Causal interactions among phytoplankton and Pseudo-nitzschia species revealed by empirical dynamic modelling

Abstract

Harmful algal blooms (HABs) are a worldwide problem and have increased in frequency and intensity in Chile. Evidence supports the notion that interactions between certain HAB species and their pairing algal species could have either a positive or negative effect on their growth. The present study analyzed phytoplankton data using Empirical Dynamic Modelling to identify causal networks between two Pseudo-nitzschia species groups (P. delicatissima group and P. seriata group) and other phytoplankton species as well as the effect of temperature and salinity. Our results showed that each studied Pseudo-nitzschia species had unique paring algal species. Salinity showed a marginally significant influence on Pseudo-nitzchia seriata group. in Melinka, while temperature was not linked to any of the species. The results in this study could be considered as a novel and preliminary approach to use species interactions in predicting harmful algal blooms which could be developed by utilizing empirical dynamic modelling.