par Xu, Sinan;Liu, Bo;Arndt, Sandra ;Kasten, Sabine;Wu, Zijun
Référence Biogeosciences, 20, 12, page (2251-2263)
Publication Publié, 2023-06
Référence Biogeosciences, 20, 12, page (2251-2263)
Publication Publié, 2023-06
Article révisé par les pairs
Résumé : | Organic matter (OM) degradation in marine sediments is largely controlled by its reactivity and profoundly affects the global carbon cycle. Yet, there is currently no general framework that can constrain OM reactivity on a global scale. In this study, we propose a reactive continuum model based on a lognormal distribution (l-RCM), where OM reactivity is fully described by parameters μ (the mean reactivity of the initial OM bulk mixture) and σ (the variance of OM components around the mean reactivity). We use the l-RCM to inversely determine μ and σ at 123 sites across the global ocean. The results show that the apparent OM reactivity (〈k〉 = μ·exp (σ2/2)) decreases with decreasing sedimentation rate (ω) and that OM reactivity is more than 3 orders of magnitude higher in shelf than in abyssal regions. Despite the general global trends, higher than expected OM reactivity is observed in certain ocean regions characterized by great water depth or pronounced oxygen minimum zones, such as the eastern-western coastal equatorial Pacific and the Arabian Sea, emphasizing the complex control of the depositional environment (e.g., OM flux, oxygen content in the water column) on benthic OM reactivity. Notably, the l-RCM can also highlight the variability in OM reactivity in these regions. Based on inverse modeling results in our dataset, we establish the significant statistical relationships between (k) and ω and further map the global OM reactivity distribution. The novelty of this study lies in its unifying view but also in contributing a new framework that allows predicting OM reactivity in data-poor areas based on readily available (or more easily obtainable) information. Such a framework is currently lacking and limits our abilities to constrain OM reactivity in global biogeochemical or Earth system models. |