Linking trait network parameters with plant growth across light gradients and seasons

Reduced light availability induced by eutrophication has dramatically affected the growth of submerged macrophytes and caused their rapid decline globally in lakes. Functional traits have usually been used to predict ecological processes and explain plant adaptation. Trait networks, which are constr...

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Published inFunctional ecology Vol. 37; no. 6; pp. 1732 - 1746
Main Authors Rao, Qingyang, Chen, Jianfeng, Chou, Qingchuan, Ren, Wenjing, Cao, Te, Zhang, Meng, Xiao, Huoqing, Liu, Zugen, Chen, Jun, Su, Haojie, Xie, Ping
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LanguageEnglish
Published London Wiley Subscription Services, Inc 01.06.2023
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Abstract Reduced light availability induced by eutrophication has dramatically affected the growth of submerged macrophytes and caused their rapid decline globally in lakes. Functional traits have usually been used to predict ecological processes and explain plant adaptation. Trait networks, which are constructed from a series of nodes (traits) and edges (trait–trait correlations), can reveal complex relationships among traits. Plant traits belonging to different organs are considered relevant for overall plant performance. Therefore, variation in trait network topology at the whole plant level can better reflect plant adaptation and response to environments than traditional methods, but the mechanisms underlying the decline of plants from a trait network perspective are not well understood. In this study, based on a 1‐year manipulation experiment for Potamogeton maackianus cultured with four levels of light intensity, we constructed trait networks from 20 traits belonging to different organs. Our results showed that trait network connectivity decreases in harsh environments, probably due to increased trait modules responding independently to stress. Network connectivity was positively related to the plant relative growth rate (RGR), as high trait connectivity and coordination should be beneficial for plants to acquire and transport resources efficiently across the whole plant. Additionally, we found that specific stem length, leaf: root mass ratios and leaf total non‐structural carbohydrates were hub traits with high connectivity. Hub traits expressed high phenotypic plasticity, had close links with plant growth and consistently held their higher importance within the network across light gradients or seasons. We found that low phenotypic integration in stressful environments may constrain plant growth, which can provide important implications for understanding plant adaptation strategies to low‐light stress and even predicting community dynamics in the context of global environmental change. Read the free Plain Language Summary for this article on the Journal blog. Read the free Plain Language Summary for this article on the Journal blog.
AbstractList Reduced light availability induced by eutrophication has dramatically affected the growth of submerged macrophytes and caused their rapid decline globally in lakes. Functional traits have usually been used to predict ecological processes and explain plant adaptation. Trait networks, which are constructed from a series of nodes (traits) and edges (trait–trait correlations), can reveal complex relationships among traits. Plant traits belonging to different organs are considered relevant for overall plant performance. Therefore, variation in trait network topology at the whole plant level can better reflect plant adaptation and response to environments than traditional methods, but the mechanisms underlying the decline of plants from a trait network perspective are not well understood.In this study, based on a 1‐year manipulation experiment for Potamogeton maackianus cultured with four levels of light intensity, we constructed trait networks from 20 traits belonging to different organs.Our results showed that trait network connectivity decreases in harsh environments, probably due to increased trait modules responding independently to stress. Network connectivity was positively related to the plant relative growth rate (RGR), as high trait connectivity and coordination should be beneficial for plants to acquire and transport resources efficiently across the whole plant. Additionally, we found that specific stem length, leaf: root mass ratios and leaf total non‐structural carbohydrates were hub traits with high connectivity. Hub traits expressed high phenotypic plasticity, had close links with plant growth and consistently held their higher importance within the network across light gradients or seasons.We found that low phenotypic integration in stressful environments may constrain plant growth, which can provide important implications for understanding plant adaptation strategies to low‐light stress and even predicting community dynamics in the context of global environmental change.Read the free Plain Language Summary for this article on the Journal blog.
Reduced light availability induced by eutrophication has dramatically affected the growth of submerged macrophytes and caused their rapid decline globally in lakes. Functional traits have usually been used to predict ecological processes and explain plant adaptation. Trait networks, which are constructed from a series of nodes (traits) and edges (trait–trait correlations), can reveal complex relationships among traits. Plant traits belonging to different organs are considered relevant for overall plant performance. Therefore, variation in trait network topology at the whole plant level can better reflect plant adaptation and response to environments than traditional methods, but the mechanisms underlying the decline of plants from a trait network perspective are not well understood. In this study, based on a 1‐year manipulation experiment for Potamogeton maackianus cultured with four levels of light intensity, we constructed trait networks from 20 traits belonging to different organs. Our results showed that trait network connectivity decreases in harsh environments, probably due to increased trait modules responding independently to stress. Network connectivity was positively related to the plant relative growth rate (RGR), as high trait connectivity and coordination should be beneficial for plants to acquire and transport resources efficiently across the whole plant. Additionally, we found that specific stem length, leaf: root mass ratios and leaf total non‐structural carbohydrates were hub traits with high connectivity. Hub traits expressed high phenotypic plasticity, had close links with plant growth and consistently held their higher importance within the network across light gradients or seasons. We found that low phenotypic integration in stressful environments may constrain plant growth, which can provide important implications for understanding plant adaptation strategies to low‐light stress and even predicting community dynamics in the context of global environmental change. Read the free Plain Language Summary for this article on the Journal blog.
Reduced light availability induced by eutrophication has dramatically affected the growth of submerged macrophytes and caused their rapid decline globally in lakes. Functional traits have usually been used to predict ecological processes and explain plant adaptation. Trait networks, which are constructed from a series of nodes (traits) and edges (trait–trait correlations), can reveal complex relationships among traits. Plant traits belonging to different organs are considered relevant for overall plant performance. Therefore, variation in trait network topology at the whole plant level can better reflect plant adaptation and response to environments than traditional methods, but the mechanisms underlying the decline of plants from a trait network perspective are not well understood. In this study, based on a 1‐year manipulation experiment for Potamogeton maackianus cultured with four levels of light intensity, we constructed trait networks from 20 traits belonging to different organs. Our results showed that trait network connectivity decreases in harsh environments, probably due to increased trait modules responding independently to stress. Network connectivity was positively related to the plant relative growth rate (RGR), as high trait connectivity and coordination should be beneficial for plants to acquire and transport resources efficiently across the whole plant. Additionally, we found that specific stem length, leaf: root mass ratios and leaf total non‐structural carbohydrates were hub traits with high connectivity. Hub traits expressed high phenotypic plasticity, had close links with plant growth and consistently held their higher importance within the network across light gradients or seasons. We found that low phenotypic integration in stressful environments may constrain plant growth, which can provide important implications for understanding plant adaptation strategies to low‐light stress and even predicting community dynamics in the context of global environmental change. Read the free Plain Language Summary for this article on the Journal blog. Read the free Plain Language Summary for this article on the Journal blog.
Author Rao, Qingyang
Chou, Qingchuan
Xiao, Huoqing
Chen, Jun
Ren, Wenjing
Liu, Zugen
Zhang, Meng
Chen, Jianfeng
Cao, Te
Su, Haojie
Xie, Ping
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  email: xieping@ihb.ac.cn
  organization: Chinese Academy of Sciences
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Copyright 2023 The Authors. Functional Ecology © 2023 British Ecological Society.
2023 British Ecological Society
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Notes Qingyang Rao and Jianfeng Chen contributed equally to this work.
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Snippet Reduced light availability induced by eutrophication has dramatically affected the growth of submerged macrophytes and caused their rapid decline globally in...
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SubjectTerms Adaptation
Aquatic plants
Carbohydrates
Connectivity
Environmental changes
Eutrophication
global change
Harsh environments
Leaves
Light intensity
Light levels
low‐light stress
Luminous intensity
Macrophytes
Mass ratios
network connectivity and centrality
Network topologies
Organs
phenotype
phenotypic integration
Phenotypic plasticity
plant adaptation
Plant growth
plant relative growth rate
Plants (botany)
Potamogeton
Topology
Title Linking trait network parameters with plant growth across light gradients and seasons
URI https://onlinelibrary.wiley.com/doi/abs/10.1111%2F1365-2435.14327
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Volume 37
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