Plant hydraulic transport controls transpiration  sensitivity to soil water stress

Abstract. Plant transpiration downregulation in the presence of soil water stress is a critical mechanism for predicting global water, carbon, and energy cycles. Currently, many terrestrial biosphere models (TBMs) represent this mechanism with an empirical correction function (β) of soil moisture – a convenient approach that can produce large prediction uncertainties. To reduce this uncertainty, TBMs have increasingly incorporated physically based plant hydraulic models (PHMs). However, PHMs introduce additional parameter uncertainty and computational demands. Therefore, understanding why and when PHM and β predictions diverge would usefully inform model selection within TBMs. Here, we use a minimalist PHM to demonstrate that coupling the effects of soil water stress and atmospheric moisture demand leads to a spectrum of transpiration responses controlled by soil–plant hydraulic transport (conductance). Within this transport-limitation spectrum, β emerges as an end-member scenario of PHMs with infinite conductance, completely decoupling the effects of soil water stress and atmospheric moisture demand on transpiration. As a result, PHM and β transpiration predictions diverge most for soil–plant systems with low hydraulic conductance (transport-limited) that experience high variation in atmospheric moisture demand and have moderate soil moisture supply for plants. We test these minimalist model results by using a land surface model at an AmeriFlux site. At this transport-limited site, a PHM downregulation scheme outperforms the β scheme due to its sensitivity to variations in atmospheric moisture demand. Based on this observation, we develop a new “dynamic β” that varies with atmospheric moisture demand – an approach that overcomes existing biases within β schemes and has potential to simplify existing PHM parameterization and implementation.

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Plant Hydraulic Transport Controls Transpiration Response to Soil Water Stress

10.5194/hess-2020-671 ◽

2021 ◽

Author(s):

Brandon P. Sloan ◽

Sally E. Thompson ◽

Xue Feng

Keyword(s):

Soil Moisture ◽

Water Stress ◽

Soil Water ◽

Land Surface ◽

Correction Function ◽

Additional Parameter ◽

Hydraulic Transport ◽

Atmospheric Moisture ◽

Soil Water Stress ◽

Demand Variation

Abstract. Plant transpiration downregulation in the presence of soil water stress is a critical mechanism for predicting global water, carbon, and energy cycles. Currently, many terrestrial biosphere models (TBMs) represent this mechanism with an empirical correction function (β) of soil moisture – a convenient approach that can produce large prediction uncertainties. To reduce this uncertainty, TBMs have increasingly incorporated physically-based Plant Hydraulic Models (PHMs). However, PHMs introduce additional parameter uncertainty and computational demands. Therefore, understanding why and when PHM and β predictions diverge would usefully inform model selection within TBMs. Here, we use a minimalist PHM to demonstrate that coupling the effects of soil water stress and atmospheric moisture demand leads to a spectrum of transpiration response controlled by soil-plant hydraulic transport (conductance). Within this transport-limitation spectrum, β emerges as an end-member scenario of PHMs with infinite conductance, completely decoupling the effects of soil water stress and atmospheric moisture demand on transpiration. As a result, PHM and β transpiration predictions diverge most when conductance is low (transport-limited), atmospheric moisture demand variation is high, and soil moisture is moderately available to plants. We apply these minimalist model results to land surface modeling of an Ameriflux site. At this transport-limited site, a PHM downregulation scheme outperforms the β scheme due to its sensitivity to variations in atmospheric moisture demand. Based on this observation, we develop a new dynamic β that varies with atmospheric moisture demand – an approach that balances realism with parsimony and overcomes existing biases within β schemes.

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On the Treatment of Soil Water Stress in GCM Simulations of Vegetation Physiology

Frontiers in Environmental Science ◽

10.3389/fenvs.2021.689301 ◽

2021 ◽

Vol 9 ◽

Author(s):

P. L. Vidale ◽

G. Egea ◽

P. C. McGuire ◽

M. Todt ◽

W. Peters ◽

...

Keyword(s):

Soil Moisture ◽

Water Stress ◽

Stomatal Conductance ◽

Soil Water ◽

Land Surface ◽

Spatiotemporal Variability ◽

Climate Conditions ◽

Soil Water Stress ◽

Forest Meteorology ◽

Weather And Climate

Current land surface schemes in weather and climate models make use of the so-called coupled photosynthesis–stomatal conductance (A–gs) models of plant function to determine the surface fluxes that govern the terrestrial energy, water and carbon budgets. Plant physiology is controlled by many environmental factors, and a number of complex feedbacks are involved, but soil moisture control on root water uptake is primary, particularly in sub-tropical to temperate ecosystems. Land surface models represent plant water stress in different ways, but most implement a water stress factor, β, which ranges linearly (more recently also curvilinearly) between β = 1 for unstressed vegetation and β = 0 at the wilting point, expressed in terms of volumetric water content (θ). β is most commonly used to either limit A or gs, and hence carbon and water fluxes, and a pertinent research question is whether these treatments are in fact interchangeable. Following Egea et al. (Agricultural and Forest Meteorology, 2011, 151 (10), 1,370–1,384) and Verhoef et al. (Agricultural and Forest Meteorology, 2014, 191, 22–32), we have implemented new β treatments, reflecting higher levels of biophysical complexity in a state-of-the-art LSM, Joint UK Land Environment Simulator, by allowing root zone soil moisture to limit plant function non-linearly and via individual routes (carbon assimilation, stomatal conductance, or mesophyll conductance) as well as any (non-linear) combinations thereof. The treatment of β does matter to the prediction of water and carbon fluxes: this study demonstrates that it represents a key structural uncertainty in contemporary LSMs, in terms of predictions of gross primary productivity, energy fluxes and soil moisture evolution, both in terms of climate means and response to a number of European droughts, including the 2003 heat wave. Treatments allowing ß to act on vegetation fluxes via stomatal and mesophyll routes are able to simulate the spatiotemporal variability in water use efficiency with higher fidelity during the growing season; they also support a broader range of ecosystem responses, e.g., those observed in regions that are radiation limited or water limited. We conclude that current practice in weather and climate modelling is inconsistent, as well as too simplistic, failing to credibly simulate vegetation response to soil water stress across the typical range of variability that is encountered for current European weather and climate conditions, including extremes of land surface temperature and soil moisture drought. A generalized approach performs better in current climate conditions and promises to be, based on responses to recently observed extremes, more trustworthy for predicting the impacts of climate change.

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Simulating Gross Primary Productivity of vegetation under soil water stress using in-situ and reanalysis soil moisture data inputs

10.5194/egusphere-egu2020-21397 ◽

2020 ◽

Author(s):

Timothy Lam ◽

Amos P. K. Tai

Keyword(s):

Soil Moisture ◽

Water Stress ◽

Soil Water ◽

Primary Productivity ◽

Gross Primary Productivity ◽

Efficiency Coefficient ◽

Community Land Model ◽

Soil Water Stress ◽

Soil Moisture Data

This study utilises in-situ and reanalysis soil moisture data inputs from various sources to evaluate the effect of soil water stress on Gross Primary Productivity (GPP) of different Plant Functional Types (PFTs) using Terrestrial Ecosystem Model in R (TEMIR), which is under development by Tai Group of Atmosphere-Biosphere Interactions (Tai et al. in prep.). An empirical soil water stress function with reference to Community Land Model (CLM) Version 4.5 is employed to quantify water stress experienced by vegetation which hinders stomatal conductance and thus carboxylation rate. The model results are compared against observations at FLUXNET sites in semi-arid regions across the globe at daily timescale where in-situ GPP data is available and water stress inhibits plant functions to some extent. By dividing the soil into two layers (topsoil and root zone), GPP simulation improves significantly comparing with using single layer bulk soil (Modified Nash-Sutcliffe Model Efficiency Coefficient N increases from -0.686 to -0.586). Such upgrade is particularly substantial for vegetation with shallow roots such as grass PFTs. Despite this improvement, the model is characterised by an overall overestimation of GPP when water stress occurs, and inconsistency of accuracy subject to PFTs and degree of water stress experienced. This study informs responses of various PFTs to soil water stress, capacity of TEMIR in simulating the responses, and possible drawbacks of empirical soil water stress functions, and highlights the importance of topsoil moisture data input for vegetation drought monitoring.Keywords: Soil water stress, Terrestrial model representation, Photosynthesis, In-situ data, Reanalysis data, FLUXNET

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Effect of Irrigation and Soil Water Stress on Densities of Macrophomina phaseolina in Soil and Roots of Two Soybean Cultivars

Plant Disease ◽

10.1094/pdis.2000.84.8.895 ◽

2000 ◽

Vol 84 (8) ◽

pp. 895-900 ◽

Cited By ~ 42

Author(s):

S. R. Kendig ◽

J. C. Rupe ◽

H. D. Scott

Keyword(s):

Soil Moisture ◽

Water Stress ◽

Soil Water ◽

Growth Stage ◽

Root Colonization ◽

Growing Season ◽

Moisture Stress ◽

Macrophomina Phaseolina ◽

Soil Moisture Stress ◽

Soil Water Stress

The effects of irrigation and soil water stress on Macrophomina phaseolina microsclerotial (MS) densities in the soil and roots of soybean were studied in 1988, 1989, and 1990. Soybean cvs. Davis and Lloyd received irrigation until flowering (TAR2), after flowering (IAR2), full season (FSI), or not at all (NI). Soil water matric potentials at 15- and 30-cm depths were recorded throughout the growing season and used to schedule irrigation. Soil MS densities were determined at the beginning of each season. Root MS densities were determined periodically throughout the growing season. Microsclerotia were present in the roots of irrigated as well as nonirrigated soybean within 6 weeks after planting. By vegetative growth stage V13, these densities reached relatively stable levels in the NI and FSI treatments (2.23 to 2.35 and 1.35 to 1.63 log [microsclerotia per gram of dry root], respectively) through reproductive growth stage R6. After R6, irrigation was discontinued and root densities of microsclerotia increased in all treatments. Initiation (IAR2) or termination (TAR2) of irrigation at R2 resulted in significant changes in root MS densities, with densities reaching levels intermediate between those of FSI and NI treatments. Year to year differences in root colonization reflected differences in soil moisture due to rainfall. The rate of root colonization in response to soil moisture stress decreased with plant age. Root colonization was significantly greater in Davis than Lloyd at R5 and R8. This was reflected in a trend toward higher soil densities of M. phaseolina at planting in plots planted with Davis than in plots planted with Lloyd. Although no charcoal rot symptoms in the plant were observed in this study, these results indicated that water management can limit, but not prevent, colonization of soybean by M. phaseolina, that cultivars differ in colonization, and that these differences may affect soil densities of the fungus.

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Assessment of the JULES model surface soil moisture using in-situ observations over the Brazilian North East semiarid region

10.5194/egusphere-egu2020-2373 ◽

2020 ◽

Author(s):

Marcelo Zeri ◽

Karina Williams ◽

Eleanor Blyth ◽

Ana Paula Cunha ◽

Toby Marthews ◽

...

Keyword(s):

Soil Moisture ◽

Soil Water ◽

Land Surface ◽

Semiarid Region ◽

Drought Indices ◽

Surface Model ◽

Spatial And Temporal Variability ◽

Drought Risk ◽

Rainfed Agriculture ◽

North East

Monitoring of soil water is essential to assess drought risk over rainfed agriculture. Soil water indicates the onset or progress of dry spells, the start of the rainy season and good periods for sowing or harvesting. Monitoring soil water over rainfed agriculture can be a valuable tool to support field activities and the knowledge of climate risks.A network of soil moisture sensors was established over the Brazilian North East semiarid region in 2015 with measurements at 10 and 20 cm, together with rainfall and other variables in a subset of locations. The data are currently being used to assess the available water over the region in monthly bulletins and reports of potential impacts on yields.In this work, we present a comparison of a dataset of observations from 2015 to 2019 with the soil water estimated by the JULES land surface model (the Joint UK Land Environment Simulator). Overall, the model captures the spatial and temporal variability observed in the measured data well, with an average correlation coefficient of 0.6 across the domain. The performance was compared for each station, resulting in a selection of locations with significant correlation.Based on the regression results, we derive modelled soil moisture for the time span of the JULES run (1979 to 2016). The modeled data enabled the calculation of a standardized soil moisture anomaly (SSMA). The values of SSMA in the period were in agreement with the patterns of drought in the region, especially the recent long-term drought in the Brazilian semiarid region, with significant dry years in 2012, 2013 and 2015. Further analysis will focus on comparisons with other drought indices and measures of impacts on yields at the municipality level.

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Four decades of soil water stress history together with host genotype constrain the response of the wheat microbiome to soil moisture

FEMS Microbiology Ecology ◽

10.1093/femsec/fiaa098 ◽

2020 ◽

Vol 96 (7) ◽

Cited By ~ 3

Author(s):

Hamed Azarbad ◽

Julien Tremblay ◽

Charlotte Giard-Laliberté ◽

Luke D Bainard ◽

Etienne Yergeau

Keyword(s):

Soil Moisture ◽

Water Stress ◽

Soil Water ◽

Its Region ◽

Rrna Gene ◽

Short Term ◽

Host Genotype ◽

Stress History ◽

Wheat Field ◽

Soil Water Stress

ABSTRACT There is little understanding about how soil water stress history and host genotype influence the response of wheat-associated microbiome under short-term decreases in soil moisture. To address this, we investigated how plant breeding history (four wheat genotypes; two with recognized drought resistance and two without) and soil water stress history (same wheat field soil from Saskatchewan with contrasting long-term irrigation) independently or interactively influenced the response of the rhizosphere, root and leaf bacterial and fungal microbiota to short-term decreases in soil water content (SWC). We used amplicon sequencing (16S rRNA gene for bacteria and ITS region for fungi) to characterize the wheat microbiome. Fungal and bacterial communities responses to short-term decreases in SWC were mainly constrained by soil water stress history, with some smaller, but significant influence of plant genotype. One exception was the leaf-associated fungal communities, for which the largest constraint was genotype, resulting in a clear differentiation of the communities based on the genotype's sensitivity to water stress. Our results clearly indicate that soil legacy does not only affect the response to water stress of the microbes inhabiting the soil, but also of the microorganisms more closely associated with the plant tissues, and even of the plant itself.

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Impacts of the Soil Water Transfer Parameterization on the Simulation of Evapotranspiration over a 14-Year Mediterranean Crop Succession

Journal of Hydrometeorology ◽

10.1175/jhm-d-17-0058.1 ◽

2018 ◽

Vol 19 (1) ◽

pp. 3-25 ◽

Cited By ~ 6

Author(s):

S. Garrigues ◽

A. Boone ◽

B. Decharme ◽

A. Olioso ◽

C. Albergel ◽

...

Keyword(s):

Soil Moisture ◽

Soil Water ◽

Land Surface ◽

Large Scale ◽

Field Capacity ◽

Water Transfer ◽

Soil Parameters ◽

Surface Model ◽

Crop Succession

Abstract This paper presents a comparison of two water transfer schemes implemented in land surface models: a three-layer bulk reservoir model based on the force–restore scheme (FR) and a multilayer soil diffusion scheme (DIF) relying on explicit mass-diffusive equations and a root profile. The performances of each model at simulating evapotranspiration (ET) over a 14-yr Mediterranean crop succession are compared when the standard pedotransfer estimates versus the in situ values of the soil parameters are used. The Interactions between Soil, Biosphere, and Atmosphere (ISBA) generic land surface model is employed. When the pedotransfer estimates of the soil parameters are used, the best performance scores are obtained with DIF. DIF provides more accurate simulations of soil evaporation and gravitational drainage. It is less sensitive to errors in the soil parameters compared to FR, which is strongly driven by the soil moisture at field capacity. When the in situ soil parameters are used, the performance of the FR simulations surpasses those of DIF. The use of the proper maximum available water content for the plant removes the bias in ET and soil moisture over the crop cycle with FR, while soil water stress is simulated too early and the transpiration is underestimated with DIF. Increasing the values of the root extinction coefficient and the proportion of homogeneous root distribution slightly improves the DIF performance scores. Spatiotemporal uncertainties in the soil parameters generate smaller uncertainties in ET simulated with DIF compared to FR, which highlights the robustness of DIF for large-scale applications.

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DETECTION AND CORRECTION OF MIDSEASON P DEFICIENCY IN IRRIGATED POTATOES

Canadian Journal of Plant Science ◽

10.4141/cjps88-064 ◽

1988 ◽

Vol 68 (2) ◽

pp. 523-534 ◽

Cited By ~ 7

Author(s):

D. C. MacKAY ◽

J. M. CAREFOOT ◽

T. ENTZ

Keyword(s):

Soil Moisture ◽

Water Stress ◽

Soil Water ◽

Field Experiments ◽

P Fertilization ◽

P Deficiency ◽

Leaf Analysis ◽

Moisture Management ◽

Soil Water Stress ◽

Leaf P

Three experiments were performed in an automatic rainshelter and two in the field to determine the role of soil moisture management and phosphorus (P) fertilization in controlling P nutrition of potatoes (Solanum tuberosum L. ’Russet Burbank’). The rainshelter experiments indicated that permitting the upper layer (25 cm) of soil to remain dry during the early part of the growing season depressed the total P concentrations in the leaf blades at the 10% bloom stage to well below the sufficiency range of 0.45 – 0.50%, in spite of high P application rates at planting. Relieving stress at 10% bloom and maintaining soil water potential between −60 and −20 kPa until harvest significantly increased P concentrations. Tuber yields were only slightly less than on those soils without water stress throughout the growing period, provided ample P had been applied. By delaying stress relief in the upper soil layer for 3 wk, 6 wk, or until maturity, tuber yields were reduced 28, 47 and 49% respectively. Without P fertilization of this P-deficient soil at planting, leaf-P levels at 10% bloom were very low (0.26%), but application of P at this stage (banded, broadcast, or in solution) increased leaf-P concentrations and yields were similar to treatments receiving P at planting. Trimetaphosphate was particularly effective in increasing P concentrations in the leaves. In the two field experiments, tuber yields were high on all plots and treatment differences were small, even though leaf-P concentrations were relatively low. However, in the highest-yielding treatment (banded at planting) leaf-P levels averaged from 0.40 to 0.49% which is close to that considered as a sufficiency range (0.45 – 0.50), reported previously. From the practical standpoint, leaf analysis at the early bloom stage can be used to detect P deficiency, which may be caused by inadequate P fertilization or early season soil water stress. If soil and fertilizer P are insufficient, immediate application of fertilizer P will correct deficiencies and enhance yields if adequate soil water is also provided. Soil moisture stress from early bloom to near maturity should be avoided with this crop to obtain efficient use of applied P and maximum yields of tubers.Key words: Leaf analysis, P fertilizers, trimetaphosphate, soil water stress, automated rainshelter.

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Impacts of Enhanced Soil Water and Heat Dynamics on Ecosystem Functioning

10.5194/egusphere-egu2020-13774 ◽

2020 ◽

Author(s):

Zhongbo Su ◽

Lianyu Yu ◽

Yunfei Wang ◽

Yijian Zeng

Keyword(s):

Soil Moisture ◽

Soil Water ◽

Land Surface ◽

Ecosystem Functioning ◽

Biogeochemical Model ◽

Surface Model ◽

Strong Impact ◽

Tight Coupling ◽

Frozen Ground ◽

Thermal Dynamics

In the current Earth System Model (ESM), the soil water and heat transport in the land surface model (LSM) is not strongly coupled. As such, the discrepancy between the modelled land surface states and fluxes and the observed ones was mainly remedied by revising relevant simplified parameters, while the detailed physics (and/or physiography) was not necessarily consistent. While zooming in those studies over the cold region, the current ESMs do not consider the hydro-permafrost-carbon coupling. For example, the strong impact of soil moisture on spatial patterns of soil carbon stocks has been observed at sites, while the current ESMs cannot show this impact. On the other hand, soil moisture can affect the temperature sensitivity of decomposition rate and alter soil thermal dynamics significantly. To address the foregoing issues, it calls for an interdisciplinary approach to investigate soil-water-energy-plant interactions. Such approach is even more so desired for cold regions, where permafrost and seasonal frozen ground widely spread. This pressing need is mainly due to the carbon release from climate-induced permafrost thawing into the atmosphere, called as permafrost carbon feedback (PCF). It is also due to the tight coupling between hydrological processes and carbon dynamics, which, if ignored, will lead to the underestimation of global carbon turnover time by 36%. As a trial, this research coupled the detailed soil water and heat model with the biogeochemical model to investigate the mechanisms behind the impacts of enhanced soil water and heat dynamics on ecosystem functioning.

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Towards long-term satellite root-zone soil moisture: 40-year Soil Water Index dataset from ESA CCI COMBINED Soil Moisture product.

10.5194/egusphere-egu2020-15066 ◽

2020 ◽

Author(s):

Adam Pasik ◽

Bernhard Bauer-Marschallinger ◽

Wolfgang Preimesberger ◽

Tracy Scanlon ◽

Wouter Dorigo ◽

...

Keyword(s):

Soil Moisture ◽

Soil Water ◽

Land Surface ◽

Root Zone ◽

Land Surface Model ◽

Surface Model ◽

Water Index ◽

Global Coverage ◽

T Values

Multiple satellite-based global surface soil moisture (SSM) datasets are presently available, these however, address exclusively the top layer of the soil (0-5cm). Meanwhile, root-zone soil moisture cannot be directly quantified with remote sensing but can be estimated from SSM using a land surface model. Alternatively, soil water index (SWI; calculated from SSM as a function of time needed for infiltration) can be used as a simple approximation of root-zone conditions. SWI is a proxy for deeper layers of the soil profile which control evapotranspiration, and is hence especially important for studying hydrological processes over vegetation-covered areas and meteorological modelling.&#160; Here we present the first long-term SWI dataset from ESA CCI Soil Moisture v04.5 COMBINED product, covering a 40-year period between 1978 and 2018. The ESA CCI dataset is unique because of its long-term global coverage based on merged observations from both active and passive sensors. The SWI is calculated for eight T-values (1, 5, 10, 15, 20, 40, 60, 100), where T-value is a temporal length ruling the infiltration; depending on the soil characteristics it translates into different soil depths. Primary results show promise for pursuing development of an operational SWI product. Here, we present the results of SWI validation against data from the International Soil Moisture Network (ISMN) using the QA4SM framework, as well as results of the attempt to establish relationship between T-values and particular soil depths.

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