Intra‐Specific Variability in Plant Hydraulic Parameters Inferred From Model Inversion of Sap Flux Data. Issue 6 (13th June 2022)

• Record Type: Journal Article
• Authors: Lu, Yaojie; Sloan, Brandon; Thompson, Sally E.; Konings, Alexandra G.; Bohrer, Gil; Matheny, Ashley; Feng, Xue
• Is Part Of: Journal of geophysical research. Volume 127:Issue 6(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-06-13
• Subjects: plant hydraulics -- xylem vulnerability -- model inversion -- MCMC -- sap flow; Geobiology -- Periodicals; Biogeochemistry -- Periodicals; Biotic communities -- Periodicals; Geophysics -- Periodicals; 577.14
• DOI: 10.1029/2021JG006777
• Languages: English
• ISSNs: 2169-8953

Abstract

Abstract: Understanding plant hydraulic regulation is critical for predicting plant and ecosystem responses to projected increases in drought stress. Plant hydraulic regulation is controlled by observable, diverse plant hydraulic traits that can vary as much across individuals of the same species as they do across different species. Direct measurements of plant hydraulic traits from a range of ecosystems remain limited in comparison to other, more readily measured traits (e.g., specific leaf area). Furthermore, plant hydraulic trait measurements, often made at leaf or branch levels, are not easily scaled to whole‐plant values that are typically used to predict plant and ecosystem fluxes. In this study, multiple whole‐plant hydraulic parameters are inferred from observations of plant water use (i.e., sap flow), soil properties, and meteorological data. We use a Markov Chain Monte Carlo model inversion approach to obtain the best estimates and uncertainty of plant hydraulic parameters that capture whole‐plant effective embolism resistance and stomatal sensitivity to decreasing plant water potential. We then use the inferred values in the model to estimate whole‐tree water use and isohydricity. This approach reliably infers whole‐plant parameter values with enough specificity to resolve inter‐ and intra‐specific differences, and thus supplements time‐ and labor‐intensive direct measurements of traits. Key Points: Plant hydraulic parameters are inferred with low uncertainty from sap flow data Inferred parameter values capture whole‐plant response and water use strategies instead of leaf or branch‐level responses The model inversion method complements field measurement of plant hydraulic traits