Understanding the mechanisms underlying community stability is key to ecosystem conservation and management, as a fluctuating (less stable) community is vulnerable to catastrophic shifts. Theoretical studies have indicated that multispecies interactions play a critical role in determining the stability of the community. For example, species diversity, the topology of the interaction network, the distribution of interaction strengths, and the composition of interaction types can affect community stability. Although experimental and observational studies support this theory, these studies have assumed that the network structure is static; this assumption is unlikely to be true in nature, considering the changing environment. Thus, evidence from natural ecosystems remains scarce, owing to the challenges of tracking rapid changes in interspecific interactions and identifying the effect of such changes on large-scale community dynamics.
To test current ecological theory in a natural system, Professor Chih-hao Hsieh from the Institute of Oceanography and PhD student Chun-Wei Chang from Academia Sinica, together with an international research team, analyze time series data from a 12-year-long dataset of fortnightly collected observations of a marine fish community in Maizuru Bay, Japan. The researchers observe that short-term changes in interaction networks influence overall community dynamics and show that the strengths and even types of interactions change over time; in other words, the interaction network is dynamic rather than static (Figure 1). Moreover, the dynamical pattern of the network critically affects the stability of the community over time. Specifically, the team finds seasonal patterns in dynamic stability for this fish community that broadly support the expectations of current ecological theory: the dominance of weak interactions and higher species diversity during summer months are associated with higher dynamic stability and smaller population fluctuations.
By developing a widely applicable analytical framework for nonlinear time series, the team finds that interspecific interactions, community network structures, 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. These findings have important implications for ecosystem management and conservation. Most excitingly, relating fluctuating interaction networks to community stability provides a promising approach for determining how to systematically maintain natural ecological communities. The research also highlights the importance of long-term time series monitoring for ecosystem management.
Figure 1. Based on the empirical time series data collected from the natural fish community in Maizuru Bay, Japan (a), empirical dynamic modeling (EDM) was used to reconstruct the interaction network among fish species at each time step (b). The structure of the networks is highly dynamic, in which some of the important network properties, including (c) mean interaction strength and dynamic stability, fluctuate over time. In particular, dynamic stability is a critical index measuring the tendency of a dynamical system to return to its original state upon perturbation. Interestingly, networks with many weak interactions and high diversity usually facilitate dynamic stability. (Fish photo credit: Reiji Masuda)
Reference
Ushio, M., C.-H. Hsieh, R. Masuda, E. R. Deyle, H. Ye, C. W. Chang, G. Sugihara, and M. Kondoh, (2018). Fluctuating interaction network and time-varying stability of a natural fish community. Nature, 554(7692): 360-363. DOI:10.1038/nature25504.
Chun-Wei Chang
Taiwan International Graduate Program (TIGP)–Earth System Science Program, Academia Sinica and National Central University
Chih-hao Hsieh
Professor, Institute of Oceanography