DOI: 10.5061/dryad.msbcc2fx0
title: Analyzing coastal fog effects on carbon and water fluxes in a California agricultural system using approaches in biometeorology, remote sensing, and plant physiology

description: 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&lt;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.
description: <strong>Study area: </strong>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). <strong>General approach:</strong> 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. <strong>Remote sensing:</strong>  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.
 <strong>Biometeorology:</strong> 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 CO<sub>2</sub> and
 H<sub>2</sub>O. 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). <strong>Plant physiology:
 </strong>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 CO<sub>2</sub> and
 H<sub>2</sub>O vapor fluxes. We<i> </i>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
 CO<sub>2</sub> and H<sub>2</sub>O were recorded
 once per second over approximately 300 s (5 min) per sample. Change in
 concentration (mg m<sup>-3 </sup>s<sup>-1</sup>)
 of gases measured in the chamber were converted to a flux (μmol
 m<sup>-2</sup> canopy area
 s<sup>-1</sup>)<sup> </sup>(Patrick et al. 2007;
 Baguskas et al. 2018).<sup> </sup>To normalize canopy-level
 CO<sub>2</sub> and H<sub>2</sub>O 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
 CO<sub>2</sub> and H<sub>2</sub>O flux
 measurements. <strong>Irrigation & soil
 moisture: </strong>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).
description: 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.