采样密度对中国红壤地区土壤有机碳空间变异研究的影响效应

Spatial variability of soil organic carbon (SOC) of different land use patterns and soil types was examined in a county-wide red soil region of South China,using six sampling densities,14,34,68,130,255,and 525 samples designed by the method of grid sampling in 6 different grid sizes,labeled as D14,D34,D68,D130,D255,and D525,respectively.The results showed that the coefficients of variation (CVs) of SOC decreased gradually from 62.8% to 47.4% with the increase in soil sampling densities.The SOC CVs in the paddy field change slightly from 30.8% to 28.7%,while those of the dry farmland and forest land decreased remarkably from 58.1% to 48.7% and from 99.3% to 64.4%,respectively.The SOC CVs of the paddy soil change slightly,while those of red soil decreased remarkably from 82.8% to 63.9%.About 604,500,and 353 (P < 0.05) samples would be needed a number of years later if the SOC change was supposedly 1.52 g kg-1,based on the CVs of SOC acquired from the present sampling densities of D14,D68,and D525,respectively.Moreover,based on the same SOC change and the present time CVs at D255,the ratio of samples needed for paddy field,dry farmland,and forest land should be 1:0.81:3.33,while the actual corresponding ratio in an equal interval grid sampling was 1:0.74:0.46.These indicated that the sampling density had important effect on the detection of SOC variability in the county-wide region,the equal interval grid sampling was not efficient enough,and the respective CV of each land use or soil type should be fully considered when determining the sampling number in the future.     

中国福建省永春县柑橘园土壤有机碳储量研究

Studies related to the quantitation and distribution of soil organic carbon(C) under different land use types can help to fill the knowledge gaps regarding estimation of the amount of C stored in soils at a global scale. Orchards are an important land use type in southern China; the total area(1.15 × 10~7 ha) of orchards in China comprises approximately 20.5% of the area of all orchards worldwide. We assessed soil organic C stocks(SOCS) in citrus orchards in Yongchun County(consisting of 22 towns), Fujian Province,China in 1982 and 2010. The southeastern part of the county, an area featuring extensive citrus farming with a gently sloping landscape and low rates of water erosion, had the highest SOCS. In contrast, the lowest SCOS was observed in the northern part of the county,where steep hills with severe erosion problems are common and citrus orchards are sparsely distributed. From 1982 to 2010, the mean SOCS in citrus orchards increased from 22.1 to 41.7 Mg ha~(-1), which indicated that current management practices such as fertilization,irrigation, and cultivation enhanced soil C stocks. Further in-depth studies on the effects of these practices on C sequestration would be worthwhile and surveys of SOCS throughout Fujian Province are needed, to support efforts to mitigate global C emission.     

北京市农田土壤有机碳密度空间变异及影响因素

探明区域农田土壤有机碳密度（soil organic carbon density, SOCD）空间分布特征及其影响因素对增加农田土壤碳汇、实现“双碳”目标具有重要意义。该研究以北京市为研究区,基于2022年采样实测的0～60 cm各层SOCD数据,采用3D概念模型、Mantel test、地理加权回归、地理探测器模型开展SOCD空间变异分析,探究不同因素对SOCD的影响程度及各因素间交互后的作用力。结果表明：1）研究区SOCD在空间上呈自表层向深层逐渐降低的趋势,其中0～15 cm土层的SOCD显著高于30～60 cm（P < 0.05）,0～60 cm土层的有机碳储量约为10.80 Tg。2）土壤含水率、土壤亚类、地形部位分别对0～15、15～60、45～60 cm土层的SOCD产生了显著影响（P < 0.05）;土壤亚类、土壤母质、土壤质地、地形部位与SOCD的空间关联性较强,关联程度自表层向下逐渐增大。3）各重要因子交互后对研究区SOCD的解释能力呈双因子增强或非线性增强的关系,土壤亚类与其他各因子交互后对SOCD的解释能力提升最为突出。今后研究区内开展土壤有机碳空间变异等相关研究时应尽可能综合考虑多因素间的交互作用,其中土壤亚类（土壤类型）可作为重点指标。研究结果可为优化农田资源空间结构,制定农田固碳增汇措施提供科学参考。     

江西省耕地土壤有机碳空间变异的主控因素研究

准确地获取省域尺度下土壤有机碳空间变异的主控因素对土壤碳调控以及全球环境保护具有重要意义。本文基于江西省2012年测土配方施肥项目采集的16 582个耕地表层(0~20 cm)土壤样点数据,探讨江西省耕地表层土壤有机碳空间变异的主控因素。运用普通克里格法、单因素方差分析与回归分析方法对比地形因子、耕地利用方式、成土母质、土壤类型、灌溉能力和秸秆还田方式对江西省土壤有机碳空间分布的影响。结果表明:(1)江西省土壤有机碳含量在5.22~40.31 g/kg之间,平均值为17.90 g/kg,变异系数为31.01%,呈中等程度的变异性。(2)经半方差分析,土壤有机碳的变程为30.6 km,空间自相关范围较小;块金效应值为12.49%,表明土壤有机碳空间变异受结构性因素影响大于随机性因素。(3)在空间分布上,高值区主要分布在萍乡市、新余市、南昌市、抚州市与景德镇市。(4)回归分析与单因素方差分析结果表明,地形因子、灌溉能力、成土母质、耕地利用方式、土壤类型和秸秆还田方式对土壤有机碳空间变异影响均显著(P0.05),但影响程度不一。秸秆还田方式对土壤有机碳空间变异的独立解释能力最高,为38.9%,是江西耕地表层土壤有机碳空间变异的主控因素。     

祁连山天老池小流域土壤有机碳空间异质性及其影响因素

采用野外取样和室内分析,结合地统计学方法和方差分析方法,分析了祁连山天老池小流域0~30 cm层的土壤有机碳的分布特征及其与植被类型、地形和土壤性质等因素的关系。结果表明,该流域土壤有机碳垂直分布存在显著的差异,随着土层深度的增加,土壤有机碳含量显著减少,0~10、10~20、20~30 cm土层土壤有机碳含量分别为105.08、81.46、62.62 g/kg,土壤平均有机碳含量为83.05 g/kg,变异系数为0.56。不同的植被类型0~10 cm土层土壤有机碳含量表现为青海云杉(138.20 g/kg)灌丛(118.49 g/kg)亚高山草甸(100.43 g/kg)祁连圆柏(74.17 g/kg)干草原(43.94 g/kg);随着海拔的升高土壤有机碳含量增加,阴坡有机碳含量明显高于阳坡;经相关性分析表明,土壤有机碳与土壤全氮和砂粒呈显著正相关关系,与土壤体积质量、黏粒和粉粒呈显著负相关关系。     

皖北平原蒙城县农田土壤有机碳空间变异及影响因素

以皖北平原典型农业生产大县亳州市蒙城县为代表,运用统计学、地统计学方法和GIS技术研究了其农田耕作层(0～20 cm)土壤有机碳(SOC)含量的空间分布及其影响因子。结果表明:研究区SOC含量为10.41±2.52 g kg-1,近30年来提高了55.61%,SOC变异系数为24%,属于中等变异程度。SOC含量在空间分布上表现为东北部、中部和西南部含量高,由西北向东南先逐渐增加后逐渐降低,变异程度较高。整个县域范围内SOC空间变异的主要影响因素为土壤机械组成(粉粒和砂粒含量),其次为秸秆还田。     

渝东南农田土壤有机碳空间分布特征及影响因素

为评价区域农田土壤肥力及优化农业生产管理措施,选取渝东南地区黔江区为研究区域,基于重庆市测土配方施肥的615个表层(0~20 cm)土样数据,运用地统计学和地理信息系统(GIS)相结合的方法分析黔江区土壤有机碳(SOC)的空间分布特征及其影响因素。结果表明,研究区土壤表层SOC含量为13.27 g·kg^-1,变异系数为31.44%,具有中等程度的空间变异且空间自相关范围较大。块金效应为45.59%,空间分布受结构性因素和随机性因素的共同影响。研究区SOC分布呈斑块状,总体表现为东高西低。方差分析和回归分析表明,成土母质、土壤类型、土地利用方式及坡度、坡向对SOC的空间分布的影响极显著(P<0.01),土壤质地、海拔高度的影响显著(P<0.05)。随着海拔的增加,土壤中SOC含量也逐渐增加。而随着坡度增加,土壤中SOC含量呈先降低后增加的趋势。本研究结果为渝东南农田SOC管理及农作物合理施肥提供了理论依据。     

基于多元分析的岷江下游土壤有机碳密度空间分布及影响因素研究

采用传统统计、灰色关联度、逐步回归和通径分析相结合的多元分析方法对岷江下游1 138个样点的表层(0~20 cm)土壤有机碳密度及其影响因素进行研究。结果表明,该区表层土壤有机碳密度在0.89~6.49 kg/m2之间,均值为3.24 kg/m2。其在空间上呈不规则的斑块状分布,具中等空间相关性,表现出中部浅丘区高而西北和东部高丘区低的分布趋势。土地利用类型、土壤酸碱度(p H)、成土母质、地貌类型、坡度和土壤质地均是影响土壤有机碳密度的主要因素。其中,土地利用类型、p H、地貌类型、坡度和土壤质地与有机碳密度呈极显著相关。灰色关联度的分析表明与土壤有机碳密度关联最为密切的是地貌类型,其次是p H和成土母质,逐步回归和通径分析的结果均表明地貌类型是最主要因素,成土母质和p H次之。综合比较以上方法,得出地貌类型、成土母质和p H为影响岷江下游研究区表层土壤有机碳密度的主要因素。     

滇黔桂地区土壤有机碳密度变异的影响因素研究

土壤有机碳是土壤肥力的重要指标之一,也是陆地碳库的主要部分。揭示影响土壤有机碳储量的主要因素,对合理地利用土壤资源,减少土壤温室气体的排放,增加土壤碳存储等方面都具有重要的意义。土壤有机碳储量受气候、植被、土壤属     

北方半干旱地区梯田土壤有机碳密度影响因素研究

针对北方半干旱地区小流域内旱地梯田的地形因子以及农作物类型对土壤有机碳密度的影响进行了研究,为合理地保障农作物生产和维持小流域的生态安全提供理论依据。试验地点在敖汉旗大五家流域,在流域内选取样地25块,共计125个土壤剖面,主要针对地形因子和农作物类型来分析其对土壤有机碳密度的影响,并得出以下结论:(1)玉米、高粱、谷子和绿豆4种作物的土壤有机碳密度随土壤深度的增加呈先下降再上升的趋势,在50~100 cm深度时土壤有机碳密度最大;(2)玉米、高粱、谷子和绿豆4种作物的土壤有机碳密度在不同的海拔高度表现不同,海拔为400~500 m时土壤碳密度最大,其次为海拔≥600 m的区域,海拔为500~600 m的区域最小;(3)玉米、高粱、谷子和绿豆4种作物的土壤有机碳密度随坡度的增大均呈现先下降后升高的趋势,坡度≤2°时土壤有机碳密度最小,在坡度为2~6°时最大;(4)在p0.05水平下,玉米、高粱、谷子和绿豆4种作物的土壤有机碳密度在不同坡向表现不同,谷子和玉米为南坡北坡西坡东坡,而高粱和绿豆则为北坡南坡西坡东坡;(5)玉米、高粱、谷子和绿豆4种作物中,绿豆的有机碳密度高于其他3种作物,平均土壤有机碳密度为0.81 g·cm-2。     

黄土高原小流域土壤有机碳空间变异性研究

Soil organic carbon (SOC) has great impacts on global warming, land degradation and food security. Classic statistical and geostatistical methods were used to characterize and compare the spatial heterogeneity of SOC and related factors, such as topography, soil type and land use, in the Liudaogou watershed on the Loess Plateau of North China. SOC concentrations followed a log-normal distribution with an arithmetic and geometric means of 23.4 and 21.3 g kg^-1, respectively, were moderately variable (CV = 75.9%), and demonstrated a moderate spatial dependence according to the nugget ratio (34.7%). The experimental variogram of SOC was best-fitted by a spherical model, after the spatial outliers had been detected and subsequently eliminated. Lower SOC concentrations were associated with higher elevations. Warp soils and farmland had the highest SOC concentrations, while aeolian sand soil and shrublands had the lowest SOC values. The geostatistical characteristics of SOC for the different soil and land use types were different. These patterns were closely related to the spatial structure of topography, and soil and land use types.     

广东省典型土壤类型和土地利用方式对土壤酶活性的影响

通过野外调查与室内分析,研究了广东省韶关红壤、广州赤红壤、雷州砖红壤3个典型地带性土壤分布区4种不同土地利用方式(包括林地、果园、草地和农田)对表层(0~20 cm)土壤几种主要酶活性(过氧化氢酶、纤维素酶、蔗糖酶、脲酶、蛋白酶活性)的影响。结果表明,不同土壤类型和不同土地利用方式对土壤酶活性均有一定影响,其中土地利用方式影响更为明显。土壤酶活性多表现为果园和林地较高,农田和草地较低;而土壤过氧化氢酶对土地利用方式和土壤类型的响应均较其它几种酶弱。典范相关分析结果表明,全磷、速效磷、速效氮含量是土壤养分因子中影响土壤酶活性的最重要因素,5种酶中纤维素酶和蛋白酶活性与土壤养分因子关系最大,而土壤酶活性之间也存在着一定的共性关系。     

Land Use and Soil Organic Carbon in China’s Village Landscapes

Village landscapes, which integrate small-scale agriculture with housing, forestry, and a host of other land use practices, cover more than 2 million square kilometers across China. Village lands tend to be managed at very fine spatial scales (≤ 30 m), with managers both adapting their practices to existing variation in soils and terrain (e.g., fertile plains vs. infertile slopes) and also altering soil fertility and even terrain by terracing, irrigation, fertilizing, and other land use practices. Relationships between fine-scale land management patterns and soil organic carbon (SOC) in the top 30 cm of village soils were studied by sampling soils within fine-scale landscape features using a regionally weighted landscape sampling design across five environmentally distinct sites in China. SOC stocks across China’s village regions (5 Pg C in the top 30 cm of 2 × 10 6 km 2 ) represent roughly 4% of the total SOC stocks in global croplands. Although macroclimate varied from temperate to tropical in this study, SOC density did not vary significantly with climate, though it was negatively correlated with regional mean elevation. The highest SOC densities within landscapes were found in agricultural lands, especially paddy, the lowest SOC densities were found in nonproductive lands, and forest lands tended toward moderate SOC densities. Due to the high SOC densities of agricultural lands and their predominance in village landscapes, most village SOC was found in agricultural land, except in the tropical hilly region, where forestry accounted for about 45% of the SOC stocks. A surprisingly large portion of village SOC was associated with built structures and with the disturbed lands surrounding these structures, ranging from 18% in the North China Plain to about 9% in the tropical hilly region. These results confirmed that local land use practices, combined with local and regional variation in terrain, were associated with most of the SOC variation within and across China’s village landscapes and may be an important cause of regional variation in SOC.     

四川省仁寿县土壤有机碳空间分布特征及其主控因素

准确地获取区域尺度内土壤有机碳含量信息对土壤碳调控及全球环境变化具有重要意义。本研究基于野外实地采集的555个表层(0~20 cm)土样,探讨四川省仁寿县土壤有机碳空间分布特征及其主控因素。运用方差分析和回归分析对比了成土母质、土壤类型和土地利用方式对仁寿县土壤有机碳空间分布的影响。结果表明:研究区表层土壤有机碳含量为3.36~37.10 g·kg-1,平均13.46 g·kg-1,变异系数为48.87%,属中等强度的空间变异性。块金效应C0/(C0+C)为66.7%,空间分布受结构性因素和随机性因素的共同影响,总体呈现北高南低的趋势。土地利用方式和土壤类型对土壤有机碳的影响极显著(P0.01),而成土母质的影响不明显(P=0.256)。土类能够独立解释23.7%的土壤有机碳空间变异;亚类和土类的解释能力接近,分别为27.0%和27.1%,土壤亚类可作为探讨该区域土壤有机碳空间变化的最小土壤分级单元。土地利用方式能独立解释53.0%的土壤有机碳空间变异,远大于土壤类型,是研究区土壤有机碳空间分布的主控因素。     

江西省土地利用变化及其对人类活动的响应

采用人机交互式判读解译2005年、2010年、2013年3期TM/ETM+遥感影像,提取获得江西省土地利用数据。从土地利用变化速度、土地利用转移空间特征与方向、土地利用程度等角度对江西省人类活动作用下的土地利用变化时空规律进行了深入分析。结果表明:(1)2005—2010年、2010—2013年两个时间段,江西土地利用变化速度呈现下降趋势,各地类增减变化较为显著;(2)2005年以来,耕地与建设用地、林地3种地类间的转移流在土地转移网络中占主导地位;地类间转移面积密度总体呈下降趋势,土地利用类型转移热点区呈片状及散点状分布;(3)总体来看,江西省土地利用程度整体水平普遍提升,土地利用程度综合变化指数区域差异逐步缩小;土地利用程度综合指数变化极值区受政策影响显著,在两个时期内促使了赣北环鄱区、赣南地区土地利用活跃区的形成。     

沱江流域中游土壤有机质的空间变异特点及其影响因素

土壤有机质(SOM)是陆地生态系统中碳循环的重要源与汇[1-3]。其不仅能提高土壤肥力和生产力,且其对碳的固定也是人类应对大气CO2浓度升高的重要途径[4-5]。在区域尺度上,土壤有机质主要受气候、土地利用方式、地理因素如海拔高度、坡度和质地等差异的影响[6-9]。且不同自然地理条件和社会经济发展水平的区域,其土壤有机质的主要影响因素及其影响程度也会有所差异[10-12]。     

东北黑土区农林混合利用坡面土壤水分空间异质性及主控因素

针对黑土区坡面尺度上土壤水分在土地利用结构(从坡顶到坡脚,即沿着坡长方向,不同土地利用类型的排列方式)、土地利用类型(农地和林地)及地形要素的协同作用下的空间分异规律及影响机制尚不清楚的现状,以黑龙江省黑土区的农林混合利用典型坡面(克山县)为研究对象,应用植被数量生态学中的冗余分析方法(RDA)分析0~20、20~40、40~60 cm土壤水分剖面变异特征、不同土地利用结构下(农地-农地-农地-农地-农地,农地-农地-林地-林地-农地,农地-农地-林地-林地-林地,林地-林地-农地-林地-农地)坡面土壤水分异质性及其与环境因子的定量关系。结果表明:研究区坡面土壤含水率介于5.77%~45.57%,农地土壤含水率显著高于林地(P0.05),纵向上不同土地利用类型层间土壤含水率差异均不显著;土壤水分呈中等变异,纵向上农地各土层的变异系数(35.9%~39.6%)均高于林地(30.0%~36.5%),农林混合利用加强了土壤水分的空间变异程度;4种土地利用结构下,坡面土壤水分沿坡长方向呈不同的变化趋势,与土地利用镶嵌分布规律有关;冗余分析结果显示土地利用类型是影响黑土区坡面土壤水分异质性的主控因素,坡度次之,坡位和海拔高度对坡面土壤水分异质性也有影响。对于黑龙江黑土区坡面,需要结合土地利用结构配置等土地管理措施与不同的农业措施来防止坡面土壤侵蚀、提高东北区土壤肥力,实现经济效益、生态效益的协调统一。     

松嫩平原土壤有机碳空间分异

Soil organic carbon (SOC) and its relationship with landscape attributes are important for evaluating current regional, continental, and global carbon stores. Data of SOC in surface soils (0–20 cm) of four main soils, Cambisol, Arenosol, Phaeozem, and Chernozem, were collected at 451 locations in Nongan County under maize monoculture in the Song-Nen Plain, Northeast China. The spatial characteristics of soil organic carbon were studied, using geographic information systems (GIS) and geostatistics. Effects of other soil physical and chemical properties, elevation, slope, and soil type on SOC were explored. SOC concentrations followed a normal distribution, with an arithmetic mean of 14.91 g kg-1 . The experimental variogram of SOC was fitted with a spherical model. There were significant correlations between soil organic carbon and bulk density (r =-0.374**), pH (r = 0.549**), total nitrogen (r = 0.781**), extractable phosphorus (r =-0.109*), exchangeable potassium (r = 0.565**), and cation exchange capacity (r = 0.313**). Generally, lower SOC concentrations were significantly associated with high elevation (r =-0.429**). Soil organic carbon was significantly negatively correlated with slope gradient (r =-0.195**). Samples of the Cambisol statistically had the highest SOC concentrations, and samples of the Arenosol had the lowest SOC value.     

Influence of former lynchets on soil cover structure and soil organic carbon storage in agricultural land,Central Czechia

Lynchets represent a traditional landscape element in agricultural landscapes having multiple functions in soil material redistribution, water retention, biodiversity and landscape character. They act as a barrier to translocated soil matter, and they can store a significant amount of soil material and soil organic carbon. Lynchets developed in many regions during formation of agriculture landscape as field boundaries or path networks. Further management led to unleveling of the fields and development of lynchets. During the 20th century, a large number of lynchets disappeared in Central and Western Europe due to land consolidation, intensification and industrialization of agriculture. This study was performed at a large agricultural study plot with dissected relief (Central Czechia) with the aim of assessing the influence of former but now completely levelled lynchets on actual soil stratigraphy, depth, soil organic carbon stocks and structure of soil units. The soil profiles in 20‐m‐long transects perpendicular to former lynchets were analysed, and statistical relationships between the positions above, in and below the former lynchets were assessed. The results showed high variability of studied soil characteristics in the areas of former lynchets. Statistically significant greater A horizon thickness (50–100 cm) and SOC stock (12.7 kg/m²) were observed in the location of a former lynchet, where colluvial soils were identified. Other areas of accumulation were identified below a lynchet, at the former break‐in‐slope. The strip above a lynchet was identified as a sediment delivery area, having a partly truncated soil profile. SOC concentration and SOC stock in A horizon did not differ significantly in the positions in, above or below a lynchet.