Predicting microbial redox dynamics in spatially heterogeneous and dynamic conditions using a numerical modeling approach

Abstract:

The Earth’s Critical Zone is a complex non-linear system exhibiting spatial heterogeneity and temporal dynamics, wherein biogeochemical cycles control the distribution of nutrients in all environmental compartments. Predictability of microbial redox dynamics at such conditions is critical to improvement of prediction of biogeochemical cycles. Understanding microbial dynamics in low-growth conditions in the spatially heterogeneous subsurface that is influenced by temporal dynamics resulting from weather events is challenging due to limited observational opportunities. Therefore, the authors undertake a numerical modeling approach to link the response of microbial dynamics resulting from spatio-temporal heterogeneities in the subsurface with easily measurable indicators. For this purpose, an extended biogeochemical process network that accounted for life cycle processes of microbes in a variety of redox environments was set up. Several scenarios that described spatial and temporal heterogeneity were conceptualized, driven by data obtained from a subject site (AquaDiva Critical Zone Observatory, Hainich National Park, Thuringia, Germany¹). Simulations investigating different combinations of these scenarios were carried out using OGSBRNS². Results indicate that in general spatially heterogeneous domains exhibit less nutrient removal as compared to homogenous domains. Temporally dynamic domains also have an impact on nutrient removal. The degree of impact of these spatio-temporal heterogeneities on nutrient cycling, however, depends on both the Damköhler number and the Peclet number of the regime. These two indicators also govern the traceability of changes in nutrient removal in time linked to disturbances in the past. Since both values can be estimated by field scale measurements, these results may assist in further upscaling of the process descriptions.

References:

[1] Küsel et al., 2016. Frontiers in Earth Science, 4: 32.

[2] Centler et al., 2010. Computers & Geosci. 36: 397-405.