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Modeling the interplay between deepwater oxygen dynamics and sediment diagenesis in a hard-water mesotrophic lake.
- Source :
- Ecological Informatics; Jan2016, Vol. 31, p59-69, 11p
- Publication Year :
- 2016
-
Abstract
- Sediment diagenesis can be a significant driver of oxygen depletion in lakes and may dramatically impact the hypolimnetic oxygen concentrations. In this study, our aim is to simulate sediment oxygen demand (SOD) dynamics under varying conditions of organic matter sedimentation and hypolimnetic oxygen levels. Specifically, we use a process-based sediment diagenesis model to identify the critical processes that regulate dissolved oxygen levels in the hypolimnion of the mesotrophic Lake Simcoe, Ontario, Canada. We quantify the spatial distribution of organic matter mineralization and subsequently assess the role of sediment oxygen demand in hypolimnetic oxygen depletion. Our model reinforces the notion that aerobic mineralization is a major diagenetic process that shapes sediment oxygen demand in the system. Our model confirms existing empirical evidence that SOD contribution to the hypolimnetic oxygen deficit is less than 30% in Lake Simcoe. Our analysis also sheds light on the potential drivers of the significant spatial heterogeneity of the sediment oxygen demand among Kempenfelt Bay, Cook’s Bay, and the main basin of Lake Simcoe, namely, the differences in primary production rates, the origins of the settling organic matter, the redistribution of sediments, and the oxygen concentration at the sediment–water interface due to differences in morphology and hydrodynamics. We conclude by arguing that the pace of the planned re-oligotrophication and the anticipated hypolimnetic oxygen improvements, induced by nutrient loading reductions, may experience short-term delays from years to several decades due to the potential effects of a number of feedback mechanisms across the sediment–water interface in Lake Simcoe. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 15749541
- Volume :
- 31
- Database :
- Supplemental Index
- Journal :
- Ecological Informatics
- Publication Type :
- Academic Journal
- Accession number :
- 112366608
- Full Text :
- https://doi.org/10.1016/j.ecoinf.2015.11.005