Quantifying the drivers of ecosystem fluxes and water potential across the soil-plant-atmosphere continuum in an arid woodland

Kannenberg, Steven A.; Barnes, Mallory L.; Bowling, David R.; Driscoll, Avery W.; Guo, Jessica S.; Anderegg, William R.L.

doi:10.1016/j.agrformet.2022.109269

Quantifying the drivers of ecosystem fluxes and water potential across the soil-plant-atmosphere continuum in an arid woodland

Journal Article · Tue Dec 06 00:00:00 EST 2022 · Agricultural and Forest Meteorology

DOI:https://doi.org/10.1016/j.agrformet.2022.109269· OSTI ID:1903195

^[1]; Barnes, Mallory L. ^[2]; Bowling, David R. ^[3]; Driscoll, Avery W. ^[4]; Guo, Jessica S. ^[5]; Anderegg, William R.L. ^[3]

Colorado State Univ., Fort Collins, CO (United States); Univ. of Utah, Salt Lake City, UT (United States); Colorado State University
Indiana Univ., Bloomington, IN (United States)
Univ. of Utah, Salt Lake City, UT (United States)
Univ. of Utah, Salt Lake City, UT (United States); Colorado State Univ., Fort Collins, CO (United States)
Univ. of Arizona, Tucson, AZ (United States)

Dryland ecosystems occupy a vast swath of the terrestrial land surface and exert a sizeable impact on the cycling of carbon and water globally. These biomes are characterized by tightly coupled carbon and water cycles that respond rapidly to transient pulses in water availability. However, there exist many mechanistic uncertainties regarding the environmental drivers of, and linkages between, plant and ecosystem processes. Thus, drylands are often poorly represented in many vegetation and land surface models. An enhanced understanding of dryland ecosystem function is limited by the lack of long-term, co-located, and frequent measurements of plant and ecosystem processes. At a piñon-juniper woodland in southeastern Utah, USA, we collected a continuous dataset of meteorological conditions, soil water potential from surface to bedrock, tree water potential, and ecosystem carbon and water fluxes from eddy covariance. We found that predawn and midday tree water potential and daily ecosystem fluxes were highly sensitive to fluctuations in soil water availability, particularly in shallower layers, and that daytime variability in atmospheric drivers only loosely controlled these processes. The strong connections between shallow soil water potential, tree water potential, and ecosystem fluxes occurred because of the dominant role of precipitation pulses in driving vegetation activity, as even small pulses of moisture stimulated shallow soil water potential, tree water potential, and evapotranspiration for between 1 and 2 weeks. Carbon fluxes (net ecosystem exchange and gross primary productivity) were sensitive to precipitation pulses for longer, up to 3 weeks. Our results highlight that improved monitoring and sensing of shallow soil moisture can greatly enhance our understanding of dryland ecosystem function. Here, a better mechanistic understanding of the impacts of precipitation pulses is also needed to improve vegetation modeling of dryland ecosystems.

View Accepted Manuscript (DOE)

Research Organization:: Univ. of Utah, Salt Lake City, UT (United States); University of Utah, Salt Lake City, UT (United States)

Sponsoring Organization:: US National Science Foundation (NSF); USDA National Institute of Food and Agriculture Agricultural and Food Research Initiative Competitive Programme Ecosystem Services and Agro‐Ecosystem Management; USDOE Office of Science (SC), Biological and Environmental Research (BER). Earth & Environmental Systems Science (EESS); USDOE Office of Science (SC), Biological and Environmental Research (BER). Earth and Environmental Systems Science Division

Grant/Contract Number:: SC0022052

OSTI ID:: 1903195

Alternate ID(s):: OSTI ID: 1991287

Journal Information:: Agricultural and Forest Meteorology, Journal Name: Agricultural and Forest Meteorology Vol. 329; ISSN 0168-1923

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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AmeriFlux AmeriFlux US-CdM Cedar Mesa Bowling, David; Kannenberg, Steve; Anderegg, William AmeriFlux; University of Utah https://doi.org/10.17190/amf/1865477	dataset	January 2022

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