甘南地区二氧化碳施肥效应对生态系统的影响

陆地生态系统是全球第二大碳库,其碳收支一直是气候变化研究的热点领域,而研究二氧化碳（CO₂）施肥效应又是全球变化碳循环领域较为关注的前沿部分。CO₂与生态系统关系复杂,当前仍无法厘清CO₂对陆地生态系统碳循环的影响作用。基于太阳辐射数据、气温数据及归一化植被指数数据等,利用光能利用率遥感模型,模拟2019年甘南地区的碳循环,选取三个指标,即GPP （陆地生态系统总初级生产力）、NPP （净初级生产力）和NEP （净生态系统生产力）来分析甘南地区植被固碳的时空变化特征及CO₂施肥效应。结果表明：（1）甘南地区2019年植被固碳总量约为2611 tC。甘南地区生态系统GPP、NPP和NEP季节性特征明显,其值均在夏季达到最高;而在空间上,GPP、NPP表现为东高西低的特征,NEP呈现出北高南低的分布特征。（2） CO₂对GPP、NPP存在正向的施肥效应,分别增加了14.4%和14.3%;而对NEP具有负向反馈效应,使其减少了0.3%,并且CO₂对NEP的影响整体也表现为北高南低的特征。研究揭示出：虽然CO₂在提升GPP和NPP时,正向的施肥效应明显,但是对甘南地区的NEP,即固碳量来说,CO₂的影响却很有限。因此在研究CO₂施肥效应时不应一概而论,生态地理环境对其的影响不可忽视。研究可以为揭示陆地生态系统碳循环的动态机制提供一定的理论依据。     

中国亚热带-暖温带过渡区锐齿栎林净生态系统碳交换特征

在2017年1月1日-2017年12月31日期间,采用涡度相关法对位于亚热带-暖温带气候过渡区的河南宝天曼国家级自然保护区的65年生锐齿栎（Quercus aliena）天然次生林的碳通量进行了连续观测。结果表明：在观测期间,该森林生态系统在生长季5-10月份为碳汇,非生长季各月为碳源,净碳吸收量与释放量分别在7月和4月达到最大。净生态系统生产力为569.4 g C m^-2a^-1,生态系统呼吸为529.9 g C m^-2a^-1,总生态系统生产力为1099.3 g C m^-2a^-1。30min尺度上夜间净生态系统碳交换量与5cm深度土壤温度的关系可用指数方程表示（R²=0.21,P < 0.001）,其温度敏感性系数（Temperature sensitivity coefficient,Q₁₀）为2.2。如果排除夜间通量观测的误差,处在海拔较高地区的夜间低温和非生长季的低温抑制了生态系统呼吸排放,可能导致全年生态系统呼吸量较低。在生长季5-10月份,各月的白天净生态系统碳交换量对光合有效辐射的响应符合直角双曲线模型,初始光能利用效率、平均最大光合速率和白天平均生态系统呼吸强度呈明显的季节变化,范围分别是0.06-0.12 μmol CO₂ μmol^-1 photon、0.44-1.47 mg CO₂ m^-2s^-1和0.07-0.19 mg CO₂ m^-2s^-1。夏季7、8月份,较高的饱和水汽压差对白天锐齿栎林的碳吸收有明显的抑制作用;生长季末期9月份较高的土壤含水量对白天锐齿栎林的碳吸收也产生了抑制作用,表明生长末期降水过多影响森林的碳吸收。     

植被类型变化对土壤微生物碳利用效率的影响研究进展

植被类型变化强烈影响着土壤碳循环。土壤微生物碳利用效率（CUE）是微生物将从环境中获取的碳分配给自身生长的比例,是土壤碳循环的综合指标。研究植被类型变化对CUE的影响有助于从微生物视角理解该过程中的土壤碳动态,可以为评估植被类型变化对土壤质量及生态系统碳循环的影响提供基础,具有重要的理论及实际价值。通过系统查阅相关文献,综述了植被类型变化导致的CUE变化情况,以及该过程中影响CUE的因子与机制。目前,相关研究主要涉及以林地、草地和农业用地为起点或终点的植被变化类型。天然林（原生林、次生林）变化为人工林、林地变化为草地后CUE普遍下降,随终点植被的发展CUE可能恢复至起点水平。植被成熟度越高,发生转变时CUE变化越剧烈。植被类型变化以农业用地为起点或终点时,CUE变化方向的不确定性及幅度的变异性均增加。植被类型变化导致的CUE变化主要受到植被、土壤、微生物因子及其交互作用的驱动,指示CUE的指标、采样季节和土层也会一定程度上影响CUE的变化。今后相关研究应采用直接的CUE测定方法,拓宽研究气候区及植被变化类型,关注植被变化过程中CUE变化的土层差异及动态监测,深入对植被类型变化导致的生态环境因子变化与CUE的关系及作用机制的研究。     

毛乌素沙地油蒿叶性状对光能利用效率动态的影响

目前对于荒漠灌木光能利用效率（LUE）的季节变异及其调控因素,尤其是其生物调控因素的认识非常有限,导致了荒漠生态系统生产力模型的不确定性。拟验证假设：长期干旱环境下,典型荒漠灌木油蒿光能利用效率日均值（LUE_day）的动态变化与叶片性状的季节性调整有关。试验采用Li-6400便携式光合仪定期测量了油蒿生长季叶片LUE_day的季节动态及相关叶性状指标,探究叶性状对LUE_day的影响。结果表明：LUE_day的季节波动范围为0.003-0.017 mol/mol,整体变异系数（CV）为38.75%。完全展叶期LUE_day均值相比生长季平均值降低17.37%,相比展叶期和落叶期时降低30%;8个叶性状的季节变异幅度差异较大,其中总叶绿素含量（Chl）、类胡萝卜素含量（Car）和叶氮含量（LNC）均表现出较大的季节变异性（CV ≥ 20%）,叶碳含量（LCC）和叶片相对含水量（LRWC）的变异程度最低（CV<7%）。LRWC与所有叶片化学性状（Chl、Chl a/b、Car、LNC和LCC）均存在显著相关,表明其变化与叶片的养分吸收、光合色素合成以及碳同化的运输过程密切相关;油蒿LUE_day的相对变化与LRWC、Chl a/b和LNC显著正相关,而LRWC和LNC的季节动态受空气温度（T_a）和土壤含水量（VWC）的共同调节,Chl a/b的季节波动主要由浅层土壤含水量（10 cm VWC）控制。以上研究结果强调,在未来预计极端的气候事件（如极端干旱和持续热浪事件）发生更频繁的旱地场景中,时间尺度植物叶性状对于土壤干旱和高温的适应性调整应当被充分考虑到旱地生态系统的通量建模方案中。该结果将为构建叶片尺度的光合生理模型与厘清LUE的生物调控机制提供理论依据。     

潮汐作用对黄河三角洲盐沼湿地甲烷排放的影响

盐沼湿地作为陆海交互作用的过渡带是CH₄重要的自然来源。潮汐活动通过影响CH₄的产生、氧化和传输驱动了湿地CH₄间歇性、周期性的排放。利用涡度相关和微气象监测技术,对黄河三角洲一个盐地碱蓬生态系统CH₄通量、环境因子和水文要素（潮汐）进行了长期连续监测分析了该生态系统生长季CH₄排放的季节动态及潮汐作用对CH₄排放的影响。结果表明：生长季该生态系统是CH₄的排放源,排放日均值为0.063 mg m^-2 h^-1,（范围为-0.36-0.57 mg m^-2 h^-1）。潮汐淹水阶段和落潮后湿润阶段表现为CH₄的显著源。此外我们发现,短期潮汐活动引起土壤干湿状况的变化促进了CH₄脉冲式的排放,因此未来气候变化下温度升高和降雨季节分配引起的土壤干湿变化将会对该区域CH₄排放甚至碳循环产生积极影响。     

森林碳利用效率研究进展北大核心CSCD

植物碳利用效率(CUE)指净初级生产力与总初级生产力的比率,它不仅反映了植被生态系统将大气中CO2转化为生物量的能力和固碳潜力,而且可确定呼吸对植被生产力的影响。CUE是比较不同生态系统碳循环差异的重要参数,了解生态系统CUE有助于分析陆地生态系统是碳源还是碳汇,对于预测全球变化和人类干扰对森林碳收支的影响具有重要意义。我国在森林CUE研究方面还十分欠缺。该文在介绍森林CUE计算方法和测定技术的基础上,综述了植被、气象、森林经营等因子对森林CUE的影响,得出主要结论:(1)关于不同森林植被类型CUE变化有两种截然相反的观点,即:恒定CUE和变量CUE。越来越多的研究支持第二种观点,不同生态系统、不同森林类型、不同物种和植物发育阶段的CUE存在较大差异,森林CUE较灌丛和草地低,落叶林比混交林和常绿林具有较高的CUE,热带森林CUE通常低于温带森林,CUE与植被演替和林龄相关,森林地上、地下部分和不同组织的CUE不同,以树干为最高;(2)植被的CUE与气温相关,全球尺度上,森林植被年平均CUE与年平均气温呈抛物线关系,温带、寒带、干旱地区植物呼吸的温度适应驱动其较高的CUE;CUE随着降水量的增加而减少,在水分充足或过剩的地区保持不变;光照减弱降低维持呼吸系数,增加生长呼吸系数,导致植物CUE降低,生长在高光照下的植物CUE高于低光照下的植物;(3)CO2浓度升高引起植物CUE的升高或降低,也有人认为CO2浓度升高对森林CUE没有影响,CO2浓度升高对CUE的影响可能取决于树木年龄或基因型;(4)生长在土壤瘠薄、低温、干旱等胁迫环境下的植物CUE通常比生长在适宜环境下的植物具有较大的可塑性,施肥、灌溉和择伐等管理措施影响森林CUE;(5)植物CUE具有明显的季节变化,温带森林以春季CUE为最高。建议今后森林CUE研究应着重围绕以下3个关键问题:(1)从不同空间尺度和生态系统层次,探讨森林CUE的变异特征及其驱动机制;(2)从不同时间尺度,探讨森林CUE动态过程与机制;(3)森林CUE对气候变化的响应与适应。     

黄土丘陵区退耕草地群落优势种叶片光合生理对氮磷添加的响应

以黄土丘陵区退耕草地群落典型优势种白羊草、长芒草和达乌里胡枝子为研究对象,测定不同氮磷（主区N：0,50,100 kg N hm^-2 a^-1;副区P：0,40,80 kg P₂O₅ hm^-2 a^-1）添加处理下叶片光合气体交换参数、叶绿素荧光参数、叶片氮磷含量、光合氮利用效率（PNUE）和光合磷利用效率（PPUE）,探究不同优势种光合生理特征对外源氮磷添加的响应特征与物种差异。结果表明：单独氮添加下,3个优势种的净光合速率（P_n）、蒸腾速率、水分利用效率（WUE_i）、气孔限制值（Ls）和光系统Ⅱ（PSⅡ）活性高于或显著高于未施肥处理,白羊草和达乌里胡枝子的PNUE和PPUE以及长芒草的PPUE显著增加。单独磷添加下,仅达乌里胡枝子的P_n、WUE_i、Ls和PNUE相比未施肥处理显著增加。氮磷共同添加下,50 kg N hm^-2 a^-1处理下,施磷后达乌里胡枝子的P_n以及三个优势种的PNUE显著增加,白羊草的PPUE显著降低;100 kg N hm^-2 a^-1处理下,施磷后达乌里胡枝子的P_n和PNUE均显著增加,白羊草PPUE和长芒草的PNUE的仅在40 kg P₂O₅ hm^-2 a^-1处理下显著增加。3个优势种的P_n均与PSⅡ最大光化学效率和叶片氮含量呈显著正相关关系,长芒草和达乌里胡枝子的P_n与PSⅡ潜在活性和叶片磷含量呈显著正相关关系。总体表明,氮磷对黄土丘陵区退耕草地优势种光合生理具有一定的交互作用,物种属性和施肥水平影响其光合生理特征响应程度。     

植物功能性状与湿地生态系统土壤碳汇功能

湿地生态系统碳平衡对气候变化极为敏感,是陆地生态系统碳循环响应全球变化的重要环节。然而,湿地生态系统碳汇调节机制仍不十分清楚,并且对影响因子的研究多集中在非生物因子上。综述了植物功能性状和功能性状多样性对湿地生态系统土壤碳汇功能的影响,阐明了生物因子对生态系统碳循环响应全球变化的重要性,介绍了植物功能性状对生态系统碳输入和输出过程的影响,简述了植物功能性状多样性的研究现状及其在指示生态系统碳汇功能现状和预测未来趋势等方面的应用。从优势植物、植物种间关系和植物-微生物种间关系3方面总结了植物功能性状多样性直接和间接影响生态系统碳循环的途径。展望了植物功能性状和功能性状多样性与湿地生态系统土壤碳汇功能的研究前景。     

基于SSR标记的新疆野杏群体遗传多样性及遗传结构

利用27对SSR分子标记对新疆4个野杏群体遗传多样性和遗传结构进行分析,评价新疆野杏遗传多样性水平和分化程度,为新疆野杏合理保护与利用提供科学依据。结果显示：（1）27对SSR引物共检测到431个等位基因（N_a）,各位点平均等位基因数（N_a）和多态性信息含量（PIC）分别为15.96和0.84;物种水平上Shannons信息指数（I）和期望杂合度（H_e）分别为2.21和0.78。（2）群体水平上等位基因数（N_a）、有效等位基因（N_e）、Shannons信息指数（I）、期望杂合度（H_e）和观察杂合度（H_o）分别为10.98、5.85、1.92、0.79和0.55;其中新源县野杏群体遗传多样性最丰富,巩留县群体遗传多样性最低。（3）基于F统计量分析的遗传分化系数（F_st）为0.05,基因流（N_m）为5.26;分子方差分析显示新疆野杏群体大部分遗传变异来自群体内（95.4%）,群体间的遗传变异仅占4.6%。（4）新疆野杏群体遗传距离为0.06~0.49,平均为0.24;遗传相似度为0.61~0.94,平均为0.80;遗传相似度的聚类分析和遗传距离的主坐标分析结果一致,均将供试4个群体划分为两组;Mantel检测显示,新疆野杏群体遗传距离与地理距离无显著相关（r=0.332,P＝0.16）。研究表明,新疆野杏资源具有丰富的遗传多样性,群体遗传分化程度较低,群体间遗传距离较小,这与新疆野杏群体的大小和悠久的演化历史以及群体间频繁的基因交流相关。     

大气CO2浓度升高对土壤碳库稳定性的影响

工业革命以来,大气CO₂浓度持续上升,升高的CO₂浓度会改变植物光合产物积累、土壤碳库的碳输入和碳输出过程,进而通过影响有机碳组成和周转特征来调控土壤碳库动态变化。土壤碳库是陆地生态系统碳库的重要组成部分,其碳储量的微小变化都会对大气CO₂浓度和气候变化产生巨大影响。但目前关于CO₂浓度升高对土壤碳库动态和稳定性的影响还不清楚,很大程度上限制了预测陆地生态系统碳循环对气候变化的反馈。系统综述国内外大气CO₂浓度升高对植被生产力、植被碳输入和土壤碳库影响的研究进展,旨在揭示土壤碳库物理、化学组成以及周转特征对CO₂浓度升高的响应过程和机理,探讨CO₂升高情境下土壤微生物特征对土壤碳库稳定性的影响和驱动机制,为深入理解全球变化下的土壤碳循环特征提供理论支撑。     

鄱阳湖流域不同土地覆被碳水利用效率时空变化及其与气候因子的相关性

鄱阳湖流域作为较突出的碳汇功能区,深入掌握不同土地覆被碳素利用率（CUE）和水分利用效率（WUE）的时空分异规律及其对气候因子的响应,对明确气候变化背景下该流域生态功能和碳水循环有重要意义。利用MODIS数据产品,结合流域土地利用和气象监测数据,辅以趋势分析和相关分析等方法研究了2000-2014年鄱阳湖流域不同土地利用类型CUE和WUE的时空变化特征,并探讨了其与降水、气温和日照时数的相关性。结果表明：1）鄱阳湖流域CUE和WUE多年平均值分别为0.458和0.682 gC/kgH₂O,不同土地利用类型的CUE大小依次为草地 > 水田 > 其他林地 > 旱地 > 疏林地 > 灌木林 > 有林地,WUE大小依次为有林地 > 灌木林 > 旱地 > 疏林地 > 水田 > 其他林地 > 草地;2）鄱阳湖流域CUE、WUE在研究时段内均呈微弱下降趋势,各土地利用类型CUE和WUE则表现出较大的年际波动,且年际变化趋势率具有高度的相似性,其中林地各类型下降趋势最大,其次是旱地和水田,草地最小;3）降水是影响鄱阳湖流域土地覆被碳水利用效率变化的关键因素,其他因子与CUE和WUE的相关性均不显著,不同覆被CUE和WUE对气温、降水和日照时数的响应程度存在较大差异。     

Carbon use efficiency of microbial communities: stoichiometry,methodology and modelling

Carbon use efficiency (CUE) is a fundamental parameter for ecological models based on the physiology of microorganisms. CUE determines energy and material flows to higher trophic levels, conversion of plant‐produced carbon into microbial products and rates of ecosystem carbon storage. Thermodynamic calculations support a maximum CUE value of ~ 0.60 (CUE _max). Kinetic and stoichiometric constraints on microbial growth suggest that CUE in multi‐resource limited natural systems should approach ~ 0.3 (CUE _max/2). However, the mean CUE values reported for aquatic and terrestrial ecosystems differ by twofold (~ 0.26 vs. ~ 0.55) because the methods used to estimate CUE in aquatic and terrestrial systems generally differ and soil estimates are less likely to capture the full maintenance costs of community metabolism given the difficulty of measurements in water‐limited environments. Moreover, many simulation models lack adequate representation of energy spilling pathways and stoichiometric constraints on metabolism, which can also lead to overestimates of CUE. We recommend that broad‐scale models use a CUE value of 0.30, unless there is evidence for lower values as a result of pervasive nutrient limitations. Ecosystem models operating at finer scales should consider resource composition, stoichiometric constraints and biomass composition, as well as environmental drivers, to predict the CUE of microbial communities.     

Energy use efficiency of soil microorganisms: Driven by carbon recycling and reduction

Carbon use efficiency (CUE) is being intensively applied to quantify carbon (C) cycling processes from microbial cell to global scales. Energy use efficiency (EUE) is at least as important as the CUE because (i) microorganisms use organic C mainly as an energy source and not as elemental C per se, and (ii) microbial growth and maintenance are limited by energy, but not by C as a structural element. We conceptualize and review the importance of EUE by soil microorganisms and focus on (i) the energy content in organic compounds depending on the nominal oxidation state of carbon (NOSC), (ii) approaches to assess EUE, (iii) similarities and differences between CUE and EUE, and (iv) discuss mechanisms responsible for lower EUE compared to CUE. The energy content per C atom (enthalpy of combustion, the total energy stored in a compound) in organic compounds is very closely (R² = 0.98) positively related to NOSC and increases by 108 kJ mol⁻¹ C per one NOSC unit. For the first time we assessed the NOSC of microbial biomass in soil (−0.52) and calculated the corresponding energy content of −510 kJ mol⁻¹ C. We linked CUE and EUE considering the NOSC of microbial biomass and element compositions of substrates utilized by microorganisms. The mean microbial EUE (0.32–0.35) is 18% lower than CUE (0.41) using glucose as a substrate. This definitely indicates that microbial growth is limited by energy relative to C. Based on the comparison of a broad range of processes of C and energy utilization for cell growth and maintenance, as well as database of experimental CUE from various compounds, we clearly explained five mechanisms and main factors why EUE is lower than CUE. The two main mechanisms behind lower EUE versus CUE are: (i) microbial recycling: C can be microbially recycled, whereas energy is always utilized only once, and (ii) chemical reduction of organic and inorganic compounds: Energy is used for reduction, which is ongoing without C utilization.     

Microbial carbon use efficiency in different ecosystems: A meta-analysis based on a biogeochemical equilibrium model

Soil microbial carbon use efficiency (CUE) is a crucial parameter that can be used to evaluate the partitioning of soil carbon (C) between microbial growth and respiration. However, general patterns of microbial CUE among terrestrial ecosystems (e.g., farmland, grassland, and forest) remain controversial. To address this knowledge gap, data from 41 study sites (n = 197 soil samples) including 58 farmlands, 95 forests, and 44 grasslands were collected and analyzed to estimate microbial CUEs using a biogeochemical equilibrium model. We also evaluated the metabolic limitations of microbial growth using an enzyme vector model and the drivers of CUE across different ecosystems. The CUEs obtained from soils of farmland, forest, and grassland ecosystems were significantly different with means of 0.39, 0.33, and 0.42, respectively, illustrating that grassland soils exhibited higher microbial C sequestration potentials (p < .05). Microbial metabolic limitations were also distinct in these ecosystems, and carbon limitation was dominant exhibiting strong negative effects on CUE. Exoenzyme stoichiometry played a greater role in impacting CUE values than soil elemental stoichiometry within each ecosystem. Specifically, soil exoenzymatic ratios of C:phosphorus (P) acquisition activities (EEA_C:P) and the exoenzymatic ratio of C:nitrogen (N) acquisition activities (EEA_C:N) imparted strong negative effects on soil microbial CUE in grassland and forest ecosystems, respectively. But in farmland soils, EEA_C:P exhibited greater positive effects, showing that resource constraints could regulate microbial resource allocation with discriminating patterns across terrestrial ecosystems. Furthermore, mean annual temperature (MAT) rather than mean annual precipitation (MAP) was a critical climate factor affecting CUE, and soil pH as a major factor remained positive to drive the changes in microbial CUE within ecosystems. This research illustrates a conceptual framework of microbial CUEs in terrestrial ecosystems and provides the theoretical evidence to improve soil microbial C sequestration capacity in response to global change.     

中亚热带人工针叶林生态系统碳通量拆分差异分析

涡度通量观测可直接获取陆地生态系统与大气之间CO2净交换量(NEE),但深入认识碳循环过程和校验生态系统模型需要不同时间尺度总初级生产力(GPP)和生态系统呼吸(Re)等碳通量数据。利用中国陆地生态系统通量观测与研究网络(ChinaFLUX)中亚热带人工针叶林生态系统2003—2009年的涡度通量和气象观测数据,分析了两种NEE拆分方法对不同时间尺度GPP和Re评估的影响,结果表明:(1)两种拆分方法得到的生态系统碳通量组分(GPP和Re)的季节动态变化一致,都在生长季7、8月份达到峰值;(2)非线性回归模型拆分得到的全年Re和GPP相较于光响应曲线模型分别高出2%—28.6%和1.6%—23%,最大高出317.6 gC·m-2·a-1(2006年),逐月最大差值主要发生在8、9月份;(3)不同时间尺度上,两种方法拆分得到的GPP和Re之间差值的环境响应因子不同。在广泛采用非线性回归模型进行拆分时,如果当月光合有效辐射接近到905mol·m-2·月-1,月平均空气饱和水汽压差接近1.18 kPa时,需要考虑使用光响应曲线模型拆分该月通量,结合两种拆分方法以减小全年的误差。     

Atmospheric CO2 mole fraction affects stand‐scale carbon use efficiency of sunflower by stimulating respiration in light

Plant carbon‐use‐efficiency (CUE), a key parameter in carbon cycle and plant growth models, quantifies the fraction of fixed carbon that is converted into net primary production rather than respired. CUE has not been directly measured, partly because of the difficulty of measuring respiration in light. Here, we explore if CUE is affected by atmospheric CO₂. Sunflower stands were grown at low (200 μmol mol^?1) or high CO₂ (1000 μmol mol^?1) in controlled environment mesocosms. CUE of stands was measured by dynamic stand‐scale ¹³C labelling and partitioning of photosynthesis and respiration. At the same plant age, growth at high CO₂ (compared with low CO₂) led to 91% higher rates of apparent photosynthesis, 97% higher respiration in the dark, yet 143% higher respiration in light. Thus, CUE was significantly lower at high (0.65) than at low CO₂ (0.71). Compartmental analysis of isotopic tracer kinetics demonstrated a greater commitment of carbon reserves in stand‐scale respiratory metabolism at high CO₂. Two main processes contributed to the reduction of CUE at high CO₂: a reduced inhibition of leaf respiration by light and a diminished leaf mass ratio. This work highlights the relevance of measuring respiration in light and assessment of the CUE response to environment conditions.     

Reconciling Carbon-cycle Concepts, Terminology, and Methods

Recent projections of climatic change have focused a great deal of scientific and public attention on patterns of carbon (C) cycling as well as its controls, particularly the factors that determine whether an ecosystem is a net source or sink of atmospheric carbon dioxide (CO₂). Net ecosystem production (NEP), a central concept in C-cycling research, has been used by scientists to represent two different concepts. We propose that NEP be restricted to just one of its two original definitions—the imbalance between gross primary production (GPP) and ecosystem respiration (ER). We further propose that a new term—net ecosystem carbon balance (NECB)—be applied to the net rate of C accumulation in (or loss from [negative sign]) ecosystems. Net ecosystem carbon balance differs from NEP when C fluxes other than C fixation and respiration occur, or when inorganic C enters or leaves in dissolved form. These fluxes include the leaching loss or lateral transfer of C from the ecosystem; the emission of volatile organic C, methane, and carbon monoxide; and the release of soot and CO₂ from fire. Carbon fluxes in addition to NEP are particularly important determinants of NECB over long time scales. However, even over short time scales, they are important in ecosystems such as streams, estuaries, wetlands, and cities. Recent technological advances have led to a diversity of approaches to the measurement of C fluxes at different temporal and spatial scales. These approaches frequently capture different components of NEP or NECB and can therefore be compared across scales only by carefully specifying the fluxes included in the measurements. By explicitly identifying the fluxes that comprise NECB and other components of the C cycle, such as net ecosystem exchange (NEE) and net biome production (NBP), we can provide a less ambiguous framework for understanding and communicating recent changes in the global C cycle.     

Respiration acclimation contributes to high carbon-use efficiency in a seasonally dry pine forest

Predictions of warming and drying in the Mediterranean and other regions require quantifying of such effects on ecosystem carbon dynamics and respiration. Long‐term effects can only be obtained from forests in which seasonal drought is a regular feature. We carried out measurements in a semiarid Pinus halepensis (Aleppo pine) forest of aboveground respiration rates of foliage, R_f, and stem, R_t over 3 years. Component respiration combined with ongoing biometric, net CO₂ flux [net ecosystem productivity (NEP)] and soil respiration measurements were scaled to the ecosystem level to estimate gross and net primary productivity (GPP, NPP) and carbon‐use efficiency (CUE=NPP/GPP) using 6 years data. GPP, NPP and NEP were, on average, 880, 350 and 211 g C m^?2 yr^?1, respectively. The above ground respiration made up half of total ecosystem respiration but CUE remained high at 0.4. Large seasonal variations in both R_f and R_t were not consistently correlated with seasonal temperature trends. Seasonal adjustments of respiration were observed in both the normalized rate (R₂₀) and short‐term temperature sensitivity (Q₁₀), resulting in low respiration rates during the hot, dry period. R_f in fully developed needles was highest over winter–spring, and foliage R₂₀ was correlated with photosynthesis over the year. Needle growth occurred over summer, with respiration rates in developing needles higher than the fully developed foliage at most times. R_t showed a distinct seasonal maximum in May irrespective of year, which was not correlated to the winter stem growth, but could be associated with phenological drivers such as carbohydrate re‐mobilization and cambial activity. We show that in a semiarid pine forest photosynthesis and stem growth peak in (wet) winter and leaf growth in (dry) summer, and associated adjustments of component respiration, dominated by those in R₂₀, minimize annual respiratory losses. This is likely a key for maintaining high CUE and ecosystem productivity similar to much wetter sites, and could lead to different predictions of the effect of warming and drying climate on productivity of pine forests than based on short‐term droughts.     

黄淮海玉米生产能源利用效率和净生态系统碳平衡时空特征

黄淮海地区是我国重要的玉米产区之一,定量化该区域玉米生产的能源利用效率和净生态系统碳平衡对提高资源利用效率和实现碳中和具有重要意义。基于国家统计数据,利用生命周期评价(LCA)、能值分析和碳平衡等方法,定量化了2004-2018年黄淮海地区(包括河北、河南、山东、安徽和江苏5个省)玉米生产的能源利用效率和净生态系统碳平衡,并阐明其时空变化特征。结果表明:黄淮海地区玉米生产的平均能源利用效率、温室气体排放量、净生态系统碳平衡和可持续性指数分别为3.9、3.8 t CO₂-eq/hm²、12.6 t C/hm²和6.8。不同年份间黄淮海地区玉米生产的能源利用效率和净生态系统碳平衡存在显著差异,能源利用效率在2012年最高,为4.3,在2005和2007年最低,为3.7;净生态系统碳平衡在2015年最高,为14.2 t C/hm²,在2005年最低,为10.1 t C/hm²。各省份中以河北省玉米生产的能源利用效率、净生态系统碳平衡和可持续性指数最高,分别高于区域平均15.3%、9.6%和26.4%,较最低的江苏省高45.5%、22.0%和88.8%。河北省、河南省和山东省的综合得分均为正值,具有较高的资源利用效率和生态环境效益。黄淮海地区玉米生产资源投入、能源利用效率、生态环境效益和净生态系统碳平衡在时空尺度上存在较大的差异,应制定区域特异性优化管理策略,减少化肥和农药的施用,施用增效肥料和高效生物农药等,采用秸秆还田等保护性耕作措施,积极推进规模化和机械化的发展,实现黄淮海地区玉米生产的绿色可持续发展。