Comparison of soil respiration methods in a mid-latitude deciduous forest

In forest ecosystems the single largest respiratory flux influencing net ecosystem productivity (NEP) is the total soil CO₂ efflux; however, it is difficult to make measurements of this flux that are accurate at the ecosystem scale. We examined patterns of soil CO₂ efflux using five different methods: auto-chambers, portable gas analyzers, eddy covariance along and two models parameterized with the observed data. The relation between soil temperature and soil moisture with soil CO₂ effluxes are also investigated, both inter-annually and seasonally, using these observations/results. Soil respiration rates (R _soil) are greatest during the growing season when soil temperatures are between 15 and 25 °C, but some soil CO₂ efflux occurs throughout the year. Measured soil respiration was sensitive to soil temperature, particularly during the spring and fall. All measurement methods produced similar annual estimates. Depending on the time of the year, the eddy covariance (flux tower) estimate for ecosystem respiration is similar to or slightly lower than estimates of annual soil CO₂ efflux from the other methods. As the eddy covariance estimate includes foliar and stem respiration which the other methods do not; it was expected to be larger (perhaps 15–30%). The auto-chamber system continuously measuring soil CO₂ efflux rates provides a level of temporal resolution that permits investigation of short- to longer term influences of factors on these efflux rates. The expense of building and maintaining an auto chamber system may not be necessary for those researchers interested in estimating R _soil annually, but auto-chambers do allow the capture of data from all seasons needed for model parameterization.     

Seasonal and annual respiration of a ponderosa pine ecosystem

The net ecosystem exchange of CO₂ between forests and the atmosphere, measured by eddy covariance, is the small difference between two large fluxes of photosynthesis and respiration. Chamber measurements of soil surface CO₂ efflux (F_s), wood respiration (F_w) and foliage respiration (F_f) help identify the contributions of these individual components to net ecosystem exchange. Models developed from the chamber data also provide independent estimates of respiration costs. We measured CO₂ efflux with chambers periodically in 1996–97 in a ponderosa pine forest in Oregon, scaled these measurements to the ecosystem, and computed annual totals for respiration by component. We also compared estimated half-hourly ecosystem respiration at night (F_nc) with eddy covariance measurements. Mean foliage respiration normalized to 10 °C was 0.20 μmol m^–2 (hemi-leaf surface area) s^–1, and reached a maximum of 0.24 μmol m^–2 HSA s^–1 between days 162 and 208. Mean wood respiration normalized to 10 °C was 5.9 μmol m^–3 sapwood s^–1, with slightly higher rates in mid-summer, when growth occurs. There was no significant difference (P > 0.10) between wood respiration of young (45 years) and old trees (250 years). Soil surface respiration normalized to 10 °C ranged from 0.7 to 3.0 μmol m^–2 (ground) s^–1 from days 23 to 329, with the lowest rates in winter and highest rates in late spring. Annual CO₂ flux from soil surface, foliage and wood was 683, 157, and 54 g C m^–2 y^–1, with soil fluxes responsible for 76% of ecosystem respiration. The ratio of net primary production to gross primary production was 0.45, consistent with values for conifer sites in Oregon and Australia, but higher than values reported for boreal coniferous forests. Below-ground carbon allocation (root turnover and respiration, estimated as F_s– litterfall carbon) consumed 61% of GPP; high ratios such as this are typical of sites with more water and nutrient constraints. The chamber estimates were moderately correlated with change in CO₂ storage in the canopy (F_stor) on calm nights (friction velocity u* < 0.25 m s^–1; R² = 0.60); F_stor was not significantly different from summed chamber estimates. On windy nights (u* > 0.25 m s^–1), the sum of turbulent flux measured above the canopy by eddy covariance and F_stor was only weakly correlated with summed chamber estimates (R² = 0.14); the eddy covariance estimates were lower than chamber estimates by 50%.     

二氧化碳储存通量对森林生态系统碳收支的影响

涡度相关系统观测高度以下的CO₂储存通量对准确评价森林生态系统与大气间净CO₂交换量（NEE）有着重要的影响.本研究以长白山阔叶红松林为研究对象,利用2003年的涡度相关观测数据以及CO₂浓度廓线数据,分析了CO₂储存通量的变化规律及其对碳收支过程的影响.结果表明：涡度相关观测高度以下的CO₂储存通量具有典型的日变化特征,其最大变化量出现在大气稳定与不稳定层结转换期.利用涡度相关系统观测的单点CO₂浓度变化方法与利用CO₂浓度廓线方法计算的CO₂储存通量差异不显著.忽略CO₂储存通量,在半小时尺度上会造成对夜间和白天的NEE分别低估25%和19%,在日和年尺度上,会对NEE低估10%和25%;忽略CO₂储存通量,会低估Michaelis-Menten光响应方程及Lloyd-Taylor呼吸方程的参数,并且对表观初始量子效率α和参考呼吸R_ref的低估最大;忽略CO₂储存通量,在半小时、日及年尺度上,均会对总光合作用（GPP）和生态系统呼吸（R_e）低估约20%.     

Representative estimates of soil and ecosystem respiration in an old beech forest

Respiration has been proposed to be the main determinant of the carbon balance in European forests and is thus essential for our understanding of the carbon cycle. However, the choice of experimental design strongly affects estimates of annual respiration and of the contribution of soil respiration to total ecosystem respiration. In a detailed study of ecosystem and soil respiration fluxes in an old unmanaged deciduous forest in Central Germany over 3 years (2000–2002), we combined soil chamber and eddy covariance measurements to obtain a comprehensive picture of respiration in this forest. The closed portable chambers offered to investigate spatial variability of soil respiration and its controls while the eddy covariance system offered continuous measurements of ecosystem respiration. Over the year, both fluxes were mainly correlated with temperature. However, when soil moisture sank below 23 vol.% in the upper 6 cm, water limitations also became apparent. The temporal resolution of the eddy covariance system revealed that relatively high respiration rates occurred during budbreak due to increased metabolic activity and after leaf fall because of increased decomposition. Spatial variability in soil respiration rates was large and correlated with fine root biomass (r ² = 0.56) resulting in estimates of annual efflux varying across plots from 730 to 1,258 (mean 898) g C m⁻² year⁻¹. Power function calculations showed that achieving a precision in the soil respiration estimate of 20% of the full population mean at a confidence level of 95%, requires about eight sampling locations. Our results can be used as guidelines to improve the representativeness of soil respiration measurements by nested sampling designs, being applied in long-term and large-scale carbon sequestration projects such as FLUXNET and CarboEurope.     

Evaluation of methods for estimating soil carbon dioxide efflux across a gradient of forest disturbance

Better understanding of variation in soil carbon dioxide (CO₂) efflux caused by measurement techniques is needed, especially over gradients of site disturbance, to accurately estimate the global carbon cycle. We present soil CO₂ efflux data from a gradient of disturbance to ponderosa pine (Pinus ponderosa C. Lawson var. scopulorum Engelm.) forests in northern Arizona, USA that were obtained using four different techniques: vented static chambers, a Licor 6400‐09, and soil CO₂ diffusion profiles using two different models (Moldrup, Millington–Quirk) to estimate soil gas diffusivity. We also compared soil CO₂ efflux measured by the Moldrup and Millington–Quirk diffusion profile methods to nighttime total ecosystem respiration (TER) data from an eddy covariance tower. We addressed four questions: (1) Does the use of a given method to measure soil CO₂ efflux bias results across a disturbance gradient? (2) Does the magnitude of difference between observed and modeled estimates of soil CO₂ differ between methods and across sites? (3) What is the spatial variability of each method at each site? (4) Which method is closest to the estimate of TER measured by the eddy covariance tower? Although soil CO₂ efflux varied significantly among methods the differences were consistent among sites. Measured and modeled total growing season fluxes were generally higher for the Licor 6400‐09 and Millington–Quirk diffusion gradient methods compared with static chamber and the Moldrup diffusion gradient methods. A power analysis showed that the larger static chamber was the most efficient method at sampling spatial variation in soil CO₂ efflux. Nighttime measurements of soil CO₂ efflux from the Moldrup diffusion gradient method were most strongly related to nighttime TER assessed with eddy covariance. The use of a single, well‐implemented method to measure soil CO₂ efflux is unlikely to create bias in comparisons across a gradient of forest disturbance.     

On the separation of net ecosystem exchange into assimilation and ecosystem respiration: review and improved algorithm

This paper discusses the advantages and disadvantages of the different methods that separate net ecosystem exchange (NEE) into its major components, gross ecosystem carbon uptake (GEP) and ecosystem respiration (R_eco). In particular, we analyse the effect of the extrapolation of night‐time values of ecosystem respiration into the daytime; this is usually done with a temperature response function that is derived from long‐term data sets. For this analysis, we used 16 one‐year‐long data sets of carbon dioxide exchange measurements from European and US‐American eddy covariance networks. These sites span from the boreal to Mediterranean climates, and include deciduous and evergreen forest, scrubland and crop ecosystems. We show that the temperature sensitivity of R_eco, derived from long‐term (annual) data sets, does not reflect the short‐term temperature sensitivity that is effective when extrapolating from night‐ to daytime. Specifically, in summer active ecosystems the long‐term temperature sensitivity exceeds the short‐term sensitivity. Thus, in those ecosystems, the application of a long‐term temperature sensitivity to the extrapolation of respiration from night to day leads to a systematic overestimation of ecosystem respiration from half‐hourly to annual time‐scales, which can reach >25% for an annual budget and which consequently affects estimates of GEP. Conversely, in summer passive (Mediterranean) ecosystems, the long‐term temperature sensitivity is lower than the short‐term temperature sensitivity resulting in underestimation of annual sums of respiration. We introduce a new generic algorithm that derives a short‐term temperature sensitivity of R_eco from eddy covariance data that applies this to the extrapolation from night‐ to daytime, and that further performs a filling of data gaps that exploits both, the covariance between fluxes and meteorological drivers and the temporal structure of the fluxes. While this algorithm should give less biased estimates of GEP and R_eco, we discuss the remaining biases and recommend that eddy covariance measurements are still backed by ancillary flux measurements that can reduce the uncertainties inherent in the eddy covariance data.     

Precipitation pulses enhance respiration of Mediterranean ecosystems: the balance between organic and inorganic components of increased soil CO2 efflux

In regions characterized by arid seasons, such as the Mediterranean basin, soil moisture is a major driver of ecosystem CO₂ efflux during periods of drought stress. Here, a rain event can induce a disproportional respiratory pulse, releasing an amount of CO₂ to the atmosphere that may significantly contribute to the annual ecosystem carbon balance. The mechanisms behind this pulse are unclear, and it is still unknown whether it is due to the stimulation of autotrophic, heterotrophic and/or inorganic CO₂ fluxes. On the Mediterranean island of Pianosa, eddy flux measurements showed respiratory pulses after rain events following prolonged drought periods, which occurred in the summer of 2003 and 2006. To investigate the mechanisms of this observed enhanced respiration fluxes and partition of the soil CO₂ sources, two water manipulation experiments were performed. The first was designed to estimate the effect of soil rewetting on soil CO₂ efflux, in the different ecosystem types existing on the island (i.e. woodland, ex‐agricultural and Mediterranean shrubland). The second was a soil CO₂ partitioning experiment to investigate the relative contribution of inorganic and organic CO₂ sources to soil respiration, under dry and wet soil conditions. Our results suggest that the pulse in the CO₂ efflux is primarily due to the enhancement of heterotrophic respiration, likely caused by the degradation of easily decomposable substrates, accumulated in soils during the dry period. In fact, the vegetation at the site was senescent and did not play any significant role in CO₂ exchange, as suggested by the absence of diurnal CO₂ uptake in eddy covariance measurements. In addition, soil rewetting did not significantly enhance inorganic CO₂ efflux.     

Forest ecosystem respiration estimated from eddy covariance and chamber measurements under high turbulence and substantial tree mortality from bark beetles

Eddy covariance nighttime fluxes are uncertain due to potential measurement biases. Many studies report eddy covariance nighttime flux lower than flux from extrapolated chamber measurements, despite corrections for low turbulence. We compared eddy covariance and chamber estimates of ecosystem respiration at the GLEES Ameriflux site over seven growing seasons under high turbulence [summer night mean friction velocity (u*) = 0.7 m s^?1], during which bark beetles killed or infested 85% of the aboveground respiring biomass. Chamber‐based estimates of ecosystem respiration during the growth season, developed from foliage, wood, and soil CO₂ efflux measurements, declined 35% after 85% of the forest basal area had been killed or impaired by bark beetles (from 7.1 ± 0.22 μmol m^?2 s^?1 in 2005 to 4.6 ± 0.16 μmol m^?2 s^?1 in 2011). Soil efflux remained at ~3.3 μmol m^?2 s^?1 throughout the mortality, while the loss of live wood and foliage and their respiration drove the decline of the chamber estimate. Eddy covariance estimates of fluxes at night remained constant over the same period, ~3.0 μmol m^?2 s^?1 for both 2005 (intact forest) and 2011 (85% basal area killed or impaired). Eddy covariance fluxes were lower than chamber estimates of ecosystem respiration (60% lower in 2005, and 32% in 2011), but the mean night estimates from the two techniques were correlated within a year (r² from 0.18 to 0.60). The difference between the two techniques was not the result of inadequate turbulence, because the results were robust to a u* filter of >0.7 m s^?1. The decline in the average seasonal difference between the two techniques was strongly correlated with overstory leaf area (r² = 0.92). The discrepancy between methods of respiration estimation should be resolved to have confidence in ecosystem carbon flux estimates.     

Gap filling strategies and error in estimating annual soil respiration

Soil respiration (R_soil) is one of the largest CO₂ fluxes in the global carbon (C) cycle. Estimation of annual R_soil requires extrapolation of survey measurements or gap filling of automated records to produce a complete time series. Although many gap filling methodologies have been employed, there is no standardized procedure for producing defensible estimates of annual R_soil. Here, we test the reliability of nine different gap filling techniques by inserting artificial gaps into 20 automated R_soil records and comparing gap filling R_soil estimates of each technique to measured values. We show that although the most commonly used techniques do not, on average, produce large systematic biases, gap filling accuracy may be significantly improved through application of the most reliable methods. All methods performed best at lower gap fractions and had relatively high, systematic errors for simulated survey measurements. Overall, the most accurate technique estimated R_soil based on the soil temperature dependence of R_soil by assuming constant temperature sensitivity and linearly interpolating reference respiration (R_soil at 10 °C) across gaps. The linear interpolation method was the second best‐performing method. In contrast, estimating R_soil based on a single annual R_soil – T_soil relationship, which is currently the most commonly used technique, was among the most poorly‐performing methods. Thus, our analysis demonstrates that gap filling accuracy may be improved substantially without sacrificing computational simplicity. Improved and standardized techniques for estimation of annual R_soil will be valuable for understanding the role of R_soil in the global C cycle.     

腾格里荒漠红砂-珍珠群落CO2收支变化及其不同观测方法间的比较

由于荒漠生态系统植被覆盖度低、生产力低下,其在全球碳循环中的作用被长期忽视。为探讨荒漠生态系统碳收支各组分的变化规律,以腾格里荒漠红砂(Reaumuria soongorica Maxim.)-珍珠(Salsola passerina Beg.)群落为研究对象,采用静态箱式法研究了该群落的净生态系统CO2交换量(NEE)、生态系统呼吸、土壤呼吸的日变化规律,同时将该方法所获得的NEE结果与涡动相关法观测的结果进行了比较。结果表明:(1)红砂-珍珠群落NEE的日变化表现为,在6:00—9:00左右出现一个CO2吸收的高峰值,随后在12:00—15:00左右出现一个CO2释放高峰值。红砂种群、珍珠种群和整个群落NEE的平均值分别为0.018、0.020和0.028 mg CO2m-2s-1;(2)红砂种群、珍珠种群、土壤及整个群落生态系统呼吸速率的日变化规律一致,均表现为明显的单峰变化趋势,在12:00—15:00左右出现一个CO2释放的高峰值。红砂种群、珍珠种群、土壤和整个群落的生态系统呼吸的平均值分别为:0.121、0.062、0.029和0.040 mg CO2m-2s-1。以盖度为加权因子计算得到红砂种群、珍珠种群和土壤呼吸占生态系统呼吸的比例分别为:9%、21%和70%,由此可见,生态系统呼吸主要来源于土壤呼吸。(3)将箱式法和涡动相关法观测的NEE进行比较,结果表明两种方法观测的NEE变化规律基本一致,相关系数达到0.7。采用箱式法观测的NEE高于涡动相关法观测的结果,平均值分别0.028 mg CO2m-2s-1(箱式法)和0.015 mg CO2m-2s-1(涡动相关法),涡动相关法的观测结果与箱式法观测结果的比值为0.54。综上可得,荒漠生态系统土壤呼吸的变化速率决定了生态系统呼吸的变化规律,采用箱式法可能高估了荒漠生态系统CO2的释放量。     

Soil CO2 efflux in contrasting boreal deciduous and coniferous stands and its contribution to the ecosystem carbon balance

Similar nonsteady‐state automated chamber systems were used to measure and partition soil CO₂ efflux in contrasting deciduous (trembling aspen) and coniferous (black spruce and jack pine) stands located within 100 km of each other near the southern edge of the Boreal forest in Canada. The stands were exposed to similar climate forcing in 2003, including marked seasonal variations in soil water availability, which provided a unique opportunity to investigate the influence of climate and stand characteristics on soil CO₂ efflux and to quantify its contribution to the net ecosystem CO₂ exchange (NEE) as measured with the eddy‐covariance technique. Partitioning of soil CO₂ efflux between soil respiration (including forest‐floor vegetation) and forest‐floor photosynthesis showed that short‐ and long‐term temporal variations of soil CO₂ efflux were related to the influence of (1) soil temperature and water content on soil respiration and (2) below‐canopy light availability, plant water status and forest‐floor plant species composition on forest‐floor photosynthesis. Overall, the three stands were weak to moderate sinks for CO₂ in 2003 (NEE of ?103, ?80 and ?28 g C m^?2 yr^?1 for aspen, black spruce and jack pine, respectively). Forest‐floor respiration accounted for 86%, 73% and 75% of annual ecosystem respiration, in the three respective stands, while forest‐floor photosynthesis contributed to 11% and 14% of annual gross ecosystem photosynthesis in the black spruce and jack pine stands, respectively. The results emphasize the need to perform concomitant measurements of NEE and soil CO₂ efflux at longer time scales in different ecosystems in order to better understand the impacts of future interannual climate variability and vegetation dynamics associated with climate change on each component of the carbon balance.     

Indirect partitioning of soil respiration in a series of evergreen forest ecosystems

A simple estimation of heterotrophic respiration can be obtained analytically as the y-intercept of the linear regression between soil-surface CO₂ efflux and root biomass. In the present study, a development of this indirect methodology is presented by taking into consideration both the temporal variation and the spatial heterogeneity of heterotrophic respiration. For this purpose, soil CO₂ efflux, soil carbon content and main stand characteristics were estimated in seven evergreen forest ecosystems along an elevation gradient ranging from 250 to 1740 m. For each site and for each sampling date the measured soil CO₂ efflux (R _S) was predicted with the model R _S = a × S _C + b × R _D ± ε, where S _C is soil carbon content per unit area to a depth of 30 cm and R _D is the root density of the 2–5 mm root class. Regressions with statistically significant a and b coefficients allowed the indirect separation of the two components of soil CO₂ efflux. Considering that the different sampling dates were characterized by different soil temperature, it was possible to investigate the temporal and thermal dependency of autotrophic and heterotrophic respiration. It was estimated that annual autotrophic respiration accounts for 16–58% of total soil CO₂ efflux in the seven different evergreen ecosystems. In addition, our observations show a decrease of annual autotrophic respiration at increasing availability of soil nitrogen. Section Editor: A. Hodge     

A scaling approach for quantifying the net CO2 flux of the Kuparuk River Basin,Alaska

Net CO₂ flux measurements conducted during the summer and winter of 1994–96 were scaled in space and time to provide estimates of net CO₂ exchange during the 1995–96 (9 May 1995–8 May 1996) annual cycle for the Kuparuk River Basin, a 9200 km² watershed located in NE Alaska. Net CO₂ flux was measured using dynamic chambers and eddy covariance in moist‐acidic, nonacidic, wet‐sedge, and shrub tundra, which comprise 95% of the terrestrial landscape of the Kuparuk Basin. CO₂ flux data were used as input to multivariate models that calculated instantaneous and daily rates of gross primary production (GPP) and whole‐ecosystem respiration (R) as a function of meteorology and ecosystem development. Net CO₂ flux was scaled up to the Kuparuk Basin using a geographical information system (GIS) consisting of a vegetation map, digital terrain map, dynamic temperature and radiation fields, and the models of GPP and R. Basin‐wide estimates of net CO₂ exchange for the summer growing season (9 May?5 September 1995) indicate that nonacidic tundra was a net sink of ?31.7 ± 21.3 GgC (1 Gg = 10⁹ g), while shrub tundra lost 32.5 ± 6.3 GgC to the atmosphere (negative values denote net ecosystem CO₂ uptake). Acidic and wet sedge tundra were in balance, and when integrated for the entire Kuparuk River Basin (including aquatic surfaces), whole basin summer net CO₂ exchange was estimated to be in balance (?0.9 ± 50.3 GgC). Autumn to winter (6 September 1995–8 May 1996) estimates of net CO₂ flux indicate that acidic, nonacidic, and shrub tundra landforms were all large sources of CO₂ to the atmosphere (75.5 ± 8.3, 96.4 ± 11.4, and 43.3 ± 4.7 GgC for acidic, nonacidic, and shrub tundra, respectively). CO₂ loss from wet sedge surfaces was not substantially different from zero, but the large losses from the other terrestrial landforms resulted in a whole basin net CO₂ loss of 217.2 ± 24.1 GgC during the 1995–96 cold season. When integrated for the 1995–96 annual cycle, acidic (66.4 + 25.25 GgC), nonacidic (64.7 ± 29.2 GgC), and shrub tundra (75.8 ± 8.4 GgC) were substantial net sources of CO₂ to the atmosphere, while wet sedge tundra was in balance (0.4 + 0.8 GgC). The Kuparuk River Basin as a whole was estimated to be a net CO₂ source of 218.1 ± 60.6 GgC over the 1995–96 annual cycle. Compared to direct measurements of regional net CO₂ flux obtained from aircraft‐based eddy covariance, the scaling procedure provided realistic estimates of CO₂ exchange during the summer growing season. Although winter estimates could not be assessed directly using aircraft measurements of net CO₂ exchange, the estimates reported here are comparable to measured values reported in the literature. Thus, we have high confidence in the summer estimates of net CO₂ exchange and reasonable confidence in the winter net CO₂ flux estimates for terrestrial landforms of the Kuparuk river basin. Although there is larger uncertainty in the aquatic estimates, the small surface area of aquatic surfaces in the Kuparuk river basin (≈ 5%) presumably reduces the potential for this uncertainty to result in large errors in basin‐wide CO₂ flux estimates.     

Modelling night‐time ecosystem respiration by a constrained source optimization method

One of the main challenges to quantifying ecosystem carbon budgets is properly quantifying the magnitude of night‐time ecosystem respiration. Inverse Lagrangian dispersion analysis provides a promising approach to addressing such a problem when measured mean CO₂ concentration profiles and nocturnal velocity statistics are available. An inverse method, termed ‘Constrained Source Optimization’ or CSO, which couples a localized near‐field theory (LNF) of turbulent dispersion to respiratory sources, is developed to estimate seasonal and annual components of ecosystem respiration. A key advantage to the proposed method is that the effects of variable leaf area density on flow statistics are explicitly resolved via higher‐order closure principles. In CSO, the source distribution was computed after optimizing key physiological parameters to recover the measured mean concentration profile in a least‐square fashion. The proposed method was field‐tested using 1 year of 30‐min mean CO₂ concentration and CO₂ flux measurements collected within a 17‐year‐old (in 1999) even‐aged loblolly pine (Pinus taeda L.) stand in central North Carolina. Eddy‐covariance flux measurements conditioned on large friction velocity, leaf‐level porometry and forest‐floor respiration chamber measurements were used to assess the performance of the CSO model. The CSO approach produced reasonable estimates of ecosystem respiration, which permits estimation of ecosystem gross primary production when combined with daytime net ecosystem exchange (NEE) measurements. We employed the CSO approach in modelling annual respiration of above‐ground plant components (c. 214 g C m^?2 year^?1) and forest floor (c. 989 g C m^?2 year^?1) for estimating gross primary production (c. 1800 g C m^?2 year^?1) with a NEE of c. 605 g C m^?2 year^?1 for this pine forest ecosystem. We conclude that the CSO approach can utilise routine CO₂ concentration profile measurements to corroborate forest carbon balance estimates from eddy‐covariance NEE and chamber‐based component flux measurements.     

On the assessment of root and soil respiration for soils of different textures: interactions with soil moisture contents and soil CO2 concentrations

Estimates of root and soil respiration are becoming increasingly important in agricultural and ecological research, but there is little understanding how soil texture and water content may affect these estimates. We examined the effects of soil texture on (i) estimated rates of root and soil respiration and (ii) soil CO₂ concentrations, during cycles of soil wetting and drying in the citrus rootstock, Volkamer lemon (Citrus volkameriana Tan. and Pasq.). Plants were grown in soil columns filled with three different soil mixtures varying in their sand, silt and clay content. Root and soil respiration rates, soil water content, plant water uptake and soil CO₂ concentrations were measured and dynamic relationships among these variables were developed for each soil texture treatment. We found that although the different soil textures differed in their plant-soil water relations characteristics, plant growth was only slightly affected. Root and soil respiration rates were similar under most soil moisture conditions for soils varying widely in percentages of sand, silt and clay. Only following irrigation did CO₂ efflux from the soil surface vary among soils. That is, efflux of CO₂ from the soil surface was much more restricted after watering (therefore rendering any respiration measurements inaccurate) in finer textured soils than in sandy soils because of reduced porosity in the finer textured soils. Accordingly, CO₂ reached and maintained the highest concentrations in finer textured soils (> 40 mmol CO₂ mol⁻¹). This study revealed that changes in soil moisture can affect interpretations of root and soil measurements based on CO₂ efflux, particularly in fine textured soils. The implications of the present findings for field soil CO₂ flux measurements are discussed. This revised version was published online in June 2006 with corrections to the Cover Date.     

Decrease in winter respiration explains 25% of the annual northern forest carbon sink enhancement over the last 30 years

Aim Winter snow has been suggested to regulate terrestrial carbon (C) cycling by modifying microclimate, but the impacts of change in snow cover on the annual C budget at a large scale are poorly understood. Our aim is to quantify the C balance under changing snow depth. Location Non‐permafrost region of the northern forest area. Methods Here, we used site‐based eddy covariance flux data to investigate the relationship between depth of snow cover and ecosystem respiration (R_eco) during winter. We then used the Biome‐BGC model to estimate the effect of reductions in winter snow cover on the C balance of northern forests in the non‐permafrost region. Results According to site observations, winter net ecosystem C exchange (NEE) ranged from 0.028 to 1.53 gC·m^?2·day^?1, accounting for 44 ± 123% of the annual C budget. Model simulation showed that over the past 30 years, snow‐driven change in winter C fluxes reduced non‐growing season CO₂ emissions, enhancing the annual C sink of northern forests. Over the entire study area, simulated winter R_eco significantly decreased by 0.33 gC·m^?2·day^?1·year^?1 in response to decreasing depth of snow cover, which accounts for approximately 25% of the simulated annual C sink trend from 1982 to 2009. Main conclusion Soil temperature is primarily controlled by snow cover rather than by air temperature as snow serves as an insulator to prevent chilling impacts. A shallow snow cover has less insulation potential, causing colder soil temperatures and potentially lower respiration rates. Both eddy covariance analysis and model‐simulated results show that both R_eco and NEE are significantly and positively correlated with variation in soil temperature controlled by variation in snow depth. Overall, our results highlight that a decrease in winter snow cover restrains global warming as less C is emitted to the atmosphere.     

Short‐term carbon cycling responses of a mature eucalypt woodland to gradual stepwise enrichment of atmospheric CO2 concentration

Projections of future climate are highly sensitive to uncertainties regarding carbon (C) uptake and storage by terrestrial ecosystems. The Eucalyptus Free‐Air CO₂ Enrichment (EucFACE) experiment was established to study the effects of elevated atmospheric CO₂ concentrations (eCO₂) on a native mature eucalypt woodland with low fertility soils in southeast Australia. In contrast to other FACE experiments, the concentration of CO₂ at EucFACE was increased gradually in steps above ambient (+0, 30, 60, 90, 120, and 150 ppm CO₂ above ambient of ~400 ppm), with each step lasting approximately 5 weeks. This provided a unique opportunity to study the short‐term (weeks to months) response of C cycle flux components to eCO₂ across a range of CO₂ concentrations in an intact ecosystem. Soil CO₂ efflux (i.e., soil respiration or R_soil) increased in response to initial enrichment (e.g., +30 and +60 ppm CO₂) but did not continue to increase as the CO₂ enrichment was stepped up to higher concentrations. Light‐saturated photosynthesis of canopy leaves (A_sat) also showed similar stimulation by elevated CO₂ at +60 ppm as at +150 ppm CO₂. The lack of significant effects of eCO₂ on soil moisture, microbial biomass, or activity suggests that the increase in R_soil likely reflected increased root and rhizosphere respiration rather than increased microbial decomposition of soil organic matter. This rapid increase in R_soil suggests that under eCO_2, additional photosynthate was produced, transported belowground, and respired. The consequences of this increased belowground activity and whether it is sustained through time in mature ecosystems under eCO₂ are a priority for future research.     

An analysis of soil respiration across northern hemisphere temperate ecosystems

Over two-thirds of terrestrial carbon is stored belowground and a significant amount of atmospheric CO₂ is respired by roots and microbes in soils. For this analysis, soil respiration (Rs) data were assembled from 31 AmeriFlux and CarboEurope sites representing deciduous broadleaf, evergreen needleleaf, grasslands, mixed deciduous/evergreen and woodland/savanna ecosystem types. Lowest to highest rates of soil respiration averaged over the growing season were grassland and woodland/savanna < deciduous broadleaf forests < evergreen needleleaf, mixed deciduous/evergreen forests with growing season soil respiration significantly different between forested and non-forested biomes (p < 0.001). Timing of peak respiration rates during the growing season varied from March/April in grasslands to July–September for all other biomes. Biomes with overall strongest relationship between soil respiration and soil temperature were from the deciduous and mixed forests (R² ≥ 0.65). Maximum soil respiration was weakly related to maximum fine root biomass (R² = 0.28) and positively related to the previous years’ annual litterfall (R² = 0.46). Published rates of annual soil respiration were linearly related to LAI and fine root carbon (R² = 0.48, 0.47), as well as net primary production (NPP) (R² = 0.44). At 10 sites, maximum growing season Rs was weakly correlated with annual GPP estimated from eddy covariance towersites (R² = 0.29; p < 0.05), and annual soil respiration and total growing season Rs were not correlated with annual GPP (p > 0.1). Yet, previous studies indicate correlations on shorter time scales within site (e.g., weekly, monthly). Estimates of annual GPP from the Biome-BGC model were strongly correlated with observed annual estimates of soil respiration for six sites (R² = 0.84; p < 0.01). Correlations from observations of Rs with NPP, LAI, fine root biomass and litterfall relate above and belowground inputs to labile pools that are available for decomposition. Our results suggest that simple empirical relationships with temperature and/or moisture that may be robust at individual sites may not be adequate to characterize soil CO₂ effluxes across space and time, agreeing with other multi-site studies. Information is needed on the timing and phenological controls of substrate availability (e.g., fine roots, LAI) and inputs (e.g., root turnover, litterfall) to improve our ability to accurately quantify the relationships between soil CO₂ effluxes and carbon substrate storage.For this study, these authors received significant contributions from: M. Aubinet, D. Baldocchi, C. Bernhofer, P. Bolstad, A. Bosc, J.L. Campbell, Y. Cheng, J. Curiel Yuste, P. Curtis, E.A. Davidson, D. Epron, A. Granier, T. Grünwald, D. Hollinger, I.A. Janssens, B. Longdoz, D. Loustau, J. Martin, R. Monson, W. Oechel, J. Pippen, F. Ponti, R. Ryel, K. Savage, L. Scott-Denton, J.-A. Subke, J. Tang, J. Tenhunen, V. Turcu, C. S. Vogel.     

Assessing the eddy covariance technique for evaluating carbon dioxide exchange rates of ecosystems: past, present and future

The eddy covariance technique ascertains the exchange rate of CO₂ across the interface between the atmosphere and a plant canopy by measuring the covariance between fluctuations in vertical wind velocity and CO₂ mixing ratio. Two decades ago, the method was employed to study CO₂ exchange of agricultural crops under ideal conditions during short field campaigns. During the past decade the eddy covariance method has emerged as an important tool for evaluating fluxes of carbon dioxide between terrestrial ecosystems and the atmosphere over the course of a year, and more. At present, the method is being applied in a nearly continuous mode to study carbon dioxide and water vapor exchange at over a hundred and eighty field sites, worldwide. The objective of this review is to assess the eddy covariance method as it is being applied by the global change community on increasingly longer time scales and over less than ideal surfaces. The eddy covariance method is most accurate when the atmospheric conditions (wind, temperature, humidity, CO₂) are steady, the underlying vegetation is homogeneous and it is situated on flat terrain for an extended distance upwind. When the eddy covariance method is applied over natural and complex landscapes or during atmospheric conditions that vary with time, the quantification of CO₂ exchange between the biosphere and atmosphere must include measurements of atmospheric storage, flux divergence and advection. Averaging CO₂ flux measurements over long periods (days to year) reduces random sampling error to relatively small values. Unfortunately, data gaps are inevitable when constructing long data records. Data gaps are generally filled with values produced from statistical and empirical models to produce daily and annual sums of CO₂ exchange. Filling data gaps with empirical estimates do not introduce significant bias errors because the empirical algorithms are derived from large statistical populations. On the other hand, flux measurement errors can be biased at night when winds are light and intermittent. Nighttime bias errors tend to produce an underestimate in the measurement of ecosystem respiration. Despite the sources of errors associated with long‐term eddy flux measurements, many investigators are producing defensible estimates of annual carbon exchange. When measurements come from nearly ideal sites the error bound on the net annual exchange of CO₂ is less than ±50 g C m^?2 yr^?1. Additional confidence in long‐term measurements is growing because investigators are producing values of net ecosystem productivity that are converging with independent values produced by measuring changes in biomass and soil carbon, as long as the biomass inventory studies are conducted over multiple years.     

Natural variations in snow cover do not affect the annual soil CO2 efflux from a mid‐elevation temperate forest

Climate change might alter annual snowfall patterns and modify the duration and magnitude of snow cover in temperate regions with resultant impacts on soil microclimate and soil CO₂ efflux (F_soil). We used a 5‐year time series of F_soil measurements from a mid‐elevation forest to assess the effects of naturally changing snow cover. Snow cover varied considerably in duration (105–154 days) and depth (mean snow depth 19–59 cm). Periodically shallow snow cover (<10 cm) caused soil freezing or increased variation in soil temperature. This was mostly not reflected in F_soil which tended to decrease gradually throughout winter. Progressively decreasing C substrate availability (identified by substrate induced respiration) likely over‐rid the effects of slowly changing soil temperatures and determined the overall course of F_soil. Cumulative CO₂ efflux from beneath snow cover varied between 0.46 and 0.95 t C ha^?1 yr^?1 and amounted to between 6 and 12% of the annual efflux. When compared over a fixed interval (the longest period of snow cover during the 5 years), the cumulative CO₂ efflux ranged between 0.77 and 1.18 t C ha^?1 or between 11 and 15% of the annual soil CO₂ efflux. The relative contribution (15%) was highest during the year with the shortest winter. Variations in snow cover were not reflected in the annual CO₂ efflux (7.44–8.41 t C ha^?1) which did not differ significantly between years and did not correlate with any snow parameter. Regional climate at our site was characterized by relatively high amounts of precipitation. Therefore, snow did not play a role in terms of water supply during the warm season and primarily affected cold season processes. The role of changing snow cover therefore seems rather marginal when compared to potential climate change effects on F_soil during the warm season.