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Multiscale analysis of temporal variability of soil CO₂ production as influenced by weather and vegetation

VARGAS, RODRIGO ; DETTO, MATTEO ; BALDOCCHI, DENNIS D ; ALLEN, MICHAEL F

Global change biology, 2010-05, Vol.16 (5), p.1589-1605 [Periódico revisado por pares]

Oxford, UK: Oxford, UK : Blackwell Publishing Ltd

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  • Título:
    Multiscale analysis of temporal variability of soil CO₂ production as influenced by weather and vegetation
  • Autor: VARGAS, RODRIGO ; DETTO, MATTEO ; BALDOCCHI, DENNIS D ; ALLEN, MICHAEL F
  • Assuntos: Animal and plant ecology ; Animal, plant and microbial ecology ; Biological and medical sciences ; Carbon dioxide ; Climate change ; CO2 sensors ; CO₂ sensors ; Fundamental and applied biological sciences. Psychology ; General aspects ; Meteorology ; model performance ; rain pulse ; soil respiration ; Soil testing ; Spectrum analysis ; temperature independent ; time series analysis ; wavelet analysis ; wavelet coherence ; wireless sensors
  • É parte de: Global change biology, 2010-05, Vol.16 (5), p.1589-1605
  • Notas: http://dx.doi.org/10.1111/j.1365-2486.2009.02111.x
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  • Descrição: Ecosystem processes are influenced by weather and climatic perturbations at multiple temporal scales with a large range of amplitudes and phases. Technological advances of automated biometeorological measurements provide the opportunity to apply spectral methods on continuous time series to identify differences in amplitudes and phases and relationships with weather variation. Here we used wavelet coherence analysis to study the temporal covariance between soil CO₂ production and soil temperature, soil moisture, and photosynthetically active radiation (PAR). Continuous (hourly average) data were acquired over 2 years among three vegetation types in a semiarid mixed temperate forest. We showed that soil temperature and soil moisture influence soil CO₂ production differently at multiple periods (e.g. hours, days, weeks, months, years), especially after rain pulse events. Our results provide information about the periodicity of soil CO₂ production among vegetation types, and provide insights about processes controlling CO₂ production through the study of phase relationships between two time series (e.g. soil CO₂ production and PAR). We tested the performance of empirical models of soil CO₂ production using the continuous wavelet transform. These models, built around soil temperature and moisture, failed at multiple periods across the measured dates, suggesting that empirical models should include other factors that regulate soil CO₂ production at different temporal scales. Our results add a new dimension for the analysis of continuous time series of biometeorological measurements and model testing, which will prove useful for analysis of increasing sensor data obtained by environmental networks.
  • Editor: Oxford, UK: Oxford, UK : Blackwell Publishing Ltd
  • Idioma: Inglês
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  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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