CYCLE COMPLEX DYNAMICS OF COASTAL ECOSYSTEMS: RESILIENCE TO CLIMATE CHANGE. MODELLING AND SIMULATIONS.

Complex Dynamics of Coastal Ecosystems: Resilience to Climate Change (CYCLE) is a coordinated multidisciplinary research project that brings together the efforts of experts in the fields of marine ecology and the physics of complex systems. Its purpose is to understand the effects of global change on coastal marine ecosystems and their biodiversity. Its main challenge, is to transfer the information generated to help public or private entities and institutions in a better decision making in the conservation of the marine environment. The data obtained will contribute to assessing the state of conservation and resilience of these ecosystems, and the models developed will project their evolution under different scenarios, as well as design optimal ecological restoration strategies. These objectives are part of Strategic Action # 6 of the Plan Estatal de Investigación Científica, Técnica y de Innovación 2021-2023.
Sub-project 2 is made up of researchers from the IFISC (CSIC-UIB), an interdisciplinary physics institute recognized as a María de Maeztu unit of excellence, with extensive experience in the study and modeling of complex systems with applications to ecology. Their skills especially qualify them for the development of numerical models that integrate experimental data and observations within the paradigm of quantitative ecology and theoretical ecology. Previous collaboration with members of Sub-project 1 has resulted in the development of computational growth models of clonal plants (i.e. Posidonia oceanica). The integration of different mechanisms of interaction, both cooperative and competitive, have made it possible to explain the generation of vegetation patterns and establish their correspondence with their state of conservation.
The two CYCLE sub-projects are closely linked. The general objectives are common and the contributions of both sub-projects are essential for their achievement. Measurements and time series are essential for a correct parameterization of numerical models, in turn, the results of these models provide valuable information in planning field work. The interaction between the members of the two sub- projects constitutes one of the most outstanding strengths of this coordinated project.