Respiration regimes in rivers: Partitioning source-specific respiration from metabolism time series

dc.contributor.authorBertuzzo, Enrico
dc.contributor.authorHotchkiss, Erin R.
dc.contributor.authorArgerich, Alba
dc.contributor.authorKominoski, John S.
dc.contributor.authorOviedo-Vargas, Diana
dc.contributor.authorSavoy, Philip
dc.contributor.authorScarlett, Rachel
dc.contributor.authorSchiller Calle, Daniel von
dc.contributor.authorHeffernan, James B.
dc.date.accessioned2022-12-22T18:33:46Z
dc.date.available2022-12-22T18:33:46Z
dc.date.issued2022-09-14
dc.date.updated2022-12-22T18:33:46Z
dc.description.abstractRespiration in streams is controlled by the timing, magnitude, and quality of organic matter (OM) inputs from internal primary production and external fluxes. Here, we estimated the contribution of different OM sources to seasonal, annual, and event-driven characteristics of whole-stream ecosystem respiration (ER) using an inverse modeling framework that accounts for possible time-lags between OM inputs and respiration. We modeled site-specific, dynamic OM stocks contributing to ER: autochthonous OM from gross primary production (GPP); allochthonous OM delivered during flow events; and seasonal pulses of leaf litter. OM stored in the sediment and dissolved organic matter (DOM) transported during baseflow were modeled as a stable stock contributing to baseline respiration. We applied this modeling framework to five streams with different catchment size, climate, and canopy cover, where multi-year time series of ER and environmental variables were available. Overall, the model explained between 53% and 74% of observed ER dynamics. Respiration of autochthonous OM tracked seasonal peaks in GPP in spring or summer. Increases in ER were often associated with high-flow events. Respiration associated with litter inputs was larger in smaller streams. Time lags between leaf inputs and respiration were longer than for other OM sources, likely due to lower biological reactivity. Model estimates of source-specific ER and OM stocks compared well with existing measures of OM stocks, inputs, and respiration or decomposition. Our modeling approach has the potential to expand the scale of comparative analyses of OM dynamics within and among freshwater ecosystems.
dc.format.extent15 p.
dc.format.mimetypeapplication/pdf
dc.identifier.idgrec725229
dc.identifier.issn0024-3590
dc.identifier.urihttps://hdl.handle.net/2445/191803
dc.language.isoeng
dc.publisherAmerican Society of Limnology and Oceanography.
dc.relation.isformatofReproducció del document publicat a: https://doi.org/10.1002/lno.12207
dc.relation.ispartofLimnology and Oceanography, 2022, vol. 67, num. 11, p. 2374-2388
dc.relation.urihttps://doi.org/10.1002/lno.12207
dc.rightscc by-nc-nd (c) Bertuzzo, Enrico et al., 2022
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.sourceArticles publicats en revistes (Biologia Evolutiva, Ecologia i Ciències Ambientals)
dc.subject.classificationEcologia fluvial
dc.subject.classificationCompostos orgànics
dc.subject.otherStream ecology
dc.subject.otherOrganic compounds
dc.titleRespiration regimes in rivers: Partitioning source-specific respiration from metabolism time series
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion

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