Temporal variation mechanisms of plant-floralvisitors’ networks in a seasonal area of Cerrado stricto sensu

Abstract

Interaction networks vary in time and space. This happens because they are influenced by biotic and abiotic mechanisms, which act directly on the probability of species interaction. However, like the vast majority of studies in ecology, interaction networks are also influenced by sampling, either by the influence of different sampling methods, or by the low sampling effort. That said, this dissertation is divided into two chapters. In the first chapter, we verified the influence of biotic mechanisms (abundance of floral visitors and number of flowers) and abiotics (temperature and precipitation) on metrics of floral plant-visitor interaction networks over a 12-month time series. In the second chapter, we are concerned with verifying the sampling effort required in each of the four seasons (spring, summer, autumn and winter) and whether that effort differed between seasons. For chapter one, we observed that the dry season (characterized by periods of lower temperature and precipitation) negatively affects the robustness of the networks; while, the abundance of floral visitors increases modularity and decreases the weighted connectance of networks. The number of flowers had no significant effect on the metrics. In the second chapter, using species accumulation curves and non-linear models, we observed that the seasons differ in relation to the sampling effort required to achieve stability in six properties of the network (animals richness, plants richness, interactions richness, Shannon's diversity, network specialization (H2) and weighted connectivity). We observed that the seasons of the year differed in each metric, and these differences are generally explained by the richness and abundance of the species. Finally, our results reiterate the importance of studying the interactions and the mechanisms behind them, since the interaction between species is what forms biodiversity and maintains the functioning of the ecosystem.