Adaptive cycles of ecosystems under natural perturbation and human intervention

<p>In light of global changes and the need of a sustainable lifestyle, understanding the dynamics of ecological systems is steadily gaining in importance. However, with ecosystems being shaped by the complex interplay of physical, chemical, and biological processes, this remains a demanding endeavor. Addressing this challenge, we have developed a computational method to assess complex systems development, based on the abstract framework provided by Gunderson&#8217;s and Holling&#8217;s adaptive cycle metaphor [1]. The metaphor describes ecosystem development as alternating phases of stability and reorganization, being shaped by three systemic properties: the system&#8217;s potential available for future change, the connectedness among its internal variables and processes, and its resilience in the light of unpredicted perturbations. Resilience, in the sense of Gunderson and Holling, denotes the amount of disturbance that a system can absorb without changing its identity [2]. Our definitions of these three notions are based on a representation of the system as directed network of information transfer. While we consider the system&#8217;s potential and connectedness as information theoretical features of the network, we approach the system&#8217;s resilience via the spectral properties of the network&#8217;s Laplacian matrices.</p> <p>In the present study, we follow this approach to provide holistic analyses of two ecosystems evolving through different successional stages. One of the systems, a vascular plant community on a volcanic island near Iceland, has been largely unspoiled since its formation and has therefore been exposed to natural perturbations, like droughts and breeding birds, only [3]. In contrast, we consider a plant community in the prairie-forest ecotone of Kansas, which has been subject to regular direct human interventions in the form of spring burns [4]. In both cases, our method reveals phases of system breakdown and reorganization, allows us to identify the corresponding drivers of change, and gives hints on the systemic role of single species in the maturation process [1,5].</p> <p>The case studies illustrate the application of the R-package QtAC (Quantifying the adaptive cycle), which provides an easy access to our method [6].</p> <p>&#160;</p> <p>[1] W. zu Castell, and H. Schrenk, Computing the adaptive cycle, Scienti&#64257;c Reports 2020(10):18175 (2020).</p> <p>[2] L. H. Gunderson and C. S. Holling. Panarchy: understanding transformations in human and natural systems (Island, Washington, D.C., 2002).</p> <p>[3] S. Fridriksson, Surtsey. Ecosystems formed (University of Iceland Press, 2005).</p> <p>[4] Long-term studies of secondary succession and community assembly in the prairie-forest ecotone of eastern Kansas. https://foster.ku.edu/long-term-studies-secondary-succession-and-community-assembly-prairie-forest-ecotone-eastern-kansas. Accessed: 2019-05-19.</p> <p>[5] H. Schrenk, B. Magn&#250;sson, B. D. Sigurdsson, and W. zu Castell, Systemic analysis of a developing plant community on the island of Surtsey, Ecology and Society 27(1):35 (2022).</p> <p>[6] H. Schrenk, C. Garcia-Perez, N. Schreiber, and W. zu Castell, QtAC: an R-package for analyzing complex systems development in the framework of the adaptive cycle metaphor, Ecological Modelling 466:109860 (2022).<br /><br /></p>