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Soil macrofaunal biodiversity in Amazonian pastures: matching sampling with patterns.

机译:亚马逊草场的土壤大型动物生物多样性:采样与模式匹配。

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Soil biodiversity varies through space as influenced by habitat features and land-use history. The performance of any sampling strategy highly depends on its relevance with regards to this pattern. We surveyed the soil macrofaunal species richness in the pastures of the Benfica Field Station (Eastern Amazonia, State of Para, Brazil) and described its variability in 4 independent replicate plots. We designed a within-plot sampling scheme that accounted for the soil spatial variation (stratified sampling). Replicated pasture plots had different species richness (49-65) corresponding to a low proportion (40-53%) of the total number of species (123). Pairs of replicated plots showed an outstandingly low number of shared species (28-41% of the species pool). Likewise, different classes of soil thickness, corresponding to a Ferralsol-Cambisol sequence, had different species richness (12-44) and exhibited a very low proportion of shared species (15-29%). The proportion of rare species, i.e. singletons, ranged from 40-51% of the total species richness depending on the plot considered. We used the abundance-based coverage estimator of species richness (ACE) and the Chao shared species estimator that provides a correction based on the relative abundance of rare species. These indices also showed both a high between plots dissimilarity and a substantial within plot variability of species composition. Because of the high proportion of rare species, the rarefaction curves failed to reach any asymptote in all replicated plots. Bootstrap resampling showed that less than 5 samples per stratum (class of soil thickness) provided inconsistent species richness values. We simulated the efficiency of sampling strategies that included our 4 replicate plots and the 3 classes of soil thickness but with varying sampling effort within each stratum. The results indicated that a fairly large (74%) proportion of species would be recorded if strata were sampled using 5 sampling units (hence 15 samples per plot for a total of 4x15=60 samples). This study showed the need for adequate plot replication in soil macrofaunal biodiversity studies. Also, the main relevant factors of within-replicate plot spatial heterogeneity (e.g. soil, vegetation) should be accounted for through stratified sampling. The results showed that there is no way of reducing the local sampling effort below a certain level (here, 5 sampling units per stratum)..
机译:土壤生物多样性受生境特征和土地使用历史的影响,随空间变化。任何采样策略的性能在很大程度上取决于其与该模式的相关性。我们调查了本菲卡田地站(巴西帕拉州东部亚马逊河)牧场上的土壤大型动物物种丰富度,并描述了其在4个独立重复样地中的变异性。我们设计了一个考虑土壤空间变化的分层抽样方案(分层抽样)。复制的牧场具有不同的物种丰富度(49-65),相当于物种总数(123)的低比例(40-53%)。成对的复制地块显示出极少的共有物种(占物种库的28-41%)。同样,对应于Ferralsol-Cambisol序列的不同类别的土壤厚度具有不同的物种丰富度(12-44),并且显示出极低的共有物种比例(15-29%)。根据所考虑的地块,稀有物种(即单例物种)的比例为物种总丰富度的40-51%。我们使用了基于物种丰富度(ACE)的基于丰度的覆盖率估计器和基于稀有物种的相对丰度提供校正的Chao共享物种估计器。这些指数还显示出不同地块之间的差异很高,并且不同地块之间的物种组成差异很大。由于稀有物种的比例很高,稀疏曲线未能在所有重复样区中达到任何渐近线。 Bootstrap重采样显示,每层少于5个样本(土壤厚度类别)提供的物种丰富度值不一致。我们模拟了采样策略的效率,其中包括我们的4个重复样地和3种土壤厚度类别,但每个层中的采样工作有所不同。结果表明,如果使用5个采样单位采样地层,则将记录相当大比例的物种(74%)(因此,每块地15个采样,总共4x15 = 60个采样)。这项研究表明,在土壤大型动物生物多样性研究中需要适当地块复制。同样,应通过分层抽样考虑重复样区内空间异质性的主要相关因素(例如土壤,植被)。结果表明,没有办法将本地采样工作降低到一定水平以下(此处,每层5个采样单位)。

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