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The intersection of diversity metrics and spatial mapping: a case study of regional vegetation patterns for a complex community

机译:多样性度量与空间测绘的交点 - 以复杂社区为例

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We evaluate the contribution of small-scale floristic diversity to regional vegetation patterns, if current vegetation classification methods adequately account for small-scale floristic diversity and the potential role of diversity metrics in contributing to improved classification and mapping of plant community patterns. Upland swamps in the Greater Blue Mountains World Heritage Area, Australia, were used as a case study for this evaluation. Eight hundred and eleven survey plots using two contrasting survey designs were used to generate diversity metrics (α; β; ?; ζ; multivariate dispersion) and these were intersected with spatial mapping across 69 swamps. A novel classification informed by small-scale floristic diversity was also implemented. Diversity patterns at the regional scale were significantly affected by survey design (both β and ζ overestimated by a survey design using large plots, but α, ? and multivariate dispersion not significantly different among plot designs). Secondly, the novel classification revealed that the majority of assemblages present were previously unreported. Thirdly, floristic assemblages previously mapped only in discrete parts of the region were found to be widespread. A poor correlation exists between current standard classification approaches and a classification informed by small-scale floristic diversity. Thus, recommended and implemented standards for survey and classification in many jurisdictions globally are inadequate for revealing diversity patterns and mapping communities with complex small-scale diversity patterns. Communities of this type are widespread globally. Our study demonstrates that the intersection of advanced diversity metrics and spatial mapping, using small-scale survey data, provides critical insights into regional vegetation patterns that may otherwise remain obscure.
机译:我们评估小规模的植物多样性对区域植被模式的贡献,如果目前的植被分类方法充分考虑了小规模的植物多样性以及多样性指标的潜在作用,可以改善植物群落模式的分类和映射。澳大利亚大蓝山世界遗产地区的高地沼泽被用作该评估的案例研究。使用使用两个对比调查设计的八百和十一调查图来产生分集度量(α;β;β;ζ;多变量分散体),并且这些地位与69沼泽的空间映射相交。还实施了小型植物多样性的新型分类。区域规模的多样性模式受到调查设计的显着影响(β和ζ通过调查设计使用大图,但α,α,绘图设计中没有显着不同的多变量分散)。其次,新颖的分类透露,大多数大多数集会都是未报告的。第三,发现此前仅在该地区的离散地区映射的植物组装是普遍的。当前标准分类方法之间存在差的相关性和小规模植物多样性的分类。因此,全球许多司法管辖区的调查和分类的建议和实施标准对于具有复杂的小规模多样性模式的多样性模式和映射社区不足。这种类型的社区在全球范围内普遍存在。我们的研究表明,使用小规模调查数据的高级分集度量和空间映射的交叉对区域植被模式的关键见解提供了否则可能仍然模糊的区域。

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