Diurnal and Seasonal Dynamics of Soil Respiration at Temperate Leymus Chinensis Meadow Steppes in Western Songnen Plain, China

To evaluate the diurnal and seasonal variations in soil respiration(Rs) and understand the controlling factors, we measured carbon dioxide(CO2) fluxes and their environmental variables using a LI-6400 soil CO2 flux system at a temperate Leymus chinensis meadow steppe in the western Songnen Plain of China in the growing season(May–October) in 2011 and 2012. The diurnal patterns of soil respiration could be expressed as single peak curves, reaching to the maximum at 11:00–15:00 and falling to the minimum at 21:00–23:00(or before dawn). The time-window between 7:00 and 9:00 could be used as the optimal measuring time to represent the daily mean soil CO2 efflux. In the growing season, the daily value of soil CO2 efflux was moderate in late spring(1.06–2.51 μmol/(m2·s) in May), increased sharply and presented a peak in summer(2.95–3.94 μmol/(m2·s) in July), and then decreased in autumn(0.74–0.97 μmol/(m2·s) in October). Soil temperature(Ts) exerted dominant control on the diurnal and seasonal variations of soil respiration. The temperature sensitivity of soil respiration(Q10) exhibited a large seasonal variation, ranging from 1.35 to 3.32, and decreased with an increasing soil temperature. Rs gradually increased with increasing soil water content(Ws) and tended to decrease when Ws exceeded the optimum water content(27%) of Rs. The Ts and Ws had a confounding effect on Rs, and the two-variable equations could account for 72% of the variation in soil respiration(p < 0.01).

Contribution of aboveground litter to soil respiration in Populus davidiana Dode plantations at different stand ages

Soil respiration from decomposing aboveground litter is a major component of the terrestrial carbon cycle.However,variations in the contribution of aboveground litter to the total soil respiration for stands of varying ages are poorly understood.To assess soil respiration induced by aboveground litter,treatments of litter and no litter were applied to 5-,10-,and 20-year-old stands of Populus davidiana Dode in the sandstorm source area of Beijing -Tianjin,China.Optimal nonlinear equations were applied to model the combined effects of soil temperature and soil water content on soil respiration.Results showed that the monthly average contribution of aboveground litter to total soil respiration were 18.46% ± 4.63%,16.64% ± 9.31%,and 22.37% ± 8.17% for 5-,10-,and 20-year-old stands,respectively.The relatively high contribution in 5-and 20-year-old stands could be attributed to easily decomposition products and high accumulated litter,respectively.Also,it fluctuated monthly for all stand ages due to substrate availability caused by phenology and environmental factors.Litter removal significantly decreased soil respiration and soil water content for all stand ages(p < 0.05) but not soil temperature(p > 0.05).Variations of soil respiration could be explained by soil temperature at 5-cm depth using an exponential equation and by soil water content at 10-cm depth using a quadratic equation,whereas soil respiration was better modeled using the combined parameters of soil temperature and soil water content than with either soil temperature or soil water content alone.Temperature sensitivity(Q_(10))increased with stand age in both the litter and the no litter treatments.Considering the effects of aboveground litter,this study provides insights for predicting future soil carbon fluxes and for accurately assessing soil carbon budgets.

Spatio-temporal Variation of Soil Respiration and Its Driving Factors in Semi-arid Regions of North China

Soil respiration(SR) is the second-largest flux in ecosystem carbon cycling. Due to the large spatio-temporal variability of environmental factors, SR varied among different vegetation types, thereby impeding accurate estimation of CO_2 emissions via SR. However, studies on spatio-temporal variation of SR are still scarce for semi-arid regions of North China. In this study, we conducted 12-month SR measurements in six land-use types, including two secondary forests(Populus tomentosa(PT) and Robinia pseudoacacia(RP)), three artificial plantations(Armeniaca sibirica(AS), Punica granatum(PG) and Ziziphus jujuba(ZJ)) and one natural grassland(GR), to quantify spatio-temporal variation of SR and distinguish its controlling factors. Results indicated that SR exhibited distinct seasonal patterns for the six sites. Soil respiration peaked in August 2012 and bottomed in April 2013. The temporal coefficient of variation(CV) of SR for the six sites ranged from 76.98% to 94.08%, while the spatial CV of SR ranged from 20.28% to 72.97% across the 12-month measurement. Soil temperature and soil moisture were the major controlling factors of temporal variation of SR in the six sites, while spatial variation in SR was mainly caused by the differences in soil total nitrogen(STN), soil organic carbon(SOC), net photosynthesis rate, and fine root biomass. Our results show that the annual average SR and Q_(10)(temperature sensitivity of soil respiration) values tended to decrease from secondary forests and grassland to plantations, indicating that the conversion of natural ecosystems to man-made ecosystems may reduce CO_2 emissions and SR temperature sensitivity. Due to the high spatio-temporal variation of SR in our study area, care should be taken when converting secondary forests and grassland to plantations from the point view of accurately quantifying CO_2 emissions via SR at regional scales.

Comparing the temperature sensitivity of organic matter decomposition in oxic and oxygen-deprived soils

No consistent variation was found in soil respiration Q10 under various O2 conditions.Substrate C quality had a strong effect on Q10 in oxic soils.N limitation had a large impact on Q10 in soils under O2 limitation.Current studies on the temperature sensitivity(Q10)of soil organic matter(SOM)decomposition mainly focus on aerobic conditions.However,varia-tions and determinants of Q10 in oxygen(O2)-deprived soils remain unclear.Here we incubated three grassland soils under oxic,suboxic,and anoxic conditions subjected to varying temperatures to compare variations in Q10 in relation to changing substrates.No consistent variation was found in Q10 under various O2 conditions.Further analysis of edaphic properties demon-strated that substrate carbon quality showed a strong influence on Q10 in oxic soils,whereas nitrogen limitation played a more important role in suboxic and anoxic soils.These results suggest that substrate carbon quality and nitrogen limitation may play roles of varying importance in determining the temperature sensitivity of SOM decomposition under various O2 conditions.

Modeling the contribution of abiotic exchange to CO_2 flux in alkaline soils of arid areas

Recent studies on alkaline soils of arid areas suggest a possible contribution of abiotic exchange to soil CO2 flux(Fc).However,both the overall contribution of abiotic CO2 exchange and its drivers remain unknown.Here we analyzed the environmental variables suggested as possible drivers by previous studies and constructed a function of these variables to model the contribution of abiotic exchange to Fc in alkaline soils of arid areas.An automated flux system was employed to measure Fc in the Manas River Basin of Xinjiang Uygur autonomous region,China.Soil pH,soil temperature at 0–5 cm(Ts),soil volumetric water content at 0–5 cm(θs)and air temperature at10 cm above the soil surface(Tas)were simultaneously analyzed.Results highlight reduced sensitivity of Fc to Ts and good prediction of Fc by the model Fc=R10Q10(Tas–10)/10+r7q7(pH–7)+λTas+μθs+e which represents Fc as a sum of biotic and abiotic components.This presents an approximate method to quantify the contribution of soil abiotic CO2 exchange to Fc in alkaline soils of arid areas.

Soil Microbial Metabolic Quotient in Inner Mongolian Grasslands: Patterns and Influence Factors

Microbial metabolic quotient(MMQ) is the rate of soil microbial respiration per unit of microbial biomass, and represents the capacity of soil microbes to utilize soil organic matter.Understanding the regional variation and determinants of MMQ can help predict the responses of soil respiration rate to global climate change.Accordingly, we measured and analyzed MMQ-related data(e.g., soil basic respiration rate at 20℃ and soil microbial biomass) from 17 grassland sites, which located in meadow steppe, typical steppe, and desert steppe along a 1000-km transect across the Inner Mongolian grasslands, China.Results showed that MMQ varied significantly among the different grassland types(P < 0.05;desert > typical > meadow) and decreased from southwest to northeast(r =–0.81) with increasing latitude(r = – 0.50), and with increasing mean annual precipitation(r = –0.69).Precipitation accounted for 56% of the total variation in MMQ, whereas temperature accounted for 26%.MMQ was negatively correlated with precipitation across the Inner Mongolian grasslands.Therefore, climate change, especially in regard to precipitation, may influence soil microbial respiration and soil carbon dynamics through altering MMQ.These results highlighted the importance of spatial patterns in MMQ for accurately evaluating the responses of soil respiration to climate change at regional and global scales.

Seasonal Changes in Soil Respiration with An Elevation Gradient in Abies nephrolepis(Trautv.)Maxim.Forests in North China

Soil respiration(Rs)plays an important role in regulating carbon cycle of terrestrial ecosystems and presents temporal and spatial heterogeneity.Abies nephrolepis is a tree species that prefers the cold and wet environment and is mainly distributed in Northeast Asia and East Asia.The Rs variations of Abies nephrolepis forests communities are generally environmental-sensitive and can effectively reflect the adaptive responses of forest ecosystems to climate change.In this study,the growing-seasonal variations of Rs,soil temperature,soil water content and soil properties of Abies nephrolepis forests were analyzed along an altitude gradient(2000,2100,2200 and 2300 m)over two years on Wutai Mountain in North China.As the main results showed,soil respiration keeps the same change trend as soil temperature and reached peaks in July at 2000 m in 2019 and 2020.During 26th July to 25th October in 2019 and 27th May to 23rd October in 2020,on the whole,the soil temperature independently explained 76.2%of Rs variations while the soil water content independently explained 26.8%.Soil temperature and soil water content jointly explained 81.8%of Rs variations.Soil properties explained 61.8%and 69.6%of Rs variation in 2019 and 2020,respectively.Soil organic carbon content and soil enzyme activity had the signifi-cant(P<0.01)negative and positive relationships,respectively,with Rs variation.With altitudes evaluated from 2000 to 2300 m,soil respiration temperature sensitivity(Q10)and the soil organic carbon content increased by 12.4%and 10.4%,respectively,while invertase activity,cellulase activity and urease activity dropped by 41.2%,29.45%and 38.19%,respectively.The results demonstrate that(1)soil temperature is the major factor affecting Rs variations in Abies nephrolepis forests;(2)weakened microbial carbon metabolism in high-altitude areas results in the accumulation of soil organic carbon;(3)with a higher Q10,forest ecosystems in high-altitude areas might be more easily affected by climate change;(4)climate warming might accelerate the consumption of soil organic carbon sink in forest ecosystems,especially in high-altitude areas.

Spatial patterns in temperature sensitivity of soil respiration in China: Estimation with inverse modeling

Temperature sensitivity of soil respiration (Q10) is an important parameter in modeling the effects of global warming on ecosystem carbon release. Experimental studies of soil respiration have ubiquitously indicated that Q10 has high spatial heterogeneity. However, most biogeochemical models still use a constant Q10 in projecting future climate change and no spatial pattern of Q10 values at large scales has been derived. In this study, we conducted an inverse modeling analysis to retrieve the spatial pattern of Q10 in China at 8 km spatial resolution by assimilating data of soil organic carbon into a proc-ess-based terrestrial carbon model (CASA model). The results indicate that the optimized Q10 values are spatially heterogeneous and consistent to the values derived from soil respiration observations. The mean Q10 values of different soil types range from 1.09 to 2.38, with the highest value in volcanic soil, and the lowest value in cold brown calcic soil. The spatial pattern of Q10 is related to environmental factors, especially precipitation and top soil organic carbon content. This study demonstrates that inverse modeling is a useful tool in deriving the spatial pattern of Q10 at large scales, with which being incorporated into biogeochemical models, uncertainty in the projection of future carbon dynamics could be potentially reduced.

绿肥还田结合减氮对麦田土壤呼吸及其温度敏感性的影响

研究绿肥还田结合氮肥减施对麦田土壤呼吸动态及小麦产量的影响,以期为干旱绿洲灌区农田碳减排技术研发提供理论依据。试验于2021—2022年在甘肃河西绿洲灌区开展,以常规施氮无绿肥还田(N100)为对照,设施用15000 kg∙hm^(−2)绿肥+85%氮肥(G_(1)N_(85))、22500 kg∙hm^(−2)绿肥+85%氮肥(G_(2)N_(85))、30000 kg∙hm^(−2)绿肥+85%氮肥(G_(3)N_(85))、15000 kg∙hm^(−2)绿肥+70%氮肥(G_(1)N_(70))、22500 kg∙hm^(−2)绿肥+70%氮肥(G_(2)N_(70))和30000 kg∙hm^(−2)绿肥+70%氮肥(G_(3)N_(70))共7个处理。探讨小麦生育期的土壤呼吸速率、碳排放量、产量及碳排放效率,分析土壤呼吸对土壤温度的响应。结果表明:不同处理下麦田土壤呼吸速率均呈先升高后降低的单峰趋势,全生育期内变化范围为0.8~6.2μmol∙m^(−2)∙s−1。绿肥还田结合氮肥减施显著提高麦田土壤呼吸速率及土壤碳排放总量,与N100相比,平均增幅分别为7.2%~19.8%和5.7%~18.8%;其中G_(3)N_(85)和G_(3)N_(70)较其他处理土壤呼吸速率分别增加2.3%~16.0%和3.3%~19.8%,土壤碳排放总量分别增加2.9%~15.2%和3.1%~18.8%;与G_(3)N_(85)相比,G_(3)N_(70)处理两年平均土壤呼吸速率及土壤碳排放总量分别增加3.3%和3.1%(P<0.05)。绿肥还田结合氮肥减施处理显著降低土壤呼吸温度敏感性(Q10),与N100相比,Q10值降幅为10.4%~18.1%(P<0.05)。绿肥还田结合氮肥减施显著影响了小麦产量和土壤碳排放效率,其中G_(3)N_(85)处理分别显著高于其他处理4.2%~45.6%和0.3%~26.4%(P<0.05)。可见,绿肥还田结合氮肥减施在增强麦田土壤呼吸的同时,显著降低土壤呼吸温度敏感性,提高小麦产量和碳排放效率,其中翻压绿肥30000 kg∙hm^(−2)配合氮肥减量15%处理(G_(3)N_(85))是河西绿洲灌区小麦田节氮减排和提高农田土壤生产力的有效途径。

增温与凋落物去除对人工草地土壤呼吸的影响

人工草地是重要的碳汇,但其土壤呼吸及其温度敏感性(Q10)对气候变化和干扰的响应尚不清楚。本研究在大陆性季风气候区的紫苜蓿(Medicago sativa)和无芒雀麦(Bromus inermis)2种人工草地开展了增温和凋落物处理试验,测量了土壤呼吸速率和Q10,并分析了不同草地对这些影响的响应差异。结果表明:增温使年均土壤温度显著增加约2℃(P<0.05);同时,使年均土壤湿度和电导率显著降低(P<0.05)。增温使年平均土壤呼吸速率降低8.81%;凋落物去除使年平均土壤呼吸速率降低9.33%。增温和凋落物去除均使Q10降低。不同草地对增温和凋落物处理有不同的响应,其中紫苜蓿草地对增温的响应大于无芒雀麦草地,而无芒雀麦草地对凋落物处理的响应大于紫苜蓿草地。本研究表明,试验区无芒雀麦群落相较于紫苜蓿群落更能抵抗气候变化和干扰的影响,有利于减少碳排放,是更好的建植人工草地的物种。

河岸杨树人工林土壤呼吸及其组分对不同降雨模式的响应

【目的】确定不同降雨模式下土壤呼吸及其组分的响应差异及其原因,为精确预测和模拟全球变化背景下土壤碳循环的过程和陆地碳汇能力提供理论指导。【方法】对两年(2018—2019年)土壤呼吸及其组分(自养呼吸和异养呼吸)进行连续测量,并利用K-均值聚类分析对降雨进行分类,探究自然降雨过程对环境因子和土壤呼吸速率的影响。【结果】(1)土壤呼吸速率在长历时小雨、中历时小雨和短历时大雨下分别降低41.6%、36.3%和45.8%,异养呼吸速率分别降低60.5%、41.2%和85.1%;自养呼吸速率在长历时小雨和中历时小雨下分别降低了11.7%和30.0%,在短历时大雨下提高了72.5%。(2)异养呼吸对降雨的响应更快且雨后变化幅度更大。(3)降雨事件通过改变土壤湿度影响呼吸速率,土壤温度在降雨前后变化不显著。【结论】随着降雨强度增加或降雨持续时间的延长,土壤呼吸和异养呼吸受到的抑制效果愈发显著,且相较于自养呼吸,异养呼吸对降雨的响应更为敏感,降雨主要通过改变异养呼吸来影响土壤呼吸。

黄土高原退耕方式与年限对土壤呼吸及其温度敏感性的影响

土壤呼吸是陆地生态系统碳循环的关键过程,明确退耕后土地利用变化对土壤呼吸及其温度敏感性的影响是提升土壤碳汇能力的重要前提。以黄土高原20 a耕地、退耕3、6、10 a的苹果园与撂荒地为研究对象,原位监测样地2018年7-12月的土壤呼吸速率,估算其温度敏感性,并应用偏最小二乘结构方程模型,明确土壤呼吸及其温度敏感性的关键影响因子。结果表明,随退耕年限的增加,撂荒地土壤有机碳和全氮含量呈现先降低后升高的趋势,苹果园则与之相反。监测期间撂荒地平均土壤呼吸速率为2.73~4.65μmol·m^(-2)·s^(-1),苹果园为1.07~3.13μmol·m^(-2)·s^(-1),退耕3 a和6 a撂荒地的土壤呼吸速率显著高于苹果园(P<0.05)。土壤呼吸温度敏感性的变化范围为1.477~4.055,不同退耕方式间土壤呼吸温度敏感性并无显著差异。偏最小二乘-结构方程模型结果表明,土壤因子共解释了土壤呼吸及其温度敏感性34.4%的变化;相比于化学和生物因子,土壤水分与温度等物理因子对土壤呼吸及其温度敏感性的影响更为显著。研究表明,退耕后短期内(0~6 a),苹果园的固碳潜力更大,但随着退耕年限的延长(>6 a),撂荒地更有利于土壤固碳。

麦玉轮作长期秸秆还田下土壤呼吸及有机碳库对温度变化的响应

为探明华北麦玉轮作区长期秸秆还田下增温对土壤呼吸及土壤碳库的影响,本试验基于41年不同秸秆还田水平(分别为0 kg/hm^(2)(S1)、2250 kg/hm^(2)(S2)、4500 kg/hm^(2)(S3)和9000 kg/hm^(2)(S4))田间定位试验,采集土壤样品后分别在15、25和35℃下进行125 d的室内恒温培养,针对土壤呼吸速率及有机碳组分含量进行监测。结果表明:在整个培养期间,土壤呼吸速率呈现先下降后平稳的变化趋势,秸秆还田量与温度显著影响土壤呼吸速率和呼吸累积释放量。各处理间土壤呼吸速率和呼吸累积释放量整体为35℃>25℃>15℃,S4>S3>S2>S1。秸秆还田量和温度显著影响土壤有机碳及各组分含量,培养后S4处理土壤有机碳含量显著高于其他处理,S3和S4处理土壤颗粒有机碳和微生物量碳含量显著高于其他处理,随培养温度的提高土壤有机碳组分呈降低趋势。土壤呼吸与土壤有机碳、颗粒有机碳、微生物量碳含量呈显著正相关。S3和S4处理较S1和S2处理可以显著降低土壤呼吸温度敏感性(Q_(10))。总的来看,华北麦玉轮作区长期中量和高量秸秆还田可以提高土壤有机碳库,降低土壤呼吸温度敏感性,减缓CO_(2)的释放,且4500 kg/hm^(2)还田量具有更高的固碳潜力与空间。

Soil microbial communities regulate the threshold effect of salinity stress on SOM decomposition in coastal salt marshes

Salinity stress is one of the critical environmental drivers of soil organic matter(SOM)decomposition in coastal ecosystems.Although the temperature sensitivity(Q_(10))of SOM decomposition has been widely applied in Earth system models to forecast carbon processes,the impact of salinity on SOM decomposition by restructuring microbial communities remains uncovered.Here,we conducted a microcosm experiment with soils collected from the coastal salt marsh in the Yellow River Estuary,which is subjected to strong dynamics of salinity due to both tidal flooding and drainage.By setting a gradient of salt solutions,soil salinity was adjusted to simulate salinity stress and soil carbon emission(CO_(2))rate was measured over the period.Results showed that as salinity increased,the estimated decomposition constants based on first-order kinetics gradually decreased at different temperatures.Below the 20‰salinity treatments,which doubled the soil salinity,Q_(10)increased with increasing salinity;but higher salinity constrained the temperature-related response of SOM decomposition by inhibiting microbial growth and carbon metabolisms.Soil bacteria were more sensitive to salinity stress than fungi,which can be inferred from the response of microbial beta-diversity to changing salinity.Among them,the phylotypes assigned to Gammaproteobacteria and Bacilli showed higher salt tolerance,whereas taxa affiliated with Alphaproteobacteria and Bacteroidota were more easily inhibited by the salinity stress.Several fungal taxa belonging to Ascomycota had higher adaptability to the stress.As the substrate was consumed with the incubation,bacterial competition intensified,but the fungal co-occurrence pattern changed weakly during decomposition.Collectively,these findings revealed the threshold effect of salinity on SOM decomposition in coastal salt marshes and emphasized that salt stress plays a key role in carbon sequestration by regulating microbial keystone taxa,metabolisms,and interactions.

施用粪肥对我国北方农田土壤呼吸温度敏感性的影响

[目的]本研究旨在探明粪肥施用对我国北方农田土壤呼吸温度敏感性Q_(10)的影响及主要驱动因素,为制定合理的农业管理措施、减少农田土壤CO_(2)排放提供科学依据。[方法]本研究在中国知网、万方数据和Web of Science数据库收集国内外关于施用粪肥对土壤呼吸温度敏感性影响的相关文献,用关键词“粪肥”、“土壤呼吸”、“温度敏感性”和“中国北方”进行检索,共提取已公开发表的16篇文献中试验数据104组。采用整合分析(Meta-analysis)探讨不同粪肥施用条件下各因素对土壤呼吸温度敏感性的影响。[结果]粪肥施用可显著提高土壤呼吸温度敏感性,平均提升幅度为8.11%。施肥类型中,猪粪对土壤呼吸温度敏感性的增幅(12.72%)显著高于鸡粪的增幅(5.56%);粪肥施用量≤15000 kg·hm^(-2)对土壤呼吸温度敏感性的增幅最大(11.48%);单施粪肥的增幅(11.96%)显著高于粪肥配施化肥的增幅(5.22%)。土壤有机碳含量≥12 g·kg^(-1)时土壤呼吸温度敏感性的增幅(7.17%)显著高于6~12 g·kg^(-1)水平(2.23%)时的增幅;土壤初始pH≥7的增幅(8.11%)显著高于pH<7的增幅(3.48%)。不同气候条件下,年均温≤5℃时土壤呼吸温度敏感性的增幅为8.49%,年降雨量为400~600 mm时的增幅(8.98%)显著高于≤400 mm(2.71%)和≥600 mm时的增幅(-3.13%)。此外,随机森林结果表明土壤有机碳含量是影响土壤呼吸温度敏感性变化的关键因素,其解释率达42.6%。[结论]综上,在我国北方农田鸡粪配施化肥且粪肥施用量>15000 kg·hm^(-2)对土壤呼吸温度敏感性的增幅最小,可以有效减缓农田土壤的碳排放,以达到应对全球变暖现状的目的。此外,土壤有机碳含量是影响粪肥施用下中国北方农田土壤呼吸温度敏感性变化的主要驱动因素。

Does a General Temperature-Dependent Q10 Model of Soil Respiration Exist at Biome and Global Scale？

Soil respiration （SR） is commonly modeled by a Q10 （an indicator of temperature sensitivity） function in ecosystem models. Q10 is usually treated as a constant of 2 in these models, although Q10 value of SR often decreases with increasing temperatures. It remains unclear whether a general temperature- dependent Q10 model of SR exists at biome and global scale. In this paper, we have compiled the long-term Q10 data of 38 SR studies ranging from the Boreal, Temperate, to Tropical/Sublropical biome on four continents. Our analysis indicated that the general temperature-dependent biome Q10 models of SR existed, especially in the Boreal and Temperate biomes. A single-exponential model was better than a simple linear model in fitting the average Q10 values at the biome scale. Average soil temperature is a better predictor of Q10 value than average air temperature in these models, especially in the Boreal biome. Soil temperature alone could explain about 50% of the Q10 variations in both the Boreal and Temperate biome single-exponential Q10 model. Q10 value of SR decreased with increasing soil temperature but at quite different rates among the three biome Q10 models. The k values （Q10 decay rate constants） were 0.09, 0.07, and 0.02/℃ in the Boreal, Temperate, and Tropical/Subtropical biome, respectively, suggesting that Q10 value is the most sensitive to soil temperature change in the Boreal biome, the second in the Temperate biome, and the least sensitive in the Tropical/ Subtropical biome. This also indirectly confirms that acclimation of SR in many soil warming experiments probably occurs. The k value in the ＂global＂ single-exponential Q10 model which combined both the Boreal and Temperate biome data set was 0.08/℃. However, the global general temperature-dependent Q10 model developed using the data sets of the three biomes is not adequate for predicting Q10 values of SR globally. The existence of the general temperature-dependent Q10 models of SR in the Boreal and Temperate biome has important implications for modeling SR, especially in the Boreal biome. More detail model runs are needed to exactly evaluate the impact of using a fixed Q10 vs a temperature-dependent Q10 on SR estimate in ecosystem models （e.g., TEM, Biome-BGC, and PnET）.

Dependence of Soil Respiration on Soil Temperature and Soil Moisture in Successional Forests in Southern China

The spatial and temporal variations in soil respiration and its relationship with biophysical factors In forests near the Tropic of Cancer remain highly uncertain. To contribute towards an Improvement of actual estimates, soil respiration rates, soil temperature, and soil moisture were measured In three successional subtropical forests at the Dlnghuahan Nature Reserve （DNR） In southern China from March 2003 to February 2005. The overall objective of the present study was to analyze the temporal variations of soil respiration and Its biophysical dependence in these forests. The relationships between biophysical factors and soil respiration rates were compared In successional forests to test the hypothesis that these forests responded similarly to biophysical factors. The seasonality of soil respiration coincided with the seasonal climate pattern, with high respiration rates in the hot humid season （April-September） and with low rates In the cool dry season （October-March）. Soil respiration measured at these forests showed a clear Increasing trend with the progressive succession. Annual mean （± SD） soil respiration rate In the DNR forests was （9.0 ± 4.6） Mg CO2-C/hm^2 per year, ranging from （6.1 ± 3.2） Mg CO2-C/hm^2 per year in early successional forests to （10.7 ± 4.9） Mg CO2-C/hm^2 per year in advanced successional forests. Soil respiration was correlated with both soil temperature and moisture. The T/M model, where the two biophysical variables are driving factors, accounted for 74%-82% of soil respiration variation In DNR forests. Temperature sensitivity decreased along progressive succession stages, suggesting that advanced-successional forests have a good ability to adjust to temperature. In contrast, moisture Increased with progressive succession processes. This increase is caused, in part, by abundant respirators In advanced-successional forest, where more soil moisture is needed to maintain their activities.

红壤侵蚀区马尾松林恢复过程中土壤异养呼吸及微生物多样性的变化特征

土壤异养呼吸是影响土壤有机碳积累的关键因素。以南方红壤水土流失区不同恢复年限的马尾松林(未治理地(Y0)、恢复14 a(Y14)、恢复31 a(Y31))为对象,对不同呼吸组分进行测定并结合温度、水分以及微生物等因子,研究马尾松林恢复对土壤异养呼吸的影响。结果表明:不同恢复年限马尾松林土壤异养呼吸差异显著,恢复31 a显著大于恢复14 a以及未治理地,未治理地异养呼吸速率仅为0.99μmol·m^(–2)·s^(–1),而治理14 a、31 a分别为2.20、2.80μmol·m^(–2)·s^(–1);温度是异养呼吸季节变化的主要影响因子,分别解释季节变化的40.6%(Y0)、62.2%(Y14)、66.6%(Y31);马尾松林恢复后土壤异养呼吸温度敏感性(Q10)显著增加,Y0、Y14、Y31的Q10分别为1.58、1.93和1.82;不同恢复年限土壤异养呼吸占土壤总呼吸比例为77.94%(Y0)、70.84%(Y14)、77.35%(Y31)。结构方程表明,在马尾松林恢复过程中,土壤有机碳(SOC)、温度以及土壤微生物多样性变化是影响土壤异养呼吸变化的主要因子,其中SOC、土壤微生物与异养呼吸显著正相关,而植被恢复过程中土壤温度变化与异养呼吸显著负相关。本研究结果表明,马尾松林植被恢复过程中SOC的积累以及缺乏有效的物理保护增加了微生物对SOC的分解,另一方面土壤环境温度的降低和细菌、真菌丰度的增加以及群落中变形菌、子囊菌、酸杆菌的增加,更进一步加剧微生物对原有土壤有机质的分解强度,导致异养呼吸碳排放的持续增加,最终限制了马尾松林土壤碳吸存效率。因此,较高的土壤异养呼吸可能是影响红壤侵蚀退化区土壤有机质进一步提升的关键。

养分添加和浅耕翻对晋北赖草草地土壤呼吸的影响

为了探究外源养分输入和人为干扰及其交互作用对农牧交错带草地土壤呼吸的影响,本研究以晋北农牧交错带草地为研究对象,设置对照、养分添加(氮磷钾NPK)、浅耕翻(15 cm)和养分添加+浅耕翻4个处理进行探究。结果表明:养分添加使土壤呼吸提高了39.0%,而浅耕翻对其无显著影响;浅耕翻和养分添加的交互作用对土壤呼吸的影响与年际降水有关,在湿润年份(2020),浅耕翻增强了养分添加对土壤呼吸的正效应,干旱年份(2021)削弱;结构方程模型的结果表明,土壤呼吸的变化与地下生物量有关;浅耕翻和养分添加处理对土壤呼吸温度敏感性无显著影响,养分添加+浅耕翻处理对土壤呼吸的温度敏感性无显著影响但存在明显的年际差异。综上所述,探究农牧交错带草地养分管理及人为干扰对土壤碳通量的影响应考虑年际降水的变化。

拉萨河流域河岸带湿地土壤CO_(2)排放对变温的响应

通过对26份青藏高原拉萨河流域湿地土壤样品的分析,发现土壤有机碳和总氮呈现中游西部流域低东部流域高,汇入雅鲁藏布江口较低,源头彭措较高;土壤中CO_(2)排放速率随着培养温度的升高而增加,下游各位点CO_(2)平均排放速率显著高于中游和上游.土壤呼吸温度敏感性(Q_(10))在流域内汇入口和下游左侧流域(堆龙曲)表现与排放速率相似的特征,更好地突出了在下游右侧流域(墨竹工卡流域)和上游流域(麦地藏布流域)的土壤温度敏感性较低的特征.通过地理探测器探寻气象、植被、地理、双评价、生化、人口经济6个圈层对Q_(10)值的不同影响,结果表明:气象(降雨、太阳辐射)、地理(流域、海拔)、生化、人口经济等因素对Q_(10)有较强影响,其中降雨(80.76%)和太阳辐射(74.68%)在气候因素中占主要影响;流域(88.95%)分布的q值在地理因素中起到重要作用;生化因子中,各检测指标对Q_(10)的影响排序为OC(88.16%)>MBC/OC(78.72%)>MBN/TN(77.30%)>TN(72.37%)>C/N(35.14%)>MBN(8.70%)>MBC(6.80%)>MBC/MBN(5.89%);降雨侵蚀归一化指数对Q_(10)的影响达到了79.67%.此外,任何两种因子对Q_(10)值的交互作用都要大于单一因素的单独作用.地理因素中流域与其他因素间的交互作用对Q_(10)的影响最为强烈(0.90~0.96),生化因素OC与其他因素间的交互作用对Q_(10)较强烈(0.89~0.94),气象因素中降雨和太阳辐射与其他因素交互作用对Q_(10)的影响更加不可忽略.