Modelling of polychaete functional diversity: Large marine ecosystem response to multiple natural factors and human impacts on the West African continental margin

Abstract

Polychaetes are one of the most diverse groups of marine organisms, characterized by high species richness, diversity of feeding guilds, life styles, and mobility types. Marine annelids are useful indicators of ecosystem responses to changes in environmental conditions. The aim of our study was to assess the influence of natural and anthropogenic factors on functional diversity of polychaete communities in the Gulf of Guinea, a large marine ecosystem (LME) located in West Africa. This area can be considered as a model marine ecosystem affected by various human influences, such as pollution associated with the oil industry. Material was collected in 2012 across the coast of Ghana. Samples were gathered along four transects, each with six sampling stations (25–1000 m depth range). Analyses of functional richness and evenness, based on generalized linear mixed-effect models and hierarchical partitioning, allowed for complex assessments of the interactions between polychaete communities and environmental factors (e.g., sediments, total organic matter, salinity, fluorescence, oxygen, concentration of toxic metals, total hydrocarbons). Overall species richness of polychaetes was outstandingly high, with 253 species recorded. Functional richness decreased along a depth gradient, while functional evenness increased with depth, and was positively correlated with Ba content, which reached the highest values in the upper bathyal. Gravel content was an important factor in shaping functional composition of shallow water communities. High values of functional richness observed in the shallows may be an expression of high stability of this ecosystem, at the same time indicating its high resilience. Elevated concentrations of lead also influenced community structure at a local scale. Our study demonstrated how a complex set of factors operating along a depth gradient can influence the functional composition of communities. These results are crucial for future management of industrial and environmental protection activities in this region.