Chin J Plant Ecol ›› 2021, Vol. 45 ›› Issue (10): 1075-1093.DOI: 10.17521/cjpe.2020.0055
Special Issue: 全球变化与生态系统; 生态系统结构与功能
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Received:
2020-03-03
Accepted:
2020-07-02
Online:
2021-10-20
Published:
2020-07-03
Contact:
HE Qiang
Supported by:
HE Qiang. Biotic interactions and ecosystem dynamics under global change: from theory to application[J]. Chin J Plant Ecol, 2021, 45(10): 1075-1093.
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URL: https://www.plant-ecology.com/EN/10.17521/cjpe.2020.0055
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).
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., |
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., |
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, |
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., |
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., |
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., |
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, |
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., |
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.
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.
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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