Estimating uncertainty in ambient and saturation nutrient uptake metrics from nutrient pulse releases in stream ecosystems
Abstract
Nutrient spiraling is an important ecosystem process characterizing nutrient transport and uptake in streams. Various nutrient addition methods are used to estimate uptake metrics; however, uncertainty in the metrics is not often evaluated. A method was developed to quantify uncertainty in ambient and saturation nutrient uptake metrics estimated from saturating pulse nutrient additions (Tracer Additions for Spiraling Curve Characterization; TASCC). Using a Monte Carlo (MC) approach, the 95% confidence interval (CI) was estimated for ambient uptake lengths (Sw-amb) and maximum areal uptake rates (Umax) based on 100,000 datasets generated from each of four nitrogen and five phosphorous TASCC experiments conducted seasonally in a forest stream in eastern Tennessee, U.S.A. Uncertainty estimates from the MC approach were compared to the CIs estimated from ordinary least squares (OLS) and non-linear least squares (NLS) models used to calculate Sw-amb and Umax, respectively, from the TASCC method. The CIs for Sw-amb and Umax were large, but were not consistently larger using the MC method. Despite the large CIs, significant differences (based on nonoverlapping CIs) in nutrient metrics among seasons were found with more significant differences using the OLS/NLS vs. the MC method. Lastly, we suggest that the MC approach is a robust way tomore »
- Authors:
-
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Environmental Sciences Division
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Biosciences Division
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Climate Change Science Institute and Environmental Sciences Division
- Publication Date:
- Research Org.:
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Biological and Environmental Research (BER)
- OSTI Identifier:
- 1343498
- Grant/Contract Number:
- AC05-00OR22725
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Limnology and Oceanography Methods
- Additional Journal Information:
- Journal Volume: 15; Journal Issue: 1; Journal ID: ISSN 1541-5856
- Publisher:
- Association for the Sciences of Limnology and Oceanography (ASLO)
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES; 59 BASIC BIOLOGICAL SCIENCES
Citation Formats
Brooks, Scott C., Brandt, Craig C., and Griffiths, Natalie A. Estimating uncertainty in ambient and saturation nutrient uptake metrics from nutrient pulse releases in stream ecosystems. United States: N. p., 2016.
Web. doi:10.1002/lom3.10139.
Brooks, Scott C., Brandt, Craig C., & Griffiths, Natalie A. Estimating uncertainty in ambient and saturation nutrient uptake metrics from nutrient pulse releases in stream ecosystems. United States. https://doi.org/10.1002/lom3.10139
Brooks, Scott C., Brandt, Craig C., and Griffiths, Natalie A. Fri .
"Estimating uncertainty in ambient and saturation nutrient uptake metrics from nutrient pulse releases in stream ecosystems". United States. https://doi.org/10.1002/lom3.10139. https://www.osti.gov/servlets/purl/1343498.
@article{osti_1343498,
title = {Estimating uncertainty in ambient and saturation nutrient uptake metrics from nutrient pulse releases in stream ecosystems},
author = {Brooks, Scott C. and Brandt, Craig C. and Griffiths, Natalie A.},
abstractNote = {Nutrient spiraling is an important ecosystem process characterizing nutrient transport and uptake in streams. Various nutrient addition methods are used to estimate uptake metrics; however, uncertainty in the metrics is not often evaluated. A method was developed to quantify uncertainty in ambient and saturation nutrient uptake metrics estimated from saturating pulse nutrient additions (Tracer Additions for Spiraling Curve Characterization; TASCC). Using a Monte Carlo (MC) approach, the 95% confidence interval (CI) was estimated for ambient uptake lengths (Sw-amb) and maximum areal uptake rates (Umax) based on 100,000 datasets generated from each of four nitrogen and five phosphorous TASCC experiments conducted seasonally in a forest stream in eastern Tennessee, U.S.A. Uncertainty estimates from the MC approach were compared to the CIs estimated from ordinary least squares (OLS) and non-linear least squares (NLS) models used to calculate Sw-amb and Umax, respectively, from the TASCC method. The CIs for Sw-amb and Umax were large, but were not consistently larger using the MC method. Despite the large CIs, significant differences (based on nonoverlapping CIs) in nutrient metrics among seasons were found with more significant differences using the OLS/NLS vs. the MC method. Lastly, we suggest that the MC approach is a robust way to estimate uncertainty, as the calculation of Sw-amb and Umax violates assumptions of OLS/NLS while the MC approach is free of these assumptions. The MC approach can be applied to other ecosystem metrics that are calculated from multiple parameters, providing a more robust estimate of these metrics and their associated uncertainties.},
doi = {10.1002/lom3.10139},
journal = {Limnology and Oceanography Methods},
number = 1,
volume = 15,
place = {United States},
year = {Fri Oct 07 00:00:00 EDT 2016},
month = {Fri Oct 07 00:00:00 EDT 2016}
}
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