Mean environmental associations obscure drivers of zooplankton community dynamics

Abstract

Zooplankton communities are influenced by multiple environmental factors, including temperature, nutrient and resource availability, which fluctuate seasonally and across years. While long-term average effects can identify overall drivers, they may overlook dynamic, context-dependent effects that govern short-term changes in diversity and abundance. Understanding and disentangling both perspectives is crucial for identifying and estimating the drivers that shape community structure under varying environmental states. Here, we applied Empirical Dynamic Modeling (CCM, SMap) to a 12-year weekly zooplankton time series to identify causal environmental drivers of taxonomic and morphological diversity and quantify how the influence of each driver shifts over time. We contrast these results with static long-term average effects inferred from Generalized Linear Models which included predictor sets identified using covariate adjustment and accounting for temporal autocorrelation. Drivers linked to long-term average associations differed from those regulating short-term zooplankton dynamics, revealing a decoupling between mean environmental effects and the drivers of temporal variability. Temperature emerged as a persistent regulator of zooplankton dynamics across multiple diversity dimensions, while variables commonly associated with background trophic conditions (e.g. particulate organic matter) were primarily associated with long-term patterns and showed limited dynamical relevance. Importantly, we find evidence for morphological homogenisation in response to short-term fluctuations in chlorophyll a, which was not detectable in long-term average relationships. This contrast highlights that mean environmental associations do not necessarily reflect the mechanisms governing community dynamics. Impacts might be underestimated if average effects appear weak, or misinterpreted if arising mainly from shared trends or seasonality rather than direct mechanisms Integrating both perspectives clarifies the identity and role of environmental drivers, improving inference and prediction of zooplankton community change through time.