Contribution of combined stressors on density and gene expression dynamics of the copepod Temora longicornis in the North Sea

Mol Ecol. 2024 Mar 1:e17312. doi: 10.1111/mec.17312. Online ahead of print.

Abstract

The impact of multiple environmental and anthropogenic stressors on the marine environment remains poorly understood. Therefore, we studied the contribution of environmental variables to the densities and gene expression of the dominant zooplankton species in the Belgian part of the North Sea, the calanoid copepod Temora longicornis. We observed a reduced density of copepods, which were also smaller in size, in samples taken from nearshore locations when compared to those obtained from offshore stations. To assess the factors influencing the population dynamics of this species, we applied generalised additive models. These models allowed us to quantify the relative contribution of temperature, nutrient levels, salinity, turbidity, concentrations of photosynthetic pigments, as well as chemical pollutants such as polychlorinated biphenyls and polycyclic aromatic hydrocarbons (PAHs), on copepod density. Temperature and Secchi depth, a proxy for turbidity, were the most important environmental variables predicting the densities of T. longicornis, followed by summed PAH and chlorophyll concentrations. Analysing gene expression in field-collected adults, we observed significant variation in metabolic and stress-response genes. Temperature correlated significantly with genes involved in proteolytic activities, and encoding heat shock proteins. Yet, concentrations of anthropogenic chemicals did not induce significant differences in the gene expression of genes involved in the copepod's fatty acid metabolism or well-known stress-related genes, such as glutathione transferases or cytochrome P450. Our study highlights the potential of gene expression biomonitoring and underscores the significance of a changing environment in future studies.

Keywords: monitoring; organic chemicals; GAM model; North Sea; copepods; gene expression; multiple stressors; transcriptomics.