Global functional variation in alpine vegetation

Abstract

Questions: What are the functional trade-offs of vascular plant species in global alpine ecosystems? How is functional variation related to vegetation zones, climatic groups and biogeographic realms? What is the relative contribution of macroclimate and evolutionary history in shaping the functional variation of alpine plant communities? Location: Global. Methods:We compiled a data set of alpine vegetation with 5,532 geo-referenced plots, 1,933 species and six plant functional traits. We used principal component analysis to quantify functional trade-offs among species and trait probability density to assess the functional dissimilarity of alpine vegetation in different vegetation zones, climatic groups and biogeographic realms. We used multiple regression on distance matrices to model community functional dissimilarity against environmental and phylogenetic dissimilarity, controlling for geographic distance. Results:The first two PCA axes explained 66% of the species' functional variation and were related to the leaf and stem economic spectra, respectively. Trait probability density was largely independent of vegetation zone and macroclimate but differed across biogeographic realms. The same pattern emerged for both species pool and community levels. The effects of environmental and phylogenetic dissimilarities on community functional dissimilarity had similar magnitude, while the effect of geographic distance was negligible.Conclusions: Plant species in alpine areas reflect the global variation of plant function, but with a predominant role of resource use strategies. Current macroclimate exerts a limited effect on alpine vegetation, mostly acting at the community level in combination with evolutionary history. Global alpine vegetation is functionally unrelated to the vegetation zones in which it is embedded, exhibiting strong functional convergence across regions.

Collaboration networks and hot topics in the Journal of Vegetation Science

“…Based on their own fieldwork and literature review, they defined fairy circles as a specific phenomenon and compared it to other types of circular vegetation gaps and herbaceous rings. The two forerunners are Testolin et al (2021) and McKone et al (2021). Riccardo Testolin and co‐authors compiled and analysed a large database of alpine vegetation plots to identify the main axes of functional trade‐offs at the species level, which were then integrated at the community level.…”

Macroecology of vegetation — Lessons learnt from the Virtual Special Issue

“…For plants, this Special Issue demonstrates that many studies and large initiatives have addressed this gap since then. A total of 15 contributions used fine‐grain plant community data to address macroecological questions at various extents: global (Kusumoto et al, 2021; Testolin et al, 2021), across the whole Palaearctic (Biurrun et al, 2021; Dembicz et al, 2021; Zhang et al, 2021), across Europe (Axmanová et al, 2021; Boonman et al, 2021; Padullés Cubino et al, 2021; Sporbert et al, 2021; Večera et al, 2021), larger parts of Europe (Cao Pinna et al, 2021; Wagner et al, 2021) or at state level (Bourgeois et al, 2021; Craven et al, 2021). Most of these studies rely on two large vegetation‐plot databases established and maintained by two working groups of the International Association for Vegetation Science (IAVS), the European Vegetation Archive (EVA; Chytrý et al, 2016) by the European Vegetation Survey (Axmanová et al, 2021; Boonman et al, 2021; Cao Pinna et al, 2021; Padullés Cubino et al, 2021; Sporbert et al, 2021; Večera et al, 2021; Wagner et al, 2021) and the GrassPlot database (Dengler et al, 2018) by the Eurasian Dry Grassland Group (Biurrun et al, 2021; Dembicz et al, 2021; Zhang et al, 2021).…”

“…Most of these studies rely on two large vegetation‐plot databases established and maintained by two working groups of the International Association for Vegetation Science (IAVS), the European Vegetation Archive (EVA; Chytrý et al, 2016) by the European Vegetation Survey (Axmanová et al, 2021; Boonman et al, 2021; Cao Pinna et al, 2021; Padullés Cubino et al, 2021; Sporbert et al, 2021; Večera et al, 2021; Wagner et al, 2021) and the GrassPlot database (Dengler et al, 2018) by the Eurasian Dry Grassland Group (Biurrun et al, 2021; Dembicz et al, 2021; Zhang et al, 2021). Testolin et al (2021) used data from the global vegetation‐plot database sPlot (Bruelheide et al, 2019), and four relied on regional data compilations (Bourgeois et al, 2021; Craven et al, 2021; Kusumoto et al, 2021; Tordoni et al, 2021). This pattern highlights that community efforts of collating extensive collaborative vegetation‐plot databases, such as EVA, sPlot and GrassPlot, have the potential to facilitate new research avenues (Bruelheide et al, 2019; Dengler et al, 2011; Wiser, 2016), often beyond the initial scopes imagined by the founders of these databases, not mentioning the aims of most original field workers.…”

sPlotOpen – An environmentally balanced, open‐access, global dataset of vegetation plots

“…Established in 2013, sPlot v3.0 currently contains more than 1.9 million vegetation plots, and is fully integrated with the TRY database (Kattge et al., 2020), from which it derives information on plant functional traits. The sPlot database is increasingly being used to study continental‐to‐global scale vegetation patterns (Cai et al., 2021; Testolin, Attorre, et al., 2021; Testolin, Carmona, et al., 2021), such as the relative contribution of regional versus local factors to the global patterns of fern richness (Weigand et al., 2020), the mechanisms underlying the spread and abundance of native versus invasive tree species (van der Sande et al., 2020), and worldwide trait–environment relationships in plant communities (Bruelheide et al., 2018).…”