干湿季节下基于遥感和电磁感应技术的塔里木盆地北缘绿洲土壤盐分的空间变异性

土壤盐渍化问题是制约干旱半干旱区植被生长最主要的生态环境地质问题,也是影响绿洲农业生产的障碍性问题.而将遥感与近感技术相结合,是当前评价、监测及预报土壤盐渍化程度的先进方法.以新疆塔里木盆地北缘的渭干河-库车河三角洲绿洲为例,以遥感数据和解译后的电磁感应数据为基础数据源,利用解译后的数据结合GIS和地统计学知识以及野外实测所得到的土壤电导率和盐分资料,分别采用泛克里格(Universal Kriging)、光谱指数回归(Spectral Index Regression)和回归残差泛克里格(Regression-Universal Kriging)3种方法研究了该地区两个关键季节(干季和湿季)土壤盐分的空间变异特征.研究结果表明:研究区的土壤浸提液电导率EC1∶5和土壤盐分呈现显著相关,可以用EC1∶5来代替土壤的全盐量进行分析;电磁感应仪(EM38)所测各季节土壤表观电导率与EC1∶5的相关系数均达到1％显著水平,以表观电导率垂直读数(EMv)和水平读数(EMH)为自变量的多元回归模型拟合效果较好;研究区各季节的表层土壤电导率的空间分布均表现为强相关性,说明土壤采样点间的内部结构性良好,采用能够充分考虑到干旱区表层土壤电导率空间变异的尺度依赖性的球状套合模型,能够更好的拟合土壤表观电导率的空间结构;经过精度比较,回归残差泛克里格法为最优预测方法,这表明将遥感和电磁感应技术相结合,能够有效的提高预测与评估土壤盐分空间分布的精度,为精确地进行土壤盐分预测以及土壤次生盐渍化的防控提供了一定的依据.     

基于电磁感应技术的土壤剖面盐分空间分布建模研究

土壤盐渍化问题是干旱半干旱地区农业发展的主要障碍,也是制约荒漠植物生长状况的关键因素之一,严重影响到绿洲生态环境的稳定与安全。研究土壤剖面盐分的分布情况,能及时探究盐渍化对生态的影响。以渭干河-库车河三角洲绿洲为研究靶区,利用电磁感应仪技术与传统采样方法获取该地区典型地块的土壤电导率,剖析其剖面分布特征,在建立磁感式表观电导率和土壤样本实测电导率之间的线性混合模型的基础上,采用自然邻近插值方法解析和评估研究区土壤剖面盐分的空间分布特征。结果表明:研究区土壤电导率具有较强的表聚性与空间变异强度,土壤主体属于中度盐渍化类型;基于各深度层土壤电导率与磁感表观电导率所构建的3种线性混合模型均能达到0.01的显著性水平,其中磁感表观电导率两种模式相结合解译模型预测精度最高;自然邻近法插值结果直观反映研究区土壤剖面盐分的空间分布状况,与水平模式和垂直模式相结合的土壤盐分解译模型相结合则能够更有效的提高土壤盐分空间分布的预测精度。研究结果表明,借助构建的土壤盐分解译模型可对研究区土壤盐渍化空间分布情况进行快速监测与评估,为该区土壤盐渍化的防治提供了一定的技术支撑。     

干旱区土壤盐渍化特征空间建模

当前,土壤盐渍化以及因灌溉引起的土壤次生盐渍化问题是我国干旱、半干旱区所面临的主要生态环境问题。在特征空间理论的支持下,以波谱分解技术为基础,以Landsat-TM、Landsat-ETM+多光谱遥感影像和野外调查数据为基础数据源,通过分析干旱区土壤盐渍化对地表生物物理特征的影响,探讨了表征盐渍化过程与地表生物物理特征之间的规律及定量关系,进而利用土壤盐渍化遥感监测中关键的3个指标——经过波谱分解技术获得的直接表征盐渍化的土壤盐渍化光谱、间接表征盐渍化的植被覆盖度和土壤水分含量协同构建了二维特征空间支持下的土壤盐渍化遥感监测模型VSSI(Vegetation fraction and Soil fraction Soil Index)、SVSI(Soil water contents and Vegetation fraction Soil Index)、SSSI(Soil water contents and Soil salinization fraction Soil Index)和三维特征空间支持下的土壤盐渍化遥感监测模型SVWSI和SDI。研究结果表明:基于三维特征空间建立的SVWSI(Soil salinization fraction-Vegetation fraction-Water contents Soil Index)和SDI(Soil Distance Index)模型对不同盐渍化程度土壤的敏感程度要高于基于传统二维特征空间建立的VSSI、SVSI和SSSI模型。其中,SVWSI和SDI模型与实测0—10 cm土壤盐分含量决定系数分别为R2=0.8325和R2=0.8646,这充分说明基于高维数特征空间所构建的土壤盐渍化遥感监测模型能更准确地反映盐渍化土壤地表盐量组合及其变化信息,且指标简单、易于获取,对于今后干旱区区域大尺度盐渍地信息提取以及动态监测研究具有重要意义。     

典型毛乌素沙漠-黄土高原过渡带土壤盐渍化空间异质性及其影响因素

毛乌素沙漠-黄土高原过渡带土壤盐渍化的空间异质性和生态学过程,对沙荒地整治的机理研究具有重要的意义.以毛乌素沙漠-黄土过渡带为研究区,结合布点取样和室内分析,运用经典统计学和地统计学方法对其pH、电导率、全盐含量的空间异质性进行分析.结果表明: 1)土壤pH、电导率、全盐含量的平均含量分别为8.44、5.13 mS·cm^-1和21.66 g·kg^-1,变异系数范围为6.9%～73.3%,pH属于弱变异,电导率和全盐含量属于中等程度变异.2)半方差分析结果显示,3个指标的空间变异性的最佳拟合模型均为球形模型,块金值/基台值比值范围为8.6%～14.3%,均具有强烈的空间自相关性,结构性因素对变异起主导作用;变程由小到大表现为pH＜全盐<电导率.克里金插值图显示,pH、电导率、全盐含量整体呈条带状分布,连续性较好.pH值表现出随着地势的升高而升高的特点,而电导率和全盐含量则表现出随着地势的升高而降低的特点.3)在垂直分布上,重度盐渍化区域的盐分有表聚现象,轻度盐渍化区域盐分垂直分布为先减少后增大.毛乌素沙漠-黄土过渡带土壤盐渍化的空间变异性与气候、地质条件、地形地貌、水文地质条件、植被分布等有关,以地形因素和水文地质条件的影响为主.     

黄河三角洲夏季典型田块土壤盐分的多尺度空间变异

土壤盐渍化严重阻碍黄河三角洲农业经济发展,掌握田间多尺度下土壤盐分的空间变异性特征对于盐渍土改良利用和农业生产有重要意义。选取黄河三角洲垦利区代表性夏季玉米田块,划分为大田、地块、垄间3个尺度,通过实地调查采样获取152 组电导率数据,运用经典统计学、地统计学和克里格插值方法,分析多尺度下田块土壤盐分的空间变异性特征及其尺度效应。结果表明: 试验区土壤为中度盐渍化,土壤盐分在3种尺度下均呈中等强度变异,从大田、地块到垄间,随着采样尺度的减小,土壤盐分的变异性趋强、标准差增大;垄间和地块尺度表现为强空间相关性,最优拟合模型为高斯模型,主要受结构性因素影响,大田尺度为中等空间相关性,最优拟合模型为指数模型,受随机性因素和结构性因素共同影响;不同尺度土壤盐分的空间分布特征有明显差异,小尺度的空间特征在大尺度下被掩盖,存在明显的尺度效应;垄间微域尺度下土壤盐分分布变异明显,土壤含盐量随微地貌由高到低、植被覆盖由疏至密而逐渐降低。     

沈阳市郊耕地土壤交换性Ca含量的空间异质性特征

利用地统计学和地理信息系统相结合的方法研究了沈阳市郊耕地土壤(0～20crn)交换性钙含量的空间异质性特征,绘制了交换性钙含量的空间分布图。结果表明,土壤交换性钙含量经对数转换后基本符合正态分布,变异函数的最佳理论模型为球状模型,交换性钙含量具有很强的空间相关性,空间自相关距离为15．8km,其空间异质性主要受成土母质和土壤类型等结构性因子的影响。     

基于改进遥感解译方法的盐碱耕地变化特征

以河北省滨海城市黄骅市为研究对象,以1992和2011年遥感影像为数据源,通过大量野外实地调查对遥感影像反演,建立了适于滨海盐碱地的基于盐碱地等级-地物标识植被特征-影像特征的分级分类解译标志系统.在此基础上采用遥感影像解译的监督分类法,提取了黄骅市盐碱耕地信息,进一步分析了1992—2011年间盐渍化耕地面积、盐碱等级转换及空间分布变化的特征.结果表明:研究期间,黄骅市耕地盐渍化程度减轻;与1992年相比,2011年黄骅市盐碱生态系统中重度和中度盐渍化耕地的面积减少,非或轻度盐渍化耕地面积增加,黄骅市东南部大量的中度盐渍化耕地转换为非或轻度盐渍化耕地,远离海岸线的黄骅市西部重度盐渍化耕地转换为中度或非或轻度盐渍化耕地;重度和非或轻度盐渍化耕地的重心向东部海岸线转移,中度盐渍化耕地的重心由东南海岸线向西北方向转移.黄骅市盐碱耕地变化的主要影响因素是气候、水文条件和人类活动.     

基于流域尺度的土壤盐分空间变异特征——以渭干河-库车河流域三角洲绿洲为例

土壤中水溶性盐的分析,是发展研究盐渍土盐分动态监测与预报技术的重要基础工作。针对目前干旱半干旱区广泛存在的绿洲土壤次生盐渍化问题,基于GIS和地统计学方法,研究了渭干河—库车河流域三角洲绿洲盐渍化土壤特征(土壤含盐量)的空间变异性。研究结果表明:渭-库绿洲土壤含盐量的空间变异性为中等变异,且随土壤深度增加而减弱。各层土壤的合理采样数为在95%置信水平,20%误差下的合理采样数目。高斯模型能够较好的拟合10-30cm及30-50cm层土壤含盐量的空间结构。各层土壤盐分空间变异性受到结构性与随机性因素共同作用的影响,呈强空间相关性。套合结构模型考虑到0-10cm层土壤盐分空间变异的尺度依赖性,能够更好的拟合0-10cm层土壤含盐量的空间结构。Kriging插值以及空间等值线分布趋势图能够直观的表现研究区内土壤盐分含量的空间分布状况和变化情况。研究为土壤特征变量空间变异分析与评价提供了普适性较强的实现方法,为构建盐渍土定量动态监测模型以及盐渍土的改良利用提供一定的科学依据。     

艾比湖流域小尺度农田土壤养分的空间分布和盐渍化风险评价

为了解绿洲经济迅速发展背景下新疆典型尾闾绿洲-艾比湖流域小尺度农田土壤的养分和盐渍化状况,对该地区典型农田土壤中有机质、碱解氮、速效磷和速效钾等养分元素的空间分布、影响因素以及盐渍化风险状况进行了评价。结果表明:(1)农田土壤中有机质、碱解氮、速效磷和速效钾的含量均较高。所有土壤样点中总盐分含量属于高度变异,其他指标属于低度变异。(2)半方差函数分析表明土壤中碱解氮、速效磷和速效钾含量的空间变异性主要受施肥和灌溉等随机性因素的影响;而有机质和总盐分含量的空间变异性则受植被覆盖和土壤质地等结构性因素以及施肥、灌溉等随机性因素的共同影响。(3)空间分析表明,总体看农田土壤中有机质、碱解氮、速效磷和速效钾含量较高区域主要分布在中部和北部,受施肥、灌溉方式和植被盖度等因素的影响;而盐分含量较高区域主要分布在研究区南部和边缘区域,主要受地形、土壤质地和植被盖度的影响。(4)相关分析表明农田土壤中有机质、速效钾、速效磷、碱解氮和总盐分含量呈显著的负相关关系。盐渍化风险评估表明土壤中总盐分含量属于低度到中度的盐渍化风险,不会对主要作物棉花的生长产生危害,但应改进灌溉方式和种植制度,同时采用增施有机肥、进行秸秆还田等措施促进棉花作物的稳产、高产。     

新疆玛纳斯流域非农业种植地盐碱性空间变异特征

土壤盐渍化是导致干旱区土地退化的主要原因之一,也是影响干旱区可持续发展和环境改善的基本问题。充分挖掘不同分类体系下盐渍土空间变异性可以为实施开垦或恢复生态措施提供科学依据。以干旱区开垦近50a的玛纳斯流域为研究区,在不同分类体系下,以土壤盐度,p H值,离子类型为指标,分析该区域非农业种植地(弃耕地,盐碱地,裸地,沙地)盐渍土类型的空间分布特征。结果表明:(1)研究区68%的样本属于非盐渍化,不同类型的盐渍土主要以链状分布于泉水溢出带-冲积平原-干三角洲地带,由南向北,区域整体盐分大致遵循先升高后降低再升高趋势,半方差函数分析土壤盐分呈现弱变异,说明这种分布情况是受随机(人为)因素的影响;而p H整体由南向北递增,传统统计学和地统计学的分析结果都表明土壤碱化呈现中等变异,受结构(自然)因素和随机(人为)因素的共同影响。表层土壤除在溢出带为氯化物型盐渍土外,其他地区自南向北由硫酸-氯化物型逐渐变为氯化-硫酸盐型和硫酸盐土、苏打盐土,离子的半方差函数拟合模型结果均是弱变异和中等变异,与美国盐度实验室分类体系的变异性结果相同,此类分布特征也是结构因素和随机因素共同作用的结果。(2)分析五种典型地貌的盐渍土分布,方差分析结果表明,5种地貌类型均呈现盐分表聚特征,碱化度则由南向北递增;其中盐碱特征最为显著的是泉水溢出带。泉水溢出带的盐土垂直方向的变化趋势为由表层至深层,盐土类型由硫酸-氯化物盐土变为氯化盐土;冲积平原和干三角洲样点处全剖面为氯化物-硫酸盐土,冲积洪积扇和沙漠地区则包含所有阴离子盐土类型。对玛纳斯流域盐渍土特性的空间异质性进行分析,可以为下一步有针对性地治理与改善土壤盐渍化提供科学依据。     

Effects of soil moisture on the temperature sensitivity of heterotrophic respiration vary seasonally in an old‐field climate change experiment

Microbial decomposition of soil organic matter produces a major flux of CO₂ from terrestrial ecosystems and can act as a feedback to climate change. Although climate‐carbon models suggest that warming will accelerate the release of CO₂ from soils, the magnitude of this feedback is uncertain, mostly due to uncertainty in the temperature sensitivity of soil organic matter decomposition. We examined how warming and altered precipitation affected the rate and temperature sensitivity of heterotrophic respiration (R_h) at the Boston‐Area Climate Experiment, in Massachusetts, USA. We measured R_h inside deep collars that excluded plant roots and litter inputs. In this mesic ecosystem, R_h responded strongly to precipitation. Drought reduced R_h, both annually and during the growing season. Warming increased R_h only in early spring. During the summer, when R_h was highest, we found evidence of threshold, hysteretic responses to soil moisture: R_h decreased sharply when volumetric soil moisture dropped below ~15% or exceeded ~26%, but R_h increased more gradually when soil moisture rose from the lower threshold. The effect of climate treatments on the temperature sensitivity of R_h depended on the season. Apparent Q₁₀ decreased with high warming (~3.5 °C) in spring and fall. Presumably due to limiting soil moisture, warming and precipitation treatments did not affect apparent Q₁₀ in summer. Drought decreased apparent Q₁₀ in fall compared to ambient and wet precipitation treatments. To our knowledge, this is the first field study to examine the response of R_h and its temperature sensitivity to the combined effects of warming and altered precipitation. Our results highlight the complex responses of R_h to soil moisture, and to our knowledge identify for the first time the seasonal variation in the temperature sensitivity of microbial respiration in the field. We emphasize the importance of adequately simulating responses such as these when modeling trajectories of soil carbon stocks under climate change scenarios.     

基于分数阶微分优化光谱指数的土壤电导率高光谱估算

土壤电导率与含盐量具有高度相关性,精准的土壤电导率监测有助于了解区域土壤的盐渍化程度,对区域盐渍化防治与调控,农业可持续发展以及生态文明建设具有重要意义。为寻求预测土壤电导率的最佳高光谱参数,实现土壤盐分信息的高效监测,本研究对土壤样品进行室内高光谱和电导率测定,利用两波段优化算法对简化光谱指数(nitrogen planar domain index, NPDI)进行波段优化,筛选不同高光谱数据(原始高光谱反射率及其对应的5种数学变换)运算下的最敏感高光谱参数,从而建立土壤电导率高光谱估算模型。结果表明:1)NPDIs与土壤电导率之间的相关性显著,在原数据及其平方根、倒数、对数倒数、1.6阶微分变换形式下,优化光谱指数对土壤电导率的敏感程度更强,相关系数绝对值均超过0.80,且基于1.6阶微分变换的(R_(2020nm)+R_(1893 nm))/R_(1893 nm)波段组合相关系数绝对值最高,达到0.888。2)基于1.6阶微分波段优化的预测模型效果最佳,预测精度为R■=0.84,RMSE_(Pre)=2.07mS/cm,RPD=2.94,AIC=158.11。因此,对高光谱数据的适当数学变换有利于优化光谱指数更好地估算土壤电导率,进一步实现土壤盐渍化高精度动态监测。     

Improvement of degraded physical properties of a saline-sodic soil by reclamation with kallar grass (Leptochloa fusca)

A field experiment was conducted to evaluate the effectiveness of growing salt tolerant plants to improve the physical characteristics of a saline-sodic soil. Kallar grass [Leptochloa fusca (L.) Kunth], a species tolerant to salinity, sodicity and alkalinity, was irrigated for five years with poor quality ground water (EC = 0.14 S m^–1, SAR_adj=19.3, RSC = 9.7 meq L^–1). The soil physical properties of plant available water, saturated hydraulic conductivity, structural stability, bulk density and porosity were determined at the end of each year. The growth of kallar grass for three years significantly improved the physical properties of the soil and these were maintained with further growth of grass up to five years. Kallar grass significantly increased plant available water with time (r=0.97^**). The available water was highly correlated (r=0.92^**) with increases in soil organic matter content, porosity (r=0.99^**) and other physical properties. Soil hydraulic conductivity increased substantially with time from 0.035 to 55.6 mm d^–1 in the topsoil (0–20 cm) in five years and was significantly correlated with porosity, water retention, structural stability and organic matter content of soil. The soil structural stability index improved significantly from 32 to 151 with kallar grass and showed greater increases in the surface soil than at depth. The cropping of kallar grass resulted in a linear increase of soil organic matter content (r=0.92^**) which improved porosity and other soil physical properties (r0.82^*). This study confirmed that kallar grass is effective for rehabilitation and restoration of soil fertility in saline-sodic areas on a sustainable basis.     

Comparative regional-scale soil salinity assessment with near-ground apparent electrical conductivity and remote sensing canopy reflectance

Soil salinity is recognized worldwide as a major threat to agriculture, particularly in arid and semi-arid regions. Producers and decision makers need updated and accurate maps of salinity in agronomically and environmentally relevant ranges (i.e., <20 dS m⁻¹, when salinity is measured as electrical conductivity of the saturation extract, EC_e). State-of-the-art approaches for creating accurate EC_e maps beyond field scale (i.e., 1 km²) include: (i) Analysis Of Covariance (ANOCOVA) of near-ground measurements of apparent soil electrical conductivity (EC_a) and (ii) regression modeling of multi-year remote sensing canopy reflectance and other co-variates (e.g., crop type, annual rainfall). This study presents a comparison of the two approaches to establish their viability and utility. The approaches were tested using 22 fields (total 542 ha) located in California’s western San Joaquin Valley. In 2013 EC_a-directed soil sampling resulted in the collection of 267 soil samples across the 22 fields, which were analyzed for EC_e, ranging from 0 to 38.6 dS m⁻¹. The ANOCOVA EC_a-EC_e model returned a coefficient of determination (R²) of 0.87 and root mean square prediction error (RMSPE) of 3.05 dS m⁻¹. For the remote sensing approach seven years (2007–2013) of Landsat 7 reflectance were considered. The remote sensing salinity model had R² = 0.73 and RMSPE = 3.63 dS m⁻¹. The robustness of the models was tested with a leave-one-field-out (lofo) cross-validation to assure maximum independence between training and validation datasets. For the ANOCOVA model, lofo cross-validation provided a range of scenarios in terms of RMSPE. The worst, median, and best fit scenarios provided global cross-validation R² of 0.52, 0.80, and 0.81, respectively. The lofo cross-validation for the remote sensing approach returned a R² of 0.65. The ANOCOVA approach performs particularly well at EC_e values <10 dS m⁻¹, but requires extensive field work. Field work is reduced considerably with the remote sensing approach, but due to the larger errors at low EC_e values, the methodology is less suitable for crop selection, and other practices that require accurate knowledge of salinity variation within a field, making it more useful for assessing trends in salinity across a regional scale. The two models proved to be viable solutions at large spatial scales, with the ANOCOVA approach more appropriate for multiple-field to landscape scales (1–10 km²) and the remote sensing approach best for landscape to regional scales (>10 km²).     

Local distribution of ectomycorrhizae-associated basidiomycetes in forest soil correlates with the degree of soil organic matter humification and available electrolytes

Spatial distribution of ectomycorrhizae-associated basidiomycetes was determined in oakbirch forest using terminal restriction fragment length polymorphism (T-RFLP) analysis. The data were correlated with actual soil humidity, pH, electric conductivity of the soil extract, absorbance A ₄₆₅ and A ₆₆₅ of water and alkali soil extracts and with the ratio A ₄₆₅/A ₆₆₅ (parameter A4/A6). Natural non-homogeneity of the soil parameters was used as experimental gradient. Distance-based redundancy analysis of the T-RFLP data (with soil parameters being taken as environmental parameters) provided significant results when ITS1F-terminanted restriction fragments were analyzed. Among other fungi, a Mycena galericulata related fungus was observed to correlate negatively with A4/A6, indicating its association with highly humified soil organic matter. Positive association of other, unidentified fungi with A4/A6 was also observed. Several other unidentified fungi negatively correlated with electric conductivity of the soil extract. The results may explain nonhomogeneity of the spatial distribution of the fungi associated with ectomycorrhizae as a result of their interaction with non-homogeneous soil environment.     

Spatial heterogeneity distribution of soil total nitrogen and total phosphorus in the Yaoxiang watershed in a hilly area of northern China based on geographic information system and geostatistics

Soil total nitrogen (STN) and total phosphorus (STP) are important indicators of soil nutrients and the important indexes of soil fertility and soil quality evaluation. Using geographic information system (GIS) and geostatistics, the spatial heterogeneity distribution of STN and STP in the Yaoxiang watershed in a hilly area of northern China was studied. The results showed that: (1) The STN and STP contents showed a declining trend with the increase in soil depth; the variation coefficients (C_v) of STN and STP in the 0‐ to 10‐cm soil layer (42.25% and 14.77%, respectively) were higher than in the 10‐ to 30‐cm soil layer (28.77% and 11.60%, respectively). Moreover, the C_v of STN was higher than that of STP. (2) The maximum C₀/(C₀ + C₁) of STN and STP in the soil layers was less than 25%, this indicated that a strong spatial distribution autocorrelation existed for STN and STP; and the STP showed higher intensity and more stable variation than the STN. (3) From the correlation analysis, we concluded that the topographic indexes such as elevation and slope direction all influenced the spatial distribution of STN and STP (correlation coefficients were 0.688 and 0.518, respectively). (4) The overall distribution of STN and STP in the Yaoxiang watershed decreased from the northwest to the southeast. This variation trend was similar to the watershed DEM trend and was significantly influenced by vegetation and topographic factors. These results revealed the spatial heterogeneity distribution of STN and STP, and addressed the influences of forest vegetation coverage, elevation, and other topographic factors on the spatial distribution of STN and STP at the watershed scale.     

Effects of mycorrhizal fungus isolates on mineral acquisition by Panicum virgatum in acidic soil

 Plant ability to withstand acidic soil mineral deficiencies and toxicities can be enhanced by root-arbuscular mycorrhizal fungus (AMF) symbioses. The AMF benefits to plants may be attributed to enhanced plant acquisition of mineral nutrients essential to plant growth and restricted acquisition of toxic elements. Switchgrass (Panicum virgatum L.) was grown in pH_Ca (soil:10 mM CaCl₂, 1 : 1) 4 and 5 soil (Typic Hapludult) inoculated with Glomus clarum, G. diaphanum, G. etunicatum, G. intraradices, Gigaspora albida, Gi. margarita, Gi. rosea, and Acaulospora morrowiae to determine differences among AMF isolates for mineral acquisition. Shoots of mycorrhizal (AM) plants had 6.2-fold P concentration differences when grown in pH_Ca 4 soil and 2.9-fold in pH_Ca 5 soil. Acquisition trends for the other mineral nutrients essential for plant growth were similar for AM plants grown in pH_Ca 4 and 5 soil, and differences among AMF isolates were generally higher for plants grown in pH_Ca 4 than in pH_Ca 5 soil. Both declines and increases in shoot concentrations of N, S, K, Ca, Mg, Zn, Cu, and Mn relative to nonmycorrhizal (nonAM) plants were noted for many AM plants. Differences among AM plants for N and Mg concentrations were relatively small (<2-fold) and were large (2- to 9-fold) for the other minerals. Shoot concentrations of mineral nutrients did not relate well to dry matter produced or to percentage root colonization. Except for Mn and one AMF isolate, shoot concentrations of Mn, Fe, B, and Al in AM plants were lower than in nonAM plants, and differences among AM plants for these minerals ranged from a low of 1.8-fold for Fe to as high as 6.9-fold for Mn. Some AMF isolates were effective in overcoming acidic soil mineral deficiency and toxicity problems that commonly occur with plants grown in acidic soil. Accepted: 14 June 1999     

Central boreal mire plant communities along soil nutrient potential and water content gradients

Peatlands have traditionally been exploited in forestry and agriculture over the boreal region, yet they also provide substantial source of fuel production. The large-scale exploitation of peatlands has raised a concern about the diversity of mire plant communities. We studied composition of mire plant communities along soil nutrient potential and water content gradients, to recognize the areas with the high plant diversity. Soil electrical conductivity (EC_b) was measured to characterise soil nutrient regimes and soil dielectric permittivity (DP) the soil (volumetric) water regimes. A total of 115 mire sites were studied in the central boreal region of south-western Finnish Lapland. We found that Ward’s hierarchical cluster analysis produced eight stable EC_b and DP clusters with discrete vegetation compositions. On the basis of a locally weighted regression analysis (Loess), Carex dioica L., Comarum palustre L., Equisetum fluviatile L., Menyanthes trifoliata L., and Scorpidium scorpioides (Hedw.) Limpr. were found as indicator species for nutrient-rich regimes as designated by high soil EC_b. The soil EC_b is a diagnostic measure of plant diversity as EC_b?>?7 mSm^?1 resulted in a considerable increase in species richness. Our classification method, based on electrical measurements, provides a simple way to classify mires and focus detailed research to areas with potentially high conservation value.