{"id":"RDIUNCO_775f9978493351c43bc72eb8ff8cde3c","dc:title":"Predicting dissolved organic matter lability and carbon accumulation in temperate freshwater ecosystems","dc:creator":"Modenutti, Beatriz","dc:date":"2020","dc:description":["Dissolved organic matter (DOM) dynamics influence aquatic ecosystem metabolism with ecological and biogeochemical effects. During microbial degradation, certain DOM molecules accumulate in the environments constituting the residual refractory pool that has a key role in the global carbon cycle by sequestering carbon in lakes and oceans. The present study aims to model the factors driving bacterial C-consumption, and thus predicting the potential residual carbon accumulation. We developed mechanistic models to represent bacterial C-consumption, considering the contribution of DOM quality and P and N concentrations in the total carbon pool. Based on 82 different environments we establish DOM components and nutrient concentration for deep lakes, shallow lakes, high altitude lakes, low-order streams, and wetlands from North-Andean Patagonian glacial lake district (around 41\u00b0S). We applied Bayesian methods to estimate model parameters from laboratory C-lability experiments performed in 29 environments. We tested the predictive accuracy of our models with an external dataset consisting of C-lability experiments with natural lake water enriched with organic matter from different sources. We found a model that performed excellently in both, fit to training data and prediction to external experiments. Based on the selected model, an increase in P concentration stimulates C-consumption, and an increase in the proportion of DOM protein-like compounds reduces the amount of residual C. Based on the predictive accuracy, we demonstrated that our model is very useful to anticipate C accumulation due to changes in the inputs to water bodies."],"dc:format":["application\/ms-excel","application\/octet-stream","application\/vnd.openxmlformats-officedocument.spreadsheetml.sheet"],"dc:language":["eng"],"dc:type":"dataset","dc:subject":["Bayesian","PARAFAC","Microbial respiration","Dissolved organic matter","Modeling","Forcasting","Ciencias de la tierra y Medio ambiente"],"dc:coverage":["ARG"],"dc:rights":["info:eu-repo\/semantics\/openAccess","https:\/\/creativecommons.org\/licenses\/by-nc-sa\/2.5\/ar\/"],"dc:publisher":"Universidad Nacional del Comahue","dc:identifier":"https:\/\/repositoriosdigitales.mincyt.gob.ar\/vufind\/Record\/RDIUNCO_775f9978493351c43bc72eb8ff8cde3c"}