Repositorio Institucional
Repositorio Institucional
CONICET Digital
  • Inicio
  • EXPLORAR
    • AUTORES
    • DISCIPLINAS
    • COMUNIDADES
  • Estadísticas
  • Novedades
    • Noticias
    • Boletines
  • Ayuda
    • General
    • Datos de investigación
  • Acerca de
    • CONICET Digital
    • Equipo
    • Red Federal
  • Contacto
JavaScript is disabled for your browser. Some features of this site may not work without it.
  • INFORMACIÓN GENERAL
  • RESUMEN
  • ESTADISTICAS
 
Artículo

Predicting Dissolved Organic Matter Lability and Carbon Accumulation in Temperate Freshwater Ecosystems

Bastidas Navarro, Marcela AlejandraIcon ; Schenone, LucaIcon ; Martyniuk, Nicolás AlejandroIcon ; Vega, Evelyn NathalieIcon ; Modenutti, Beatriz EstelaIcon ; Balseiro, Esteban GabrielIcon
Fecha de publicación: 08/2021
Editorial: Springer
Revista: Ecosystems
ISSN: 1432-9840
Idioma: Inglés
Tipo de recurso: Artículo publicado
Clasificación temática:
Ecología

Resumen

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 carbon (C) pool that has a key role in the global carbon cycle in lakes and oceans. The present study aims to model the factors driving bacterial C-consumption, thus predicting the potential residual carbon accumulation. We developed mechanistic models to represent bacterial C-consumption, considering the contribution of DOM quality and phosphorus (P) and nitrogen (N) concentrations in the total carbon pool. Based on 59 different environments, we established DOM components and nutrient concentration for deep lakes, shallow lakes, high-altitude lakes, and wetlands from North-Andean Patagonian glacial lake district (around 41°S). We applied Bayesian methods to estimate model parameters from laboratory C-lability experiments performed in 26 environments. We tested the statistically 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. The selected model showed that 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 statistically predictive accuracy, we showed that our model is very useful to anticipate C-accumulation due to changes in the inputs to water bodies.
Palabras clave: BAYESIAN , BROWNING , DISSOLVED ORGANIC MATTER , FORECASTING , MICROBIAL RESPIRATION , MODELING , PARAFAC
Ver el registro completo
 
Archivos asociados
Tamaño: 1.046Mb
Formato: PDF
.
Solicitar
Licencia
info:eu-repo/semantics/restrictedAccess Excepto donde se diga explícitamente, este item se publica bajo la siguiente descripción: Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Unported (CC BY-NC-SA 2.5)
Identificadores
URI: http://hdl.handle.net/11336/183372
URL: https://link.springer.com/article/10.1007/s10021-021-00682-0
DOI: http://dx.doi.org/10.1007/s10021-021-00682-0
Colecciones
Articulos(INIBIOMA)
Articulos de INST. DE INVEST.EN BIODIVERSIDAD Y MEDIOAMBIENTE
Citación
Bastidas Navarro, Marcela Alejandra; Schenone, Luca; Martyniuk, Nicolás Alejandro; Vega, Evelyn Nathalie; Modenutti, Beatriz Estela; et al.; Predicting Dissolved Organic Matter Lability and Carbon Accumulation in Temperate Freshwater Ecosystems; Springer; Ecosystems; 25; 4; 8-2021; 795-811
Compartir
Altmétricas
 

Enviar por e-mail
Separar cada destinatario (hasta 5) con punto y coma.
  • Facebook
  • X Conicet Digital
  • Instagram
  • YouTube
  • Sound Cloud
  • LinkedIn

Los contenidos del CONICET están licenciados bajo Creative Commons Reconocimiento 2.5 Argentina License

https://www.conicet.gov.ar/ - CONICET

Inicio

Explorar

  • Autores
  • Disciplinas
  • Comunidades

Estadísticas

Novedades

  • Noticias
  • Boletines

Ayuda

Acerca de

  • CONICET Digital
  • Equipo
  • Red Federal

Contacto

Godoy Cruz 2290 (C1425FQB) CABA – República Argentina – Tel: +5411 4899-5400 repositorio@conicet.gov.ar
TÉRMINOS Y CONDICIONES