Uncertainty in the representation of vegetation in Earth System Models is a major contributor to the intermodel spread in climate projections under global warming.
Empirical soil moisture stress parameterizations to model drought effects on photosynthesis have been identified as a major driver of this uncertainty, leading to a call to develop more mechanistic models that leverage the principles of soil and plant hydraulic theory.
The goal of this dissertation is to develop and install a simplified plant hydraulics representation within a major Earth System Model, compare its dynamics with a non-hydraulic model, and refine methods to use transient leaf water potential observations to infer vegetation water-use strategy.
Chapter 1 presents the full model description of Plant Hydraulic Stress (PHS), which we developed to implement plant hydraulics within the Community Land Model (CLM). PHS has since been adopted as the default representation of vegetation water use in version 5 of the CLM.
PHS updates vegetation water stress and root water uptake to better reflect plant hydraulic theory, advancing the physical basis of the modeled vegetation hydrodynamics. Point simulations of a tropical forest site (Caxiuanã, Brazil) under ambient conditions and partial precipitation exclusion highlight the differences between PHS and the previous CLM implementation. Model description and simulation results are contextualized with a list of benefits and limitations of the new model formulation, including hypotheses that were not testable in previous versions of the model. Key results include reductions in transpiration and soil moisture biases relative to a control model under both ambient and exclusion conditions, correcting excessive dry season soil moisture stress in the control model. The new model structure, which bases water stress on leaf water potential, could have significant implications for vegetation-climate feedbacks, including increased sensitivity of photosynthesis to atmospheric vapor pressure deficit.
Chapter 2 extends the analysis of PHS to the global scale. Historical simulations with and without plant hydraulics are compared to understand the influence on interannual soil moisture and photosynthesis dynamics.
The focus of this chapter is on analyzing model dynamics across the semi-arid tropics.
The PHS simulation yields longer soil moisture memory and increases interannual photosynthesis variability as compared to the non-hydraulic model.
With an analytical derivation and analyses of soil moisture dynamics, we demonstrate the importance of the root water uptake parameterization for soil moisture memory and carbon cycle variability.
Chapter 3 investigates methods to use transient leaf water potential observations to infer vegetation water-use strategy. We use a set of soil-plant-atmosphere models, ranging in complexity, to investigate the underlying meaning of three isohydricity metrics and identify potential classification errors.
The model-based approach allows us to derive analytical expressions for the three metrics and to more methodically sample both environmental space and trait space to generate idealized experiments to test the fidelity of the resulting water-use strategy classifications.
We consider two previously defined metrics, isohydricity slope and hydroscape area, in comparison to a third metric, relative isohydricity, defined herein.
We describe classification challenges resulting from trait coordination and environmental variability, suggest practical recommendations for metric retrieval, and discuss the value and limitations of isohydricity and the broader pursuit of response-based metrics of vegetation traits.
Our results indicate that the major limitations of the isohydricity slope and hydroscape area metrics can be corrected with the relative isohydricity methods described here.
| Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/d8-9cfn-nc45 |
| Date | January 2020 |
| Creators | Kennedy, Daniel Joseph |
| Source Sets | Columbia University |
| Language | English |
| Detected Language | English |
| Type | Theses |
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