ABSTRACT: Ever since marine heterotrophic bacteria were understood to mediate carbon fluxes to upper trophic levels via the microbial loop, quantifying the coupling between bacteria and phytoplankton has been one of the main priorities for marine microbiologists. The complex nature of phytoplankton-bacterial interactions may lead to nonlinear and regime-dependent coupling, for which conventional statistical approaches such as cross-correlation provide an incomplete picture of the dynamics. Here, we employed a nonlinear method for detecting causality, called convergent cross mapping (CCM), to examine a causal linkage between phytoplankton (primary production) and bacteria (bacterial production) at the Bermuda Atlantic Time-series Study (BATS) site. First, we verified the robustness of our CCM models with synthetic time series output from the Fasham-Ducklow-McKelvie ecosystem model. Initially, we hypothesized a strong bi-directional causal link between phytoplankton and bacteria due to the importance of the microbial loop at BATS. However, the results from our CCM models highlight that phytoplankton-bacterial causal coupling depends on seasonally distinct mixing regimes. While there was no evidence for bi-directional causality between phytoplankton and bacteria during the mixing period, moderate unidirectional causality of bacteria on phytoplankton was detected during the stratification period. Our study reveals causal associations between the 2 major microbial loop processes, for which better quantification is needed to improve our understanding of carbon cycling and export via microbial food webs.