OxyPOM: a biogeochemical model for Oxygen and Particulate Organic Matter dynamics with detailed temperature sensitivity

TL;DR

OxyPOM is a detailed biogeochemical model that incorporates nuanced temperature sensitivities for oxygen and organic matter processes, improving predictions of hypoxia dynamics under climate change scenarios.

Contribution

The paper introduces OxyPOM, a process-based model with detailed temperature sensitivities for key oxygen-related processes, enhancing hypoxia prediction accuracy.

Findings

Nuanced temperature sensitivities significantly affect seasonal oxygen process patterns.

Uniform sensitivities underestimate particulate organic carbon production by up to four times.

Model differences impact nutrient concentration estimates during seasonal cycles.

Abstract

Periods of low dissolved oxygen concentration -- hypoxia and anoxia -- threaten the health of aquatic ecosystems and the services they provide.Hypoxia is strongly influenced by temperature, but the different sensitivities and response functions of oxygen removal and production processes to temperature are not regarded in most models. Here we present OxyPOM -- Oxygen and Particulate Organic Matter, a nuanced temperature-aware process-based biogeochemical model. OxyPOM incorporates nuanced temperature sensitivities for the key oxygen-related processes photosynthesis, re-aeration, respiration, mineralization, and nitrification. Further sensitive variables like optimal light intensity, winter grazing inhibition, and pathogenesis are also represented. Our model was tested in an idealized water column experiment, representing a typical estuarine seasonal low-oxygen environment. Differences between nuanced and uniform temperature sensitivities affect seasonal patterns of oxygen-related processes, resulting in under- or overestimation during different times of the year, particularly with higher differences in summer. While these changes may balance in the overall annual oxygen budget, uniform sensitivities underestimate particulate organic carbon production by up to a factor of four along the year and overestimate nutrient concentrations. This nuanced approach to temperature sensitivity allows us to explore and test new hypotheses related to climate warming and heatwaves, addressing the ecosystem changes demanded by climate change models.