Ecosystem respiration of old and young irrigated citrus orchards in a semiarid climate

  • Bernardo Martin-Gorriz /
  • María M. González-Real /
  • Gregorio Egea /
  • Alain Baille
Journal ar
Agricultural and Forest Meteorology
  • Volumen: 280
  • Fecha: 15 enero 2020
  • ISSN: 01681923
  • Tipo de fuente: Revista
  • DOI: 10.1016/j.agrformet.2019.107787
  • Tipo de documento: Artículo
  • Editorial: Elsevier B.V.
© 2019 Elsevier B.V.Both biotic and abiotic factors are involved in the seasonal variability of ecosystem respiration (Re) and its aboveground (Rag) and belowground (Rs) components. Knowledge of these factors is crutial to predict the respiration processes of structurally-distinct orchards under varying environmental conditions. This paper aims to characterize those factors in and across adult (AO) and young (YO) drip-irrigated citrus orchards over a 2-year period. Two methods for estimating Re were used and compared. In the first one (C-method) Re was calculated as the sum of Rag and Rs components, with each being estimated using organ-specific and soil respiration models previously validated and calibrated from chamber-based respiration and biometric canopy measurements. The second method was based on the determination of nighttime Re from data of early morning Net Ecosystem Exchange (NEE-method) provided by eddy covariance sensors located above the canopy. Estimates of Re by the two methods compared reasonably well. The C-method indicated that Rs was the predominant component of Re in both orchards, with a main peak in early spring (ratio Rs/Re ~0.75 and 0.65 in AO and YO, respectively) during the period with no fruit load and minimum Rag. Data obtained with the NEE-method were used to test the performance of functional relationships between Re and abiotic factors (i.e., temperature through a Q10 function, and soil water content). It was found that a model only based on abiotic factors was unable to explain the differences in Re across sites; whereas accounting for canopy productivity and structure by introducing the leaf area index (LAI) as an additional driving variable notably increased the predictive power of the models in describing changes in Re, both seasonally and across sites. The study suggested that biotic factors explained a large part of the differences in Re between orchards, and that LAI could be an appropriate driving variable for predicting the impact of tree age and structural heterogeneity on Re.

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