Ecosystem-scale nutrient cycling responses to increasing air temperatures vary with lake trophic state

Kaitlin J. Farrell, Nicole K. Ward, Arianna I. Krinos, Paul C. Hanson, Vahid Daneshmand, Renato J. Figueiredo and Cayelan C. Carey

Ecological Modelling, 2020, vol. 430, issue C

Abstract: Understanding potential effects of climate warming on biogeochemical cycling in freshwater ecosystems is of pressing importance. Specifically, increasing air and water temperatures could accelerate nutrient cycling in lakes, which has major implications for in-lake nutrient concentrations, water column nutrient stoichiometry, and downstream nutrient export. Lakes may respond differentially to warming based on their current trophic state, although direct comparisons of temperature-driven changes in nutrient cycling between low- and high-nutrient lakes are lacking. Here, we used an open-source coupled hydrodynamic biogeochemical model to simulate ecosystem-scale changes in water column total nitrogen (TN) and total phosphorus (TP) concentrations and TN:TP ratios due to potential incremental changes in air temperature (from +0 °C to +6 °C) in a low-nutrient and a high-nutrient lake. Warming resulted in lower TN and higher TP epilimnetic (surface water) concentrations in both lakes, resulting in reduced molar TN:TP ratios in both lakes. While the high- and low-nutrient lakes had similar magnitude reductions in TN:TP ratio between the +0 °C and +6 °C scenarios (30.3% and 34.6%, respectively), median epilimnetic TN:TP in the low-nutrient lake significantly decreased with as little as 1 °C of warming. Warming also altered net nutrient retention, with decreased downstream export of TN but increased downstream export of TP in both lakes. Our modeling results suggest that low-nutrient lakes may respond to warming at lower levels of temperature increase than high-nutrient lakes, and that climate warming could intensify effects of nutrient enrichment driven by increased N and P loading due to land-use change.

Keywords: Biogeochemical cycling; Climate change; Distributed computing; Grapler; Nutrients; Simulation modeling (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:430:y:2020:i:c:s0304380020302064

DOI: 10.1016/j.ecolmodel.2020.109134

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