Estrutura e dinâmica de uma rede trófica marinha neotropical: uma ponte entre a teoria de redes e as estratégias de conservação

Abstract

Coastal marine ecosystems experience strong impacts in an unprecedented rate in the Anthropocene, such as pollution, introduction of alien species, climate change and overfishing. Overfishing erodes marine biodiversity and ecosystem functioning as it affects species interactions, abundances, trait diversity and ultimately ecosystem services. Advances in ecological network theory can help us to assess and mitigate anthropogenic impacts on marine biodiversity. For example, structural network analyses can describe patterns of species interactions, which represent fundamental connections between the architecture of biodiversity and ecosystem functions, and also inform the structural and functional role that each species plays in an ecological community. Additionally, network modeling and simulations can provide theoretically founded predictions of how biodiversity loss is expected to reshape community-level properties, such as resilience, robustness, and functional diversity, and influence the long-term persistence of ecosystems. Particularly, adaptive network models can predict dynamic changes that arise from interaction rewiring -the reconfiguration of species interactions driven by extinctions alongside with several other ecological and evolutionary processes. An adaptive network is defined by the mutual effects between changes in interaction patterns and associated network properties that characterize community structure and dynamics, such as nestedness, modularity, and stability; and population-level, eco-evolutionary processes shaping the properties of species that form the network, such as their abundances and trait values. In this thesis, we apply the network approach to bridge ecological community theory and evidence-based conservation. We followed three steps towards the inception of network theory into evidence-based conservation strategies for marine biodiversity. In the first chapter, we explored and discussed how the ecological network approach is used to understand the structure of marine biodiversity, and to predict the response of trophic networks to management strategies such as reducing fishing pressure. In this the chapter we introduced novel theoretical and methodological perspectives that now allow us to bridge adaptive network models, species-interaction "big data" and field experiments, in order to build an interface ensuring multidirectional knowledge flows among theoretical network models, experimental marine ecology, and conservation policies and practices in the tropical Pacific Ocean. In the second chapter, we described the structure of a species-rich food web in the Colombian Pacific coast, unravelling the functional roles of more than 300 species alongside with small- and large-scale fisheries, identifying some network hubs, module hubs and connectors entities (fisheries and species) that drive up to 1,100 trophic interactions over the entire network. We discuss the high degree of interaction dissimilarity among network hubs in terms of resource partitioning that would be the ghost of past competition imposed by decades of intensive fisheries. In terms of conservation prioritization, our analyses identify two hammerhead shark species (S. lewini and S. media) whose centrality in the network make them qualitatively comparable to small-scale fisheries as hyper-hubs -- a concept that we propose here to define highly central network hubs that prey on other network hubs and hence are likely to exert amplified top-down effects over the entire food web. Simulations of single-species extinctions with varying topological roles, including hyper-hubs, and trophic levels did not change the overall architecture of the food web nor the relative frequencies of topological roles. However, simulated extinctions often change the species identities within topological roles, with several Sphyrna species recurrently emerging as network hubs, reinforcing the notion that a high conservation priority should be given to them. Finally, in the third chapter, we developed an adaptive network model to investigate if our predictions regarding the effects of fisheries regulation and species losses hold on under adaptive rewiring, i.e., as species adjust their interactions following extinctions and the trait-interaction-abundance feedbacks that they trigger. These first results have shown that the rewiring and fishery strength may potentially aggravate the consequences of loss of species, and possibly trigger extinction cascades affecting the resilience and causing strong changes in the dynamics of the coastal marine food web. These network models are founded on the ongoing synthesis between ecological and evolutionary theories and hence can greatly improve our ability to understand and predict community-wide outcomes of anthropogenic disturbances in coastal marine ecosystems.