The partitioning of β-diversity is a recurrent practice in biogeographic and ecological studies that can provide key insights for land management, such as identification of biodiversity hot-spots. In this study, we used Baselga’s metrics to measure the contribution of spatial turnover (β_sim) and nestedness-resultant dissimilarity (β_nes) to overall β-diversity (β_sor) within- and between-forest types. We analyzed a presence/absence dataset concerning 593 species of nocturnal Lepidoptera sampled within chestnut, silver fir, beech, and black pine forests of southern Italy. Ordination methods and analysis of similarities were used to assess the relative contribution of β_sim and β_nes to β_sor, and to assess their relationships with variables linked to the experimental design and known to be determinant for insect diversity and abundance. We found that β_sor was mostly due to turnover, around 98.5% in β-diversity assessment of the whole sample, and around 91% in β-diversity assessment of individual forests. Using ordination analyses based on β_sim, stands were grouped according to forest type, while β_nes alone was used to ordinate stands coherently with their species richness. Nevertheless, the addition of β_nes to β_sim produced a more ecologically coherent grouping of stands within individual forest types, and β_nes alone was able to recognize patterns determined by human disturbance. In conclusion, we demonstrate that β-diversity partitioning can help to detect differences in magnitude and role of processes determining the composition of forest moth communities as in different forests the same pattern can be due to opposite processes, providing strong ecological insights into managing forest biodiversity.

中文翻译：

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不同森林类型内和之间的蛾类群落的β-多样性分配

β多样性的划分是生物地理学和生态学研究中的一种常见做法，可以为土地管理提供重要见解，例如确定生物多样性热点。在这项研究中，我们使用巴塞尔加（Baselga）的度量标准来衡量森林内部和森林之间类型的空间周转率（_βsim）和嵌套性结果不相似度（_βnes）对总体β多样性（_βsor）的贡献。我们分析了在意大利南部的栗子，银杉，山毛榉和黑松林中采样的593种夜间鳞翅目的有无数据集。使用排序方法和相似性分析来评估_βsim和_βnes对_βsor的相对贡献，并评估它们与与实验设计相关的变量的关系，这些变量已知是决定昆虫多样性和丰度的因素。我们发现_βsor主要是由于营业额引起的，整个样本的β多样性评估约占98.5％，单个森林的β多样性评估约占91％。使用基于_βsim的排序分析，根据森林类型对林分进行分组，而仅使用_βnes来对林分与其物种丰富度进行连贯协调。然而，另外的β_内斯以β _SIM产生个别森林类型内看台的生态更连贯的分组和β_内斯一个人就能识别出由人为干扰决定的模式。总而言之，我们证明了β-多样性分区可以帮助检测决定森林蛾类群落组成的过程的大小和作用差异，因为在不同的森林中，相同的模式可能是由于相反的过程所致，从而为管理森林生物多样性提供了强大的生态学见解。