Controladores biometeorológicos da eficiência de uso de água em savanas sob diferentes sazonalidades climáticas
Savannas play a crucial role in global water and carbon cycles. For this reason, manystudies were initiated, dedicating special attention to the effects of biometeorological parameters on CO2 exchanges in these ecosystems. In this study, we evaluatedthebiometeorological impact on water use efficienc...
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| Formato: | Dissertação |
| Idioma: | pt_BR |
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Universidade Federal do Rio Grande do Norte
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| Endereço do item: | https://repositorio.ufrn.br/handle/123456789/53105 |
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| Resumo: | Savannas play a crucial role in global water and carbon cycles. For this reason, manystudies were initiated, dedicating special attention to the effects of biometeorological parameters on CO2 exchanges in these ecosystems. In this study, we evaluatedthebiometeorological impact on water use efficiency (WUE, Water Use Efficiency) intwo tropical savannas under different climatic seasonalities, using data frommicrometeorological towers equipped with the eddy covariance system, which weremade available by the global network of flux towers (FLUXNET). The sites considered are AU-DaS tropical savannas (Australia, ecological savannah) andSN- Dhr (Senegal, dry savannah) with data from 2008-2014 for AU-DaS and 2010-2013for SN-Dhr. The results indicated that the dry savannah (SN-Dhr) was more efficient than the wet savannah (AU-DaS) whose average annual WUE values were 2.0and1.88 gC kg H2O-1, respectively. This greater efficiency is probably associated withthe different responses of each savanna's gross primary productivity (GPP) andevapotranspiration (ET) in wet/dry conditions. SN-Dhr showed more excellent
resistance to drought than AU-DaS, given that in AU-DaS both the GPP variationandthe ET variation were strongly influenced by the extreme water deficit condition (DSI → 1.0). In SN-Dhr this same influence was considerably weaker. This findingis reflected in the analysis of WUE dynamics with biometeorological factors since WUEdid not show expressively (p-value < 0.05) with any of these parameters in SN-Dhr. On the other hand, WUE from AU-DaS is strongly influenced by GPP and moderatelyby Temperature (Ta). |
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