The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Michio Kondoh - One of the best experts on this subject based on the ideXlab platform.
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fluctuating interaction network and time varying stability of a natural fish community
Nature, 2018Co-Authors: Masayuki Ushio, Chihhao Hsieh, Reiji Masuda, Ethan R Deyle, Hao Ye, Chunwei Chang, George Sugihara, Michio KondohAbstract:A method for modelling time-varying dynamic stability in a natural marine fish community finds that seasonal patterns in community stability are driven by species diversity and interspecific interactions. Ecological Theory suggests that ecosystem stability—the ability of an ecosystem to persist through perturbations—is influenced by changes in the interactions between different species. Masayuki Ushio and colleagues use a 12-year observational dataset of species interactions in a marine fish community in Maizuru Bay, Japan, to examine the link between fluctuations in interspecific interactions and community stability. They find that short-term changes in the interaction network influence the overall community dynamics, with weak interactions and higher species diversity promoting community stability. Ecological Theory suggests that large-scale patterns such as community stability can be influenced by changes in interspecific interactions that arise from the behavioural and/or physiological responses of individual species varying over time1,2,3. Although this Theory has experimental support2,4,5, evidence from natural ecosystems is lacking owing to the challenges of tracking rapid changes in interspecific interactions (known to occur on timescales much shorter than a generation time)6 and then identifying the effect of such changes on large-scale community dynamics. Here, using tools for analysing nonlinear time series6,7,8,9 and a 12-year-long dataset of fortnightly collected observations on a natural marine fish community in Maizuru Bay, Japan, we show that short-term changes in interaction networks influence overall community dynamics. Among the 15 dominant species, we identify 14 interspecific interactions to construct a dynamic interaction network. We show that the strengths, and even types, of interactions change with time; we also develop a time-varying stability measure based on local Lyapunov stability for attractor dynamics in non-equilibrium nonlinear systems. We use this dynamic stability measure to examine the link between the time-varying interaction network and community stability. We find seasonal patterns in dynamic stability for this fish community that broadly support expectations of current Ecological Theory. Specifically, the dominance of weak interactions and higher species diversity during summer months are associated with higher dynamic stability and smaller population fluctuations. We suggest that interspecific interactions, community network structure and community stability are dynamic properties, and that linking fluctuating interaction networks to community-level dynamic properties is key to understanding the maintenance of Ecological communities in nature.
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fluctuating interaction network and time varying stability of a natural fish community
Nature, 2018Co-Authors: Masayuki Ushio, Chihhao Hsieh, Reiji Masuda, Ethan R Deyle, Chunwei Chang, George Sugihara, Michio KondohAbstract:Ecological Theory suggests that large-scale patterns such as community stability can be influenced by changes in interspecific interactions that arise from the behavioural and/or physiological responses of individual species varying over time. Although this Theory has experimental support, evidence from natural ecosystems is lacking owing to the challenges of tracking rapid changes in interspecific interactions (known to occur on timescales much shorter than a generation time) and then identifying the effect of such changes on large-scale community dynamics. Here, using tools for analysing nonlinear time series and a 12-year-long dataset of fortnightly collected observations on a natural marine fish community in Maizuru Bay, Japan, we show that short-term changes in interaction networks influence overall community dynamics. Among the 15 dominant species, we identify 14 interspecific interactions to construct a dynamic interaction network. We show that the strengths, and even types, of interactions change with time; we also develop a time-varying stability measure based on local Lyapunov stability for attractor dynamics in non-equilibrium nonlinear systems. We use this dynamic stability measure to examine the link between the time-varying interaction network and community stability. We find seasonal patterns in dynamic stability for this fish community that broadly support expectations of current Ecological Theory. Specifically, the dominance of weak interactions and higher species diversity during summer months are associated with higher dynamic stability and smaller population fluctuations. We suggest that interspecific interactions, community network structure and community stability are dynamic properties, and that linking fluctuating interaction networks to community-level dynamic properties is key to understanding the maintenance of Ecological communities in nature.
Chihhao Hsieh - One of the best experts on this subject based on the ideXlab platform.
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fluctuating interaction network and time varying stability of a natural fish community
Nature, 2018Co-Authors: Masayuki Ushio, Chihhao Hsieh, Reiji Masuda, Ethan R Deyle, Hao Ye, Chunwei Chang, George Sugihara, Michio KondohAbstract:A method for modelling time-varying dynamic stability in a natural marine fish community finds that seasonal patterns in community stability are driven by species diversity and interspecific interactions. Ecological Theory suggests that ecosystem stability—the ability of an ecosystem to persist through perturbations—is influenced by changes in the interactions between different species. Masayuki Ushio and colleagues use a 12-year observational dataset of species interactions in a marine fish community in Maizuru Bay, Japan, to examine the link between fluctuations in interspecific interactions and community stability. They find that short-term changes in the interaction network influence the overall community dynamics, with weak interactions and higher species diversity promoting community stability. Ecological Theory suggests that large-scale patterns such as community stability can be influenced by changes in interspecific interactions that arise from the behavioural and/or physiological responses of individual species varying over time1,2,3. Although this Theory has experimental support2,4,5, evidence from natural ecosystems is lacking owing to the challenges of tracking rapid changes in interspecific interactions (known to occur on timescales much shorter than a generation time)6 and then identifying the effect of such changes on large-scale community dynamics. Here, using tools for analysing nonlinear time series6,7,8,9 and a 12-year-long dataset of fortnightly collected observations on a natural marine fish community in Maizuru Bay, Japan, we show that short-term changes in interaction networks influence overall community dynamics. Among the 15 dominant species, we identify 14 interspecific interactions to construct a dynamic interaction network. We show that the strengths, and even types, of interactions change with time; we also develop a time-varying stability measure based on local Lyapunov stability for attractor dynamics in non-equilibrium nonlinear systems. We use this dynamic stability measure to examine the link between the time-varying interaction network and community stability. We find seasonal patterns in dynamic stability for this fish community that broadly support expectations of current Ecological Theory. Specifically, the dominance of weak interactions and higher species diversity during summer months are associated with higher dynamic stability and smaller population fluctuations. We suggest that interspecific interactions, community network structure and community stability are dynamic properties, and that linking fluctuating interaction networks to community-level dynamic properties is key to understanding the maintenance of Ecological communities in nature.
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fluctuating interaction network and time varying stability of a natural fish community
Nature, 2018Co-Authors: Masayuki Ushio, Chihhao Hsieh, Reiji Masuda, Ethan R Deyle, Chunwei Chang, George Sugihara, Michio KondohAbstract:Ecological Theory suggests that large-scale patterns such as community stability can be influenced by changes in interspecific interactions that arise from the behavioural and/or physiological responses of individual species varying over time. Although this Theory has experimental support, evidence from natural ecosystems is lacking owing to the challenges of tracking rapid changes in interspecific interactions (known to occur on timescales much shorter than a generation time) and then identifying the effect of such changes on large-scale community dynamics. Here, using tools for analysing nonlinear time series and a 12-year-long dataset of fortnightly collected observations on a natural marine fish community in Maizuru Bay, Japan, we show that short-term changes in interaction networks influence overall community dynamics. Among the 15 dominant species, we identify 14 interspecific interactions to construct a dynamic interaction network. We show that the strengths, and even types, of interactions change with time; we also develop a time-varying stability measure based on local Lyapunov stability for attractor dynamics in non-equilibrium nonlinear systems. We use this dynamic stability measure to examine the link between the time-varying interaction network and community stability. We find seasonal patterns in dynamic stability for this fish community that broadly support expectations of current Ecological Theory. Specifically, the dominance of weak interactions and higher species diversity during summer months are associated with higher dynamic stability and smaller population fluctuations. We suggest that interspecific interactions, community network structure and community stability are dynamic properties, and that linking fluctuating interaction networks to community-level dynamic properties is key to understanding the maintenance of Ecological communities in nature.
Masayuki Ushio - One of the best experts on this subject based on the ideXlab platform.
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fluctuating interaction network and time varying stability of a natural fish community
Nature, 2018Co-Authors: Masayuki Ushio, Chihhao Hsieh, Reiji Masuda, Ethan R Deyle, Hao Ye, Chunwei Chang, George Sugihara, Michio KondohAbstract:A method for modelling time-varying dynamic stability in a natural marine fish community finds that seasonal patterns in community stability are driven by species diversity and interspecific interactions. Ecological Theory suggests that ecosystem stability—the ability of an ecosystem to persist through perturbations—is influenced by changes in the interactions between different species. Masayuki Ushio and colleagues use a 12-year observational dataset of species interactions in a marine fish community in Maizuru Bay, Japan, to examine the link between fluctuations in interspecific interactions and community stability. They find that short-term changes in the interaction network influence the overall community dynamics, with weak interactions and higher species diversity promoting community stability. Ecological Theory suggests that large-scale patterns such as community stability can be influenced by changes in interspecific interactions that arise from the behavioural and/or physiological responses of individual species varying over time1,2,3. Although this Theory has experimental support2,4,5, evidence from natural ecosystems is lacking owing to the challenges of tracking rapid changes in interspecific interactions (known to occur on timescales much shorter than a generation time)6 and then identifying the effect of such changes on large-scale community dynamics. Here, using tools for analysing nonlinear time series6,7,8,9 and a 12-year-long dataset of fortnightly collected observations on a natural marine fish community in Maizuru Bay, Japan, we show that short-term changes in interaction networks influence overall community dynamics. Among the 15 dominant species, we identify 14 interspecific interactions to construct a dynamic interaction network. We show that the strengths, and even types, of interactions change with time; we also develop a time-varying stability measure based on local Lyapunov stability for attractor dynamics in non-equilibrium nonlinear systems. We use this dynamic stability measure to examine the link between the time-varying interaction network and community stability. We find seasonal patterns in dynamic stability for this fish community that broadly support expectations of current Ecological Theory. Specifically, the dominance of weak interactions and higher species diversity during summer months are associated with higher dynamic stability and smaller population fluctuations. We suggest that interspecific interactions, community network structure and community stability are dynamic properties, and that linking fluctuating interaction networks to community-level dynamic properties is key to understanding the maintenance of Ecological communities in nature.
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fluctuating interaction network and time varying stability of a natural fish community
Nature, 2018Co-Authors: Masayuki Ushio, Chihhao Hsieh, Reiji Masuda, Ethan R Deyle, Chunwei Chang, George Sugihara, Michio KondohAbstract:Ecological Theory suggests that large-scale patterns such as community stability can be influenced by changes in interspecific interactions that arise from the behavioural and/or physiological responses of individual species varying over time. Although this Theory has experimental support, evidence from natural ecosystems is lacking owing to the challenges of tracking rapid changes in interspecific interactions (known to occur on timescales much shorter than a generation time) and then identifying the effect of such changes on large-scale community dynamics. Here, using tools for analysing nonlinear time series and a 12-year-long dataset of fortnightly collected observations on a natural marine fish community in Maizuru Bay, Japan, we show that short-term changes in interaction networks influence overall community dynamics. Among the 15 dominant species, we identify 14 interspecific interactions to construct a dynamic interaction network. We show that the strengths, and even types, of interactions change with time; we also develop a time-varying stability measure based on local Lyapunov stability for attractor dynamics in non-equilibrium nonlinear systems. We use this dynamic stability measure to examine the link between the time-varying interaction network and community stability. We find seasonal patterns in dynamic stability for this fish community that broadly support expectations of current Ecological Theory. Specifically, the dominance of weak interactions and higher species diversity during summer months are associated with higher dynamic stability and smaller population fluctuations. We suggest that interspecific interactions, community network structure and community stability are dynamic properties, and that linking fluctuating interaction networks to community-level dynamic properties is key to understanding the maintenance of Ecological communities in nature.
Chunwei Chang - One of the best experts on this subject based on the ideXlab platform.
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fluctuating interaction network and time varying stability of a natural fish community
Nature, 2018Co-Authors: Masayuki Ushio, Chihhao Hsieh, Reiji Masuda, Ethan R Deyle, Hao Ye, Chunwei Chang, George Sugihara, Michio KondohAbstract:A method for modelling time-varying dynamic stability in a natural marine fish community finds that seasonal patterns in community stability are driven by species diversity and interspecific interactions. Ecological Theory suggests that ecosystem stability—the ability of an ecosystem to persist through perturbations—is influenced by changes in the interactions between different species. Masayuki Ushio and colleagues use a 12-year observational dataset of species interactions in a marine fish community in Maizuru Bay, Japan, to examine the link between fluctuations in interspecific interactions and community stability. They find that short-term changes in the interaction network influence the overall community dynamics, with weak interactions and higher species diversity promoting community stability. Ecological Theory suggests that large-scale patterns such as community stability can be influenced by changes in interspecific interactions that arise from the behavioural and/or physiological responses of individual species varying over time1,2,3. Although this Theory has experimental support2,4,5, evidence from natural ecosystems is lacking owing to the challenges of tracking rapid changes in interspecific interactions (known to occur on timescales much shorter than a generation time)6 and then identifying the effect of such changes on large-scale community dynamics. Here, using tools for analysing nonlinear time series6,7,8,9 and a 12-year-long dataset of fortnightly collected observations on a natural marine fish community in Maizuru Bay, Japan, we show that short-term changes in interaction networks influence overall community dynamics. Among the 15 dominant species, we identify 14 interspecific interactions to construct a dynamic interaction network. We show that the strengths, and even types, of interactions change with time; we also develop a time-varying stability measure based on local Lyapunov stability for attractor dynamics in non-equilibrium nonlinear systems. We use this dynamic stability measure to examine the link between the time-varying interaction network and community stability. We find seasonal patterns in dynamic stability for this fish community that broadly support expectations of current Ecological Theory. Specifically, the dominance of weak interactions and higher species diversity during summer months are associated with higher dynamic stability and smaller population fluctuations. We suggest that interspecific interactions, community network structure and community stability are dynamic properties, and that linking fluctuating interaction networks to community-level dynamic properties is key to understanding the maintenance of Ecological communities in nature.
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fluctuating interaction network and time varying stability of a natural fish community
Nature, 2018Co-Authors: Masayuki Ushio, Chihhao Hsieh, Reiji Masuda, Ethan R Deyle, Chunwei Chang, George Sugihara, Michio KondohAbstract:Ecological Theory suggests that large-scale patterns such as community stability can be influenced by changes in interspecific interactions that arise from the behavioural and/or physiological responses of individual species varying over time. Although this Theory has experimental support, evidence from natural ecosystems is lacking owing to the challenges of tracking rapid changes in interspecific interactions (known to occur on timescales much shorter than a generation time) and then identifying the effect of such changes on large-scale community dynamics. Here, using tools for analysing nonlinear time series and a 12-year-long dataset of fortnightly collected observations on a natural marine fish community in Maizuru Bay, Japan, we show that short-term changes in interaction networks influence overall community dynamics. Among the 15 dominant species, we identify 14 interspecific interactions to construct a dynamic interaction network. We show that the strengths, and even types, of interactions change with time; we also develop a time-varying stability measure based on local Lyapunov stability for attractor dynamics in non-equilibrium nonlinear systems. We use this dynamic stability measure to examine the link between the time-varying interaction network and community stability. We find seasonal patterns in dynamic stability for this fish community that broadly support expectations of current Ecological Theory. Specifically, the dominance of weak interactions and higher species diversity during summer months are associated with higher dynamic stability and smaller population fluctuations. We suggest that interspecific interactions, community network structure and community stability are dynamic properties, and that linking fluctuating interaction networks to community-level dynamic properties is key to understanding the maintenance of Ecological communities in nature.
Ethan R Deyle - One of the best experts on this subject based on the ideXlab platform.
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fluctuating interaction network and time varying stability of a natural fish community
Nature, 2018Co-Authors: Masayuki Ushio, Chihhao Hsieh, Reiji Masuda, Ethan R Deyle, Hao Ye, Chunwei Chang, George Sugihara, Michio KondohAbstract:A method for modelling time-varying dynamic stability in a natural marine fish community finds that seasonal patterns in community stability are driven by species diversity and interspecific interactions. Ecological Theory suggests that ecosystem stability—the ability of an ecosystem to persist through perturbations—is influenced by changes in the interactions between different species. Masayuki Ushio and colleagues use a 12-year observational dataset of species interactions in a marine fish community in Maizuru Bay, Japan, to examine the link between fluctuations in interspecific interactions and community stability. They find that short-term changes in the interaction network influence the overall community dynamics, with weak interactions and higher species diversity promoting community stability. Ecological Theory suggests that large-scale patterns such as community stability can be influenced by changes in interspecific interactions that arise from the behavioural and/or physiological responses of individual species varying over time1,2,3. Although this Theory has experimental support2,4,5, evidence from natural ecosystems is lacking owing to the challenges of tracking rapid changes in interspecific interactions (known to occur on timescales much shorter than a generation time)6 and then identifying the effect of such changes on large-scale community dynamics. Here, using tools for analysing nonlinear time series6,7,8,9 and a 12-year-long dataset of fortnightly collected observations on a natural marine fish community in Maizuru Bay, Japan, we show that short-term changes in interaction networks influence overall community dynamics. Among the 15 dominant species, we identify 14 interspecific interactions to construct a dynamic interaction network. We show that the strengths, and even types, of interactions change with time; we also develop a time-varying stability measure based on local Lyapunov stability for attractor dynamics in non-equilibrium nonlinear systems. We use this dynamic stability measure to examine the link between the time-varying interaction network and community stability. We find seasonal patterns in dynamic stability for this fish community that broadly support expectations of current Ecological Theory. Specifically, the dominance of weak interactions and higher species diversity during summer months are associated with higher dynamic stability and smaller population fluctuations. We suggest that interspecific interactions, community network structure and community stability are dynamic properties, and that linking fluctuating interaction networks to community-level dynamic properties is key to understanding the maintenance of Ecological communities in nature.
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fluctuating interaction network and time varying stability of a natural fish community
Nature, 2018Co-Authors: Masayuki Ushio, Chihhao Hsieh, Reiji Masuda, Ethan R Deyle, Chunwei Chang, George Sugihara, Michio KondohAbstract:Ecological Theory suggests that large-scale patterns such as community stability can be influenced by changes in interspecific interactions that arise from the behavioural and/or physiological responses of individual species varying over time. Although this Theory has experimental support, evidence from natural ecosystems is lacking owing to the challenges of tracking rapid changes in interspecific interactions (known to occur on timescales much shorter than a generation time) and then identifying the effect of such changes on large-scale community dynamics. Here, using tools for analysing nonlinear time series and a 12-year-long dataset of fortnightly collected observations on a natural marine fish community in Maizuru Bay, Japan, we show that short-term changes in interaction networks influence overall community dynamics. Among the 15 dominant species, we identify 14 interspecific interactions to construct a dynamic interaction network. We show that the strengths, and even types, of interactions change with time; we also develop a time-varying stability measure based on local Lyapunov stability for attractor dynamics in non-equilibrium nonlinear systems. We use this dynamic stability measure to examine the link between the time-varying interaction network and community stability. We find seasonal patterns in dynamic stability for this fish community that broadly support expectations of current Ecological Theory. Specifically, the dominance of weak interactions and higher species diversity during summer months are associated with higher dynamic stability and smaller population fluctuations. We suggest that interspecific interactions, community network structure and community stability are dynamic properties, and that linking fluctuating interaction networks to community-level dynamic properties is key to understanding the maintenance of Ecological communities in nature.
