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Linking canopy‐scale mesophyll conductance and phloem sugar δ(13)C using empirical and modelling approaches
Interpreting phloem carbohydrate or xylem tissue carbon isotopic composition as measures of water‐use efficiency or past tree productivity requires in‐depth knowledge of the factors altering the isotopic composition within the pathway from ambient air to phloem contents and tree ring. One of least u...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7986199/ https://www.ncbi.nlm.nih.gov/pubmed/33222199 http://dx.doi.org/10.1111/nph.17094 |
Sumario: | Interpreting phloem carbohydrate or xylem tissue carbon isotopic composition as measures of water‐use efficiency or past tree productivity requires in‐depth knowledge of the factors altering the isotopic composition within the pathway from ambient air to phloem contents and tree ring. One of least understood of these factors is mesophyll conductance (g (m)). We formulated a dynamic model describing the leaf photosynthetic pathway including seven alternative g (m) descriptions and a simple transport of sugars from foliage down the trunk. We parameterised the model for a boreal Scots pine stand and compared simulated g (m) responses with weather variations. We further compared the simulated δ(13)C of new photosynthates among the different g (m) descriptions and against measured phloem sugar δ(13)C. Simulated g (m) estimates of the seven descriptions varied according to weather conditions, resulting in varying estimates of phloem δ(13)C during cold/moist and warm/dry periods. The model succeeded in predicting a drought response and a postdrought release in phloem sugar δ(13)C indicating suitability of the model for inverse prediction of leaf processes from phloem isotopic composition. We suggest short‐interval phloem sampling during and after extreme weather conditions to distinguish between mesophyll conductance drivers for future model development. |
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