• disturbance
• ecology
• macroalgae
• modularity
• network
• species interactions
• stability
• synchrony

Understanding the relationship between complexity and stability in natural systems is a long-standing issue of ecological research and an urgent need given the impact of human activities on natural resources. Network approaches offered ecologists new tools to investigate the relationship between complexity and stability in natural ecosystems. However, a major obstacle is to integrate theoretical prediction and empirical observations. My PhD project aims at assessing how the intrinsic structure of natural communities influences their overall stability and ability to respond to perturbations.
In Chapter 1, I explored the complex relationships among species interactions, disturbance and stability in kelp forest communities in Southern California. For this analysis, I combined non-linear statistical approaches, network analysis and community matrix theory. This framework allowed me to track the strength of significant causal interspecific interactions through time and thus derive an indicator of network stability in control and manipulated communities. The results obtained in this work corroborated the growing evidence showing that natural systems can persist out of equilibrium due to time-varying interactions.
Network theory predicts the potential of modularity to contain the propagation of local disturbances, but field experimental tests of this hypothesis are still lacking. In Chapters 3 and 4, I investigated the ability of modularity to buffer the propagation of disturbance through two manipulative field experiments. In the first experiment, I created modular networks using intertidal macroalgal assemblages associated with the canopy-forming alga Ericaria amentacea (C. Agardh) Molinari & Guiry (2020) as a model system to assess the role of modularity in confining the spread of algal turfs among modules. In Chapter 3, I further assessed the role of modularity by developing a metacommunity model which reproduced competitive dynamics between E. amentacea and algal turfs within a networked system resembling experimental networks. In the second experiment (Chapter 4), I used Posidonia oceanica (L.) Delile meadows as a model system to test the hypothesis that algal turfs can spread more easily in random than in modular networks. Overall, the results of these experiments and model simulations supported the existing literature showing that modularity limited the spreading of algal turfs within the perturbed module slowing down their diffusion to nodes in the other modules. Moreover, modular networks exhibited a larger resistance to turf spreading than random networks.
Natural disturbances are major forces generating spatial and temporal heterogeneity in marine systems. However, complex spatial patterns may also emerge due to endogenous self-organized processes, such as small-scale disturbance-recovery dynamics. In Chapter 5, I explored the effect of different regimes of disturbance on the spatial synchrony of intertidal macroalgal assemblages dominated by the brown alga Cystoseira compressa (Esper) Gerloff & Nizamuddin. The application of network approaches allowed me to explicitly analyse the topology of spatial synchrony. Overall, experimental outcomes suggested that the observed patterns of synchrony were mainly imposed by exogenous disturbances, with predictable consequences on both synchrony topology and stability.