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Impact of water scarcity on spruce and beech forests
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作者 Lenka Krupkova Katerina Havrankova +2 位作者 jan krejza Pavel Sedlak Michal V.Marek 《Journal of Forestry Research》 SCIE CAS CSCD 2019年第3期899-909,共11页
One of the greatest threats posed by ongoing climate change may be regarded the drought caused by changes in precipitation distribution. The aim of presented study was to characterize reactions to dry conditions and c... One of the greatest threats posed by ongoing climate change may be regarded the drought caused by changes in precipitation distribution. The aim of presented study was to characterize reactions to dry conditions and conditions without drought stress on gross primary production (GPP) and net ecosystem production (NEP) of spruce and beech forests, as these two species dominate within the European continent. Daily courses of GPP and NEP of these two species were evaluated in relation to an expected decrease in CO2 uptake during dry days. The occurrence of CO2 uptake hysteresis in daily production was also investigated. Our study was performed at Bily Kriz(spruce) and Stitna(beech) mountain forest sites during 2010–2012 period. We applied eddy covariance technique for the estimation of carbon fluxes, vapor pressure deficit and precipitation characteristics together with the SoilClim model for the determination of drought conditions, and the inverse of the Penman–Monteith equation to compute canopy conductance. Significant differences were found in response to reduced water supply for both species. Spruce reacts by closing its stomata before noon and maintaining a reduced photosynthetic activity for the rest of the day, while beech keeps its stomata open as long as possible and slightly reduces photosynthetic activity evenly throughout the entire day. In the spruce forest, we found substantial hysteresis in the light response curve of GPP. In the beech forest, the shape of this curve was different: evening values exceeded morning values. 展开更多
关键词 PICEA ABIES Fagus sylvatica DROUGHT stress Hysteresis EDDY COVARIANCE
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