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Broad scale distribution of ferns and lycophytes along environmental gradients in central and northern Amazonia, Brazil.

机译:在巴西中部和北部,蕨类植物和苔藓植物沿环境梯度的广泛分布。

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Establishing which factors determine species distributions is of major relevance for practical applications such as conservation planning. The Amazonian lowlands exhibit considerable internal heterogeneity that is not apparent in existing vegetation maps. We used ferns as a model group to study patterns in plant species distributions and community composition at regional and landscape scales. Fern species composition and environmental data were collected in 109 plots of 250x2 m distributed among four sites in Brazilian Amazonia. Interplot distances varied from 1 to ca 670 km. When floristically heterogeneous datasets were analyzed, the use of an extended Sorensen dissimilarity index rather than the traditional Sorensen index improved model fit and made interpretation of the results easier. Major factors associated with species composition varied among sites, difference in cation concentration was a strong predictor of floristic dissimilarity in those sites with pronounced heterogeneity in cation concentration. Difference in clay content was the most relevant variable in sites with uniform cation concentrations. In every case, environmental differences were invariably better than geographic distances in predicting species compositional differences. Our results are consistent with the ideas that: (1) the relative predictive capacity of the explanatory variables depend on the relative lengths of the observed gradients; and (2) environmental gradients can be hierarchically structured such that gradients occur inside gradients. Therefore, site-specific relationships among variables can mask the bigger picture and make it more difficult to unravel the factors structuring plant communities in Amazonia.
机译:确定哪些因素决定物种分布与诸如保护规划等实际应用具有重大关系。亚马孙低地表现出相当大的内部异质性,这在现有的植被图中是不明显的。我们使用蕨类作为模型组来研究区域和景观尺度下植物物种分布和群落组成的模式。在分布于巴西亚马逊地区四个地点的109个250x2 m地块中收集了蕨类植物的成分和环境数据。情节距离从1到大约670公里不等。在分析植物种类异类的数据集时,使用扩展的Sorensen相异指数而不是传统的Sorensen指数可以改善模型拟合,并易于解释结果。与物种组成相关的主要因素在站点之间有所不同,阳离子浓度的差异是强烈指示阳离子浓度异质性的那些站点的植物区系相似性的强烈预测因子。粘土含量的差异是阳离子浓度一致的部位中最相关的变量。在每种情况下,在预测物种组成差异方面,环境差异总是比地理距离好。我们的结果与以下思想相符:(1)解释变量的相对预测能力取决于观测到的梯度的相对长度; (2)可以对环境梯度进行分层构造,以使梯度出现在梯度内部。因此,变量之间的特定于站点的关系可以掩盖更大的前景,并且更难于揭示构成亚马逊地区植物群落的因素。

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