The impact of sampling frequency and sampling times on chamber-based measurements of N2O emissions from fertilized soils

An automated closed‐chamber system was developed to measure N₂O fluxes in the field. It was deployed at two N‐fertilized grassland sites in two successive years, together with replicated manual chambers, to investigate the spatial and temporal variability in fluxes, and the likely impact of sampling frequency on cumulative flux values. The automated system provided flux data at 8‐h intervals, while manual sampling was conducted at intervals of 3–7 days. The autochambers showed fluctuations in emissions not detected by manual sampling. However, integrated flux values based on the more intensive measurements were on average no more than 14% greater than those based on data from the autochambers that were obtained at the same time as manual sampling. This difference was not significant and well within the spatial variability determined with manual chambers. If daily sampling intervals were used immediately after fertilization, the agreement was closer still, increasing the confidence that can be placed in manual procedures. Diurnal variations in temperature and flux were small, and results from sampling at mid‐day were not significantly different from those based on early morning or evening sampling. Where diurnal fluctuations in temperature and flux are likely to be much larger, the autochamber/sampler system could prove very useful to quantify the effect.     

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.     

Soil respiration fluxes measured along a hydrological gradient in a Norway spruce stand in south Sweden (Skogaby)

Soil respiration fluxes were measured continuously in order to assess the degree to which they were influenced by spatial and temporal variation in soil moisture. The synergistic effects of the variation in soil moisture with the one in soil temperature, soil organic matter and global radiation on respiration fluxes were also analysed. The measurements were performed using an open chamber system along a hydrological gradient in a Norway spruce forest in south Sweden (Skogaby) for 3 weeks in June 1995. The measured soil respiration fluxes were quite stable and somewhat larger compared with those reported in literature. The experiment took place during the shoot elongation period with intensive nutrient uptake, and it might be that soil respiration was dominated by mycorrhizal activity. Variation in the moisture content of the litter layer accounted for most of the spatial variation in respiration fluxes. This revised version was published online in June 2006 with corrections to the Cover Date.     

Evaluating the carbon balance estimate from an automated ground‐level flux chamber system in artificial grass mesocosms

Measuring and modeling carbon (C) stock changes in terrestrial ecosystems are pivotal in addressing global C‐cycling model uncertainties. Difficulties in detecting small short‐term changes in relatively large C stocks require the development of robust sensitive flux measurement techniques. Net ecosystem exchange (NEE) ground‐level chambers are increasingly used to assess C dynamics in low vegetation ecosystems but, to date, have lacked formal rigorous field validation against measured C stock changes. We developed and deployed an automated and multiplexed C‐flux chamber system in grassland mesocosms in order rigorously to compare ecosystem total C budget obtained using hourly C‐flux measurements versus destructive net C balance. The system combines transparent NEE and opaque respiration chambers enabling partitioning of photosynthetic and respiratory fluxes. The C‐balance comparison showed good agreement between the two methods, but only after NEE fluxes were corrected for light reductions due to chamber presence. The dark chamber fluxes allowed assessing temperature sensitivity of ecosystem respiration (R_eco) components (i.e., heterotrophic vs. autotrophic) at different growth stages. We propose that such automated flux chamber systems can provide an accurate C balance, also enabling pivotal partitioning of the different C‐flux components (e.g., photosynthesis and respiration) suitable for model evaluation and developments.     

Comparing the closed static versus the closed dynamic chamber flux methodology: Implications for soil respiration studies

Soil respiration is the largest C-flux component in the terrestrial carbon (C) cycle, yet in many biomes this flux and its environmental responses are still poorly understood. Several methodological techniques exist to measure this flux, but mostly there remain comparability uncertainties. For example, the closed static chamber (CSC) and the closed dynamic chamber (CDC) systems are widely used, but still require a rigorous comparison. A major issue with the CSC approach is the generally long manual gas sampling periods causing a potential underestimation of the calculated fluxes due to an asymptotic increase in headspace CO₂ concentrations. However, shortening the sampling periods of the static chamber approach might provide comparable results to the closed dynamic chamber system. We compared these two different chamber systems using replicated CSC cover boxes and a Li-Cor 8100 CDC system under field conditions, and performed tests on both, mineral and peat soil. Whereas the automated CDC system calculated fluxes during the first two minutes, the CSC approach considered either all seven manual sampling points taken over 75?min, or only the first three sampling points over 15?min. Although flux variation was fairly large, there were considerable and statistically significant differences between the calculated fluxes considering the two chamber systems, yet this depended on soil type and the number of CSC sampling time points. The cover-box approach underestimated the chamber-based fluxes by 30% for combined samples, 21% for mineral and 39% for peat soils when calculated over 75?min but was comparable over the first 15?min. The chamber flux comparison demonstrates that the CSC approach can provide CO₂ flux measurements comparable to the CDC system when sampling at an appropriate initial frequency, preventing flux underestimation due to a build up of CO₂ headspace concentrations.     

Short-term temperature impact on soil heterotrophic respiration in limed agricultural soil samples

This study sought to investigate the hourly and daily timescale responses of soil CO₂ fluxes to temperature in a limed agricultural soil. Observations from different incubation experiments were compared with the results of a model combining biotic (heterotrophic respiration) and abiotic (carbonate weathering) components. Several samples were pre-incubated for 8–9 days at three temperatures (5, 15 and 25 °C) and then submitted to short-term temperature (STT) cycles (where the temperature was increased from 5 to 35 °C in 10 °C stages, with each stage being 3 h long). During the temperature cycles (hourly timescale), the soil CO₂ fluxes increased significantly with temperature under all pre-incubation temperature (PIT) treatments. A hysteresis effect and negative fluxes during cooling phases were also systematically observed. At a given hourly timescale temperature, there was a negative relationship of the CO₂ fluxes with the PIT. Using the combined model allowed the experimental results to be clearly described, including the negative fluxes and the hysteresis effect, showing the potentially large contribution of abiotic fluxes to total fluxes in limed soils, after STT changes. The fairly good agreement between the measured and simulated flux results also suggested that the biotic flux temperature sensitivity was probably unaffected by timescale (hourly or daily) or PIT. The negative relationship of the CO₂ fluxes with the PIT probably derived from very labile soil carbon depletion, as shown in the simulations. This was not, however, confirmed by soil carbon measurements, which leaves open the possibility of adaptation within the microbial community.     

长白山温带混交林林冠下层CO2通量对生态系统碳收支的贡献

作为ChinaFLUX的重要组成部分,从2002年年底开始利用涡度协方差技术在长白山温带混交林林冠上层和下层进行连续通量观测,这为量化林冠下层CO2通量对整个森林生态系统碳收支的贡献提供了一条有效途径.利用2003年林冠上层和林冠下层的观测数据,研究表明林冠下层夜间的CO2通量与5 cm深度的土壤温度存在明显的指数正相关关系.林冠下层的呼吸通量与箱式法观测的土壤呼吸通量之间具有很好的一致性(R2=0.77),二者在全年都与整个森林的光合产物量相耦合,且都在7～8月份达到最大值.林冠下层的呼吸量和土壤呼吸量分别为770 g Cm-2a-1和703 g Cm-2a-1,占整个森林生态系统呼吸年总量的比重高达59.88%和54.69%.林冠下层的光合作用呈双峰型季节变化,两个峰值分别出现在5月中旬和8月下旬.尽管全年林冠下层光合产物量为87 g Cm-2a-1,对整个森林光合产物量的贡献率仅为5.69%,但林冠郁闭度低的4、5月和10月份,林冠下层的光合产物贡献率也分别达到19.99%、21.06%和14.53%.林冠下层净初级生产力的季节动态受该层呼吸作用的季节变异控制,林冠下层在全年都表现为碳源,其净碳排放速率在8月份达到最大.     

CO2 flux from soil in pastures and forests in southwestern Amazonia

Stocks of carbon in Amazonian forest biomass and soils have received considerable research attention because of their potential as sources and sinks of atmospheric CO₂. Fluxes of CO₂ from soil to the atmosphere, on the other hand, have not been addressed comprehensively in regard to temporal and spatial variations and to land cover change, and have been measured directly only in a few locations in Amazonia. Considerable variation exists across the Amazon Basin in soil properties, climate, and management practices in forests and cattle pastures that might affect soil CO₂ fluxes. Here we report soil CO₂ fluxes from an area of rapid deforestation in the southwestern Amazonian state of Acre. Specifically we addressed (1) the seasonal variation of soil CO₂ fluxes, soil moisture, and soil temperature; (2) the effects of land cover (pastures, mature, and secondary forests) on these fluxes; (3) annual estimates of soil respiration; and (4) the relative contributions of grass‐derived and forest‐derived C as indicated by δ¹³CO₂. Fluxes were greatest during the wet season and declined during the dry season in all land covers. Soil respiration was significantly correlated with soil water‐filled pore space but not correlated with temperature. Annual fluxes were higher in pastures compared with mature and secondary forests, and some of the pastures also had higher soil C stocks. The δ¹³C of CO₂ respired in pasture soils showed that high respiration rates in pastures were derived almost entirely from grass root respiration and decomposition of grass residues. These results indicate that the pastures are very productive and that the larger flux of C cycling through pasture soils compared with forest soils is probably due to greater allocation of C belowground. Secondary forests had soil respiration rates similar to mature forests, and there was no correlation between soil respiration and either forest age or forest biomass. Hence, belowground allocation of C does not appear to be directly related to the stature of vegetation in this region. Variation in seasonal and annual rates of soil respiration of these forests and pastures is more indicative of flux of C through the soil rather than major net changes in ecosystem C stocks.     

哀牢山中山湿性常绿阔叶林土壤呼吸季节和昼夜变化特征及影响因子比较

 由于受到多种生物和非生物因素的影响,土壤呼吸在不同时间尺度上的动态变化可能不一致。对不同时间尺度的土壤呼吸动态变化的研究有助 于深入了解土壤呼吸变化的机理,也有利于精确推算土壤碳的排放。采用红外CO₂分析法测定哀牢山中山湿性常绿阔叶林季节间(2004年4月～ 2005年3月)和昼夜间 (2004年7、9和11月及2005年1、3和5月共6次)的土壤呼吸。哀牢山中山湿性常绿阔叶林中土壤呼吸的季节变化显著,其中 湿季(5～10月)的土壤呼吸高于干季(11月～翌年4月),全年土壤呼吸的平均值为0.442 g CO₂&;#8226;m^－2&;#8226;h^－1。6 次测定的土壤呼吸日变化模式并不 相同,7和9月、翌年1和3月夜间土壤呼吸大于昼间土壤呼吸,11月和翌年5月则相反;5、7和9月昼夜间的土壤呼吸最大值与最小值的差异比11 月、翌年1和3月的测定结果大。季节间土壤呼吸与土壤温度(p=0.000)和土壤含水量(p=0. 007) 均有显著的指数相关,土壤温度可以解释土壤 呼吸变化的56.1％,土壤含水量可以解释土壤呼吸变化的11.1％。不同季节测定的土壤呼吸日变化与土壤温度、气温和土壤含水量则没有显著 的指数相关。由土壤呼吸与土壤温度拟合的指数方程计算Q₁₀值,在温度为 5.9～16.6 ℃内,全年土壤呼吸的Q₁₀值为4.53,在温度为5.9～ 11.0 ℃内,干季土壤呼吸的Q₁₀值为7.17,在温度为10.3～16.6 ℃内,湿季土壤呼吸的Q₁₀值为2.34。在不同时间尺度上,生物和非生物因素 对哀牢山中山湿性常绿阔叶林的土壤呼吸表现出不同的影响。土壤呼吸的季节变化主要受非生物因子温度和水分变化的调控,而土壤呼吸的昼 夜变化则可能主要受植物的生理活动周期性等生物因素的影响。通过温度的指数函数关系,用土壤呼吸的瞬时值来推算土壤呼吸的日通量和年 通量时,需要考虑温度和水分外的其它生物因子的影响。     

Temporal Variability of CO<Subscript>2</Subscript> and N<Subscript>2</Subscript>O Flux Spatial Patterns at a Mowed and a Grazed Grassland

Spatial patterns of ecosystem processes constitute significant sources of uncertainty in greenhouse gas flux estimations partly because the patterns are temporally dynamic. The aim of this study was to describe temporal variability in the spatial patterns of grassland CO₂ and N₂O flux under varying environmental conditions and to assess effects of the grassland management (grazing and mowing) on flux patterns. We made spatially explicit measurements of variables including soil respiration, aboveground biomass, N₂O flux, soil water content, and soil temperature during a 4-year study in the vegetation periods at grazed and mowed grasslands. Sampling was conducted in 80 × 60 m grids of 10 m resolution with 78 sampling points in both study plots. Soil respiration was monitored nine times, and N₂O flux was monitored twice during the study period. Altitude, soil organic carbon, and total soil nitrogen were used as background factors at each sampling position, while aboveground biomass, soil water content, and soil temperature were considered as covariates in the spatial analysis. Data were analyzed using variography and kriging. Altitude was autocorrelated over distances of 40–50 m in both plots and influenced spatial patterns of soil organic carbon, total soil nitrogen, and the covariates. Altitude was inversely related to soil water content and aboveground biomass and positively related to soil temperature. Autocorrelation lengths for soil respiration were similar on both plots (about 30 m), whereas autocorrelation lengths of N₂O flux differed between plots (39 m in the grazed plot vs. 18 m in the mowed plot). Grazing appeared to increase heterogeneity and linkage of the spatial patterns, whereas mowing had a homogenizing effect. Spatial patterns of soil water content, soil respiration, and aboveground biomass were temporally variable especially in the first 2 years of the experiment, whereas spatial patterns were more persistent (mostly significant correlation at p < 0.05 between location ranks) in the second 2 years, following a wet year. Increased persistence of spatial patterns after a wet year indicated the recovery potential of grasslands following drought and suggested that adequate water supply could have a homogenizing effect on CO₂ and N₂O fluxes.     

Soil water content and temperature as independent or confounded factors controlling soil respiration in a temperate mixed hardwood forest

Variation in soil temperature can account for most of the seasonal and diel variation in soil CO₂ efflux, but the temperature effect is not always consistent, and other factors such as soil water content are known to influence soil respiration. The objectives of this research were to study the spatial and temporal variation in soil respiration in a temperate forested landscape and to evaluate temperature and soil water functions as predictors of soil respiration. Soil CO₂ fluxes were measured with chambers throughout an annual cycle in six study areas at the Harvard Forest in central Massachusetts that include soil drainage classes from well drained to very poorly drained. The mean annual estimate of soil CO₂ efflux was 7.2 Mg ha^–1, but ranged from 5.3 in the swamp site to 8.5 in a well-drained site, indicating that landscape heterogeneity is related to soil drainage class. An exponential function relating CO₂ fluxes to soil temperature accounted for 80% of the seasonal variation in fluxes across all sites (Q₁₀ = 3.9), but the Q₁₀ ranged from 3.4 to 5.6 for the individual study sites. A significant drought in 1995 caused rapid declines in soil respiration rates in August and September in five of the six sites (a swamp site was the exception). This decline in CO₂ fluxes correlated exponentially with decreasing soil matric potential, indicating a mechanistic effect of drought stress. At moderate to high water contents, however, soil water content was negatively correlated with soil temperature, which precluded distinguishing between the effects of these two confounded factors on CO₂ flux. Occurrence of high Q₁₀ values and variation in Q₁₀ values among sites may be related to: (i) confounding effects of high soil water content; (ii) seasonal and diel patterns in root respiration and turnover of fine roots that are linked to above ground phenology and metabolism; and (iii) variation in the depth where CO₂ is produced. The Q₁₀ function can yield reasonably good predictions of annual fluxes of CO₂, but it is a simplification that masks responses of root and microbial processes to variation in temperature and water content throughout the soil.     

Frontiers and challenges in soil respiration research: from measurements to model-data integration

Soil respiration, the flux of CO₂ from the soil to the atmosphere represents a major flux in the global carbon cycle. Our ability to predict this flux remains limited because of multiple controlling mechanisms that interact over different temporal and spatial scales. However, new advances in measurement and analyses present an opportunity for the scientific community to improve the understanding of the mechanisms that regulate soil respiration. In this paper, we address several recent advancements in soil respiration research from experimental measurements and data analysis to new considerations for model-data integration. We focus on the links between the soil?Cplant-atmosphere continuum at short (i.e., diel) and medium (i.e., seasonal-years) temporal scales. First, we bring attention to the importance of identifying sources of soil CO₂ production and highlight the application of automated soil respiration measurements and isotope approaches. Second, we discuss the need of quality assurance and quality control for applications in time series analysis. Third, we review perspectives about emergent ideas for modeling development and model-data integration for soil respiration research. Finally, we call for stronger interactions between modelers and experimentalists as a way to improve our understanding of soil respiration and overall terrestrial carbon cycling.     

Tree photosynthesis modulates soil respiration on a diurnal time scale

To estimate how tree photosynthesis modulates soil respiration, we simultaneously and continuously measured soil respiration and canopy photosynthesis over an oak‐grass savanna during the summer, when the annual grass between trees was dead. Soil respiration measured under a tree crown reflected the sum of rhizosphere respiration and heterotrophic respiration; soil respiration measured in an open area represented heterotrophic respiration. Soil respiration was measured using solid‐state CO₂ sensors buried in soils and the flux‐gradient method. Canopy photosynthesis was obtained from overstory and understory flux measurements using the eddy covariance method. We found that the diurnal pattern of soil respiration in the open was driven by soil temperature, while soil respiration under the tree was decoupled with soil temperature. Although soil moisture controlled the seasonal pattern of soil respiration, it did not influence the diurnal pattern of soil respiration. Soil respiration under the tree controlled by the root component was strongly correlated with tree photosynthesis, but with a time lag of 7–12 h. These results indicate that photosynthesis drives soil respiration in addition to soil temperature and moisture.     

Soil Respiration in the Cold Desert Environment of the Colorado Plateau (USA): Abiotic Regulators and Thresholds

Decomposition is central to understanding ecosystem carbon exchange and nutrient-release processes. Unlike mesic ecosystems, which have been extensively studied, xeric landscapes have received little attention; as a result, abiotic soil-respiration regulatory processes are poorly understood in xeric environments. To provide a more complete and quantitative understanding about how abiotic factors influence soil respiration in xeric ecosystems, we conducted soil- respiration and decomposition-cloth measurements in the cold desert of southeast Utah. Our study evaluated when and to what extent soil texture, moisture, temperature, organic carbon, and nitrogen influence soil respiration and examined whether the inverse-texture hypothesis applies to decomposition. Within our study site, the effect of texture on moisture, as described by the inverse texture hypothesis, was evident, but its effect on decomposition was not. Our results show temperature and moisture to be the dominant abiotic controls of soil respiration. Specifically, temporal offsets in temperature and moisture conditions appear to have a strong control on soil respiration, with the highest fluxes occurring in spring when temperature and moisture were favorable. These temporal offsets resulted in decomposition rates that were controlled by soil moisture and temperature thresholds. The highest fluxes of CO₂ occurred when soil temperature was between 10 and 16 °C and volumetric soil moisture was greater than 10%. Decomposition-cloth results, which integrate decomposition processes across several months, support the soil-respiration results and further illustrate the seasonal patterns of high respiration rates during spring and low rates during summer and fall. Results from this study suggest that the parameters used to predict soil respiration in mesic ecosystems likely do not apply in cold-desert environments.     

A geostatistical approach to the field-scale pattern of heterotrophic soil CO2 emission using covariates

Soil heterotrophic respiration fluxes at field scale may exhibit a substantial spatial variability. The aim of this study was (1) to elucidate the role of soil temperature and different carbon fractions on heterotrophic soil respiration and (2) to test by which of three different statistical approaches (multiple regression, external drift kriging and simulated annealing) such influences may be best represented. Chamber-based measurements of respiration fluxes were carried out within a 180 × 40 m bare soil plot. Soil temperature was measured simultaneously to the flux measurements. Further, we recorded total soil organic carbon content, apparent electrical conductivity as well as mid-infrared spectroscopy-based carbon fractions as co-variates in addition to basic soil properties like stone content and texture. A stepwise multiple linear regression procedure was used to spatially predict bare soil respiration from the co-variates. The results showed that the particulate organic matter (POM) fraction and terrain elevation were able to explain the spatial pattern of heterotrophic soil respiration (R ² = 0.45). In a second step we applied external drift kriging to determine the improvement of using co-variates in an estimation procedure in comparison to ordinary kriging. The maximum relative improvement using the co-variates in terms of the root mean square error was 16%. In a third step we applied simulated annealing to perform stochastic simulations conditioned with external drift kriging to generate more realistic spatial patterns of heterotrophic respiration at plot scale. The conditional stochastic simulations revealed a significantly improved reproduction of the probability density function, the G-statistics value increased from 0.36 to 0.92. Further, the error in the reproduction of the semivariogram of the original point data decreased by more than one order of magnitude. All this confirmed that the mapping of soil respiration patterns may be significantly improved when considering terrain elevation and spatial heterogeneity of POM in combination with a conditional stochastic simulation.     

Seasonal and spatial variability of soil respiration in four Sitka spruce stands

We investigated the causes for the seasonal and spatial variation of soil respiration in a first rotation Sitka spruce chronosequence composed of four age classes (10, 15, 31, and 47 year old) in Central Ireland. The study aimed at identifying easily determinable environmental parameters that explained the variation in soil respiration rates. The variation in temperature and soil water content influenced the seasonal trend observed in the spatial variability of soil respiration. The highest coefficients of variation in soil respiration were observed during autumn drought, while lower coefficients were generally observed during periods with highest soil respiration rates. On average, the sampling strategy of 30 sampling points per stand was adequate to obtain an average rate of soil respiration within 20% of its actual value at the 95% confidence level. Significantly higher soil respiration rates were observed at locations with high accumulation of organic matter and in collars established in close vicinity to tree stems. The organic layer thickness was the only variable that yielded significant regressions for explaining spatial variation in soil respiration in all the stands. Correlation analyses between the studied variables and soil respiration suggested the relative importance of heterotrophic and autotrophic components differed in their annual contribution to total soil respiration at each forest stand. Multiple regression analyses were used to assess the relative importance of primary temporal and spatial controls over soil respiration. Soil temperature and organic layer thickness explained most of the variance of soil respiration for the different sampling periods, while soil water content had a weaker effect as well as a different influence on soil respiration depending on the time of the year. The strong linear correlation between forest floor carbon and soil carbon stock further confirmed organic layer thickness as an integrative factor encompassing the effect of soil carbon pools on soil respiration. Moreover, its inclusion in the multiple regression analyses overrode the influence of both distance and fine root biomass. Overall, a multiple linear regression model driven by easily determinable environmental variables such as soil temperature, organic thickness, soil water content, soil bulk density, and soil organic carbon concentration allowed us to explain 54% of total variance of soil respiration over the different stand ages for the entire year (P < 0.05). Our results show that the adoption of an adequate sampling strategy, and the determination of some key environmental variables may help to explain a large proportion of total variation of soil respiration over the entire rotation length of afforested ecosystems.     

Environmental Drivers of Benthic Flux Variation and Ecosystem Functioning in Salish Sea and Northeast Pacific Sediments

The upwelling of deep waters from the oxygen minimum zone in the Northeast Pacific from the continental slope to the shelf and into the Salish Sea during spring and summer offers a unique opportunity to study ecosystem functioning in the form of benthic fluxes along natural gradients. Using the ROV ROPOS we collected sediment cores from 10 sites in May and July 2011, and September 2013 to perform shipboard incubations and flux measurements. Specifically, we measured benthic fluxes of oxygen and nutrients to evaluate potential environmental drivers of benthic flux variation and ecosystem functioning along natural gradients of temperature and bottom water dissolved oxygen concentrations. The range of temperature and dissolved oxygen encountered across our study sites allowed us to apply a suite of multivariate analyses rarely used in flux studies to identify bottom water temperature as the primary environmental driver of benthic flux variation and organic matter remineralization. Redundancy analysis revealed that bottom water characteristics (temperature and dissolved oxygen), quality of organic matter (chl a:phaeo and C:N ratios) and sediment characteristics (mean grain size and porosity) explained 51.5% of benthic flux variation. Multivariate analyses identified significant spatial and temporal variation in benthic fluxes, demonstrating key differences between the Northeast Pacific and Salish Sea. Moreover, Northeast Pacific slope fluxes were generally lower than shelf fluxes. Spatial and temporal variation in benthic fluxes in the Salish Sea were driven primarily by differences in temperature and quality of organic matter on the seafloor following phytoplankton blooms. These results demonstrate the utility of multivariate approaches in differentiating among potential drivers of seafloor ecosystem functioning, and indicate that current and future predictive models of organic matter remineralization and ecosystem functioning of soft-muddy shelf and slope seafloor habitats should consider bottom water temperature variation. Bottom temperature has important implications for estimates of seasonal and spatial benthic flux variation, benthic–pelagic coupling, and impacts of predicted ocean warming at high latitudes.     

Carbon dioxide fluxes in a spatially and temporally heterogeneous temperate grassland

Landscape position, grazing, and seasonal variation in precipitation and temperature create spatial and temporal variability in soil processes, and plant biomass and composition in grasslands. However, it is unclear how this variation in plant and soil properties affects carbon dioxide (CO₂) fluxes. The aim of this study is to explore the effect of grazing, topographic position, and seasonal variation in soil moisture and temperature on plant assimilation, shoot and soil respiration, and net ecosystem CO₂ exchange (NEE). Carbon dioxide fluxes, vegetation, and environmental variables were measured once a month inside and outside long-term ungulate exclosures in hilltop (dry) to slope bottom (mesic) grassland throughout the 2004 growing season in Yellowstone National Park. There was no difference in vegetation properties and CO₂ fluxes between the grazed and the ungrazed sites. The spatial and temporal variability in CO₂ fluxes were related to differences in aboveground biomass and total shoot nitrogen content, which were both related to variability in soil moisture. All sites were CO₂ sinks (NEE>0) for all our measurments taken throughout the growing season; but CO₂ fluxes were four- to fivefold higher at sites supporting the most aboveground biomass located at slope bottoms, compared to the sites with low biomass located at hilltops or slopes. The dry sites assimilated more CO₂ per gram aboveground biomass and stored proportionally more of the gross-assimilated CO₂ in the soil, compared to wet sites. These results indicate large spatio-temporal variability of CO₂ fluxes and suggest factors that control the variability in Yellowstone National Park.     

A new assessment of European forests carbon exchanges by eddy fluxes and artificial neural network spatialization

Recently flux tower data have become available for a variety of ecosystems under different climatic and edaphic conditions. Although Flux tower data represent point measurements with a footprint of typically 1 km × 1 km they can be used to validate models and to spatialize biospheric fluxes at regional and continental scales. In this paper we present a study where biospheric flux data collected in the EUROFLUX project were used to train a neural network simulator to provide spatial (1 km × 1 km) and temporal (weekly) estimates of carbon fluxes of European forests at continental scale. The novelty of the approach is that flux data were used to constrain and parameterize the neural network structure using a limited number of input driving variables. The overall European carbon uptake from this analysis was 0.47 Gt C yr^?1 with distinctive differences between boreal and temperate regions. The length of the growing season is longer in the south of Europe (about 32 weeks), compared with north and central Europe, which have a similar length‐growing season (about 27 weeks). A peak in respiration was depicted in spring at continental scale as a coherent signal which parallel the construction respiration increase at the onset of the season as usually shown by leaf level measurements.     

基于湿度分布特征的小尺度土壤碳通量空间采样策略

由于土壤碳通量的空间异质性很强,传统的随机抽样方法无法对区域土壤碳通量进行准确估算,而多点采样需耗费大量的人力及设备成本,因此确定适当的采样点数量及分布策略对于区域土壤碳通量的测算非常重要。提出一种基于湿度空间分布特征的小尺度土壤碳通量空间采样策略:首先利用无线传感网密集测量区域的土壤湿度,根据湿度数据的空间分布特征划分监测区域,通过Hammond Mc Cullagh方程计算各子区域内的最优采样点数量,最终确定整个监测区域的空间采样点部署策略。提出的方法考虑了各子区域间土壤碳通量空间分布的差异,使得采样点的部署位置与土壤碳通量的分布具有较好的相关性。研究结果证明:土壤碳通量部署策略能够获得比均匀部署策略、随机部署策略更高的区域土壤碳通量估算准确度。