Comparing Model Representations of Physiological Limits on Transpiration at a Semi‐Arid Ponderosa Pine Site. (12th November 2022)

• Record Type: Journal Article
• Authors: Hawkins, Linnia R.; Bassouni, Maoya; Anderegg, William R. L.; Venturas, Martin D.; Good, Stephen P.; Kwon, Hyojung J.; Hanson, Chad V.; Fiorella, Richard P.; Bowen, Gabriel J.; Still, Christopher J.
• Is Part Of: Journal of advances in modeling earth systems. Volume 14:Number 11(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-11-12
• Subjects: plant hydraulics -- ecosystem modeling -- stomatal function -- model evaluation -- ponderosa pine -- information theory; Geological modeling -- Periodicals; Climatology -- Periodicals; Geochemical modeling -- Periodicals; 551.5011
• DOI: 10.1029/2021MS002927
• Languages: English
• ISSNs: 1942-2466

Abstract

Abstract: Mechanistic representations of biogeochemical processes in ecosystem models are rapidly advancing, requiring advancements in model evaluation approaches. Here we quantify multiple aspects of model functional performance to evaluate improved process representations in ecosystem models. We compare semi‐empirical stomatal models with hydraulic constraints against more mechanistic representations of stomatal and hydraulic functioning at a semi‐arid pine site using a suite of metrics and analytical tools. We find that models generally perform similarly under unstressed conditions, but performance diverges under atmospheric and soil drought. The more empirical models better capture synergistic information flows between soil water potential and vapor pressure deficit to transpiration, while the more mechanistic models are overly deterministic. Although models can be parameterized to yield similar functional performance, alternate parameterizations could not overcome structural model constraints that underestimate the unique information contained in soil water potential about transpiration. Additionally, both multilayer canopy and big‐leaf models were unable to capture the magnitude of canopy temperature divergence from air temperature, and we demonstrate that errors in leaf temperature can propagate to considerable error in simulated transpiration. This study demonstrates the value of merging underutilized observational data streams with emerging analytical tools to characterize ecosystem function and discriminate among model process representations. Plain Language Summary: Earth system models are an essential tool for understanding the consequences of changing climate conditions on forest ecosystems. Models are rapidly incorporating more realistic representations of how drought impacts ecosystem carbon and water cycling. These advancements need to be thoroughly evaluated to ensure that the models adequately capture the plant functional response to drought stress. Here we merge underutilized measurements with new analytical tools to evaluate several model representations of plant response to drought. These tools allow us to both better understand relationships among drought stress and ecosystem response, as well as quantify model accuracy. We find that models generally perform similarly under unstressed conditions, but performance diverges under drought. Key Points: We evaluate several model formulations for coupling plant hydraulic and stomatal response using functional performance metrics Information flows from soil water potential and vapor pressure deficit to transpiration reflect structural differences among models Considerable biases in modeled canopy temperature propagate to a 5% offset in cumulative growing season transpiration