Estimating Soil Organic Carbon Stocks and Spatial Patterns with Statistical and GIS-Based Methods

Accurately quantifying soil organic carbon (SOC) is considered fundamental to studying soil quality, modeling the global carbon cycle, and assessing global climate change. This study evaluated the uncertainties caused by up-scaling of soil properties from the county scale to the provincial scale and from lower-level classification of Soil Species to Soil Group, using four methods: the mean, median, Soil Profile Statistics (SPS), and pedological professional knowledge based (PKB) methods. For the SPS method, SOC stock is calculated at the county scale by multiplying the mean SOC density value of each soil type in a county by its corresponding area. For the mean or median method, SOC density value of each soil type is calculated using provincial arithmetic mean or median. For the PKB method, SOC density value of each soil type is calculated at the county scale considering soil parent materials and spatial locations of all soil profiles. A newly constructed 1∶50,000 soil survey geographic database of Zhejiang Province, China, was used for evaluation. Results indicated that with soil classification levels up-scaling from Soil Species to Soil Group, the variation of estimated SOC stocks among different soil classification levels was obviously lower than that among different methods. The difference in the estimated SOC stocks among the four methods was lowest at the Soil Species level. The differences in SOC stocks among the mean, median, and PKB methods for different Soil Groups resulted from the differences in the procedure of aggregating soil profile properties to represent the attributes of one soil type. Compared with the other three estimation methods (i.e., the SPS, mean and median methods), the PKB method holds significant promise for characterizing spatial differences in SOC distribution because spatial locations of all soil profiles are considered during the aggregation procedure.     

Spatial Variability in Decomposition Rates in a Desert Scrub of Northwestern Mexico

The decomposition of leaf litter for five dominant plant species of a desert scrub in Baja California Sur, Mexico was investigated. We designed a factorial decomposition experiment using decomposition bags and the collected leaf-litter from Prosopis articulata, Jatropha cinerea, J. cuneata, Cyrtocarpa edulis, and Fouquieria diguetti. Factors, such as radiation exposure, rainfall, and the size of litter-consuming organisms were considered. The rates of litter decomposition were calculated for these plant species and the environmental conditions by using single exponential models. The initial concentration of nutrients (C, N, P, K, and Ca) and crude-fiber content of the leaf litter were determined. Our results show that the environmental heterogeneity generated by different conditions of radiation exposure and short-term rainfall patterns are the most relevant factors affecting decomposition processes in this Sonoran desert community. A species-specific pattern was observed in decay rates and mass-loss patterns. Decomposition rates varied from 0.0027 to 0.0201 depending on the species and exposure to different ecological conditions. The decay rates were higher under bare-soil conditions and during a wet year than under the shade provided by the canopy of nurse trees and during a dry year. The leaf litter of J. cuneata reincorporated to the soil more rapidly than that of P. articulata and C. edulis. Termites were the more important macroarthropods associated with litter decomposition, and their harvest distribution was independent of the resources distribution. The ecological significance of these results is discussed considering the extreme climatic conditions prevailing in this region.     

Spatial Distribution of Soil Organic Carbon and Its Influencing Factors in Desert Grasslands of the Hexi Corridor,Northwest China

Knowledge of the distribution patterns of soil organic carbon (SOC) and factors that influence these patterns is crucial for understanding the carbon cycle. The objectives of this study were to determine the spatial distribution pattern of soil organic carbon density (SOCD) and the controlling factors in arid desert grasslands of northwest China. The above- and belowground biomass and SOCD in 260 soil profiles from 52 sites over 2.7×10⁴ km² were investigated. Combined with a satellite-based dataset of an enhanced vegetation index during 2011–2012 and climatic factors at different sites, the relationships between SOCD and biotic and abiotic factors were identified. The results indicated that the mean SOCD was 1.20 (SD:+/− 0.85), 1.73 (SD:+/− 1.20), and 2.69 (SD:+/− 1.91) kg m⁻² at soil depths of 0–30 cm, 0–50 cm, and 0–100 cm, respectively, which was smaller than other estimates in temperate grassland, steppe, and desert-grassland ecosystems. The spatial distribution of SOCD gradually decreased from the southeast to the northwest, corresponding to the precipitation gradient. SOCD increased significantly with vegetation biomass, annual precipitation, soil moisture, clay and silt content, and decreased with mean annual temperature and sand content. The correlation between BGB and SOCD was closer than the correlation between AGB and SOCD. Variables could together explain about 69.8%, 74.4%, and 78.9% of total variation in SOCD at 0–30 cm, 0–50 cm, and 0–100 cm, respectively. In addition, we found that mean annual temperature is more important than other abiotic factors in determining SOCD in arid desert grasslands in our study area. The information obtained in this study provides a basis for accurately estimating SOC stocks and assessing carbon (C) sequestration potential in the desert grasslands of northwest China.     

Spatial Variability of the Topsoil Organic Carbon in the Moso Bamboo Forests of Southern China in Association with Soil Properties

Understanding the spatial variability of soil organic carbon (SOC) must be enhanced to improve sampling design and to develop soil management strategies in terrestrial ecosystems. Moso bamboo (Phyllostachys pubescens Mazel ex Houz.) forests have a high SOC storage potential; however, they also vary significantly spatially. This study investigated the spatial variability of SOC (0-20 cm) in association with other soil properties and with spatial variables in the Moso bamboo forests of Jian’ou City, which is a typical bamboo hometown in China. 209 soil samples were collected from Moso bamboo stands and then analyzed for SOC, bulk density (BD), pH, cation exchange capacity (CEC), and gravel content (GC) based on spatial distribution. The spatial variability of SOC was then examined using geostatistics. A Kriging map was produced through ordinary interpolation and required sample numbers were calculated by classical and Kriging methods. An aggregated boosted tree (ABT) analysis was also conducted. A semivariogram analysis indicated that ln(SOC) was best fitted with an exponential model and that it exhibited moderate spatial dependence, with a nugget/sill ratio of 0.462. SOC was significantly and linearly correlated with BD (r = −0.373**), pH (r = −0.429**), GC (r = −0.163*), CEC (r = 0.263**), and elevation (r = 0.192**). Moreover, the Kriging method requires fewer samples than the classical method given an expected standard error level as per a variance analysis. ABT analysis indicated that the physicochemical variables of soil affected SOC variation more significantly than spatial variables did, thus suggesting that the SOC in Moso bamboo forests can be strongly influenced by management practices. Thus, this study provides valuable information in relation to sampling strategy and insight into the potential of adjustments in agronomic measure, such as in fertilization for Moso bamboo production.     

Digital Mapping of Soil Organic Carbon Contents and Stocks in Denmark

Estimation of carbon contents and stocks are important for carbon sequestration, greenhouse gas emissions and national carbon balance inventories. For Denmark, we modeled the vertical distribution of soil organic carbon (SOC) and bulk density, and mapped its spatial distribution at five standard soil depth intervals (0−5, 5−15, 15−30, 30−60 and 60−100 cm) using 18 environmental variables as predictors. SOC distribution was influenced by precipitation, land use, soil type, wetland, elevation, wetness index, and multi-resolution index of valley bottom flatness. The highest average SOC content of 20 g kg⁻¹ was reported for 0−5 cm soil, whereas there was on average 2.2 g SOC kg⁻¹ at 60−100 cm depth. For SOC and bulk density prediction precision decreased with soil depth, and a standard error of 2.8 g kg⁻¹ was found at 60−100 cm soil depth. Average SOC stock for 0−30 cm was 72 t ha⁻¹ and in the top 1 m there was 120 t SOC ha⁻¹. In total, the soils stored approximately 570 Tg C within the top 1 m. The soils under agriculture had the highest amount of carbon (444 Tg) followed by forest and semi-natural vegetation that contributed 11% of the total SOC stock. More than 60% of the total SOC stock was present in Podzols and Luvisols. Compared to previous estimates, our approach is more reliable as we adopted a robust quantification technique and mapped the spatial distribution of SOC stock and prediction uncertainty. The estimation was validated using common statistical indices and the data and high-resolution maps could be used for future soil carbon assessment and inventories.     

Soil Organic Carbon Pools and Stocks in Permafrost-Affected Soils on the Tibetan Plateau

The Tibetan Plateau reacts particularly sensitively to possible effects of climate change. Approximately two thirds of the total area is affected by permafrost. To get a better understanding of the role of permafrost on soil organic carbon pools and stocks, investigations were carried out including both discontinuous (site Huashixia, HUA) and continuous permafrost (site Wudaoliang, WUD). Three organic carbon fractions were isolated using density separation combined with ultrasonic dispersion: the light fractions (<1.6 g cm⁻³) of free particulate organic matter (FPOM) and occluded particulate organic matter (OPOM), plus a heavy fraction (>1.6 g cm⁻³) of mineral associated organic matter (MOM). The fractions were analyzed for C, N, and their portion of organic C. FPOM contained an average SOC content of 252 g kg⁻¹. Higher SOC contents (320 g kg⁻¹) were found in OPOM while MOM had the lowest SOC contents (29 g kg⁻¹). Due to their lower density the easily decomposable fractions FPOM and OPOM contribute 27% (HUA) and 22% (WUD) to the total SOC stocks. In HUA mean SOC stocks (0–30 cm depth) account for 10.4 kg m⁻², compared to 3.4 kg m⁻² in WUD. 53% of the SOC is stored in the upper 10 cm in WUD, in HUA only 39%. Highest POM values of 36% occurred in profiles with high soil moisture content. SOC stocks, soil moisture and active layer thickness correlated strongly in discontinuous permafrost while no correlation between SOC stocks and active layer thickness and only a weak relation between soil moisture and SOC stocks could be found in continuous permafrost. Consequently, permafrost-affected soils in discontinuous permafrost environments are susceptible to soil moisture changes due to alterations in quantity and seasonal distribution of precipitation, increasing temperature and therefore evaporation.     

Controls on Soil Organic Carbon Stocks and Turnover Among North American Ecosystems

Despite efforts to understand the factors that determine soil organic carbon (SOC) stocks in terrestrial ecosystems, there remains little information on how SOC turnover time varies among ecosystems, and how SOC turnover time and C input, via plant production, differentially contribute to regional patterns of SOC stocks. In this study, we determined SOC stocks (gC m⁻²) and used soil radiocarbon measurements to derive mean SOC turnover time (years) for 0–10 cm mineral soil at ten sites across North America that included arctic tundra, northern boreal, northern and southern hardwood, subtropical, and tropical forests, tallgrass and shortgrass prairie, mountain grassland, and desert. SOC turnover time ranged 36-fold among ecosystems, and was much longer for cold tundra and northern boreal forest and dry desert (1277–2151 years) compared to other warmer and wetter habitats (59–353 years). Two measures of C input, net aboveground production (NAP), determined from the literature, and a radiocarbon-derived measure of C flowing to the 0–10 cm mineral pool, I, were positively and SOC turnover time was negatively associated with mean annual evapotranspiration (ET) among ecosystems. The best fit model generated from the independent variables NAP, I, annual mean temperature and precipitation, ET, and clay content revealed that SOC stock was best explained by the single variable I. Overall, these findings indicate the primary role that C input and the secondary role that C stabilization play in determining SOC stocks at large regional spatial scales and highlight the large vulnerability of the global SOC pool to climate change.     

Improving the Spatial Prediction of Soil Organic Carbon Stocks in a Complex Tropical Mountain Landscape by Methodological Specifications in Machine Learning Approaches

Tropical forests are significant carbon sinks and their soils’ carbon storage potential is immense. However, little is known about the soil organic carbon (SOC) stocks of tropical mountain areas whose complex soil-landscape and difficult accessibility pose a challenge to spatial analysis. The choice of methodology for spatial prediction is of high importance to improve the expected poor model results in case of low predictor-response correlations. Four aspects were considered to improve model performance in predicting SOC stocks of the organic layer of a tropical mountain forest landscape: Different spatial predictor settings, predictor selection strategies, various machine learning algorithms and model tuning. Five machine learning algorithms: random forests, artificial neural networks, multivariate adaptive regression splines, boosted regression trees and support vector machines were trained and tuned to predict SOC stocks from predictors derived from a digital elevation model and satellite image. Topographical predictors were calculated with a GIS search radius of 45 to 615 m. Finally, three predictor selection strategies were applied to the total set of 236 predictors. All machine learning algorithms—including the model tuning and predictor selection—were compared via five repetitions of a tenfold cross-validation. The boosted regression tree algorithm resulted in the overall best model. SOC stocks ranged between 0.2 to 17.7 kg m^-2, displaying a huge variability with diffuse insolation and curvatures of different scale guiding the spatial pattern. Predictor selection and model tuning improved the models’ predictive performance in all five machine learning algorithms. The rather low number of selected predictors favours forward compared to backward selection procedures. Choosing predictors due to their indiviual performance was vanquished by the two procedures which accounted for predictor interaction.     

黄淮海冲积平原区土壤有机质时空变异特征

通过分析124个样点1980年和2000年耕层土壤的有机质含量,研究了黄淮海冲积平原区河北省曲周县土壤有机质的时空变异特征,研究结果表明,该县目前土训有机质含量平均为12.89g/kg。与1980年相比较增加了4.11g/kg,年均增加0.21g/kg。但因各农户施用有机肥量的不同和管理水平的差异。占全县耕地面积6%的土壤有机质含量不升反降,县内各区域有机质的增长趋势为西南部和东南部高于中部和北部,潮上,盐土和褐土2000年有机质含量分别比1980年增加45.51%,82.48%和68.57%。     

Natural and Regenerated Saltmarshes Exhibit Similar Soil and Belowground Organic Carbon Stocks,Root Production and Soil Respiration

Ecosystems - Saltmarshes provide many valuable ecosystem services including storage of a large amount of ‘blue carbon’ within their soils. To date, up to 50% of the world’s...     

生物结皮对古尔班通古特沙漠3种荒漠草本植物生长特性与元素吸收的影响

生物结皮有可能通过物理、水文、养分循环影响与之相邻的维管植物,但二者相互关系尚存在着争议。本文以新疆古尔班通古特沙漠广泛分布的地衣结皮为研究对象,分析了生物结皮对3种荒漠草本植物：尖喙牻牛儿苗（Erodium oxyrrhynchum）、条叶庭芥（Alyssum linifolium）和琉苞菊（Hyalea pulchella）的生长及其对元素吸收的影响。研究结果表明：（1）生物结皮对3种荒漠草本植物生长的影响在生长期不同阶段存在差异。在前期,生物结皮的存在促进了植物生物量的累积;而后期,生物结皮却抑制了植物生长。生物结皮的存在显著影响了荒漠草本植物生物量的累积和冠根比。（2）生物结皮的存在显著增加了3种荒漠草本植物对N和K的吸收,而对P的吸收没有显著影响。生物结皮对3种植物Cu、Ca、Mg、Na、Cl的吸收存在种间差异。本研究结果将为该荒漠生态系统潜在的植被演替方向提供重要的科学根据。     

Changes in Biomass Carbon and Soil Organic Carbon Stocks following the Conversion from a Secondary Coniferous Forest to a Pine Plantation

The objectives of this study were to estimate changes of tree carbon (C) and soil organic carbon (SOC) stock following a conversion in land use, an issue that has been only insufficiently addressed. For this study, we examined a chronosequence of 2 to 54-year-old Pinus kesiya var. langbianensis plantations that replaced the original secondary coniferous forest (SCF) in Southwest China due to clearing. C stocks considered here consisted of tree, understory, litter, and SOC (0–1 m). The results showed that tree C stocks ranged from 0.02±0.001 Mg C ha^-1 to 141.43±5.29 Mg C ha^-1, and increased gradually with the stand age. Accumulation of tree C stocks occurred in 20 years after reforestaion and C stock level recoverd to SCF. The maximum of understory C stock was found in a 5-year-old stand (6.74±0.7 Mg C ha^-1) with 5.8 times that of SCF, thereafter, understory C stock decreased with the growth of plantation. Litter C stock had no difference excluding effects of prescribed burning. Tree C stock exhibited a significant decline in the 2, 5-year-old stand following the conversion to plantation, but later, increased until a steady state-level in the 20, 26-year-old stand. The SOC stocks ranged from 81.08±10.13 Mg C ha^-1 to 160.38±17.96 Mg C ha^-1. Reforestation significantly decreased SOC stocks of plantation in the 2-year-old stand which lost 42.29 Mg C ha^-1 in the 1 m soil depth compared with SCF by reason of soil disturbance from sites preparation, but then subsequently recovered to SCF level. SOC stocks of SCF had no significant difference with other plantation. The surface profile (0–0.1 m) contained s higher SOC stocks than deeper soil depth. C stock associated with tree biomass represented a higher proportion than SOC stocks as stand development proceeded.     

Spatial Analysis of Soil Organic Carbon in Zhifanggou Catchment of the Loess Plateau

Soil organic carbon (SOC) reflects soil quality and plays a critical role in soil protection, food safety, and global climate changes. This study involved grid sampling at different depths (6 layers) between 0 and 100 cm in a catchment. A total of 1282 soil samples were collected from 215 plots over 8.27 km². A combination of conventional analytical methods and geostatistical methods were used to analyze the data for spatial variability and soil carbon content patterns. The mean SOC content in the 1282 samples from the study field was 3.08 g·kg⁻¹. The SOC content of each layer decreased with increasing soil depth by a power function relationship. The SOC content of each layer was moderately variable and followed a lognormal distribution. The semi-variograms of the SOC contents of the six different layers were fit with the following models: exponential, spherical, exponential, Gaussian, exponential, and exponential, respectively. A moderate spatial dependence was observed in the 0–10 and 10–20 cm layers, which resulted from stochastic and structural factors. The spatial distribution of SOC content in the four layers between 20 and 100 cm exhibit were mainly restricted by structural factors. Correlations within each layer were observed between 234 and 562 m. A classical Kriging interpolation was used to directly visualize the spatial distribution of SOC in the catchment. The variability in spatial distribution was related to topography, land use type, and human activity. Finally, the vertical distribution of SOC decreased. Our results suggest that the ordinary Kriging interpolation can directly reveal the spatial distribution of SOC and the sample distance about this study is sufficient for interpolation or plotting. More research is needed, however, to clarify the spatial variability on the bigger scale and better understand the factors controlling spatial variability of soil carbon in the Loess Plateau region.     

A Shift in Seasonal Rainfall Reduces Soil Organic Carbon Storage in a Cold Desert

Shifts in the seasonal timing of rainfall have the potential to substantially affect the immense terrestrial stores of soil organic carbon (C, SOC). It remains unclear, however, how changes in the timing of rainfall are influencing SOC storage. We hypothesized that a sustained shift in rainfall timing from winter to a spring-summer regime would reduce desert SOC stores by creating moist and warm soil conditions, thus promoting decomposition. To investigate this, we evaluated how an 11-year seasonal shift in rainfall (winter to spring-summer regime) affected SOC storage (that is, dissolved organic C, light SOC, and heavy SOC) in soils beneath dominant shrub and perennial grass species in a cold desert sagebrush-steppe ecosystem. We also measured the soil C to nitrogen (N) ratios, standing litter stocks, and root biomass C to help interpret the long-term changes in SOC stores. As predicted, a seasonal shift in rainfall caused heavy SOC to decline beneath Artemisia tridentata ssp. wyomingensis by 14%, from 3.1 to 2.7 kg C m⁻², and Pseudoroegneria spicata by 19%, from 3.0 to 2.4 kg C m⁻². Neither dissolved organic C, nor the light fraction, responded to changes in rainfall. The C to N ratio of heavy SOC beneath Artemisia declined by at least 6% under the warmer and moister conditions of the spring-summer regime, suggesting that alterations in decomposition dynamics contributed to the loss of SOC. Unexpectedly, coarse litter and root C in Artemisia soils were lower under the spring-summer than winter rainfall regime, suggesting that a decline in litter inputs may also have contributed to the loss of SOC. The C to N ratio of heavy SOC, litter stores (that is, coarse litter and thatch), and root C in Pseudoroegneria soils demonstrated similar responses as in Artemisia soils, but these variables were at best only marginally significant. Our results suggest that a sustained seasonal shift in rainfall from winter to spring-summer will reduce heavy SOC across cold deserts, and that this reduction will stem from alterations in decomposition dynamics and net primary production by plants. Further, as global temperatures rise we may see more overlap of moist and warm soil conditions, especially in ecosystems with winter rainfall regimes (for example, Mediterranean-climate ecosystems and temperate forests), that may reduce SOC in the absence of rainfall changes.     

中国黑戈壁地区植物区系及其物种多样性研究

黑戈壁是戈壁中最为干旱的区域,为了系统的研究其植被及物种多样性,该研究采用无人机航拍和实地调查的方法,对中国西北内陆的黑戈壁进行了分析研究。结果表明:(1)中国西北内陆的黑戈壁地区共记录植物154种,分属28科,85属;植物生活型组成简单,主要以灌木、半灌木及多年生草本植物为主,占植物物种比例的70%以上。(2)在植物物种组成方面,与整个荒漠区比较,黑戈壁地区物种数量少,但灌木所占比例远高于荒漠区。(3)黑戈壁地区植物科、属内物种组成贫乏,科内属、种数量比较多的为藜科、菊科、豆科等。(4)黑戈壁地区优势群落的建群种为红砂、盐生草、膜果麻黄等,中国特有植物为新疆沙拐枣、哈密黄蓍、胀果甘草等,主要国家保护植物有胡杨、裸果木、胀果干草等。(5)黑戈壁地区植物区系表征科主要为蒺藜科、蓼科、麻黄科等,而属的分布型以地中海区、西亚至中亚分布及北温带分布为主,占黑戈壁地区总属的47%以上,是群落组成的优势种和建群种。(6)与其他荒漠地区植物区系相比,黑戈壁地区植物旱生种比例增加,适应类型更为贫乏,缺乏特有成分,具有明显残遗性;由于特殊极端干旱环境,形成黑戈壁地区特殊植物类群和区系特征;黑戈壁地区是荒漠地区的区域特色植物物种资源和基因资源的重要区域和保存地,而黑戈壁生态系统非常脆弱,一旦破坏,将很难恢复。     

Carbon Quality and Stocks in Organic Horizons in Boreal Forest Soils

We investigated the mechanisms that determine the quality and quantity of organic carbon (C) stocks in boreal forest soils by analyzing both qualitative and quantitative changes in the organic fractions in the soil organic matter (OM) in a vertical gradient in the decomposition continuum of the organic horizon [litter layer (L), fermentation layer (F), and humus layer (H)] in forest soils using a sequential fractionation method at two forest types along a climatic gradient in Finland. We predicted that the concentrations of water-soluble (WSE) and non-polar (NPE) extractives should decrease and those of the acid-soluble (AS) fraction and acid-insoluble residue (AIR) should increase from the L to the F, and from the F to the H layers, but the C/N ratio of soil OM should stay constant after reaching the critical quotient. We also predicted that the AIR concentrations should be higher in the south than north boreal, and in sub-xeric than mesic forests. Consistent with our hypothesis, the concentrations of WSE and NPE fractions decreased and concentrations of AIR increased in the vertical soil gradient. The highest concentrations of the AS fraction were found in the F layer. The C/N ratio was lowest in the F layer, and the highest in the H layer, indicating that soil OM is depleted in N in relation to C along the vertical soil gradient. Concentrations of WSE and NPE were lower, and concentrations of AIR were higher in the south than in north boreal forests, which is in agreement with our hypothesis that higher soil temperatures may enhance accumulation of slowly decomposable OM in the soil. The concentrations of AIR were higher in the sub-xeric than mesic forests. Contrary to our expectations, however, the differences in the chemical quality in soil OM between the site types were amplified from the L to the H layer. The size of the C storage was significantly larger in south than north boreal sites, and larger in the mesic than in the sub-xeric sites.     

Spatial Patterns and Predictors of Forest Carbon Stocks in Western Mediterranean

Mediterranean semi-arid forest ecosystems are especially sensitive to external forcing. An understanding of the relationship between forest carbon (C) stock, and environmental conditions and forest structure enable prediction of the impacts of climate change on C stocks and help to define management strategies that maximize the value of forests for C mitigation. Based on the national forest inventory of Spain (1997?C2008 with 70,912 plots), we estimated the forest C stock and spatial variability in Peninsular Spain and, we determined the extent to which the observed patterns of stand C stock can be explained by structural and species richness, climate and disturbances. Spain has an average stand C stock of 45.1?Mg C/ha. Total C stock in living biomass is 621 Tg C (7.8% of the C stock of European forests). The statistical models show that structural richness, which is driven by past land use and life forest history including age, development stage, management activities, and disturbance regime, is the main predictor of stand tree C stock with larger C stocks in structurally richer stands. Richness of broadleaf species has a positive effect on both conifer and broadleaf forests, whereas richness of conifer species shows no significant or even a negative effect on C stock. Climate variables have mainly an indirect effect through structural richness but a smaller direct predictive ability when all predictors are considered. To achieve a greater standing C stock, our results suggest promoting high structural richness by managing for uneven-aged stands and favoring broadleaf over conifer species.     

Dissolved Organic Carbon in Headwater Streams and Riparian Soil Organic Carbon along an Altitudinal Gradient in the Wuyi Mountains,China

Stream water dissolved organic carbon (DOC) correlates positively with soil organic carbon (SOC) in many biomes. Does this relationship hold in a small geographic region when variations of temperature, precipitation and vegetation are driven by a significant altitudinal gradient? We examined the spatial connectivity between concentrations of DOC in headwater stream and contents of riparian SOC and water-soluble soil organic carbon (WSOC), riparian soil C:N ratio, and temperature in four vegetation types along an altitudinal gradient in the Wuyi Mountains, China. Our analyses showed that annual mean concentrations of headwater stream DOC were lower in alpine meadow (AM) than in subtropical evergreen broadleaf forest (EBF), coniferous forest (CF), and subalpine dwarf forest (SDF). Headwater stream DOC concentrations were negatively correlated with riparian SOC as well as WSOC contents, and were unrelated to riparian soil C:N ratio. Our findings suggest that DOC concentrations in headwater streams are affected by different factors at regional and local scales. The dilution effect of higher precipitation and adsorption of soil DOC to higher soil clay plus silt content at higher elevation may play an important role in causing lower DOC concentrations in AM stream of the Wuyi Mountains. Our results suggest that upscaling and downscaling of the drivers of DOC export from forested watersheds when exploring the response of carbon flux to climatic change or other drivers must done with caution.     

荒漠草原典型植物群落土壤活性有机碳组分特征及其与酶活性的关系

以宁夏荒漠草原典型植物柠条(Caragana korshinskii)、沙蒿(Artemisia ordosica)、短花针茅(Stipa breviflora)和蒙古冰草(Agropyron mongolicum)群落为研究对象,分析不同植物群落不同土层深度(0~5、5~10和10~15cm)土壤活性有机碳组分土壤微生物量碳(MBC)、可溶性有机碳(DOC)和易氧化有机碳(EOC)特征及其与土壤酶(蔗糖酶、脲酶、碱性磷酸酶和过氧化氢酶)活性之间的关系。结果表明:(1)4种典型植物群落土壤SOC、MBC、EOC含量均随土层深度的增加而减少,且表层(0~5cm)土壤显著高于亚表层(5~10cm)和深层(10~15cm)土壤(P0.05),而土壤DOC含量随土层深度的增加呈先增加后减少的趋势。在同一土层深度,灌木(柠条和沙蒿)群落土壤活性有机碳组分含量高于禾本科植物(短花针茅和蒙古冰草)。(2)4种典型植物群落土壤酶(蔗糖酶、脲酶、磷酸酶和过氧化氢酶)活性整体上随土层深度的增加而降低,局部土层深度表现出波动性;同一土层不同植被群落土壤酶活性未表现出一定的变化规律。(3)4种典型群落土壤活性有机碳各组分除DOC外,其余均与SOC呈显著正相关关系,与土壤酶活性、微生物量熵以及有机碳活度具有一定的相关关系,表明土壤活性有机碳不仅依赖于总有机碳,也与土壤酶活性密切相关。