Miss Caterina Mintrone1, Dr. Luca Rindi1, Prof. Iacopo Bertocci1, Prof. Elena Maggi1, Prof. Lisandro Benedetti-Cecchi1
1Department Of Biology, University of Pisa, Via Derna 1, Pisa, Italy, Italy
Network theory predicts the potential of modularity to contain the propagation of local disturbances, but field experimental tests of this hypothesis are still lacking. We used intertidal macroalgal assemblages associated with the canopy-forming alga Ericaria amentacea as a model system to assess the role of modularity in confining the spread of algal turfs among modules. We first developed a metacommunity model of E. amentacea forests to explore the effect of network modularity in silico. Then, we performed a real-world experiment with direct manipulation of E. amentacea in three replicate networks. The experimental networks were created within large beds of E. amentacea and consisted of nodes connected through canopy-degraded corridors to form three modules. The local perturbation consisted in the total removal of the canopy within four nodes of the same module. Once algal turfs had colonized the cleared nodes, they could spread in the networks through vegetative propagation along the partially cleared links and compete with understory species. Overall, experimental results and model simulations supported the hypothesis that modularity limited the spread of algal turfs within the perturbed module by buffering their diffusion to nodes in the unperturbed modules. Evidence that the buffering effect of modularity can operate under real, but variable environmental conditions, has important implications for the persistence of declining algal forests and can be the ultimate mechanism preventing the collapse of fragmented ecosystems.
Presentation Slides – Caterina Mintrone
Biography:
Caterina Mintrone is a marine ecologist at University of Pisa. In 2022, she completed her PhD project, at University of Pisa, which focused on understanding the stability of complex ecological networks. Her research is based on the combination of field experiments and network analysis to study the dynamics of marine ecosystems and their stability under increasing regimes of disturbance.
