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Towards a more flexible representation of water stress effects in the nonlinear Jarvis model 被引量:2
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作者 YU Lian-yu CAI Huan-jie +2 位作者 ZHENG Zhe LI Zhi-jun WANG Jian 《Journal of Integrative Agriculture》 SCIE CAS CSCD 2017年第1期210-220,共11页
To better interpret summer maize stomatal conductance (gs) variation under conditions of changing water status at different growth stages, three water stress indicators, soil water content (SWC), leaf-air temperat... To better interpret summer maize stomatal conductance (gs) variation under conditions of changing water status at different growth stages, three water stress indicators, soil water content (SWC), leaf-air temperature difference (AT) and leaf level water stress index (CWSIL) were employed in Jarvis model, which were Js, JT and Jc models respectively. Measurements of gs were conducted in a summer maize field experiment during the year 2012-2013. In the insufficient irrigation exper- iment, three levels of irrigation amount were applied at four different growth stages of summer maize. We constructed three scenarios to evaluate the performance of the three water stress indicators for estimating maize gs in a modified Jarvis model. Results showed that JT and Jc models had better simulation accuracy than the Js model, especially at the late growth stage (Scenario 1) or considering the plant recovery compensation effects (Scenario 2). Scenario 3 indicated that the more environmental factors were adopted, the better prediction performance would be for Js model. While for JT model, two environmental factors (photosynthesis active radiation (PAR), and vapor pressure deficit (VPD)) seemed good enough to obtain a reliable simulation. When there were insufficient environmental data, CWSI, would be the best option. This study can be useful to understand the response of plant stomatal to changing water conditions and will further facilitate the application of the Jarvis model in various environments. 展开更多
关键词 summer maize stomatal conductance water status recovery compensation water stress indicators Jarvis model
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