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Classifications of forest vegetation types and characterization of related species assemblages are important analytical tools for mapping and diversity monitoring of forest communities. The discrimination of forest communities is often based on β-diversity, which can be quantified via numerous indices to derive compositional dissimilarity between samples. This study aims to evaluate the applicability of unsupervised classification for National Forest Inventory data from Georgia by comparing two cluster hierarchies. We calculated the mean basal area per hectare for each woody species across 1059 plot observations and quantified interspecies distances for all 87 species. Following an unspuervised cluster analysis, we compared the results derived from the species-neutral dissimilarity (Bray-Curtis) with those based on the Discriminating Avalanche dissimilarity, which incorporates interspecies phylogenetic variation. Incorporating genetic variation in the dissimilarity quantification resulted in a more nuanced discrimination of woody species assemblages and increased cluster coherence. Favorable statistics include the total number of clusters (23 vs. 20), mean distance within clusters (0.773 vs. 0.343), and within sum of squares (344.13 vs. 112.92). Clusters derived from dissimilarities that account for genetic variation showed a more robust alignment with biogeographical units, such as elevation and known habitats. We demonstrate that the applicability of unsupervised classification of species assemblages to large-scale forest inventory data strongly depends on the underlying quantification of dissimilarity. Our results indicate that by incorporating phylogenetic variation, a more precise classification aligned with biogeographic units is attained. This supports the concept that the genetic signal of species assemblages reflects biogeographical patterns and facilitates more precise analyses for mapping, monitoring, and management of forest diversity., Competing Interests: The authors declare no competing interests., (© 2024 The Author(s). Ecology and Evolution published by John Wiley & Sons Ltd.)

Large-scale barcoding projects help to aggregate information on genetic variability of multiple species throughout their ranges. Comparing DNA sequences of both non-conspecific and conspecific individuals from distant parts of their ranges helps to compare level of genetic isolation-by-distance patterns in different species and adaptive types. We compared mitochondrial CO1 gene sequences of 223 spiders from Georgia (Caucasus), representing 124 species and eight families, with 3097 homological sequences from spiders mostly from Europe, but also from other parts of the World. In most families, a significant isolation-by distance pattern was observed on family level. On species level, a significant isolation-by-distance was observed in 40 species, although this low proportion is most likely related to a lack of data. Simultaneously, remarkable differences in spatial structure were shown for different species. Although the majority of the studied species have a broad western Palearctic range, web-building spiders from families Araneidae, Theridiidae, and Linyphiidae are less isolated spatially than flower spiders (Thomisidae), jumping spiders (Salticidae), wolf spiders (Lycosidae), sac spiders (Clubionidae), and ground spiders (Gnaphosidae). This pattern is related with more common ballooning in web building than in actively hunting spiders, which commonly remain isolated since preglacial time. Ground spiders build the most isolated populations in the Caucasus., Competing Interests: None declared., (© 2024 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.)

All ecosystems face ecological challenges in this century. Therefore, it is becoming increasingly important to understand the ecology and degree of local adaptation of functionally important Arctic-alpine biomes by looking at the most diverse taxon of metazoans: the Arthropoda. This is the first study to utilize metabarcoding in the Alpine tundra, providing insights into the effects of micro-environmental parameters on alpha- and beta-diversity of arthropods in such unique environments. To characterize arthropod diversity, pitfall traps were set at three middle-alpine sampling sites in the Scandinavian mountain range in Norway during the snow-free season in 2015. A metabarcoding approach was then used to determine the small-scale biodiversity patterns of arthropods in the Alpine tundra. All DNA was extracted directly from the preservative EtOH from 27 pitfall traps. In order to identify the controlling environmental conditions, all sampling locations were equipped with automatic data loggers for permanent measurement of the microenvironmental conditions. The variables measured were: air temperature [°C] at 15 cm height, soil temperature [°C] at 15 cm depth, and soil moisture [vol.%] at 15 cm depth. A total of 233 Arthropoda OTUs were identified. The number of unique OTUs found per sampling location (ridge, south-facing slope, and depression) was generally higher than the OTUs shared between the sampling locations, demonstrating that niche features greatly impact arthropod community structure. Our findings emphasize the fine-scale heterogeneity of arctic-alpine ecosystems and provide evidence for trait-based and niche-driven adaptation. The spatial and temporal differences in arthropod diversity were best explained by soil moisture and soil temperature at the respective locations. Furthermore, our results show that arthropod diversity is underestimated in alpine-tundra ecosystems using classical approaches and highlight the importance of integrating long-term functional environmental data and modern taxonomic techniques into biodiversity research to expand our ecological understanding of fine- and meso-scale biogeographical patterns., Competing Interests: The authors declare no conflict of interest., (© 2024 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.)