The role of evolutionary modes for trait-based cascades in mutualistic networks

• Autor(a) principal: Bastazini, Vinicius
• Data de Publicação: 2022
• Outros Autores: Debastiani, vanderlei, et al.
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10174/33334; https://doi.org/10.1016/j.ecolmodel.2022.109983

The erosion of functional diversity may foster the collapse of ecological systems. Functional diversity is ultimately determined by the distribution of species traits. As species traits are a legacy of species evolutionary history, one might expect that the mode of trait evolution influences community resistance under the loss of functional diversity. In this paper, we investigate the role of trait evolutionary dynamics on the robustness of mutualistic networks undergoing the following scenarios of species loss: (i) random extinctions, (ii) loss of functional distinctiveness and (iii) extinctions biased towards larger sizes. We simulated networks defined by models of single trait complementary and evolutionary modes where traits can arise in recent diversification events with weak phylogenetic signal, in early diversification events with strong phylogenetic signal, or as a random walk through evolutionary time. Our simulations show that mutualistic networks are especially vulnerable to extinctions based on trait distinctiveness and more robust to random extinction dynamics. The networks show an intermediate level of robustness against size-based extinctions. Despite the small range of variation in network robustness, our results show that the mode of trait evolution matters for network robustness in all three scenarios. Networks with low phylogenetic signal are more robust than networks with high phylogenetic signal across all scenarios. As a consequence, our results predict that mutualistic networks based upon current adaptations are more likely to cope with extinction dynamics than those networks that are based upon conserved traits.