Variability in exchange of CO2 across 12 northern peatland and tundra sites

Many wetland ecosystems such as peatlands and wet tundra hold large amounts of organic carbon (C) in their soils, and are thus important in the terrestrial C cycle. We have synthesized data on the carbon dioxide (CO₂) exchange obtained from eddy covariance measurements from 12 wetland sites, covering 1–7 years at each site, across Europe and North America, ranging from ombrotrophic and minerotrophic peatlands to wet tundra ecosystems, spanning temperate to arctic climate zones. The average summertime net ecosystem exchange of CO₂ (NEE) was highly variable between sites. However, all sites with complete annual datasets, seven in total, acted as annual net sinks for atmospheric CO₂. To evaluate the influence of gross primary production (GPP) and ecosystem respiration (R_eco) on NEE, we first removed the artificial correlation emanating from the method of partitioning NEE into GPP and R_eco. After this correction neither R_eco (P= 0.162) nor GPP (P= 0.110) correlated significantly with NEE on an annual basis. Spatial variation in annual and summertime R_eco was associated with growing season period, air temperature, growing degree days, normalized difference vegetation index and vapour pressure deficit. GPP showed weaker correlations with environmental variables as compared with R_eco, the exception being leaf area index (LAI), which correlated with both GPP and NEE, but not with R_eco. Length of growing season period was found to be the most important variable describing the spatial variation in summertime GPP and R_eco; global warming will thus cause these components to increase. Annual GPP and NEE correlated significantly with LAI and pH, thus, in order to predict wetland C exchange, differences in ecosystem structure such as leaf area and biomass as well as nutritional status must be taken into account.     

Comparing the impact of cloudiness on carbon dioxide exchange in a grassland and a maize cropland in northwestern China

Light quantity and quality strongly influence plant growth. However, different ecosystems have different capabilities to assimilate solar radiation. In this study, the effects of cloudiness intensity on the net ecosystem exchange of carbon dioxide (NEE) were compared between an alpine grassland (with lower leaf area index) at A??Rou and an oasis maize cropland (with higher leaf area index) at Yingke, using flux data obtained during the middle of the growing season (July?CAugust) in 2008 and 2009. The results showed that the response of NEE to photosynthetically active radiation (PAR) was more negative (carbon uptake) under cloudy than under clear skies at both sites. The maximum NEE occurred when the clearness index (CI) ranged from 0.4 to 0.7 under cloudy skies. The maximum enhancements were 11.9% for solar elevation angles of 60?C65° in the grassland, and 34.9% for solar elevation angles of 60?C65° and 10.3% for angles of 35?C40° in the maize cropland before the irrigation period. The response of NEE to CI changed slightly with solar elevation angle in the grassland compared to the maize cropland. The results indicate that enhanced NEE under cloudy skies can be attributed to increasingly diffuse PAR and interactions with environmental factors (air temperature and vapor pressure deficit).     

泡桐属(Paulownia)花粉形态学的初步研究

泡桐属(Paulownia)花粉,均为近球形,具3(拟)孔沟,外壁外层有清楚的异胞网状雕纹,沟界极区明显。这些共同特征,说明泡桐属是一个种间亲缘极近的自然的属;其萌发孔类型,可作为泡桐属归入玄参科的证据之一。通过花粉形态的比较,对兰考泡桐、宜昌泡桐和建始泡桐的分类地位,提出了论证。     

Scaling an Instantaneous Model of Tundra NEE to the Arctic Landscape

We scale a model of net ecosystem CO₂ exchange (NEE) for tundra ecosystems and assess model performance using eddy covariance measurements at three tundra sites. The model, initially developed using instantaneous (seconds–minutes) chamber flux (~m²) observations, independently represents ecosystem respiration (ER) and gross primary production (GPP), and requires only temperature (T), photosynthetic photon flux density (I ₀), and leaf area index (L) as inputs. We used a synthetic data set to parameterize the model so that available in situ observations could be used to assess the model. The model was then scaled temporally to daily resolution and spatially to about 1 km² resolution, and predicted values of NEE, and associated input variables, were compared to observations obtained from eddy covariance measurements at three flux tower sites over several growing seasons. We compared observations to modeled NEE calculated using T and I ₀ measured at the towers, and L derived from MODIS data. Cumulative NEE estimates were within 17 and 11% of instrumentation period and growing season observations, respectively. Predictions improved when one site-year experiencing anomalously dry conditions was excluded, indicating the potential importance of stomatal control on GPP and/or soil moisture on ER. Notable differences in model performance resulted from ER model formulations and differences in how L was estimated. Additional work is needed to gain better predictive ability in terms of ER and L. However, our results demonstrate the potential of this model to permit landscape scale estimates of NEE using relatively few and simple driving variables that are easily obtained via satellite remote sensing.     

坝上地区农田及两种恢复生境中蜘蛛多样性与群落特征

蜘蛛是农田生态系统中重要的自然天敌,其生物多样性及群落特征直接决定了农田的害虫控制等生态系统服务功能质量。农田及其周边的恢复生境是蜘蛛重要的栖息地。本研究采用陷阱法,对河北省张家口市崇礼区871、1360、1635 m 3个海拔农田、自然恢复草地及人工修复林地的蜘蛛群落的物种组成、物种多样性和功能特征进行研究,分析不同恢复生境中蜘蛛群落特征。结果表明: 不同生境蜘蛛的物种多样性指数差异明显,人工修复林地蜘蛛的多度为124.3只,显著高于自然恢复草地(70.1)及农田(38.6)的蜘蛛多度;人工修复林地(16.3)与自然恢复草地(21.4)的物种丰富度没有显著差别,但均显著高于农田(8.9);人工修复林地(2.04)及自然恢复草地(2.05)的Shannon多样性指数差异不显著,且均显著高于农田(1.55)。3种生境的蜘蛛群落组成均具有显著差异;蜘蛛体长与蜘蛛捕猎类型呈正相关,大型蜘蛛倾向于通过捕猎获取食物;自然恢复草地与农田蜘蛛以游猎型为主,而人工修复林地倾向于拥有更多的结网型蜘蛛,高海拔地区的蜘蛛体积通常较小。自然恢复草地与人工修复林地均可以提升蜘蛛群落多样性,在区域生物多样性保护中起重要作用;不同生境蜘蛛群落组成出现了显著分化,即蜘蛛群落总体的功能特征发生改变和保留了部分生境特有种。2种恢复生境蜘蛛多样性指标优于农田生境,且2种恢复生境物种组成存在差异,均具有保护特有种的功能,研究结果对农田及区域尺度蜘蛛生物多样性保护与恢复具有指导意义。     

FLUXNET and modelling the global carbon cycle

Measurements of the net CO₂ flux between terrestrial ecosystems and the atmosphere using the eddy covariance technique have the potential to underpin our interpretation of regional CO₂ source–sink patterns, CO₂ flux responses to forcings, and predictions of the future terrestrial C balance. Information contained in FLUXNET eddy covariance data has multiple uses for the development and application of global carbon models, including evaluation/validation, calibration, process parameterization, and data assimilation. This paper reviews examples of these uses, compares global estimates of the dynamics of the global carbon cycle, and suggests ways of improving the utility of such data for global carbon modelling. Net ecosystem exchange of CO₂ (NEE) predicted by different terrestrial biosphere models compares favourably with FLUXNET observations at diurnal and seasonal timescales. However, complete model validation, particularly over the full annual cycle, requires information on the balance between assimilation and decomposition processes, information not readily available for most FLUXNET sites. Site history, when known, can greatly help constrain the model‐data comparison. Flux measurements made over four vegetation types were used to calibrate the land‐surface scheme of the Goddard Institute for Space Studies global climate model, significantly improving simulated climate and demonstrating the utility of diurnal FLUXNET data for climate modelling. Land‐surface temperatures in many regions cool due to higher canopy conductances and latent heat fluxes, and the spatial distribution of CO₂ uptake provides a significant additional constraint on the realism of simulated surface fluxes. FLUXNET data are used to calibrate a global production efficiency model (PEM). This model is forced by satellite‐measured absorbed radiation and suggests that global net primary production (NPP) increased 6.2% over 1982–1999. Good agreement is found between global trends in NPP estimated by the PEM and a dynamic global vegetation model (DGVM), and between the DGVM and estimates of global NEE derived from a global inversion of atmospheric CO₂ measurements. Combining the PEM, DGVM, and inversion results suggests that CO₂ fertilization is playing a major role in current increases in NPP, with lesser impacts from increasing N deposition and growing season length. Both the PEM and the inversion identify the Amazon basin as a key region for the current net terrestrial CO₂ uptake (i.e. 33% of global NEE), as well as its interannual variability. The inversion's global NEE estimate of −1.2 Pg [C] yr⁻¹ for 1982–1995 is compatible with the PEM‐ and DGVM‐predicted trends in NPP. There is, thus, a convergence in understanding derived from process‐based models, remote‐sensing‐based observations, and inversion of atmospheric data. Future advances in field measurement techniques, including eddy covariance (particularly concerning the problem of night‐time fluxes in dense canopies and of advection or flow distortion over complex terrain), will result in improved constraints on land‐atmosphere CO₂ fluxes and the rigorous attribution of mechanisms to the current terrestrial net CO₂ uptake and its spatial and temporal heterogeneity. Global ecosystem models play a fundamental role in linking information derived from FLUXNET measurements to atmospheric CO₂ variability. A number of recommendations concerning FLUXNET data are made, including a request for more comprehensive site data (particularly historical information), more measurements in undisturbed ecosystems, and the systematic provision of error estimates. The greatest value of current FLUXNET data for global carbon cycle modelling is in evaluating process representations, rather than in providing an unbiased estimate of net CO₂ exchange.     

Ecohydrological impacts of woody-plant encroachment: seasonal patterns of water and carbon dioxide exchange within a semiarid riparian environment

Across many dryland regions, historically grass‐dominated ecosystems have been encroached upon by woody‐plant species. In this paper, we compare ecosystem water and carbon dioxide (CO₂) fluxes over a grassland, a grassland–shrubland mosaic, and a fully developed woodland to evaluate potential consequences of woody‐plant encroachment on important ecosystem processes. All three sites were located in the riparian corridor of a river in the southwest US. As such, plants in these ecosystems may have access to moisture at the capillary fringe of the near‐surface water table. Using fluxes measured by eddy covariance in 2003 we found that ecosystem evapotranspiration (ET) and net ecosystem exchange of carbon dioxide (NEE) increased with increasing woody‐plant dominance. Growing season ET totals were 407, 450, and 639 mm in the grassland, shrubland, and woodland, respectively, and in excess of precipitation by 227, 265, and 473 mm. This excess was derived from groundwater, especially during the extremely dry premonsoon period when this was the only source of moisture available to plants. Access to groundwater by the deep‐rooted woody plants apparently decouples ecosystem ET from gross ecosystem production (GEP) with respect to precipitation. Compared with grasses, the woody plants were better able to use the stable groundwater source and had an increased net CO₂ gain during the dry periods. This enhanced plant activity resulted in substantial accumulation of leaf litter on the soil surface that, during rainy periods, may lead to high microbial respiration rates that offset these photosynthetic fluxes. March–December (primary growing season) totals of NEE were ?63, ?212, and ?233 g C m^?2 in the grassland, shrubland, and woodland, respectively. Thus, there was a greater disparity between ecosystem water use and the strength of the CO₂ sink as woody plants increased across the encroachment gradient. Despite a higher density of woody plants and a greater plant productivity in the woodland than in the shrubland, the woodland produced a larger respiration response to rainfall that largely offset its higher photosynthetic potential. These data suggest that the capacity for woody plants to exploit water resources in riparian areas results in enhanced carbon sequestration at the expense of increased groundwater use under current climate conditions, but the potential does not scale specifically as a function of woody‐plant abundance. These results highlight the important roles of water sources and ecosystem structure on the control of water and carbon balances in dryland areas.     

Linking flux network measurements to continental scale simulations: ecosystem carbon dioxide exchange capacity under non-water-stressed conditions

This paper examines long‐term eddy covariance data from 18 European and 17 North American and Asian forest, wetland, tundra, grassland, and cropland sites under non‐water‐stressed conditions with an empirical rectangular hyperbolic light response model and a single layer two light‐class carboxylase‐based model. Relationships according to ecosystem functional type are demonstrated between empirical and physiological parameters, suggesting linkages between easily estimated parameters and those with greater potential for process interpretation. Relatively sparse documentation of leaf area index dynamics at flux tower sites is found to be a major difficulty in model inversion and flux interpretation. Therefore, a simplification of the physiological model is carried out for a subset of European network sites with extensive ancillary data. The results from these selected sites are used to derive a new parameter and means for comparing empirical and physiologically based methods across all sites, regardless of ancillary data. The results from the European analysis are then compared with results from the other Northern Hemisphere sites and similar relationships for the simplified process‐based parameter were found to hold for European, North American, and Asian temperate and boreal climate zones. This parameter is useful for bridging between flux network observations and continental scale spatial simulations of vegetation/atmosphere carbon dioxide exchange.     

基于生态系统服务视角的山水林田湖草生态保护与修复——以洞庭湖流域为例

山水林田湖草系统保护与修复的重要目标是维护和提升区域生态系统服务。基于山水林田湖草生命共同体理念,以维护和提升人类福祉所需的重要生态系统服务为目标,提出生态系统服务视角下的山水林田湖草系统治理框架,以实现流域生态系统整体保护、质量提升和格局优化。基于该框架,以洞庭湖流域为例,通过流域生态系统格局、生态系统质量状况分析、流域生态系统服务重要性评估和生态问题识别,构建流域生态安全格局,为实现可持续的山水林田湖草生命共同体提出系统保护与修复布局建议。通过洞庭湖流域的分析案例为流域山水林田湖草生态保护与修复重要区域的识别提供了可借鉴的指标和定量分析方法,为流域尺度构建生态安全格局、实现山水林田湖草系统保护和修复提供思路和途径。     

Biotic, Abiotic, and Management Controls on the Net Ecosystem CO2 Exchange of European Mountain Grassland Ecosystems

The net ecosystem carbon dioxide (CO₂) exchange (NEE) of nine European mountain grassland ecosystems was measured during 2002–2004 using the eddy covariance method. Overall, the availability of photosynthetically active radiation (PPFD) was the single most important abiotic influence factor for NEE. Its role changed markedly during the course of the season, PPFD being a better predictor for NEE during periods favorable for CO₂ uptake, which was spring and autumn for the sites characterized by summer droughts (southern sites) and (peak) summer for the Alpine and northern study sites. This general pattern was interrupted by grassland management practices, that is, mowing and grazing, when the variability in NEE explained by PPFD decreased in concert with the amount of aboveground biomass (BM_ag). Temperature was the abiotic influence factor that explained most of the variability in ecosystem respiration at the Alpine and northern study sites, but not at the southern sites characterized by a pronounced summer drought, where soil water availability and the amount of aboveground biomass were more or equally important. The amount of assimilating plant area was the single most important biotic variable determining the maximum ecosystem carbon uptake potential, that is, the NEE at saturating PPFD. Good correspondence, in terms of the magnitude of NEE, was observed with many (semi-) natural grasslands around the world, but not with grasslands sown on fertile soils in lowland locations, which exhibited higher maximum carbon gains at lower respiratory costs. It is concluded that, through triggering rapid changes in the amount and area of the aboveground plant matter, the timing and frequency of land management practices is crucial for the short-term sensitivity of the NEE of the investigated mountain grassland ecosystems to climatic drivers.     

Biophysical regulations of NEE light response in a steppe and a cropland in Inner Mongolia

Aims Ecosystem carbon models often require accurate net ecosystem exchange of CO₂ (NEE) light-response parameters, which can be derived from the Michaelis–Menten equation. These parameters include maximum net ecosystem exchange (NEE max), apparent quantum use efficiency (α) and daytime ecosystem respiration rate (R e). However, little is known about the effects of land conversion between steppe and cropland on these parameters, especially in semi-arid regions. To understand how these parameters vary in responses to biotic and abiotic factors under land conversions, seasonal variation of light-response parameters were evaluated for a steppe and a cropland of Inner Mongolia, China, during three consecutive years (2006–08) with different precipitation amounts.Methods NEE was measured over a steppe and a cropland in Duolun, Inner Mongolia, China, using the eddy covariance technique, and NEE light-response parameters (NEE max, α and R e) were derived using the Michaelis–Menten model. Biophysical regulations of these parameters were evaluated using a stepwise regression analysis.Important findings The maximum absolute values of NEE max occurred in the meteorological regimes of 15°C ≤ T a < 25°C, vapor pressure deficit (VPD) < 1 KPa and 0.21 m 3 m ? 3 ≤ volumetric soil water content at 10 cm (SWC) < 0.28 m 3 m ? 3 for both the steppe and the cropland ecosystems. The variations of α and R e showed no regular variation pattern in different T air, VPD and SWC regimes. Under the same regime of T air, VPD and SWC, the cropland had higher absolute values of NEE max than the steppe. Canopy conductance and leaf area index (LAI) were dominant drivers for variations in NEE light-response parameters of the steppe and the cropland. The seasonal variation of NEE light-response parameters followed the variation of LAI for two ecosystems. The peak values of all light-response parameters for the steppe and the cropland occurred from July to August. The values of NEE light-response parameters (NEE max, α and R e) were lower in the driest year (2007). Seasonally averaged NEE light-response parameters for the cropland surpassed those for the steppe. Land conversion from steppe to cropland enhanced NEE light-response parameters during the plant growing period. These results will have significant implications for improving the models on regional NEE variation under climate change and land-use change scenarios.     

2000—2010年我国重点生态功能区生态系统变化状况

分析了2000—2010年我国水源涵养型、水土保持型、防风固沙型、生物多样性维护型重点生态功能区的生态系统结构、质量与核心服务的变化.结果表明: 近11年来,水源涵养型重点生态功能区的森林、草地面积减少,水体与湿的面积增加,森林、草地、湿地生态系统水源涵养总量增加了2.9%,该类区域需要遏制森林、草地的减少趋势.水土保持型重点生态功能区的农田面积减少,而森林、草地、水体与湿地的面积增加,土壤侵蚀总量减少了28.2%,生态系统土壤保持总量增加了38.1%.防风固沙型重点生态功能区的农田、森林面积增加,草地、水体与湿地的面积减少,单位面积土壤风蚀量下降,单位面积防风固沙服务量有所提升,该类区域多位于干旱半干旱区,需要减少农田面积,优先保护原有生态系统.生物多样性维护型重点生态功能区的草地、荒漠面积减少,其他类型的面积有所增加,人类扰动呈现微弱的上升趋势,该类区域需要减少人类干扰.重点生态功能区应该针对核心服务和保护目标,分类分区开展生态系统保护、改善及其效果的定量综合评估.     

Maximum carbon uptake rate dominates the interannual variability of global net ecosystem exchange

Terrestrial ecosystems contribute most of the interannual variability (IAV) in atmospheric carbon dioxide (CO₂) concentrations, but processes driving the IAV of net ecosystem CO₂ exchange (NEE) remain elusive. For a predictive understanding of the global C cycle, it is imperative to identify indicators associated with ecological processes that determine the IAV of NEE. Here, we decompose the annual NEE of global terrestrial ecosystems into their phenological and physiological components, namely maximum carbon uptake (MCU) and release (MCR), the carbon uptake period (CUP), and two parameters, α and β, that describe the ratio between actual versus hypothetical maximum C sink and source, respectively. Using long‐term observed NEE from 66 eddy covariance sites and global products derived from FLUXNET observations, we found that the IAV of NEE is determined predominately by MCU at the global scale, which explains 48% of the IAV of NEE on average while α, CUP, β, and MCR explain 14%, 25%, 2%, and 8%, respectively. These patterns differ in water‐limited ecosystems versus temperature‐ and radiation‐limited ecosystems; 31% of the IAV of NEE is determined by the IAV of CUP in water‐limited ecosystems, and 60% of the IAV of NEE is determined by the IAV of MCU in temperature‐ and radiation‐limited ecosystems. The Lund‐Potsdam‐Jena (LPJ) model and the Multi‐scale Synthesis and Terrestrial Model Inter‐comparison Project (MsTMIP) models underestimate the contribution of MCU to the IAV of NEE by about 18% on average, and overestimate the contribution of CUP by about 25%. This study provides a new perspective on the proximate causes of the IAV of NEE, which suggest that capturing the variability of MCU is critical for modeling the IAV of NEE across most of the global land surface.     

基于生态系统评价的山水林田湖草生态保护与修复体系构建研究——以乌梁素海流域为例

山水林田湖草系统保护与修复工程实施的重要目标是维护和提升区域生态系统服务。从乌梁素海流域山水林田湖草的生态现状与功能出发,对乌梁素海流域水土流失、土地沙化等生态敏感性及土壤保持、水源涵养、生物多样性等生态功能重要性进行系统评价,形成基于生态敏感性和生态功能重要性相结合的空间格局评价结果。以维护和提升人类福祉所需的重要生态系统服务为目标,以乌梁素海流域生态敏感性和生态功能重要性相结合的空间格局评价结果为基础,制定了“一中心、二重点、六要素、七工程”的乌梁素海山水林田湖草生态保护与修复体系,并基于此将乌梁素海流域生态保护修复分为6个主要治理区域,形成“四区、一带、一网”的生态安全格局,通过具体工程实施,流域生态环境质量和生态服务能力将取得明显提升,防风固沙能力有效增强,生物多样性持续改善,水环境质量稳定达标,生态系统的稳定性明显加强。通过乌梁素海流域的分析案例为流域山水林田湖草生态保护与修复关键区域的识别提供了定量分析方法,为流域尺度构建生态安全格局、实现山水林田湖草系统保护和修复提供思路和途径。     

唐古拉山以北地区生态资产核算

生态系统核算可以为生态文明建设提供定量性的决策依据,包括生态资产核算和生态系统服务核算两个方面,生态资产指生产和提供生态系统产品和服务的生态系统。以唐古拉山以北地区(简称唐北地区)为研究对象对其生态资产进行了核算,建立生态资产实物量及变化核算表、损益表,提出了生态资产综合指数。2015年唐北地区草地生态资产面积为21800.01 km²,其中良级比重最高达68.46%,湿地生态资产面积为4763.01 km²,其中优级比例最高为59.72%,野生动植物共有138种,其中重点保护动物10种。2015年唐北地区生态资产综合指数为79.77,比2000年降低了3.60%。2000—2015年,湿地、草地生态资产分别增加了164.23、2.82 km²。2000—2015年湿地生态资产存量增加202.90 km²,其中由湿地恢复导致面积增加最大为200.50 km²,存量减少38.63 km²,其中湿地退化是导致存量减少的主要原因,面积为36.23 km^...     

Partitioning net carbon dioxide fluxes into photosynthesis and respiration using neural networks

The eddy covariance (EC) technique is used to measure the net ecosystem exchange (NEE) of CO₂ between ecosystems and the atmosphere, offering a unique opportunity to study ecosystem responses to climate change. NEE is the difference between the total CO₂ release due to all respiration processes (RECO), and the gross carbon uptake by photosynthesis (GPP). These two gross CO₂ fluxes are derived from EC measurements by applying partitioning methods that rely on physiologically based functional relationships with a limited number of environmental drivers. However, the partitioning methods applied in the global FLUXNET network of EC observations do not account for the multiple co‐acting factors that modulate GPP and RECO flux dynamics. To overcome this limitation, we developed a hybrid data‐driven approach based on combined neural networks (NN_C‐part). NN_C‐part incorporates process knowledge by introducing a photosynthetic response based on the light‐use efficiency (LUE) concept, and uses a comprehensive dataset of soil and micrometeorological variables as fluxes drivers. We applied the method to 36 sites from the FLUXNET2015 dataset and found a high consistency in the results with those derived from other standard partitioning methods for both GPP (R² > .94) and RECO (R² > .8). High consistency was also found for (a) the diurnal and seasonal patterns of fluxes and (b) the ecosystem functional responses. NN_C‐part performed more realistic than the traditional methods for predicting additional patterns of gross CO₂ fluxes, such as: (a) the GPP response to VPD, (b) direct effects of air temperature on GPP dynamics, (c) hysteresis in the diel cycle of gross CO₂ fluxes, (d) the sensitivity of LUE to the diffuse to direct radiation ratio, and (e) the post rain respiration pulse after a long dry period. In conclusion, NN_C‐part is a valid data‐driven approach to provide GPP and RECO estimates and complementary to the existing partitioning methods.     

Weekly carbon dioxide exchange trend predictions in deciduous broadleaf forests from site-specific influencing variables

Weekly net-ecosystem-exchange (NEE) data recorded and verified over multiple years, together with site-specific influential ecological variables, for distinct deciduous-broadleaf-forest (DBF) sites in North America can reveal useful relationships regarding their functions as long-term carbon dioxide (CO2) sources and sinks. Machine learning (ML) and regression models have greater success at predicting weekly NEE from some DBF sites than others, from the available site variables. In particular, support vector regression (SVR) and extreme gradient boosting (XGG) ML methods perform better than multi-linear regression in the weekly NEE predictions they generate using up to 24 influential variables. The DBF sites studied are distinguished into those that have followed distinctive, albeit fluctuating seasonal NEE trends, and those that are characterized by abrupt fluctuations in NEE across the leaf-on season. ML models predict weekly NEE for the former sites more reliably than for the latter sites. Consideration of the relative influence of the variables on the XGB and regression model NEE predictions identifies which variables are most influential at specific sites. Short wave radiation (in and out) and air temperature are found to be variables exerting substantial influence on the prediction models for the sites studied. From the prediction results and the relative influences of the available environmental variables, it is concluded that complex processes are involved at those sites showing rapid NEE fluctuations in the leaf-on seasons that are not readily detectable from the environmental variables currently being continuously recorded at those sites.     

Carbon uptake in Eurasian boreal forests dominates the high-latitude net ecosystem carbon budget

Arctic-boreal landscapes are experiencing profound warming, along with changes in ecosystem moisture status and disturbance from fire. This region is of global importance in terms of carbon feedbacks to climate, yet the sign (sink or source) and magnitude of the Arctic-boreal carbon budget within recent years remains highly uncertain. Here, we provide new estimates of recent (2003–2015) vegetation gross primary productivity (GPP), ecosystem respiration (R_eco), net ecosystem CO₂ exchange (NEE; R_eco − GPP), and terrestrial methane (CH₄) emissions for the Arctic-boreal zone using a satellite data-driven process-model for northern ecosystems (TCFM-Arctic), calibrated and evaluated using measurements from >60 tower eddy covariance (EC) sites. We used TCFM-Arctic to obtain daily 1-km² flux estimates and annual carbon budgets for the pan-Arctic-boreal region. Across the domain, the model indicated an overall average NEE sink of −850 Tg CO₂-C year⁻¹. Eurasian boreal zones, especially those in Siberia, contributed to a majority of the net sink. In contrast, the tundra biome was relatively carbon neutral (ranging from small sink to source). Regional CH₄ emissions from tundra and boreal wetlands (not accounting for aquatic CH₄) were estimated at 35 Tg CH₄-C year⁻¹. Accounting for additional emissions from open water aquatic bodies and from fire, using available estimates from the literature, reduced the total regional NEE sink by 21% and shifted many far northern tundra landscapes, and some boreal forests, to a net carbon source. This assessment, based on in situ observations and models, improves our understanding of the high-latitude carbon status and also indicates a continued need for integrated site-to-regional assessments to monitor the vulnerability of these ecosystems to climate change.     

Six-year Stable Annual Uptake of Carbon Dioxide in Intensively Managed Humid Temperate Grassland

Variability and future alterations in regional and global climate patterns may exert a strong control on the carbon dioxide (CO₂) exchange of grassland ecosystems. We used 6 years of eddy-covariance measurements to evaluate the impacts of seasonal and inter-annual variations in environmental conditions on the net ecosystem CO₂ exchange (NEE), gross ecosystem production (GEP), and ecosystem respiration (ER) of an intensively managed grassland in the humid temperate climate of southern Ireland. In all the years of the study period, considerable uptake of atmospheric CO₂ occurred in this grassland with a narrow range in the annual NEE from −245 to −284 g C m⁻² y⁻¹, with the exception of 2008 in which the NEE reached −352 g C m⁻² y⁻¹. None of the measured environmental variables (air temperature (Ta), soil moisture, photosynthetically active radiation, vapor pressure deficit (VPD), precipitation (PPT), and so on) correlated with NEE on a seasonal or annual scale because of the equal responses from the component fluxes GEP and ER to variances in these variables. Pronounced reduction of summer PPT in two out of the six studied years correlated with decreases in both GEP and ER, but not with NEE. Thus, the stable annual NEE was primarily achieved through a strong coupling of ER and GEP on seasonal and annual scales. Limited inter-annual variations in Ta (±0.5°C) and generally sufficient soil moisture availability may have further favored a stable annual NEE. Monthly ecosystem carbon use efficiency (CUE; as the ratio of NEE:GEP) during the main growing season (April 1–September 30) was negatively correlated with temperature and VPD, but positively correlated with soil moisture, whereas the annual CUE correlated negatively with annual NEE. Thus, although drier and warmer summers may mildly reduce the uptake potential, the annual uptake of atmospheric CO₂, in this intensively managed grassland, may be expected to continue even under predicted future climatic changes in the humid temperate climate region.     

粤港澳大湾区生态系统格局变化与模拟

快速城市化是导致粤港澳大湾区生态系统时空格局变化的主要驱动力之一,模拟生态系统变化趋势对于优化区域土地利用格局、防控城市化的生态风险具有重要意义。以2000、2005、2010、2015、2018年5期土地利用数据,分析该区域生态系统格局演变,并运用CA-Markov模型模拟2025年的生态系统格局。研究结果表明:(1)2018年大湾区的森林、农田和城镇为主要生态系统类型,分别占区域总面积的53.99%、22.67%和14.51%。(2)2000—2018年农田、森林、湿地面积分别下降了1983、740、278 km²,城镇和草地面积分别上升了2896、103 km²,城镇面积增长的主要途径是对周围农田、林地和湿地的侵占,草地面积增长是因为管理经营不善导致部分林地退化为草地。(3)大湾区的景观多样性和均匀度下降,景观正在向小斑块趋势发展,空间连通性下降,破碎度增加。(4)模拟2025年的生态系统格局发现,与2018年相比,城镇面积增长了609 km²,农田和森林分别减少了309 km²和316 km...