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Analyzing coastal fog effects on carbon and water fluxes in a California agricultural system using approaches in biometeorology, remote sensing, and plant physiology


Baguskas, Sara; Oliphant, Andrew; Clemesha, Rachel; Loik, Michael (2021), Analyzing coastal fog effects on carbon and water fluxes in a California agricultural system using approaches in biometeorology, remote sensing, and plant physiology, Dryad, Dataset,


In coastal California, the peak growing season of economically important crops is concurrent with fog events, which buffer drought stress during the dry season. Coastal fog patterns are changing, so we quantified its effects on the energy, water, and carbon fluxes of an economically important cropland at multiple spatial and temporal scales. Our study site was a strawberry farm located in the fog-belt of the Salinas Valley, California. We used GOES-satellite total albedo to detect and quantify large scale patterns of coastal fog. We used eddy covariance (EC) to quantify actual evapotranspiration and gross primary productivity (GPP) at the field scale from July-September 2016. We measured canopy-scale strawberry physiology on foggy and non-foggy days within the measurement footprint of the EC tower. Downwelling longwave radiation (L↓), observed by a surface-mounted pyrgeometer, was consistently higher on foggy compared to clear-sky days (regardless of fog-drip), indicating that emission of longwave radiation was derived almost entirely from the cloud base. L↓ and total GOES albedo were positively and strongly correlated (R2=0.68, P<0.01). For both field- and canopy-levels, water-use and light-use efficiency increased by as much as 50% and 70%, respectively, during foggy compared to non-foggy conditions. The initial slope of the curvilinear relationship fit between GPP and photosynthetically active radiation was twice as steep during foggy (α=0.0395) than non-foggy (α=0.0210) conditions, suggesting that the scattering of light during fog events enhances photosynthetic output of whole-plants. Our results suggest that irrigation for these fields could be rescheduled during foggy periods without sacrificing plant productivity.


Study area: We conducted a field investigation in 2016 at a coastal, conventional strawberry farm located in the Salinas Valley, California. The farm was located approximately 1.5 km from the coastline near sea level (see Baguskas et al. 2018 for site map).

General approach: We measured crop response to micrometeorological conditions during the peak strawberry growing (May-September 2016) using a combination of approaches from the following fields of research: remote sensing, biometeorology, and plant physiology. We also measured irrigation output in several strawberry beds.

Remote sensing:  We used Geostationary Operational Environmental Satellite (GOES-WEST) 15 Imager measurements to identify and quantify cloudiness. As in our previous work (Baguskas et al., 2018), we used the visible, shortwave infrared (IR), longwave IR channels and an established algorithm (Clemesha et al. 2016) to identify the presence of low-level water clouds at 4 km resolution every 30 minutes over a 24 hour time period. The percent of time that low-level clouds were detected in the satellite data is referred to as the coastal low cloud and fog (CLCF) index and is summarized with monthly means for June – August 2016. Albedo is a measure of reflectivity, defined as the percent of reflected radiation to incident radiation. We used GOES total scene albedo measurements at the 4 km grid scale co-located with the study site every 30 minutes during daylight hours (0700 to 1830 h) to quantify sky conditions. If cloud cover and/or cloud optical thickness increases within a pixel, the value of albedo increases in that pixel.

Biometeorology: We deployed a micrometeorological station in the strawberry farm between June 10 and October 3, 2016, including eddy covariance (EC) instruments to measure trace gas fluxes of CO2 and H2O. The location of the station was selected to ensure reasonable fetch of homogeneous strawberry fields during the prevailing onshore air flows ranging from SW to NW. The eddy covariance system was comprised of a 3-dimensional sonic anemometer-thermometer (CSAT3, Campbell Sci., Logan, Utah, USA) and an open path infrared gas analyser (Li-7500, LiCor Inc., Lincoln Nebraska, USA), which were deployed at 3.0 m above ground level. These instruments were sampled at 10 Hz by a CR1000 data logger (Campbell Sci., Logan, Utah, USA) and stored on a flash memory card. The major components of the surface radiation budget were measured using a four-component radiometer (CNR1, Kipp&Zonen, Delft, The Netherland) deployed at 0.5 m above the strawberry canopy. Air temperature and relative humidity were measured at 3.0 m using a HMP45C probe (Vaisala Corp., Helsinki, Finland) and soil heat flux was determined using three heat flux plates (HF01, Hukseflux, Delft, The Netherlands) installed at 6 cm with soil temperature in the layer above measured by 3 sets of spatial averaging thermocouples. Eddy covariance fluxes were calculated from 30-minute covariance blocks, after removal of spikes in the high frequency data. From these, mass and energy fluxes were calculated, corrected for density fluctuations (WPL corrections), and planar-fit coordinate rotations were applied (Lee et al. 2004). The distribution of the flux source area in the upwind direction was calculated for each 30-minute period using the analytical footprint model of Hsieh (2000).

Plant physiology: We evaluated the physiology of strawberry plants at the canopy scale to foggy and non-foggy conditions within the footprint of the EC-tower by measuring CO2 and H2O vapor fluxes. We used an open-path infrared gas analyzer (IRGA; Model LI-7500A, LI-COR) placed in an infrared-transparent Tefzel® chamber (DuPont, Wilmington, DE; 0.75 m wide × 0.75 m long × 0.75 m tall) over four plant canopies per flux measurement, as described in our previous work (Baguskas et al. 2018). We haphazardly collected approximately 10 canopy flux measurements per day between 0900 –1300 h from mid-June to late-August. The concentration of CO2 and H2O were recorded once per second over approximately 300 s (5 min) per sample. Change in concentration (mg m-3 s-1) of gases measured in the chamber were converted to a flux (μmol m-2 canopy area s-1) (Patrick et al. 2007; Baguskas et al. 2018). To normalize canopy-level CO2 and H2O flux measurements by canopy area, we measured ground area per sample from a digital photograph of the four plant canopies at 1 m overhead, which was converted to a binary image from which fractional green canopy cover was calculated using the Canopeo App (Patrignani and Ochsner, 2015). We define canopy-level carbon uptake as Net Canopy Exchange (NCE), which is net ecosystem exchange with the soil component reduced due to the agronomic practice of covering strawberry soils with plastic. Likewise, soil evaporation and respiration were excluded from our canopy-level CO2 and H2O flux measurements.

Irrigation & soil moisture: Strawberry plants were planted in parallel rows on top of field beds. Each strawberry bed (52 cm wide and 30 cm tall) was planted with two rows of strawberry plants that were spaced 30 cm apart. A layer of dark gray-colored plastic mulch was used to cover the soil surface per local agricultural practices. Two drip irrigation tapes were placed in each bed beneath the plastic mulch close to the strawberry plants, and were used to water the crop during the entire growing season. Each irrigation event usually occurred between 0830 and 1030 h, and was applied at 9 psi for ~1.5 hours. We measured irrigation flow rates by installing a flowmeter (Badger Flow Meter, Meter Group Inc., Pullman, WA) in four beds where we sampled, and soil moisture sensors (EC5, Meter Group Inc., Pullman, WA) at three depths (5, 10, 20 cm).

Usage Notes

Datafile 'Eddy-Covariance-with-GOESalbedo-Data' is the eddy covariance data with the GOES-derived albedo values at our study site. Combining these datasets is more useful for generating relationships between field and satellite observations.

Datafile 'Plant-Canopy-Data' is the CO2 and water vapor fluxes at the plant-canopy scale. These instantaneous measurements were made within the footprint of the eddy flux tower.

Datafile 'Irrigation-Soilmoisture-Data' is irrigation flow rates and soil moisture at multiple depths.


U.S. Department of Agriculture, Award: 2015-67012-22769: NIFA Postdoctoral Fellowship