Critical loads of atmospheric N deposition for phytoplankton nutrient limitation shifts in western U.S. mountain lakes. Issue 10 (3rd October 2017)

• Record Type: Journal Article
• Authors: Williams, Jason J.; Lynch, Jason A.; Saros, Jasmine E.; Labou, Stephanie G.
• Is Part Of: Ecosphere. Volume 8:Issue 10(2017)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2017-10-03
• Subjects: critical load -- mountain lakes -- nitrogen deposition -- phytoplankton; Ecology -- Periodicals; Ecology; Periodicals; 577.05
• DOI: 10.1002/ecs2.1955
• Languages: English
• ISSNs: 2150-8925

Abstract

Abstract: In many oligotrophic mountain lakes, anthropogenic atmospheric nitrogen (N) deposition has increased concentrations of N, a key limiting nutrient, and thereby shifted phytoplankton biomass growth from N limitation to P limitation. In the western United States, the critical load N deposition rate for these shifts has not been quantified. We synthesized existing mountain lake chemistry, nutrient limitation bioassay, and N deposition data to estimate N critical loads for shifts from N to P limitation of phytoplankton biomass growth. Data from bioassays in 47 mountain lakes were used to define biological (RR‐N/RR‐P = 1) and chemical (NO3, DIN, DIN:TP) thresholds above which biomass P limitation is more likely than N limitation. Logistic regression was used to calculate critical loads as the total N deposition rate with >50% probability of exceeding biological or chemical thresholds, and thus where P limitation is more likely than N limitation. Logistic regression models were developed with N deposition as the only predictor and with both N deposition and watershed characteristics as predictors. Logistic model performance was evaluated by comparing predicted and observed chemical threshold exceedances in 108 mountain lakes. Across models, estimated critical loads ranged from 2.8 to 5.2 kg total N·ha −1 ·yr −1 . The best‐performing model was a univariate logistic model predicting NO3 threshold exceedance, with N deposition as the only predictor. This model yielded a critical load of 4.1 kg total N·ha −1 ·yr −1 and accurately predicted NO3 threshold exceedance in 69% of lakes. We applied this critical load to an independent sample of 385 mountain lakes with NO3 data to estimate the frequency it would fail to predict a limitation shift—cases where the NO3 threshold for biomass shifts was exceeded, but the critical load was not. The false‐negative rate was 13% across the western United States, but was higher (22%) in the Sierras. Performance analyses suggest a 2.0 kg total N·ha −1 ·yr −1 critical load may avoid false negatives entirely. Critical loads presented here can be used to assess N deposition impacts on western U.S. mountain lakes, and associated performance information can be used to consider if presented critical loads are adequate for specific management applications.