青海湖高寒湿地生态系统夏季CO_2通量日变化及其影响因子研究

利用涡度相关技术对青海湖高寒湿地生态系统夏季CO2通量日变化特征进行分析,并且结合气象观测数据对CO2通量日变化的影响因子进行探讨。结果表明,青海湖高寒湿地生态系统夏季CO2通量日变化呈"U"字型,8:00—20:00 CO2通量值为负,其他时间为正,最低值出现在12:30,为-15.34μmol·m-2·s-1。CO2通量日平均值为-3.65μmol·m-2·s-1(约-13.87 g·m-2·d-1),表现为明显的CO2吸收,是重要的碳汇。CO2通量与净辐射、气温和表层土壤温度的相关性分析表明,净辐射是影响青海湖高寒湿地生态系统夏季CO2通量日变化的主要因子,气温次之,表层土壤温度对CO2通量的影响最小。采用多元回归分析得出CO2通量与各个影响因子之间的关系符合三元一次线性回归方程,R2=0.689,且达到极显著水平(P0.01)。     

短花针茅荒漠草原生态系统净碳交换对载畜率的响应

草地生态系统作为中国最大的陆地生态系统,其碳循环的动态变化在全球碳收支平衡中扮演着重要角色。为探讨短花针茅(Stipa breviflora)荒漠草原净CO_2交换的日变化和季节变化特征,阐明放牧及土壤温度和湿度的季节性变化对生态系统净CO_2交换的影响,采用便携式光合仪LI-6400(LI-COR,USA)和密闭式箱法于2013—2014年生长季(5—10月)测定了对照(CK)、轻牧(LG)、中牧(MG)和重度放牧(HG)4个处理的生态系统净碳交换。结果表明:短花针茅荒漠草原净CO_2交换具有明显的日变化规律。净碳交换的日动态主要受气温影响,昼间净碳吸收随温度升高而降低,甚至出现碳释放;夜间随气温降低,生态系统呼吸减弱。整个生长季,短花针茅荒漠草原表现为碳汇,在植物生长季的高峰期,净碳吸收达到峰值(-2.96mol·m~(-2)·s~(-1))。年际间生态系统净碳交换差异显著(P0.000 1),净碳交换主要受降水调控。净碳吸收与土壤温度在两年间均呈显著的二次多项式关系(P0.01),而与土壤湿度的关系则是2013年为显著的线性关系(P0.000 1),2014年为显著的二次多项式关系(P0.01)。土壤温度对生态系统净CO_2交换变化的解释能力为0.31~0.36,而土壤湿度对生态系统净CO_2交换变化的解释能力为0.26~0.51。HG区净碳吸收速率(-0.66mol·m~(-2)·s~(-1))显著低于CK区(-1.65mol·m~(-2)·s~(-1))。放牧减弱了荒漠草原的固碳潜力。     

青海湖高寒湿地生态系统夏季CO2通量日变化及其影响因子研究

利用涡度相关技术对青海湖高寒湿地生态系统夏季CO２通量日变化特征进行分析,并且结合气象观测数据对CO２通量日变化的影响因子进行探讨。结果表明,青海湖高寒湿地生态系统夏季CO２通量日变化呈“U”字型,白天8：00—20：00 CO２通量值为负,其他时间为正,最低值出现在12：30,为-15.34 μmol·m-2·s-1。CO２通量日平均值为-3.65 μmol·m-2·s-1（约-13.87 g·m-2·d-1）,表现为明显的CO２吸收,是重要的碳汇。CO２通量与净辐射、气温和表层土壤温度的相关性分析表明,净辐射是影响青海湖高寒湿地生态系统夏季CO２通量日变化的主要因子,气温次之,表层土壤温度对CO２通量的影响最小。采用多元回归分析得出CO２通量与各个影响因子之间的关系符合三元一次线性回归方程,R2=0.689,且达到极显著水平（P〈0.01）。     

青海湖高寒藏嵩草湿草甸湿地生态系统CO_2通量变化特征

基于涡度相关系统对青海湖藏嵩草湿草甸湿地生态系统CO_2通量变化特征及其影响因子进行研究。结果表明,青海湖藏嵩草湿草甸湿地生态系统CO_2通量具有明显的日变化和月变化特征。生长季表现为CO_2的净吸收,其吸收峰值出现在12:30—15:00之间,最大值为0.42 mg·m~(-2)·s~(-1),排放峰值出现在20:00—22:30之间,最大值为0.24 mg·m~(-2)·s~(-1)。非生长季日变化较小,总体表现为CO_2的净排放,除了11月,其他月份白天CO_2排放通量都明显大于夜间。2015年青海湖高寒藏嵩草湿草甸湿地生态系统全年净生态系统CO_2交换量为54.55 g·m~(-2),表现为碳源。路径分析表明,土壤温度、光合有效辐射和饱和水汽压差是影响CO_2通量日交换大小的主要控制因子。     

基于DNDC模型评估水位变化对滨海湿地净生态系统CO2交换的影响

水位是影响滨海湿地生态系统蓝碳功能的重要因素。气候变化引起的海平面上升以及极端气候事件的频发,可能加快水位的变化,从而改变生态系统碳交换的过程。然而,滨海湿地碳汇功能响应水位变化的机制尚不清楚。为了评估水位对滨海湿地净生态系统CO₂交换(NEE)特征的影响,以及验证DNDC(denitrification-decomposition)模型对模拟预测滨海湿地生态系统碳交换的适用性,该研究设计了野外水位控制试验(自然水位,地下20 cm水位、地表10 cm水位),并利用DNDC模型模拟和预测水位变化对滨海湿地NEE的影响。结果表明:(1)不同水位处理之间NEE差异显著,地表10 cm水位处理促进CO₂吸收,地下20 cm水位则抑制CO₂吸收;(2)经过校准和验证的DNDC模型可以准确模拟水位变化对黄河三角洲湿地NEE的影响,NEE模拟值的日动态与田间观测结果显著相关(R²>0.6);(3)通过改变气候、土壤和田间管理等输入参数对DNDC模型进行灵敏度检验,生态系统碳交换过程对日均温、降雨和水位改变的响应最为显著,其中,水位对NEE的影响主要作用于土壤呼吸(Rs)。未来气候情境下,不同水位变化下的生态系统碳交换过程随年份增长呈现不同的规律,因此未来的模拟研究应关注DNDC中水文模块和植被演替过程的完善。该研究可为预测水文变化情境下滨海湿地碳汇功能的未来发展以及政策制定提供参考。     

湿地生态系统CO2净交换、水汽通量及二者关系浅析

湿地生态系统碳循环是陆地碳循环研究中的重要组成部分,对于全球变化具有重要意义。水汽通量是影响湿地生态系统碳循环最重要、最基本的生态因子之一,与湿地生态系统CO2净交换密切相关。本文在总结湿地生态系统CO2净交换与水汽通量变化基本规律及其主要影响因子的基础上,从宏观和微观2个方面分析二者之间的内在关系。从宏观上看,湿地生态系统本身的特点决定了CO2净交换与水汽通量之间必然是相互影响、相互制约的;就微观而言,叶片尺度上的气孔行为是水分蒸腾和净碳通量这两个生理生态过程相互联系的纽带。最后,对湿地生态系统CO2净交换与水汽通量关系的研究方向提出展望。     

黄河三角洲芦苇湿地生态系统碳通量动态特征及其影响因素

利用涡度相关法,对黄河三角洲芦苇湿地生态系统进行了连续2年的通量观测,分析了2017—2018年生长季芦苇湿地生态系统碳交换量(NEE)及其影响因素,为区域的碳收支预算和为全球碳循环模型的进一步完善提供理论基础。结果表明,在季节尺度上,芦苇湿地生长季具有明显的碳汇功能,生态系统呼吸(Rs)随着月份的增加呈倒"V"型变化特征,在8月达到最高;生态系统碳交换(NEE)和生态系统总初级生产力(GPP)随着月份的增加呈"V"型变化特征。2018年不同月份生态系统碳交换(NEE)、生态系统总初级生产力(GPP)、生态系统呼吸(Rs)均高于2017年,局部有所差异,其变化趋势与2017年总体保持一致。在日尺度上,2017—2018年芦苇湿地NEE日变化特征表现为两个CO_2吸收高峰,分别出现在11:00和16:00左右,其特点是在午间出现了碳交换通量的降低,CO_2排放的日最大值两个生长季均出现在8月。2017—2018年NEE_(night)随着月份的增加呈倒"V"型变化特征,在8月达到最高;而NEE_(total)和NEE_(day)随着月份的增加呈"V"型变化特征,在8月达到最高,局部有所差异。芦苇湿地生态系统的CO_2交换受到光合有效辐射(PAR)、土壤温度(t_s)和土壤体积含水量(T_a)的共同影响,生长季NEE通量与5 cm土壤温度和土壤湿度呈显著或极显著的指数关系(P0.05,P0.01),同时生长季NEE通量与5 cm土壤温度和土壤湿度的R2均高于NEE通量与10 cm土壤温度和土壤湿度的R~2,由此说明5 cm土壤温度和湿度能够更好的指示NEE通量的变化。     

若尔盖高寒草地沙化过程碳通量的变化特征北大核心CSCD

为了解若尔盖高原高寒草地沙化过程生态系统中CO2的收支变化,利用Li-840静态箱法于2013年生长季(5-10月),在一处典型沙化区域,分别调查未沙化(UN)、中度沙化(MO)和重度沙化(SE)草地的生态系统净通量(NEE)、生态系统呼吸(ER)和土壤呼吸(SR)的季节和日动态变化.结果显示:若尔盖高寒草地未沙化草地和中度沙化草地NEE季节变化呈单峰状,中度沙化草地波动性增强,而重度沙化草地在整个生长季节变化不明显.未沙化草地在生长季节日间瞬时NEE为-3.33μmol m-2 s-1,中度沙化草地为-2.06μmol m-2 s-1,是未沙化草地的61.86%,严重沙化草地为-0.62μmol m-2 s-1,是未沙化草地的18.61%.在沙化过程中,土壤所贡献给生态系统整体的呼吸占比,从72.90%增加到79.28%,季节变化动态呈现出与系统呼吸相似的变化规律.未沙化草地在生长季节的初期和中期均呈现出较强的碳汇特性,固碳速率分别为9.05 g m-2 d-1和28.70 g m-2 d-1,而在末期呈现出微弱碳源.本研究表明,沙化使得高寒草地在生长季节由微弱的碳汇转变成为碳源,固碳能力严重削弱.     

鄱阳湖南矶湿地净生态系统CO_2交换量的日变化特征

利用涡度相关技术分未淹水期和淹水期对2015年4月—2016年10月鄱阳湖南矶湿地净生态系统CO_2交换量(net ecosystem CO_2exchange,NEE)进行观测,分析其日变化特征和影响因子。结果表明:在未淹水期,湿地NEE日变化呈现"U"型分布特征,日间最大CO_2吸收量为18.24μmol·m~(-2)·s~(-1),夜间最大CO_2释放量为24.92μmol·m~(-2)·s~(-1)。在淹水期,除较高洲滩及湖岸高地外,植被被水面覆盖,湿地NEE日变化无明显特征,日间最大CO_2吸收量为2.29μmol·m~(-2)·s~(-1),夜间最大CO_2释放量为12.66μmol·m~(-2)·s~(-1)。相关分析和主成分分析表明在未淹水期南矶湿地日间NEE月平均日变化与光量子通量密度相关性最高,与气温、降水、土壤含水量和土壤温度的相关性次之,夜间NEE月平均日变化与气温、土壤温度和土壤含水量相关性较高。在淹水期,南矶湿地日间NEE月平均日变化与光量子通量密度、土壤含水量有关,夜间变化与土壤温度、土壤含水量和气温有关。     

广西红树林净生态系统碳交换变化特征及影响因子研究

为了研究广西红树林CO_2通量变化特征及其调控机制,利用2019年北海红树林生态观测试验站涡度相关系统观测的红树林碳通量和气象观测数据,分析红树林净生态系统碳交换变化特征及其与气象因子的响应关系。结果表明,广西红树林净生态系统碳交换的平均日变化曲线呈"U"型分布;在月尺度上,碳汇峰值出现在2月,最小值出现在6月;在季尺度上,不同季节碳汇峰值呈秋季春季冬季夏季的趋势;净生态系统碳交换月累积最大值为11月(-45.23 g·m~(-2)·月~(-1)),最小值为7月(-16.95 g·m~(-2)·月~(-1));广西红树林净生态系统碳交换、总呼吸和总初级生产力年累积量分别为-386.68、862.49和-1 249.18 g·m~(-2)·a~(-1),3者均低于福建和广东红树林;光合有效辐射是对净生态系统碳交换产生直接影响的主导因子,饱和水气压差是对净生态系统碳交换产生间接影响的主导因子,降水量是净生态系统碳交换的限制因子。     

Modelling the forest carbon budget of a Mediterranean region through the integration of ground and satellite data

This paper introduces an innovative modelling strategy aimed at simulating the main terms of net forest carbon budget (net primary production, NPP and net ecosystem exchange, NEE) in Tuscany (Central Italy). The strategy is based on the preliminary calibration and application of parametric and bio-geochemical models (C-Fix and BIOME-BGC, respectively), which simulate the behaviour of forest ecosystems close to equilibrium condition (climax). Next, the ratio of actual over-potential tree volume is computed as an indicator of ecosystem distance from climax and is combined with the model outputs to estimate the NPP and NEE of real forests. The per-pixel application of the new modelling strategy was made possible by the collection of several data layers (maps of forest type and volume, daily meteorological data and monthly normalized difference vegetation index (NDVI) images for the years 1999–2003) which served to characterize the eco-climatic and forest features of the region. The obtained estimates of forest NPP and NEE were evaluated against ground measurements of accumulated woody biomass and net carbon exchange. The results of these experiments testify the good potential of the proposed strategy and indicate some problem areas which should be the subject of future research.     

Multiple sources of predictive uncertainty in modeled estimates of net ecosystem CO2 exchange

Net ecosystem CO₂ exchange (NEE) is typically measured directly by eddy covariance towers or is estimated by ecosystem process models, yet comparisons between the data obtained by these two methods can show poor correspondence. There are three potential explanations for this discrepancy. First, estimates of NEE as measured by the eddy-covariance technique are laden with uncertainty and can potentially provide a poor baseline for models to be tested against. Second, there could be fundamental problems in model structure that prevent an accurate simulation of NEE. Third, ecosystem process models are dependent on ecophysiological parameter sets derived from field measurements in which a single parameter for a given species can vary considerably. The latter problem suggests that with such broad variation among multiple inputs, any ecosystem modeling scheme must account for the possibility that many combinations of apparently feasible parameter values might not allow the model to emulate the observed NEE dynamics of a terrestrial ecosystem, as well as the possibility that there may be many parameter sets within a particular model structure that can successfully reproduce the observed data. We examined the extent to which these three issues influence estimates of NEE in a widely used ecosystem process model, Biome-BGC, by adapting the generalized likelihood uncertainty estimation (GLUE) methodology. This procedure involved 400,000 model runs, each with randomly generated parameter values from a uniform distribution based on published parameter ranges, resulting in estimates of NEE that were compared to daily NEE data from young and mature Ponderosa pine stands at Metolius, Oregon. Of the 400,000 simulations run with different parameter sets for each age class (800,000 total), over 99% of the simulations underestimated the magnitude of net ecosystem CO₂ exchange, with only 4.07% and 0.045% of all simulations providing satisfactory simulations of the field data for the young and mature stands, even when uncertainties in eddy-covariance measurements are accounted for. Results indicate fundamental shortcomings in the ability of this model to produce realistic carbon flux data over the course of forest development, and we suspect that much of the mismatch derives from an inability to realistically model ecosystem respiration. However, difficulties in estimating historic climate data are also a cause for model-data mismatch, particularly in a highly ecotonal region such as central Oregon. This latter difficulty may be less prevalent in other ecosystems, but it nonetheless highlights a challenge in trying to develop a dynamic representation of the terrestrial biosphere.     

Light-stress avoidance mechanisms in a Sphagnum-dominated wet coastal Arctic tundra ecosystem in Alaska

The Arctic experiences a high-radiation environment in the summer with 24-hour daylight for more than two months. Damage to plants and ecosystem metabolism can be muted by overcast conditions common in much of the Arctic. However, with climate change, extreme dry years and clearer skies could lead to the risk of increased photoxidation and photoinhibition in Arctic primary producers. Mosses, which often exceed the NPP of vascular plants in Arctic areas, are often understudied. As a result, the effect of specific environmental factors, including light, on these growth forms is poorly understood. Here, we investigated net ecosystem exchange (NEE) at the ecosystem scale, net Sphagnum CO2 exchange (NSE), and photoinhibition to better understand the impact of light on carbon exchange from a moss-dominated coastal tundra ecosystem during the summer season 2006. Sphagnum photosynthesis showed photoinhibition early in the season coupled with low ecosystem NEE. However, later in the season, Sphagnum maintained a significant CO2 uptake, probably for the development of subsurface moss layers protected from strong radiation. We suggest that the compact canopy structure of Sphagnum reduces light penetration to the subsurface layers of the moss mat and thereby protects the active photosynthetic tissues from damage. This stress avoidance mechanism allowed Sphagnum to constitute a significant percentage (up to 60%) of the ecosystem net daytime CO2 uptake at the end of the growing season despite the high levels of radiation experienced.     

北京城近郊区园林绿地多目标规划

北京市城近郊区人口密集,经济活动频繁,作为改善城市空气质量的重要环境资源之一,园林绿地提供了不可或缺的生态服务功能。针对研究区降尘大、SO_2浓度高以及生产生活耗氧量大等主要环境问题,以满足城市居民环境质量基本要求为目标,通过一系列决策变量与约束条件的设定,建立起北京城近郊区园林绿地多目标线性规划模型。应用Lingo 8．0软件对规划模型求解,结果表明,规划期(2020年)不同种类园林绿地面积分配较基期(2000年)更为合理,强调通过乔灌草相结合提高园林绿地整体生态服务功能,为北京建设生态城市提供了规划依据。     

水、氮控制对短花针茅草原气体交换的影响

随着对气候变化日趋关注,人们对生态系统气体交换及其主要影响因素进行了大量研究。短花针茅草原作为荒漠草原的典型代表,是亚洲特有的一种草原类型,是最干旱的草原类型,生态环境异常严酷,系统极度脆弱,稳定性差,在自然和人为干扰下极易退化。以短花针茅（Stipa breviflora）草原为研究对象,通过控制降雨量以及氮素添加对生态系统气体交换进行监测,研究气体交换对降雨量和氮素添加的响应过程,揭示降雨量和氮素添加对生态系统气体交换的影响作用。该文在2012年自然条件下,采用自动CO2通量系统（Li-6400, Li-COR, Lincoln, NE, USA）野外测定短花针茅（Stipa breviflora）草原生态系统气体交换数据,比较研究了增雨施肥（WN）、增雨不施肥（W）、减雨施肥（RN）、减雨不施肥（R）、单独施肥（N）、自然状况（CK）条件下2012年气体交换变化规律。结果表明：整个生长季生态系统净 CO2交换（NEE）、总的生态系统生产力（GEP）、生态系统呼吸值（ER）都呈先升高后降低的趋势,并在生长旺盛期（8月）达到最大值。NEE在N、W处理下有升高,其他处理都降低。ER在N、WN处理下都有升高,其他处理都降低。GEP在W、N、WN处理下都有升高,其他处理都降低。NEE、ER、GEP都是在N处理中达到最大值。     

Modeling patterns of nonlinearity in ecosystem responses to temperature, CO2, and precipitation changes.

It is commonly acknowledged that ecosystem responses to global climate change are nonlinear. However, patterns of the nonlinearity have not been well characterized on ecosystem carbon and water processes. We used a terrestrial ecosystem (TECO) model to examine nonlinear patterns of ecosystem responses to changes in temperature, CO2, and precipitation individually or in combination. The TECO model was calibrated against experimental data obtained from a grassland ecosystem in the central United States and ran for 100 years with gradual change at 252 different scenarios. We primarily used the 100th-year results to explore nonlinearity of ecosystem responses. Variables examined in this study are net primary production (NPP), heterotrophic respiration (R(h)), net ecosystem carbon exchange (NEE), runoff, and evapotranspiration (ET). Our modeling results show that nonlinear patterns were parabolic, asymptotic, and threshold-like in response to temperature, CO2, and precipitation anomalies, respectively, for NPP, NEE, and R(h). Runoff and ET exhibited threshold-like pattern in response to both temperature and precipitation anomalies but were less sensitive to CO2 changes. Ecosystem responses to combined temperature, CO2, and precipitation anomalies differed considerably from the responses to individual factors in terms of response patterns and/or critical points of nonlinearity. Our results suggest that nonlinear patterns in response to multiple global-change factors were diverse and were considerably affected by combined climate anomalies on ecosystem carbon and water processes. The diverse response patterns in nonlinearity have profound implications for both experimental design and theoretical development.     

Sensitivity of mesquite shrubland CO2 exchange to precipitation in contrasting landscape settings

In semiarid ecosystems, physiography (landscape setting) may interact with woody-plant and soil microbe communities to constrain seasonal exchanges of material and energy at the ecosystem scale. In an upland and riparian shrubland, we examined the seasonally dynamic linkage between ecosystem CO2 exchange, woody-plant water status and photosynthesis, and soil respiration responses to summer rainfall. At each site, we compared tower-based measurements of net ecosystem CO2 exchange (NEE) with ecophysiological measurements among velvet mesquite (Prosopis velutina Woot.) in three size classes and soil respiration in sub-canopy and inter-canopy micro-sites. Monsoonal rainfall influenced a greater shift in the magnitude of ecosystem CO2 assimilation in the upland shrubland than in the riparian shrubland. Mesquite water status and photosynthetic gas exchange were closely linked to the onset of the North American monsoon in the upland shrubland. In contrast, the presence of shallow alluvial groundwater in the riparian shrubland caused larger size classes of mesquite to be physiologically insensitive to monsoonal rains. In both shrublands, soil respiration was greatest beneath mesquite canopies and was coupled to shallow soil moisture abundance. Physiography, through its constraint on the physiological sensitivity of deeply rooted woody plants, may interact with plant-mediated rates of soil respiration to affect the sensitivity of semiarid-ecosystem carbon exchange in response to episodic rainfall.     

城市屋面绿化生态热效应

文章在享有“火炉”这称的山城重庆夏末季节对草坪层面与水泥屋面的热特性进行了对比实测分析，研究结果表明草坪屋面具有显著的生态热效应。     

基于属性理论的长株潭城市群生态系统健康评价

城市生态系统是一种高度人工化的自然-社会-经济复合生态系统,其健康状况直接影响到城市的可持续发展。针对城市生态系统健康评价标准的不确定性问题,在构建评价指标体系的基础上,提出了基于属性理论的城市生态系统健康评价模型及评价方法。以长株潭城市群为研究区域,运用该模型和方法对其生态系统健康进行了综合评价。评价结果表明：长株潭城市群的生态系统现状属于一般健康类,其中自然生态子系统对区域整体健康状况有较大影响,评价结果与实际情况大体吻合。通过对各子系统层的健康度分析,识别了健康限制因素,并提出了相应的调控措施。采用属性理论方法开展城市生态系统健康评价,能较好地识别系统层综合健康状况和子系统层的健康状况,具有一定的实用价值,其评价结果为促进城市生态建设,有效实施生态系统健康管理提供了科学依据。