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

Supplementary dataset for START-Project from 2019-2022 at the Ödenwinkel research platform, Austria, used in "Using community features to track plant successions and 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, phylogenetic and/or functional level, where species’ identities and traits are considered. In this study, we additionally considered community features characterizing whole plant assemblages to capture emerging properties only available at the community level. Using a customized multispectral 3D plant scanner that returns morphological and physiological parameters of communities that represent proxies for the frequency distribution of traits within a community and inform about the productivity, the prevalence of competition among plant species, and ecosystem functions of local vegetation. By tracking taxonomic and phylogenetic composition and diversity of communities as well as changes in plant strategies and functions, our data indicate, among others, shift from fast-growing, acquisitive to slow-growing, conservative plant strategies; increased productivity; higher competition between plant species; and an increasing contribution to the biogeomorphic stability. Analogous to trait-based approaches on the species level, we used community feature dissimilarities and measures on environmental heterogeneity to infer community assembly processes. Consistent with successional theory, our results indicate that stochastic processes dominate in the early successional stage, 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.

Dataset includes:
PlantEye data
Quantitative traits
Qualitative traits

奥地利Ödenwinkel研究平台2019-2022年START-Project的补充数据集，应用于《利用群落特征追踪植物演替过程及其组装机制》研究。

摘要

在原生演替过程中，植物群落的组装对于生态系统的功能与稳定性至关重要。通常，植物演替在分类学、系统发育和/或功能层面上进行描述，其中物种的身份和特性受到关注。本研究中，我们进一步考虑了表征整个植物群落的群落特征，以捕捉仅在群落层面存在的潜在属性。通过使用定制的多光谱3D植物扫描仪，该扫描仪可返回表征群落形态和生理参数的数据，这些参数作为群落内特性频率分布的代理，并有助于了解生产力和植物物种间的竞争普遍性，以及当地植被的生态系统功能。通过追踪群落分类学和系统发育组成及多样性，以及植物策略和功能的变化，我们的数据表明，包括从快速生长、进取型向缓慢生长、保守型植物策略的转变；生产力提升；植物物种间竞争加剧；以及对生物地貌稳定性贡献的增加等方面。与基于特性的物种水平方法类似，我们利用群落特征差异性和对环境异质性的度量来推断群落组装过程。与演替理论一致，我们的结果表明，在早期演替阶段，随机过程占主导地位，而在后期演替阶段，群落主要由确定性过程塑造，包括环境筛选和物种间的相互作用。我们得出结论，借助现场可用的3D扫描仪对植物群落特征的评估，为基于物种水平的特性方法提供了补充信息，并对生态过程具有影响。

数据集包括：
PlantEye数据
定量特性
定性特性