1 INTRODUCTION

A growing effort has been devoted to understanding how ecosystems respond to extreme climatic events (hereafter ECE) such as heat waves and/or droughts (De Boeck et al., 2018). The frequency, magnitude and impact of ECE will increase in the near future (EEA, 2017), so determining the capacity of ecosystems to respond to these phenomena is a pressing task (De Boeck et al., 2018; Smith, 2011). Extreme climatic events can strongly impact the stability of ecosystem functions or nature contributions to people (Bastos et al., 2020; Díaz et al., 2018; Domeisen et al., 2023; Xu et al., 2019, 2020). Ideally, to withstand ECE, ecosystems should be able to (i) maintain their properties under strong environmental perturbations (i.e. show high resistance) and to (ii) quickly recover their functioning after environmental perturbations (i.e. show high recovery; de la Riva et al., 2017; Isbell et al., 2015; Neilson et al., 2020). Ecosystems with low resistance and recovery are expected to be more vulnerable to the effect of ECE (Oliver et al., 2015). Which biological features make ecosystems resist to and recover from ECE is, however, still a subject of research (Mahecha et al., 2022).

Under average climate, biodiversity should stabilise ecosystem functions over time, although the paradigm ‘biodiversity begets stability’ has long been debated (Díaz & Cabido, 2001; Lepš et al., 1982; Li et al., 2022; McCann, 2000; Tilman et al., 2006). In principle, biodiversity can support stability via several mechanisms related to species richness, abundance and temporal fluctuation of population sizes. More diverse communities can be more stable because they can harbour species with different responses to environmental fluctuations, which insures ecosystems against loss of functions (i.e. ‘insurance effect’; Díaz & Cabido, 2001; Ives et al., 2000; McCann, 2000). However, in line with the ‘mass ratio hypothesis’ (Grime, 1998), species' contribution to stability is proportional to their relative abundance so that few but abundant species can determine stability (i.e. ‘dominant species effect’; Lisner et al., 2022). Apart from community composition, asynchronous fluctuations of individual species' population sizes can also stabilise ecosystem functions (Allan et al., 2011; Lepš et al., 2019). Empirical and experimental studies found that taxonomic diversity has a positive (Isbell et al., 2015; Tilman & Downing, 1994), negative (Fischer et al., 2016; Pfisterer & Schmid, 2002) or no effect (Caldeira et al., 2005; De Boeck et al., 2018; Dormann et al., 2017; Kreyling et al., 2017) on resistance, recovery or both under ECE. Somewhat surprisingly, the role of community functional composition and diversity has been poorly investigated in the context of ECE (De Boeck et al., 2018; Stampfli et al., 2018; but see de la Riva et al., 2017; Fischer et al., 2016; Gazol & Camarero, 2016). Yet, accounting for it may explain how biodiversity begets stability under ECE, as functional traits, namely any biological feature measurable at the individual level (Violle et al., 2007), can reveal a mechanistic link between ecosystem functioning and environmental variability (Cadotte, 2017; Díaz & Cabido, 2001; Polley et al., 2013; Suding et al., 2008).

Recently, de Bello et al. (2021) reviewed different biodiversity-related mechanisms possibly involved in ecosystem resistance and recovery from ECE, and concluded that they generally operate via functional traits (Naeem et al., 2012). On the one hand, dominant species can exert the largest effect on the resistance and recovery of ecosystem functions through their traits (de Bello et al., 2021). For this reason, the dominant trait composition of plant communities, as measured by community-weighted means, has been used to locate communities along leaf-economic continuum (‘slow’ vs. ‘fast’ communities; Craven et al., 2018). This has shown that communities dominated by traits associated with conservative strategies (‘slow communities’) are better at withstanding perturbations (de Bello et al., 2021; Isbell et al., 2015; Lepš et al., 1982) than fast communities, which, instead, seem to more quickly restore their functioning after perturbations (Craven et al., 2018; Ghazoul et al., 2015; Karlowsky et al., 2018). On the other hand, the ‘insurance effect’ hypothesis predicts that high diversity of response traits, which relate to plant response to environmental variability (Lavorel & Garnier, 2002), promotes stability of ecosystem functioning under strong environmental perturbations (Craven et al., 2018; Griffin-Nolan et al., 2019). Under this scenario, the loss of species lacking the appropriate functional traits to resist a specific environmental perturbation (e.g. drought) should be compensated by less sensitive species. However, the impact of species loss on the stability of ecosystem functioning would only be minimised if species lost during an environmental perturbation and those that persist share the same effect traits, that is, traits producing an impact on ecosystem processes (de Bello et al., 2021; Díaz & Cabido, 2001). Nevertheless, both measures of trait composition and diversity can be important predictors of ecosystem resistance and recovery under ECE (Griffin-Nolan et al., 2019).

Here, we analysed how multiple biodiversity components (functional composition, functional diversity and taxonomic diversity) support the resistance and recovery of plant biomass of managed grasslands undergoing extreme drought. Specifically, by measuring year-to-year changes in plant above-ground biomass, we derived yearly estimates of resistance and recovery, which we related to the functional and taxonomic characteristics of plant communities. We tested this in a gradient of land-use intensity representing realistic management conditions of central European grasslands. Our aims were to: (i) assess how functional composition, functional diversity and taxonomic diversity mediate plant biomass fluctuation along a gradient of land-use intensity; (ii) test whether the association between biodiversity, biomass and land use changes under exceptional climatic conditions (i.e. moderate-to-extreme drought, hereafter also collectively referred to as severe drought); and (iii) investigate whether and how biodiversity-related mechanisms mediated by functional traits, such as dominant species and insurance effects, support ecosystem resistance and recovery during and after severe drought. To this end, we analysed an 11-year grassland time-series of field-collected plant biomass, biodiversity and land-use data from Germany.

中文翻译：

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生物多样性促进抵抗力，但优势物种塑造了极端干旱下草原的恢复

1 简介

人们越来越努力地致力于了解生态系统如何应对热浪和/或干旱等极端气候事件（以下简称 ECE）（De Boeck 等，  2018）。 ECE的频率、规模和影响在不久的将来将会增加（EEA，  2017），因此确定生态系统应对这些现象的能力是一项紧迫的任务（De Boeck等，  2018；Smith，  2011）。极端气候事件会强烈影响生态系统功能的稳定性或自然对人类的贡献（Bastos等，  2020 ； Díaz等，  2018；Domeisen等，  2023；Xu等，  2019，2020 ）。理想情况下，为了承受 ECE，生态系统应该能够 (i) 在强烈的环境扰动下保持其特性（即表现出高抵抗力），并 (ii) 在环境扰动后快速恢复其功能（即表现出高恢复性；de la Riva 等人） .，  2017；伊斯贝尔等人，  2015；尼尔森等人，  2020）。抵抗力和恢复能力较低的生态系统预计更容易受到 ECE 的影响（Oliver 等，  2015）。然而，哪些生物学特征使生态系统能够抵抗 ECE 并从中恢复，仍然是一个研究课题（Mahecha 等人，  2022）。

在平均气候下，生物多样性应该随着时间的推移稳定生态系统功能，尽管“生物多样性带来稳定性”这一范式长期以来一直存在争议（Díaz & Cabido,  2001 ; Lepš et al.,  1982 ; Li et al.,  2022 ; McCann,  2000 ; Tilman等人，  2006）。原则上，生物多样性可以通过与物种丰富度、丰度和种群规模的时间波动相关的多种机制来支持稳定性。更加多样化的群落可以更加稳定，因为它们可以容纳对环境波动有不同反应的物种，从而确保生态系统不会丧失功能（即“保险效应”；Díaz & Cabido,  2001；Ives et al.,  2000；McCann,  2000） 。然而，根据“质量比假说”（Grime，  1998），物种对稳定性的贡献与其相对丰度成正比，因此少数但丰富的物种可以决定稳定性（即“优势物种效应”；Lisner 等人，  2022）。除了群落组成外，单个物种种群规模的异步波动也可以稳定生态系统功能（Allan等，  2011；Lepš等，  2019）。实证和实验研究发现，分类多样性具有积极影响（Isbell et al.,  2015；Tilman & Downing,  1994）、消极影响（Fischer et al.,  2016；Pfisterer & Schmid,  2002）或无影响（Caldeira et al.,  2005；De Boeck 等人，  2018；Dormann 等人，  2017；Kreyling 等人，  2017）关于 ECE 下的抵抗、恢复或两者。有点令人惊讶的是，在 ECE 背景下，群落功能组成和多样性的作用很少得到研究（De Boeck 等人，  2018 年；Stampfli 等人，  2018 年；但参见 de la Riva 等人，  2017 年；Fischer 等人） .，  2016；加佐尔和卡马雷罗，  2016）。然而，对其进行解释可以解释生物多样性如何在欧洲经委会下产生稳定性，因为功能特征，即在个体水平上可测量的任何生物特征（Violle等人，  2007年）可以揭示生态系统功能与环境变异性之间的机制联系（Cadotte，  2017 ；Díaz和Cabido，  2001；  Suding 等，  2008）。

最近，德贝洛等人。 ( 2021 ) 回顾了可能涉及生态系统抵抗和 ECE 恢复的不同生物多样性相关机制，并得出结论，它们通常通过功能性状发挥作用 (Naeem 等，  2012 )。一方面，优势种可以通过其性状对生态系统功能的抵抗和恢复发挥最大的作用(de Bello等，  2021 )。因此，通过群落加权平均值测量的植物群落的显性性状组成已被用来沿着叶经济连续体定位群落（“慢”与“快”群落；Craven 等人，  2018）。这表明，以保守策略相关特征为主的群落（“慢群落”） 比快群落更能承受扰动（de Bello et al., 2021；Isbell et al.,  2015；Lepš et al.,  1982 ）。相反，它们似乎在扰动后更快地恢复其功能（Craven 等人，  2018；Ghazoul 等人，  2015；Karlowsky 等人，  2018）。另一方面，“保险效应”假说预测，与植物对环境变化的反应相关的反应性状的高度多样性（Lavorel＆Garnier，  2002）可促进强烈环境扰动下生态系统功能的稳定性（Craven等人，  2018；格里芬-诺兰等人，  2019）。在这种情况下，缺乏适当功能性状来抵抗特定环境扰动（例如干旱）的物种的损失应该由不太敏感的物种来补偿。然而，只有在环境扰动期间消失的物种和那些持续存在的物种具有相同的效应特征（即对生态系统过程产生影响的特征）的情况下，物种丧失对生态系统功能稳定性的影响才会最小化（de Bello等，2015）。 ，  2021；迪亚兹和卡比多，  2001）。尽管如此，性状组成和多样性的测量都可以成为 ECE 下生态系统抵抗力和恢复的重要预测因素（Griffin-Nolan 等，  2019）。

在这里，我们分析了多个生物多样性组成部分（功能组成、功能多样性和分类多样性）如何支持遭受极端干旱的管理草原的植物生物量的抵抗和恢复。具体来说，通过测量植物地上生物量的逐年变化，我们得出了抗性和恢复的年度估计值，并将其与植物群落的功能和分类特征相关联。我们在代表中欧草原实际管理条件的土地利用强度梯度中对此进行了测试。我们的目标是：（i）评估功能组成、功能多样性和分类多样性如何调节植物生物量沿土地利用强度梯度的波动； (ii) 测试生物多样性、生物量和土地利用之间的关联在特殊气候条件下（即中度至极度干旱，以下也统称为严重干旱）是否发生变化； (iii) 调查由优势物种和保险效应等功能特征介导的生物多样性相关机制是否以及如何支持严重干旱期间和之后生态系统的抵抗力和恢复。为此，我们分析了从德国实地收集的植物生物量、生物多样性和土地利用数据的 11 年草地时间序列。