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首页> 外文期刊>Ecosystems >Relationship of Salt Marsh Vegetation Zonation to Spatial Patterns in Soil Moisture, Salinity, and Topography
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Relationship of Salt Marsh Vegetation Zonation to Spatial Patterns in Soil Moisture, Salinity, and Topography

机译:盐沼植被分区与土壤水分,盐分和地形的空间格局的关系

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An intertidal San Francisco Bay salt marsh was used to study the spatial relationships between vegetation patterns and hydrologic and edaphic variables. Multiple abiotic variables were represented by six metrics: elevation, distance to major tidal channels and to the nearest channel of any size, edaphic conditions during dry and wet circumstances, and the magnitude of tidally induced changes in soil saturation and salinity. A new approach, quantitative differential electromagnetic induction (Q-DEMI), was developed to obtain the last metric. The approach converts the difference in soil electrical conductivity (ECa) between dry and wet conditions to quantitative maps of tidally induced changes in root zone soil water content and salinity. The result is a spatially exhaustive map of edaphic changes throughout the mapped area of the ecosystem. Spatially distributed data on the six metrics were used to explore two hypotheses: (1) multiple abiotic variables relevant to vegetation zonation each exhibit different, uncorrelated, spatial patterns throughout an intertidal salt marsh; (2) vegetation zones and habitats of individual plant species are uniquely characterized by different combinations of key metrics. The first hypothesis was supported by observed, uncorrelated spatial variability in the metrics. The second hypothesis was supported by binary logistic regression models that identified key vegetation zone and species habitat characteristics from among the six metrics. Based on results from 108 models, the Q-DEMI map of saturation and salinity change was the most useful metric of those tested for distinguishing different vegetation zones and plant species habitats in the salt marsh.
机译:潮间带旧金山湾盐沼被用来研究植被格局与水文和水文变量之间的空间关系。多个非生物变量由六个指标表示:海拔,到主要潮汐通道的距离以及到任何大小的最近通道的距离,在干燥和潮湿环境下的水土条件以及潮汐引起的土壤饱和度和盐分变化的幅度。开发了一种新的方法,即定量差分电磁感应(Q-DEMI),以获得最后一个度量。该方法将干湿条件之间的土壤电导率(ECa)差异转换为潮汐诱导的根区土壤含水量和盐分变化的定量图。结果是在生态系统的整个绘制区域中,一次深度变化的空间详尽图。六个指标的空间分布数据被用来探索两个假设:(1)与植被分区有关的多个非生物变量,每个变量在整个潮间带盐沼中表现出不同的,不相关的空间格局; (2)单个植物物种的植被带和生境通过关键指标的不同组合而具有独特的特征。第一个假设得到度量中观察到的,不相关的空间变异性的支持。第二个假设得到二进制逻辑回归模型的支持,该模型从六个指标中确定了关键的植被区和物种栖息地特征。基于108个模型的结果,饱和度和盐度变化的Q-DEMI图是用于测试以区分盐沼中不同植被区和植物物种栖息地的最有用的度量。

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