The mechanistic approach consisting of coupling Dynamic Energy Budget (DEB) models to Individual-Based Models (IBMs) allows simulating individual and population biological traits and their dynamics. This approach was developed here to study population dynamics of two sympatric intertidal ecosystem engineers, Arenicola marina and Arenicola defodiens (Annelida Polychaeta) occurring in the North-East Atlantic from Portugal to Sweden. Latitudinal heterogeneity of the two species’ performances were investigated in terms of population dynamics and biological traits using latitudinal differences in environmental forcing variables. The impact of the forcing variables on population dynamics processes (shore colonisation and migration, spawning and recruitment, etc.) within a specific foreshore (mean values and seasonal patterns) was also assessed. Published DEB parameters were used for A. marina and a specific calibration was undertaken for A. defodiens, combining literature data and new laboratory experiments and field data. Our DEB-IBM simulated super-individuals’ growth and reproduction while lugworms were colonising, migrating and dying over a simulated foreshore. Density rules affected population dynamics. Environmental forcings consisted in monthly values of chlorophyll-a (chl-a) concentrations and daily values of SST. Scenarios focusing on the two most contrasted of these forcing variables time series were used to explore their relative effects over populations’ dynamics and on-shore processes were investigated at two sites displaying highly different simulated population abundances. Overall, northern sites with higher chl-a levels performed better displaying higher biomass, maximum length and reproductive outputs for both species. As expected, Sea Surface Temperature (SST) changes between sites did not impact greatly populations dynamics. Under favourable environmental conditions, intra- and inter-specific competitions emerged from the model. Under non-favourable environmental conditions, A. defodiens’ populations crashed and A. marina displayed atypical population processes, with rare spawning events barely allowing the population’s renewal, and lower size at maturity. Further use and development of this model will lead to better insights on the lugworm populations’ evolution over the next decades.
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