Data from: Trait-based formal definition of plant functional types and functional communities in the multi-species and multi-traits context

The concepts of traits, plant functional types (PFT), and functional communities are effective tools for the study of complex phenomena such as plant community assembly. Here, we (1) suggest a procedure formalising the classification of response traits to construct a PFT system; (2) integrate the PFT, and species compositional data to formally define functional communities; and, (3) identify environmental drivers that underpin the functional-community patterns.A species–trait data set featuring species pooled from two study sites (Eneabba and Cooljarloo, Western Australia), both supporting kwongan vegetation (sclerophyllous scrub and woodland communities), was subjected to classification to define PFTs. Species of both study sites were replaced with the newly derived PFTs and projected cover abundance-weighted means calculated for every plot. Functional communities were defined by classifications of the abundance-weighted PFT data in the respective sites. Distance-based redundancy analysis (using the abundance-weighted community and environmental data) was used to infer drivers of the functional community patterns for each site.A classification based on trait data assisted in reducing trait-space complexity in the studied vegetation and revealed 26 PFTs shared across the study sites. In total, seven functional communities were identified. We demonstrate a putative functional-community pattern-driving effect of soil-texture (clay—sand) gradients at Eneabba (42% of the total inertia explained) and that of water repellence at Cooljarloo (36%). Synthesis. This paper presents a procedure formalising the classification of multiple response traits leading to the delineation of PFTs and functional communities. This step captures plant responses to stresses and disturbance characteristic of kwongan vegetation, including low nutrient status, water stress, and fire (a landscape-level disturbance factor). Our study is the first to introduce a formal procedure assisting their formal recognition. Our results support the role of short-term abiotic drivers structuring the formation of fine-scale functional community patterns in a complex, species-rich vegetation of Western Australia.

Methods
The low availability of nutrients and water, and the regular occurrence of fire are the most pronounced natural disturbance considered as the principal drivers of vegetation patterning and dynamics in kwongan vegetation of Western Australia. To develop a plant functional type system explicitly reflecting these environmental challenges, we created a trait database describing various eco-morphological and functional aspects of the life history of the species sampled in both study areas. To this end, we compiled a soft-trait database featuring 1286 species indexed according to 21 binary traits scored from published taxonomic descriptions, our in situ studies, and inspection of lodged specimens (Western Australia Herbarium 2019–). Expert advice (see Acknowledgements) was sought with some specialised traits and syndromes. The functional traits used in this analysis and their states have been linked to the functional aspects of water relations, carbon balance, nutrition and fire, affecting growth, reproduction and/or survival are detailed to provide ecological relevance (see Table 1).

性状（traits）、植物功能型（Plant Functional Types, PFT）以及功能群落（functional communities）的相关概念，是研究植物群落组装等复杂现象的有效工具。本研究（1）提出一套规范化程序，对响应性状进行分类以构建植物功能型体系；（2）整合植物功能型与物种组成数据（species compositional data），对功能群落进行正式定义；（3）明确支撑功能群落格局的环境驱动因子。
本研究整合了来自澳大利亚西部两个研究样地（伊内巴Eneabba与库贾卢Cooljarloo）的物种-性状数据集，两个样地均覆盖昆岗植被（kwongan vegetation），涵盖硬叶灌丛与林地群落（sclerophyllous scrub and woodland communities），并通过分类流程定义植物功能型。将两个研究样地的物种替换为新推导得到的植物功能型，并计算每个样方的投影盖度加权平均数值。功能群落通过对各研究样地内的加权盖度植物功能型数据进行分类得以定义。本研究采用基于距离的冗余分析（distance-based redundancy analysis），使用加权盖度群落与环境数据，推断各研究样地功能群落格局的驱动因子。
基于性状数据的分类流程有效降低了研究植被的性状空间复杂度，并揭示了两个研究样地共有的26个植物功能型。最终共识别出7个功能群落。本研究证实，伊内巴样地的土壤质地（黏土-砂土）梯度（可解释总惯性的42%）以及库贾卢样地的土壤斥水性（可解释总惯性的36%）对功能群落格局具有潜在驱动作用。
综合总结：本研究提出一套规范化程序，通过对多种响应性状进行分类，最终划定植物功能型与功能群落。该程序可捕捉植物对昆岗植被典型胁迫与干扰的响应，包括低养分状态、水分胁迫以及火（一种景观尺度的干扰因子）。本研究首次提出一套规范化流程，助力植物功能型与功能群落的正式识别。研究结果证实，短期非生物驱动因子在澳大利亚西部复杂且物种丰富的植被中，主导了细尺度功能群落格局的形成。

研究方法
养分与水分有效性低下，以及频繁发生的火干扰，是澳大利亚西部昆岗植被中最为显著的自然干扰因素，被视为植被格局与动态的核心驱动因子。为构建能够明确反映上述环境挑战的植物功能型体系，本研究构建了一套性状数据库，用以描述两个研究区域内采样物种生活史的多种生态形态与功能特征。
为此，本研究整理了一套软性状数据库（soft-trait database），涵盖1286个物种，依据21个二元性状（binary traits）进行索引，这些性状的评分来自已发表的分类学描述、本研究的原位观测（in situ studies）以及馆藏标本（lodged specimens）的检视（西澳大利亚标本馆，2019年至今）。针对部分特殊性状与性状综合征（trait syndromes），本研究征询了专家意见（详见致谢部分）。本研究详细列出了本次分析所用的功能性状及其状态，这些性状与影响植物生长、繁殖及/或存活的水分关系、碳平衡、营养代谢与火相关的功能特征紧密关联，以确保研究具备生态学相关性（详见表1）。