1 INTRODUCTION

The development of trait-based approaches in many ecosystems has driven rapid and substantial advances in understanding how communities assemble, respond to environmental change (e.g. Zakharova et al., 2019), and may best be managed in the Anthropocene. For example, terrestrial plant ecologists use trait-based approaches to improve predictions of community adaptation to anthropogenic influences like climate change and invasive species (Hui et al., 2016; Zakharova et al., 2019). Trait-based approaches also inform integrative and long-term conservation strategies for vulnerable plant species (Álvarez-Yépiz et al., 2019). For plankton, trait-based approaches successfully forecast community response to anthropogenic change (Roselli & Litchman, 2017) and how community structure and function vary along environmental gradients (Litchman & Klausmeier, 2008), which informs predictions of spatial shifts in community structure in response to climate change. The broad success of trait-based approaches in furthering our understanding of community ecology motivates research to continue its expansion to other taxa and systems.

Understanding the magnitude and pattern of interspecific variability forms a critical underpinning of trait-based approaches. Studies across systems demonstrate how traits reveal underlying ecological strategies (Albert et al., 2010) and help evaluate community functional diversity (for a review see de Bello et al., 2021). For example, plant ecologists found a trade-off between resource acquisition and herbivore defence traits in oak trees that reflect species-specific differences in the relative importance of these ecological strategies (Abdala-Roberts et al., 2018). They also linked interspecific variation to environmental drivers like temperature and precipitation, concluding that similar environmental drivers result in the emergence of similar ecological strategies. Because understanding interspecific variability has contributed broadly towards elucidating ecological strategies, it constitutes a fundamental step in developing trait-based approaches.

Evaluating intraspecific variability is another critical focus of trait-based approaches as it furthers our understanding of a species' potential to adapt to changing environmental drivers, including those impacted by humans (Albert et al., 2010; de Bello et al., 2021). There are a myriad examples of how intraspecific trait variability facilitates adaptation to different environmental conditions (Hooper et al., 2005; McGill et al., 2006), such as those associated with climate change (Bestion et al., 2015), altered land use (Schroeder et al., 2021) and environmental gradients (Lajoie & Vellend, 2015). Quantifying intraspecific variation also provides insights into environmentally driven alterations in community structure (Albert et al., 2010), niche differentiation (Jiang et al., 2016) and habitat range (He et al., 2018). Together, these studies demonstrate that evaluating intraspecific trait variability is a foundation of trait-based ecology.

The conceptual framework for understanding the functional ecology of marine macroalgae requires a paradigm shift as it is still mired in functional group models (FGMs) developed in the 1980s. These FGMs have been accepted and widely used for decades (e.g. Balata et al., 2011; Littler & Littler, 1984; Steneck & Dethier, 1994; Vélez-Rubio et al., 2021; for a critical review see Padilla & Allen, 2000). However, recent empirical challenges found some species within traditional functional groups do not share functional responses to environmental drivers. Rather, functional responses were shared more broadly between groups, thus violating underlying model assumptions (Fong & Fong, 2014). Furthermore, Ryznar et al. (2020) found intragroup variability often exceeded intergroup variability for tropical species of macroalgae, with many species assigned to different groups having similar responses, while others within the same group did not. Finally, Mauffrey et al. (2020) found trait-based approaches formed more accurate groups than the FGM, as FGs failed to capture important interspecific and intraspecific variation and their use resulted in the loss of information (Fong & Fong, 2014). One possible explanation for the inability of the FGM to group functionally similar species is that algal communities have been shifting globally since the 1980s (e.g. Fong & Paul, 2011), requiring novel approaches.

Our overarching objective was to quantify interspecific and intraspecific variability in functional traits of three ubiquitous species of tropical marine macroalgae. To capture spatial variability, we chose five fringing reefs of Mo'orea, French Polynesia that we reasoned were subject to varying environmental drivers. We explored traits relating to the ecological functions of resource acquisition, resistance to herbivory and resistance to physical disturbance and the trade-offs between them. We reasoned that the performance of macroalgae relies on their ability to acquire resources needed to grow, such as sunlight and nutrients (Fong, 2008; Fong & Paul, 2011). Furthermore, most macroalgal communities are consumed by fishes and invertebrates and exposed to physical stressors, such as wave action and current, both of which can result in loss, particularly of highly productive blades (Burnett & Koehl, 2022; Denny & Gaylord, 2002), which likely reduces survival.

中文翻译：

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使用基于性状的新型框架探索珊瑚礁藻类的种内和种间变异

 1 引言

在许多生态系统中基于特征的方法的发展推动了在理解群落如何聚集、响应环境变化方面取得了快速而实质性的进步（例如 Zakharova 等人，2019 年），并且最好在人类世进行管理。例如，陆生植物生态学家使用基于性状的方法来改进对社区对气候变化和入侵物种等人为影响的适应预测（Hui et al.， 2016;Zakharova et al.， 2019）。基于性状的方法还为脆弱植物物种的综合和长期保护策略提供信息（Álvarez-Yépiz et al.， 2019）。对于浮游生物，基于特征的方法成功地预测了社区对人为变化的反应（Roselli & Litchman，2017）以及社区结构和功能如何随环境梯度变化（Litchman & Klausmeier，2008），这为预测社区结构的空间变化提供了信息，以响应气候变化。基于特征的方法在进一步加深我们对群落生态学的理解方面取得的广泛成功促使研究继续扩展到其他分类群和系统。

了解种间变异性的大小和模式构成了基于性状的方法的关键基础。跨系统研究表明，性状如何揭示潜在的生态策略（Albert et al.， 2010）并帮助评估群落功能多样性（综述见 de Bello et al.， 2021）。例如，植物生态学家发现橡树的资源获取和食草动物防御特征之间存在权衡，这反映了这些生态策略相对重要性的物种特异性差异（Abdala-Roberts et al.， 2018）。他们还将种间变异与温度和降水等环境驱动因素联系起来，得出的结论是，相似的环境驱动因素导致了相似生态策略的出现。因为了解种间变异性对阐明生态策略有广泛的贡献，所以它构成了开发基于特征的方法的基本步骤。

评估种内变异性是基于性状的方法的另一个关键重点，因为它进一步加深了我们对物种适应不断变化的环境驱动因素的潜力的理解，包括那些受人类影响的驱动因素（Albert et al.， 2010;de Bello et al.， 2021）。有无数的例子表明种内性状变异如何促进对不同环境条件的适应（Hooper et al.， 2005;McGill等人，2006年），例如与气候变化相关的变化（Bestion等人，2015年），改变的土地利用（Schroeder等人，2021年）和环境梯度（Lajoie和Vellend，2015年）。量化种内变异还提供了对环境驱动的群落结构改变（Albert等人，2010）、生态位分化（江等人，2016）和栖息地范围（He等人，2018）的见解。总之，这些研究表明，评估种内性状变异性是基于性状的生态学的基础。

理解海洋大型藻类功能生态学的概念框架需要范式转变，因为它仍然陷入 1980 年代开发的功能群模型 （FGM） 的泥潭。几十年来，这些女性生殖器切割已被接受并广泛使用（例如 Balata 等人，2011 年;Littler & Littler， 1984;Steneck & Dethier， 1994;Vélez-Rubio等人，2021 年;有关批判性的评论，请参见Padilla&Allen，2000年）。然而，最近的实证挑战发现，传统功能组中的一些物种对环境驱动因素的功能响应并不相同。相反，功能反应在组之间更广泛地共享，从而违反了基本的模型假设（Fong & Fong，2014）。此外，Ryznar 等人（2020 年）发现，热带大型藻类物种的组内变异性经常超过组间变异性，分配到不同组的许多物种具有相似的反应，而同一组中的其他物种则没有。最后，Mauffrey 等人（2020 年）发现基于特征的方法形成的组比 FGM 更准确，因为 FG 未能捕捉重要的种间和种内变异，它们的使用导致信息丢失（Fong & Fong，2014 年）。 一种可能的解释是，自1980年代以来，藻类群落在全球范围内发生了变化（例如Fong & Paul，2011年），需要新的方法。

我们的总体目标是量化三种普遍存在的热带海洋大型藻类功能性状的种间和种内变异性。为了捕捉空间变异性，我们选择了法属波利尼西亚 Mo'orea 的五个边缘礁石，我们认为它们受到不同环境驱动因素的影响。我们探讨了与资源获取的生态功能、对食草的抵抗力和对物理干扰的抵抗力以及它们之间的权衡相关的特征。我们推断，大型藻类的性能取决于它们获取生长所需资源的能力，例如阳光和营养物质（Fong，2008 年;Fong & Paul，2011 年）。此外，大多数大型藻类群落被鱼类和无脊椎动物食用，并暴露于物理压力源，如波浪作用和水流，这两者都可能导致损失，特别是高产叶片的损失（Burnett & Koehl，2022 年;Denny & Gaylord，2002年），这可能会降低存活率。