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Optimization of leaf morphology in relation to leaf water status: A theory.
Ding, Junyan; Johnson, Edward A; Martin, Yvonne E.
Afiliación
  • Ding J; Biogeoscience Institute University of Calgary Calgary Alberta Canada.
  • Johnson EA; Department of Biological Sciences University of Calgary Calgary Alberta Canada.
  • Martin YE; Lawrence Berkeley National Laboratory Berkeley CA USA.
Ecol Evol ; 10(3): 1510-1525, 2020 Feb.
Article en En | MEDLINE | ID: mdl-32076530
The leaf economic traits such as leaf area, maximum carbon assimilation rate, and venation are all correlated and related to water availability. Furthermore, leaves are often broad and large in humid areas and narrower in arid/semiarid and hot and cold areas. We use optimization theory to explain these patterns. We have created a constrained optimization leaf model linking leaf shape to vein structure that is integrated into coupled transpiration and carbon assimilation processes. The model maximizes net leaf carbon gain (NPPleaf) over the loss of xylem water potential. Modeled relations between leaf traits are consistent with empirically observed patterns. As the results of the leaf shape-venation relation, our model further predicts that a broadleaf has overall higher NPPleaf compared to a narrowleaf. In addition, a broadleaf has a lower stomatal resistance compared to a narrowleaf under the same level of constraint. With the same leaf area, a broadleaf will have, on average, larger conduits and lower total leaf xylem resistance and thus be more efficient in water transportation but less resistant to cavitation. By linking venation structure to leaf shape and using water potential as the constraint, our model provides a physical explanation for the general pattern of the covariance of leaf traits through the safety-efficiency trade-off of leaf hydraulic design.
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Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Ecol Evol Año: 2020 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Ecol Evol Año: 2020 Tipo del documento: Article