Tracking succession by means of 3D scans of plant communities in a glacier forefield to infer assembly processes

Abstract

In primary successions, assembling plant communities are key for ecosystem functioning and stability. Often, plant successions are described on a taxonomic, functional and/or phylogenetic level, where species' identities, traits or evolutionary histories are considered. In this study, we exploited community features characterizing whole plant assemblages to capture emerging properties only available at the community level. Next to features aggregating over multiple plant species, we used a customized multispectral 3D plant scanner extracting digital community features as proxies for the frequency distribution of traits, productivity, prevalence of plant competition, and plant strategies and functions. Using these community features, we provide a comprehensive description of plant successions along glacier forefield. Additionally, we used a community feature-based framework assessing the covariance of community feature dissimilarities and environmental dissimilarity to explore the mechanisms underlying plant community assemblies. Our data indicate a shift from fast-growing and acquisitive, to slow-growing and conservative plant strategies; increased productivity; higher competition between plant species; and an increasing contribution to the biogeomorphic stability along the successional gradient. Our results further indicate that stochastic processes dominate in early succession, whereas communities are mainly shaped by deterministic processes including environmental filtering and species interactions at late succession. We conclude that assessments of plant community features, facilitated by the use of field-ready 3D scanners, provide complementary information to trait-based approaches on the species level with implications for ecological processes.