生物互作与全球变化下的生态系统动态: 从理论到应用

doi:10.17521/cjpe.2020.0055

摘要/Abstract

摘要：

随着气候变化和人类活动的加剧, 生态系统组成与结构的时空动态正变得日益剧烈和复杂, 许多生态系统呈退化趋势。全球变化背景下的生态系统动态及其形成机制既是生态学的基础理论问题, 也是生态系统修复和保护中亟需认识的关键应用问题。该文在概述连续型、阈值型和随机型等生态系统动态模式的基础上, 分析生物互作影响生态系统动态的机理; 结合次生演替、稳态转换、物种分布区移位等研究热点, 总结有关生物互作对生态系统动态影响的主要研究进展; 并探讨相关生物互作理论在生态系统保护和修复中的应用。日益丰富的研究表明, 竞争、促进(包括共生)、营养级间的互作等一系列生物互作可直接或间接驱动或改变生态系统在不同时空尺度上变化的模式、方向及速率; 在生态系统管理实践中, 应用生物互作的相关理论有望大幅提升生态系统保护和修复的成效。进一步丰富和完善该领域的基础理论及应用实践, 需要今后在生物互作对生态系统动态影响的时空变异机制、多重干扰下生物互作对生态系统动态的影响、生物互作在生态系统保护和修复中的应用等方面开展深入研究。

关键词: 生物互作, 次生演替, 稳态转换, 物种分布区移位, 生态修复, 生态学应用

Abstract:

Under intensifying human activities and climate change, spatiotemporal changes in ecosystem composition and structure are becoming increasingly drastic and intricate, and there are trends of degradation in many ecosystems. An improved understanding of ecosystem dynamics and their underlying mechanisms in the context of global change can not only help resolve fundamental theoretical questions in ecology, but can also inform applied issues in ecosystem restoration and conservation. Here, we review different models of ecosystem dynamics (gradual continuum, threshold/regime shift, and stochastic) and conceptualize the mechanisms by which biotic interactions can potentially modulate ecosystem dynamics. We then synthesize the state of understanding how biotic interactions regulate secondary succession, regime shift, and species range shift—ecosystem dynamics subject to intense recent investigation. We further discuss results from studies that applied theories on biotic interactions in ecosystem restoration and conservation. We show that there is a growing body of research revealing 1) that multiple types of biotic interactions, such as competition, facilitation (including mutualism), and trophic interactions, can drive or substantially alter the patterns, directions, and rates of ecosystem change at various spatiotemporal scales, and 2) that managing biotic interactions is likely to greatly enhance the performance of ecosystem restoration and conservation. To move forward, we highlight that further research is needed to better understand how the impacts of biotic interactions on ecosystem dynamics vary spatially and temporally, how biotic interactions modulate ecosystem dynamics under multiple anthropogenic disturbances, and how best to manage biotic interactions to optimize ecosystem conservation and restoration.

Key words: biotic interactions, secondary succession, regime shift, species range shift, restoration ecology, ecological application

贺强. 生物互作与全球变化下的生态系统动态: 从理论到应用. 植物生态学报, 2021, 45(10): 1075-1093. DOI: 10.17521/cjpe.2020.0055

HE Qiang. Biotic interactions and ecosystem dynamics under global change: from theory to application. Chinese Journal of Plant Ecology, 2021, 45(10): 1075-1093. DOI: 10.17521/cjpe.2020.0055

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链接本文: https://www.plant-ecology.com/CN/10.17521/cjpe.2020.0055

https://www.plant-ecology.com/CN/Y2021/V45/I10/1075

图/表 5

图1 自然界中的典型生物互作与生态系统动态。A, 森林生态系统中树皮甲虫导致的树木大面积死亡(开源图片, CC BY-NC 2.0, Michael McCullough拍摄)。B, 高寒生态系统中的保育植物与促进作用(开源图片, CC BY-SA 3.0, Hermanhi拍摄)。C, 热带生态系统中大型动物植食作用驱动的稀树草原稳态(开源图片, CC BY-NC 2.0, Arthur Chapman拍摄)。D, 滨海盐沼湿地中蟹类植食作用驱动的大幅度植被退化(贺强拍摄)。E, 海草床湿地与入侵植物互花米草(Spartina alterniflora)的竞争作用(贺强拍摄)。F, 滩涂湿地中红树林幼苗更新与外来植物互花米草的竞争作用(贺强拍摄)。G, 湖泊生态系统捕食性鱼类影响水体清澈度(开源图片, CC BY-SA 2.0, Paul Korecky拍摄)。H, 退化海藻林生态系统中海胆植食作用维持的瘠地稳态(开源图片, CC BY 2.0, Claire Fackler, CINMS, NOAA拍摄)。I, 珊瑚礁生态系统中大型藻类挤占珊瑚生存空间(开源图片, CC BY-NC-ND 2.0, FWC Fish and Wildlife Research Institute拍摄)。

Fig. 1 Representative biotic interactions and ecosystem dynamics in nature. A, Bark beetle-driven massive tree mortality in a forest (photographed by Michael McCullough, CC BY-NC 2.0). B, Nurse plants with facilitative effects in an alpine ecosystem (photographed by Hermanhi, CC BY-SA 3.0). C, Savanna as a stable state maintained by wildlife herbivory in tropical ecosystems (photographed by Arthur Chapman, CC BY-NC 2.0). D, Large-scale vegetation die-off driven by crab herbivory in a coastal salt marsh (photographed by HE Qiang). E, Exotic cordgrass Spartina alterniflora compete with seagrasses in the Yellow River Delta (photographed by HE Qiang). F, Mangrove regeneration affected by exotic cordgrass competition (photographed by HE Qiang). G, Predatory fish affect water clarity in a lake ecosystem (photographed by Paul Korecky, CC BY-SA 2.0). H, Barren state maintained by sea urchin grazing in a kelp forest (photographed by Claire Fackler, CINMS, NOAA, CC BY 2.0). I, Macroalgae compete with corals for space in a degraded coral reef (photographed by FWC Fish and Wildlife Research Institute, CC BY-NC-ND 2.0).

表1 生态系统动态的主要类型与特征

Table 1 Main models and characteristics of ecosystem dynamics

类型 Model	主要特征 Characteristic	实例 Empirical example	参考文献 Reference
连续型 Gradual continuum models	生态系统以线性渐变的方式响应干扰, 并随着干扰的消退向干扰前的单一顶极状态平稳演替 Ecosystems exhibit linear continuous changes and gradually progress toward the pre-disturbance climax	中国内蒙古、青海等地区的长期草地监测样地中, 虽然植物群落生产力在20世纪80年代至21世纪10年代之间未大幅上升或下降, 但是, 物种组成随气候变化而逐渐发生变化; 内蒙古草地长期监测样地中的物种丰富度还呈线性减小趋势。 At long-term monitoring sites of grasslands in Nei Mongol and Qinghai, China, although the annual biomass production of plant communities did not greatly increase or decrease from the 1980s to the 2010s, species composition gradually changed with climate change, and there was a gradual decreasing trend in species richness at long-term monitoring sites of grasslands in Nei Mongol.	Bai et al., 2004; Zhang et al., 2018; Wang et al., 2020
阈值型 Threshold models	生态系统以非线性的方式响应干扰, 当环境条件的变化导致临界阈值被超出时即发生生态系统的突变 Ecosystems exhibit nonlinear responses to disturbance, and abrupt changes occur when a threshold is approached	中国太湖水体叶绿素浓度以非线性方式响应氮、磷加载量的变化。 In Taihu Lake, China, chlorophyll concentration in the water column responded to loadings of nitrogen and phosphorus nonlinearly.	Xu et al., 2015b; Janssen et al., 2017
稳态转换¹⁾ Regime shift models¹⁾	生态系统以带有迟滞效应的非线性方式响应干扰(迟滞效应指生态系统的退化轨迹不同于恢复轨迹) Ecosystems exhibit nonlinear responses to disturbance and the trajectory of degradation differs from that of recovery	在美国亚利桑那州半干旱草地生态系统中, 过度放牧导致乔木植物群落的扩张, 但降低放牧强度不能使系统恢复至原有的草地状态。 In Arizona, USA, livestock grazing has driven the encroachment of shrubs in semiarid grasslands, and subsequent protection from grazing failed to deter shrub encroachment.	Browning & Archer, 2011
随机型 Stochastic models	物种/生态系统主要受随机过程影响, 系统状态持续波动, 不向某一特定的长期平衡态演变 Species/ecosystems are mainly affected by stochastic processes, constantly fluctuate, and do not progress toward any equilibrium	英国苏格兰地区欧鸬鹚种群大小在1963-2005年间持续强烈波动, 没有向平衡态发展的趋势。 In Scotland, UK, the population size of the European shag Phalacrocorax aristotelis continued to strongly fluctuate between 1963 and 2005, showing no tendency toward an equilibrium.	Frederiksen et al., 2008

表1 生态系统动态的主要类型与特征

Table 1 Main models and characteristics of ecosystem dynamics

类型 Model	主要特征 Characteristic	实例 Empirical example	参考文献 Reference
连续型 Gradual continuum models	生态系统以线性渐变的方式响应干扰, 并随着干扰的消退向干扰前的单一顶极状态平稳演替 Ecosystems exhibit linear continuous changes and gradually progress toward the pre-disturbance climax	中国内蒙古、青海等地区的长期草地监测样地中, 虽然植物群落生产力在20世纪80年代至21世纪10年代之间未大幅上升或下降, 但是, 物种组成随气候变化而逐渐发生变化; 内蒙古草地长期监测样地中的物种丰富度还呈线性减小趋势。 At long-term monitoring sites of grasslands in Nei Mongol and Qinghai, China, although the annual biomass production of plant communities did not greatly increase or decrease from the 1980s to the 2010s, species composition gradually changed with climate change, and there was a gradual decreasing trend in species richness at long-term monitoring sites of grasslands in Nei Mongol.	Bai et al., 2004; Zhang et al., 2018; Wang et al., 2020
阈值型 Threshold models	生态系统以非线性的方式响应干扰, 当环境条件的变化导致临界阈值被超出时即发生生态系统的突变 Ecosystems exhibit nonlinear responses to disturbance, and abrupt changes occur when a threshold is approached	中国太湖水体叶绿素浓度以非线性方式响应氮、磷加载量的变化。 In Taihu Lake, China, chlorophyll concentration in the water column responded to loadings of nitrogen and phosphorus nonlinearly.	Xu et al., 2015b; Janssen et al., 2017
稳态转换¹⁾ Regime shift models¹⁾	生态系统以带有迟滞效应的非线性方式响应干扰(迟滞效应指生态系统的退化轨迹不同于恢复轨迹) Ecosystems exhibit nonlinear responses to disturbance and the trajectory of degradation differs from that of recovery	在美国亚利桑那州半干旱草地生态系统中, 过度放牧导致乔木植物群落的扩张, 但降低放牧强度不能使系统恢复至原有的草地状态。 In Arizona, USA, livestock grazing has driven the encroachment of shrubs in semiarid grasslands, and subsequent protection from grazing failed to deter shrub encroachment.	Browning & Archer, 2011
随机型 Stochastic models	物种/生态系统主要受随机过程影响, 系统状态持续波动, 不向某一特定的长期平衡态演变 Species/ecosystems are mainly affected by stochastic processes, constantly fluctuate, and do not progress toward any equilibrium	英国苏格兰地区欧鸬鹚种群大小在1963-2005年间持续强烈波动, 没有向平衡态发展的趋势。 In Scotland, UK, the population size of the European shag Phalacrocorax aristotelis continued to strongly fluctuate between 1963 and 2005, showing no tendency toward an equilibrium.	Frederiksen et al., 2008

图2 典型生物互作影响生态系统动态的概念模型。A, 生态系统对干扰的抵抗力、恢复力及韧力(图中含恢复至系统原状态和向其他稳态转换两种情况, 系统恢复也可介于二者之间)。B, 竞争作用。C, 促进作用。D, 植食作用。在B和C中, A、B、C分别表示目标物种、邻居种、干扰后新迁入物种。为简洁起见, 以单一脉冲性干扰和两种典型生物互作情景为例进行示意。在B和C中, 生物互作情景1表示系统中原有邻居种的竞争或促进作用, 生物互作情景2表示干扰后新迁入物种的竞争或促进作用; C中促进作用为互利作用(对于偏害和偏利作用, 请参见正文)。在D中, 生物互作情景1表示植食作用降低植被的恢复速率, 增加植被恢复至平衡态所需时间, 生物互作情景2表示植食作用完全抑制植被的恢复潜力, 使干扰后的生态系统向另一平衡态演变。

Fig. 2 Conceptual models showing how species interactions may affect ecosystem dynamics. A, Ecosystem resistance to, recovery from, and resilience to disturbance (shown are two scenarios where an ecosystem fully returns to pre-disturbance state and shift to an alternative state, respectively, and ecosystem recoveries could be in between these two scenarios). B, Competition. C, Facilitation. D, Herbivory. In B and C, A, B, and C indicate target species, neighboring species, and post-disturbance immigrant species. For the sake of conciseness, a single pulse disturbance and two typical species interaction scenarios are shown as examples. In B and C, species interaction scenario 1 indicates competitive or facilitative effects of neighboring species that coexist with the target species in an ecosystem, while scenario 2 indicates competitive or facilitative effects of post-disturbance immigrant species; in C, facilitation is mutualistic (see the main text for descriptions about antagonistic and commensal facilitation). In D, species interaction scenario 1 indicates that herbivory delays vegetation recovery and increases the time required for vegetation to return to pre-disturbance equilibrium, while scenario 2 indicates that herbivory fully eliminates the potential for vegetation to recover and that the ecosystem shifts to a different equilibrium.

图3 生态系统动态3个主要研究热点的变化趋势分析。A, 次生演替(Web of Science中以“succession”和“disturbance”为主题词搜索获得的“Research Area: Environmental Sciences Ecology”中的文献数据)。B, 稳态转换(以“regime shift”“stable state”“phase shift”或“tipping point”为主题词进行文献搜索)。C, 物种分布区移位(以“range shift”“range expansion”或“range contraction”为主题词搜索)。内部小图显示包含(黑色)和不包含(白色)生物互作的文献总数的比例, 以及竞争(绿色)、促进(橙色)、营养级间的互作(蓝色)、其他生物互作(灰色)研究的文献总数的比例。包含生物互作的文献以species interaction*、herbivory*、predation*、facilitat*、compet*、mutualis*、food web、trophic interaction*或top-down control*为主题词进行搜索; 包含竞争、促进、营养级间的互作的文献分别以compet*、facilitat*或mutualis*及herbivory*、predation*、food web、trophic interaction*或top-down control*为主题词进行文献搜索。

Fig. 3 Trends in the number of published papers on three major research themes of ecosystem dynamics. A, Secondary succession (a list of publications was compiled by searching Web of Science using the query TI = “succession” and “disturbance”; all papers in the Research Area: Environmental Sciences Ecology were considered). B, Regime shift (the search query was TI = “regime shift” OR “stable state” OR “phase shift” OR “tipping point”). C, Species range shift (the search query was TI = “range shift” OR “range expansion” OR “range contraction”). Inserts in each panel show proportions of publications relevant (filled) and those irrelevant (blank) to species interactions and proportions of studies on competition (green), facilitation (orange), trophic interactions (blue), and other biotic interactions (grey). Publications relevant to species interactions were compiled using, in combination with the above search queries, the query TI = species interaction* OR herbivory* OR predation* OR facilitat* OR compet* OR mutualis* OR food web OR trophic interaction* OR top-down control*. Publications on competition, facilitation, and trophic interactions were compiled by using the queries TI = compet*, TI = facilitat* OR mutualis*, and TI = herbivory* OR predation* OR food web OR trophic interaction* OR top-down control*, respectively.

图4 生物互作在生态系统管理中的应用: 以海岸带生态系统为例。A, 辽河口盐沼湿地通过人为控制植食性蟹类进行植被修复(He et al., 2017; 图片由贺强拍摄)。B, 美国佐治亚利用Geukensia demissa与互花米草的共生关系促进干旱后互花米草植被的修复(Derksen-Hooijberg et al., 2018; 图片由贺强拍摄)。C, 美国西海岸顶级捕食动物海獭的保护可促进海藻林的恢复(Lotze et al., 2011; 开源图片, CC BY-NC 2.0, Ingrid Taylar拍摄)。D, 美国佛罗里达等世界许多地区依据植食性鱼类对藻类-珊瑚竞争的调控作用制定珊瑚礁生态系统的保护和修复政策(Mumby et al., 2014; 开源图片, CC BY 2.0, Paul Asman和Jill Lenoble 拍摄)。

Fig. 4 Applications of species interactions in ecosystem management: coastal ecosystems as examples. A, Vegetation restoration through controlling crab herbivory in salt marshes in Liaohe Estuary (He et al., 2017; photoed by HE Qiang). B, Restoration of drought-impaired cordgrass marshes using mussels in Georgia, USA (Derksen-Hooijberg et al., 2018; photoed by HE Qiang). C, Conservation of sea otters (Enhydra lutris)—a top predator—can promote restoration of kelp forests on US West Coast (Lotze et al., 2011; photoed by Ingrid Taylar, CC BY-NC 2.0). D, Coral reef conservation and restoration polices in Florida, the USA and many other places around the world were formulated based on the roles herbivorous fishes play in mediating algae-coral competition (Mumby et al., 2014; photoed by Paul Asman & Jill Lenoble, CC BY 2.0).

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