Seasonal variation in energy balance and canopy conductance for a tropical savanna ecosystem of south central Mato Grosso, Brazil
Seasonal variation in energy balance and canopy conductance for a tropical savanna ecosystem of south central Mato Grosso, Brazil
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DOI:
10.1002/2013jg002472
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发表时间:
2014-01
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影响因子:
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通讯作者:
T. Rodrigues;G. Vourlitis;F. Lobo;R. G. Oliveira;J. Nogueira
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文献类型:
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作者:
T. Rodrigues;G. Vourlitis;F. Lobo;R. G. Oliveira;J. Nogueira
Tropical savanna (locally known as cerrado) composes 24% of Brazil and is characterized by high climatic variation; however, patterns of energy exchange are poorly understood, especially for mixed grasslands (locally known as campo sujo). We used eddy covariance to measure latent (Le) and sensible (H) heat flux of a mixed grassland and linked meteorological and remote sensing data to determine the controls on these fluxes. We hypothesized that (1) seasonal variations in H and Le would be large due to variations in precipitation; (2) ecosystem phenology, estimated using the enhanced vegetation index (EVI), would be the best predictor of seasonal variation in Le; and (3) cerrado, transitional, and humid evergreen forests would have similar rates of average annual Le despite large seasonal variation in cerrado Le. Our data suggest that campo sujo exhibits large seasonal fluctuations in energy balance that are driven by rainfall and that responses to rainfall pulses are rapid and dynamic, especially during the dry season. Path analysis indicated that temporal variations in the EVI did not significantly affect Le or Gc, but this was because all three variables (EVI, Le, and Gc) responded similarly to temporal variations in surface water availability. Compared to other tropical ecosystems, wetter sites had higher rates of Le during the dry season but similar rates during the wet season when water was not limiting. Over annual time periods, average rates of Le increased significantly as average annual rainfall increased, due to dry‐season water limitations in the more seasonal tropical ecosystems.