Revisiting <i>k</i>: Time‐varying stream litter breakdown rates

Abstract Litter decomposition is usually modeled with the negative exponential model, which assumes constant proportional mass loss. We assessed this assumption and its interpretive consequences using 145 stream litter mass loss time series and process‐based simulations. Relatively simple (two to three parameters) models allowing time‐varying decay rates produced more accurate predictions and were generally more parsimonious. Decomposition trajectories strongly deviated from constant decay for at least 50% of the time series, with the shape influenced by the degree of decomposition covered by a time series. Finally, simulations and empirical evidence suggested that the degree of decomposition covered can interact with time‐varying decay rates and leachability to bias estimates of breakdown rates ( k ) from negative exponential models, obfuscating comparisons within and across studies. Considering alternative models could accelerate understanding and prediction of litter decomposition dynamics by enabling investigation of time‐explicit decomposition dynamics and more precise modeling when warranted.

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Publication Details

Journal
Limnology and Oceanography Letters
Published
2025-05-24
DOI
https://doi.org/10.1002/lol2.70029
Primary Topic
Urban Stormwater Management Solutions
Type
article
Field-Weighted Citation Impact
0.00

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article

Revisiting k: Time‐varying stream litter breakdown rates

Jérémy Jabiol, Rebecca A. Eckert, David W. P. Manning, Allyn K. Dodd et al.
Limnology and Oceanography Letters
Urban Stormwater Management Solutions
article

Revisiting k: Time‐varying stream litter breakdown rates

Jérémy Jabiol, Rebecca A. Eckert, David W. P. Manning, Allyn K. Dodd, William J. Matthaeus, Ada Pastor, Elliot Bastias, Caleb J. Robbins, Andrew S. Mehring
article en

Abstract

Abstract Litter decomposition is usually modeled with the negative exponential model, which assumes constant proportional mass loss. We assessed this assumption and its interpretive consequences using 145 stream litter mass loss time series and process‐based simulations. Relatively simple (two to three parameters) models allowing time‐varying decay rates produced more accurate predictions and were generally more parsimonious. Decomposition trajectories strongly deviated from constant decay for at least 50% of the time series, with the shape influenced by the degree of decomposition covered by a time series. Finally, simulations and empirical evidence suggested that the degree of decomposition covered can interact with time‐varying decay rates and leachability to bias estimates of breakdown rates ( k ) from negative exponential models, obfuscating comparisons within and across studies. Considering alternative models could accelerate understanding and prediction of litter decomposition dynamics by enabling investigation of time‐explicit decomposition dynamics and more precise modeling when warranted.

Limnology and Oceanography LettersVol. 10(4)
University of Nebraska at Omaha (US), Centre National de la Recherche Scientifique (FR), Université Toulouse III - Paul Sabatier (FR), University of Louisville (US), Baylor University (US), Gettysburg College (US), Université Fédérale de Toulouse Midi-Pyrénées (FR), Trinity College Dublin (IE), Universitat de Girona (ES), Aquatic Systems (United States) (US), Institut de Recherche pour le Développement (FR), Umeå University (SE)
Horizon 2020 Framework Programme, H2020 European Research Council
Openalex Percentile: Top 89%
Urban Stormwater Management Solutions
DOIOpen Access PDFOpenAlex
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