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It is important to be able to predict the growth of filter-feeding bivalves, as they grow in dense populations both naturally and for commercial production. To understand the growth of bivalves it is necessary to have a mechanistic understanding of how they acquire energy through ingestion. This study was designed to understand if capture efficiency (CE), a primary step in ingestion for filter-feeders, is variable in the blue mussel Mytilus edulis. CE was measured using natural seston in 3 populations of naturally occurring M. edulis and within 2 populations along a fjord gradient. Differences in CE were found within a single population as well as along the fjord gradient. To determine if these differences were driven by short- or long-term changes, a single population of mussels was reciprocally transplanted between 2 locations along a fjord. This study is the first time CE has been measured within a population of M. edulis using a regional transplant experiment. Results showed that CE may vary between populations and change within populations, indicating that CE seems primarily driven by environmental cues. Pumping and overall ingestion rates differed between populations and varied within populations. For widely distributed species in changing environments, it is increasingly relevant to understand the limits of plasticity of specific traits to be able to predict their growth, survival, and distribution. Here, we aimed to provide a more mechanistic description of CE, pumping rate, and overall ingestion in M. edulis.

Macroalgae can incorporate the isotopic signature (δ15N) of their external environment and be used as ‘bioindicators’ to map and identify between multiple sources of anthropogenic nitrogen. However, evidence suggests that the isotopic signature of their tissues can also be influenced by a range of other factors, which could confound their use as a monitoring tool. Hence, this study aimed to better understand the factors affecting macroalgae isotopic signatures, using Chondrus crispus as a model species. This was achieved by exposing C. crispus to 15N-enriched NO3− and/or NH4+ at varying concentrations, temperatures and incubation times under controlled laboratory conditions. Longer incubation times promoted macroalgae δ15N values closer to that of the external nitrogen source. However, even after 28 days incubation, macroalgae δ15N was still >30‰ lower than the source. This suggests that the δ15N of C. crispus is unlikely to reach isotopic equilibrium with its external environment within a time frame that is feasible for most field studies. However, C. crispus can be used to highlight relative isotopic differences between sources even at very low nitrogen concentrations (

Macroalgal blooms in eutrophic coastal waters around the globe constitute a rising issue for ecosystems and economic activities. Sometimes leading to anoxic events, a better understanding of its growth dynamics is necessary to develop mitigation strategies and inform policies on nutrient runoff management. The development of a Dynamic Energy Budget (DEB) model for the sea lettuce, Ulva lactuca, provides a generic mechanistic description of energy and matter fluxes within the macroalgae and between macroalgae and the environment. Forcing variables consist of seawater temperature, light intensity, and seawater concentrations of dissolved carbon and nitrogen. The model includes a self-shading module for light reduction under heavy biomass and simulation outputs consist of (but are not limited to) total algae biomass, nutrient uptake (carbon and nitrogen), photosynthetic rate, and state of nutrient reserve. Model parameters were estimated using data-sets from the literature and laboratory experiments, then validated using an independent field study in two estuaries with contrasting nutrient loads that feed into Malpeque Bay, PEI (Canada). The validation step yielded accurate temporal predictions of sea lettuce biomass in both of these estuaries. These results indicate that the present mechanistic modelling approach for predicting sea lettuce dynamics captures salient patterns along a spectrum of nutrient loading and could therefore be of use for managing across diverse ecological conditions, which is particularly relevant for a widespread species like Ulva lactuca.