The untapped potential of categorical traits in seaweed functional diversity research
The untapped potential of categorical traits in seaweed functional diversity research
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海藻功能多样性研究中类别性状的未开发潜力
DOI：
10.1111/1365-2745.14178
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发表时间：
2023
影响因子：
5.5
通讯作者：
Bracken, Matthew E.
中科院分区：
文献类型：
--
作者：
Griffin, John N.;Mauffrey, Alizée R.;Bracken, Matthew E.
性状是观察进化和生态的有力透镜。它们使我们能够检查生物的生态策略，它们对环境的反应，并了解它们对生态系统功能和服务的影响（Garnier et al., 2016）。虽然没有万灵药，但性状仍然是陆生植物生态学的核心支柱，标准化方法和全球数据库可以产生无数见解（Carmona等人，2021；Díaz等人，2016）。然而，对海洋大型藻类或“海藻”的基于特征的生态学理解落后于对植物的理解。在本期中，Fong等人展示了分类性状的使用如何极大地加速了新兴海藻性状生态学领域的进展（Fong et al., 2023）。基于特征的海藻研究方法缓慢出现的一个关键原因是它们固有的进化和生态复杂性。海藻是一个多种类的群体，有三个主要分支（红藻门[红色]、绿藻门[绿色]和绿藻门[棕色]）的代表，跨越了两个不同的分支（根藻超群和古藻门），最后一个共同的祖先是在10亿多年前。除了这种深刻的进化多样性外，海藻还表现出巨大的生态多样性：它们栖息在不同的环境中，从温带潮间带岩石海岸到潮下深水热带珊瑚礁，从成排的单细胞到分化的森林形成巨藻的形态范围，并表现出不同的生命周期，通常具有异型阶段（Hurd et al., 2014）。传统上，海藻生态学家通过框架来处理这种复杂性，这些框架基于总体形态来构想不同的群体，例如“片状”或“厚而坚韧”（Littler & Littler, 1980; Steneck & Dethier, 1994；图1）。然而，这些功能分组重叠很大，与基于数量特征的功能分组不太对应（Ryznar et al., 2020），减少了机制见解，限制了与类似基于特征的方法进行比较，以理解其他生产者群体的形式和功能，并限制了使用特征（例如特定功能的特定集合）的灵活性。基于系统特征的方法终于获得了关注，例如，本杂志最近的一项研究（Mauffrey et al., 2020；图1）描述了物种间一系列形态和化学计量特征的连续变化。然而，这些新兴的方法依赖于收集的海藻标本的费力的直接特征测量，可能会限制快速升级到区域或全球数据库或分析。
Traits are a powerful lens through which to view evolution and ecology. They allow us to examine organisms' ecological strategies, their response to the environment, and understand their effects on ecosystem functions and services (Garnier et al., 2016). While no panacea, traits remain a central pillar of terrestrial plant ecology, where standardised methods and global databases yield myriad insights (Carmona et al., 2021; Díaz et al., 2016). Yet, a trait-based ecological understanding of marine macroalgae, or ‘seaweed’, has lagged behind that of plants. In this issue, Fong et al. show how the use of categorical traits can greatly accelerate progress in the emerging field of seaweed trait-based ecology (Fong et al., 2023). A key reason behind the slow emergence of a trait-based approach to seaweeds is their inherent evolutionary and ecological complexity. Seaweeds are a polyphyletic group, with representatives from three major divisions (the Rhodophyta [red], Chlorophyta [green], and Gyrista [brown]) of algae spanning two distinct clades (the stramenopilealveolate-Rhizaria supergroup and the Archaeplastida), which last shared a common ancestor over a billion years ago. Alongside this deep evolutionary diversity, seaweeds show immense ecological variation: they inhabit diverse environments, from temperate intertidal rocky shores to subtidal deepwater tropical reefs, range in morphology from rows of single cells to differentiated forest-forming giant kelps, and exhibit diverse life cycles, often with heteromorphic stages (Hurd et al., 2014). Traditionally, seaweed ecologists have dealt with such complexity through frameworks that conceive distinct groups based on gross morphology, such as ‘sheet-like’or ‘thick and leathery’(Littler & Littler, 1980; Steneck & Dethier, 1994; Figure 1). However, these functional groupings overlap considerably and do not correspond well to those based on quantitative traits (Ryznar et al., 2020), reducing mechanistic insights, limiting comparisons with similar trait-based approaches to understanding form and function in other producer groups and constraining flexibility in the use of traits for example specific sets for specific functions. Systematic trait-based approaches are at last gaining traction, with, for example, a recent effort in this journal (Mauffrey et al., 2020; Figure 1) characterising continuous variation in a suite of morphological and stoichiometric traits across species. Yet, these emerging approaches have relied on laborious direct trait measurements of collected seaweed specimens, potentially limiting rapid upscaling toward regional or global databases or analyses.