Predicting the impact of spatial heterogeneity on microbially mediated nutrient cycling in the subsurface

[摘要] The subsurface is a temporally dynamic and spatially heterogeneouscompartment of the Earth's critical zone, and biogeochemical transformationstaking place in this compartment are crucial for the cycling of nutrients.The impact of spatial heterogeneity on such microbially mediated nutrientcycling is not well known, which imposes a severe challenge in the predictionof in situ biogeochemical transformation rates and further of nutrientloading contributed by the groundwater to the surface water bodies.Therefore, we used a numerical modelling approach to evaluate thesensitivity of groundwater microbial biomass distribution and nutrientcycling to spatial heterogeneity in different scenarios accounting forvarious residence times. The model results gave us an insight into domaincharacteristics with respect to the presence of oxic niches in predominantlyanoxic zones and vice versa depending on the extent of spatial heterogeneityand the flow regime. The obtained results show that microbial abundance,distribution, and activity are sensitive to the applied flow regime and thatthe mobile (i.e. observable by groundwater sampling) fraction of microbialbiomass is a varying, yet only a small, fraction of the total biomass in adomain. Furthermore, spatial heterogeneity resulted in anaerobic niches inthe domain and shifts in microbial biomass between active and inactivestates. The lack of consideration of spatial heterogeneity, thus, can resultin inaccurate estimation of microbial activity. In most cases this leads toan overestimation of nutrient removal (up to twice the actual amount) alonga flow path. We conclude that the governing factors for evaluating this arethe residence time of solutes and the Damköhler number ( D a ) of thebiogeochemical reactions in the domain. We propose a relationship to scalethe impact of spatial heterogeneity on nutrient removal governed by thelog 10 D a . This relationship may be applied in upscaled descriptions ofmicrobially mediated nutrient cycling dynamics in the subsurface therebyresulting in more accurate predictions of, for example, carbon and nitrogen cyclingin groundwater over long periods at the catchment scale.

[学科分类] 大气科学