Understanding Environmental Changes in Temperate Coastal Seas: Linking Models of Benthic Fauna to Carbon and Nutrient Fluxes - Ehrnsten, Eva; Sun, Xiaole; Humborg, Christoph; Norkko, Alf; Savchuk, Oleg P.; Slomp, Caroline P.; Timmermann, Karen; Gustafsson, Bo G. (Frontiers in Marine Science, 2020)
Coastal seas are highly productive systems, providing an array of ecosystem services to humankind, such as processing of nutrient effluents from land and climate regulation. However, coastal ecosystems are threatened by human-induced pressures such as climate change and eutrophication. In the coastal zone, the fluxes and transformations of nutrients and carbon sustaining coastal ecosystem functions and services are strongly regulated by benthic biological and chemical processes. Thus, to understand and quantify how coastal ecosystems respond to environmental change, mechanistic modelling of benthic biogeochemical processes is required. Here, we discuss the present model capabilities to quantitatively describe how benthic fauna drives nutrient and carbon processing in the coastal zone. There are a multitude of modeling approaches of different complexity, but a thorough mechanistic description of benthic-pelagic processes is still hampered by a fundamental lack of scientific understanding of the diverse interactions between the physical, chemical and biological processes that drive biogeochemical fluxes in the coastal zone. Especially shallow systems with long water residence times are sensitive to the activities of benthic organisms. Hence, including and improving the description of benthic biomass and metabolism in sediment diagenetic as well as ecosystem models for such systems is essential to increase our understanding of their response to environmental changes and the role of coastal sediments in nutrient and carbon cycling. Major challenges and research priorities are (1) to couple the dynamics of zoobenthic biomass and metabolism to sediment reactive-transport in models, (2) to test and validate model formulations against real-world data to better incorporate the context-dependency of processes in heterogeneous coastal areas in models and (3) to capture the role of stochastic events.