While experimental\nwarming significantly reduced average Rs by 32.5 % and 40.8 %\nunder long-term moderate and short-term acute warming regimes, respectively,\nwatering pulses (fully irrigating the soil to field capacity) stimulated it\nsubstantially. This indicates that climatic warming constrains soil carbon\nrelease, which is controlled mainly by decreased soil moisture, consequently\ninfluencing soil carbon dynamics. Warming did not change the exponential\nrelationship between Rs and soil temperature, whereas the relationship\nbetween Rs and soil moisture was better fitted to a sigmoid function.\nThe belowground biomass, soil nutrition, and microbial biomass were not\nsignificantly affected by either long-term or short-term warming regimes,\nrespectively. The results of this study highlight the great dependence of\nsoil carbon emission on warming regimes of different durations and the\nimportant role of precipitation pulses during the growing season in\nassessing the terrestrial ecosystem carbon balance and cycle.\n