Dependence of functional traits related to growth rates and their CO 2 response on multiple habitat climate factors across Arabidopsis thaliana populations

• Published in: Journal of plant research 2018-11, Vol.131 (6), p.987
• Main Authors: Ozaki, Hiroshi, Oguchi, Riichi, Hikosaka, Kouki
• Format: Article
• Language: English
• Subjects: Adaptation, Physiological; Altitude; Arabidopsis - growth & development; Arabidopsis - physiology; Carbon Dioxide - metabolism; Climate; Climate Change; Ecosystem; Humidity; Photosynthesis - physiology; Plant Stomata - physiology; Plant Transpiration
• ISSN: 1618-0860

The values of many plant traits are often different even within a species as a result of local adaptation. Here, we studied how multiple climate variables influence trait values in Arabidopsis thaliana grown under common conditions. We examined 9 climate variables and 29 traits related to vegetative growth rate in 44 global A. thaliana accessions grown at ambient or elevated CO concentration ([CO ]) and applied a multiple regression analysis. We found that genetic variations in the traits related to growth rates were associated with various climate variables. At ambient [CO ], plant size was positively correlated with precipitation in the original habitat. This may be a result of larger biomass investment in roots at the initial stage in plants adapting to a lower precipitation. Stomatal conductance and photosynthetic nitrogen use efficiency were negatively correlated with vapor pressure deficit, probably as a result of the trade-off between photosynthetic water- and nitrogen-use efficiency. These results suggest that precipitation and air humidity influence belowground and aboveground traits, respectively. Elevated [CO ] altered climate dependences in some of the studied traits. The CO response of relative growth rate was negatively correlated with altitude, indicating that plants inhabiting a higher altitude have less plasticity to changing [CO ]. These results are useful not only for understanding evolutionary process but also to predict the plant species that are favored under future global change.