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Cr10x

Manufactured by Campbell Scientific
Sourced in United States

The CR10X is a rugged, versatile, and reliable datalogger designed for a wide range of environmental and industrial measurement applications. It features a powerful 16-bit analog-to-digital converter, multiple input channels, and programmable control capabilities, making it suitable for a variety of data acquisition and control tasks.

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20 protocols using cr10x

1

Meteorological Measurements in Forest Ecosystem

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Global radiation (RG) was measured using a pyranometer (CMP6; Kipp & Zonen B.V., Delft, the Netherlands); air temperature and humidity were measured using a Vaisala sensor (HMP45C; Vaisala) at a height of 28.5 m. Rainfall was measured in a nearby open area using a tipping bucket rain gauge (Ikeda Keiki). All measurements were stored every 10 or 15 min on dataloggers (CR10X; Campbell Scientific Inc.). The vapour pressure deficit was calculated from air temperature and humidity by using R package “plantecophys” (Duursma, 2015 (link)).
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2

Tropical Climate Meteorological Experiment

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The experiment was carried out from April to August 2015 in Barretos city, São Paulo State, Brazil, located at 20º22'32.37" South latitude, 48º39'45. 68" West longitude, with an altitude of 507 m. According to the Köppen classification, the climate of the region is type Aw, rainy tropical, with rainfall concentration in the summer and relatively dry winter. A Campbell Scientific® meteorological mini-station was installed at 2 m height, approximately 300 m from the experiment site, being set up to perform readings every second and store the average of the data every 30 minutes by means of a datalogger (CR10X, Campbell Scientific, Logan, Utah, USA). During the period of conduction of the experiment, the mean maximum temperature was 25.5 ºC (18.3 -32.8 ºC), and the mean minimum temperature was 13.5 ºC (6.1 -20.9 ºC). The mean relative air humidity was 58.6% (17.3 -100%). The soil of the area was classified as Red-Yellow Latosol, according to criteria described in the Brazilian Soil Classification System (Embrapa, 2018) .
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3

Comprehensive Meteorological Monitoring Protocol

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Meteorological parameters such as air temperature, relative humidity, precipitation and photosynthetically active photon flux density (PPFD) were retrieved continuously from a meteorological station installed on a scaffold tower and stored half-hourly on a data logger (DL2e, Delta-T Devices Ltd., Cambridge, United Kingdom). Vapour pressure deficit (VPD) was calculated from half-hourly values of air temperature and relative humidity. Further meteorological data was retrieved from a meteorological station nearby1 (Instituto Português do Mar e da Atmosfera [IPMA], 1981–2010 ). Volumetric soil water content from four different depths (0.1, 0.2, 0.3, and 0.4 m) was measured continuously with EC-10 probes (Decagon Devices, Pullman, WA, United States) in four profiles and stored half-hourly on a data logger (CR10X and AM16/32 multiplexer, Campbell Scientific, Logan, UT, United States).
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4

Micrometeorological Tower Setup for Environmental Data Collection

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In the center of the experimental area a 3.0 m high micrometeorological tower was installed, which housed an automatic weather station, with sensors for measuring incident global solar radiation (Rg), air temperature (T) and relative humidity ( RH), rainfall and soil water moisture content (θ). These sensors were connected to a datalogger (CR10X, Campbell Scientific) and a multiplexer (AM416, Campbell Scientific), which performed readings every 10 seconds and recorded averages and totals every 10 minutes.
The vapor pressure deficit (DPV) was calculated by the difference in saturation pressure and actual water vapor pressure obtained from air temperature and relative humidity data, according to the Tetens (1930) methodology.
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5

Calculating Thermal Time Using Non-Linear Function

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Relative humidity was measured using a capacitive hygrometer (HMP35A Vaisala, Oy, Helsinki, Finland) and air temperature with copper-constantan thermocouples placed in a ventilated radiation shield at the center of the greenhouse. Photosynthetic photon flux density (PPFD) was also measured by means of PPFD sensors placed above each experimental bloc within the greenhouse. All data were stored in a datalogger (CR10X, Campbell Scientific Ltd.), with measurements taken every 30 s and an average calculated over 15 min. The data are summarized for each experiment in Supplementary Table S1.
Thermal time (TT) was calculated as the integral of a non-linear beta function of temperature (T) as proposed by Zaka et al. (2017 (link)):
f(T)=(T-TminTref-Tmin)q.(Tmax-TTmax-Tref)
TT=t0tmax[0,(Tref-Tbase).f(T)].dt
The equation has three parameters: the minimum (Tmin) and maximum (Tmax) temperatures at which development occurs and q, a shape parameter. In addition, Tref accounts for a fixed reference temperature (20°C) and Tbase (5°C) for a common base temperature used to scale time units from equivalent days at the reference temperature into degree days (°Cd). The parameters used for the different species were derived from the literature and are presented in Supplementary Table S2.
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6

Multivariate Microclimate Monitoring

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At each site, a datalogger (CR10X, Campbell Scientific, Utah) and sensors was used to record air temperature, relative humidity (Humitter 50Y, Vaisala, Finland), and photosynthetically active radiation (PPFD) (LI-190, Licor, Utah) every 15 minutes over 24 h prior to sample collection. Metadata was also collected for each sample tree, these included: GPS coordinates (WGS84 (G1762); degree minutes), elevation, tree height, and the basal diameter of the tree base at 10 cm off the ground. For each of the three branches collected per tree, height of the branch above ground and aspect (0–360°) were also recorded.
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7

Greenhouse Microclimate Monitoring and Vegetation Indices

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Air temperature in the greenhouse was measured with a ventilated aspirated psychrometer (model 1.1130, Thies Clima, Göttingen, Germany) and solar radiation with a pyranometer (model SKS 1110, Skye Instruments, Llandrindod Wells, Wales, UK). Both devices were placed in a shadow-free location of the greenhouse over the crop canopy. All data were recorded and stored using a data logger (CR10X, Campbell Scientific, Inc., Logan, UT, USA).
The photosynthetically active radiation (PAR) over the crop canopy was measured at the time of optical sensor measurements, using a linear quantum sensor (model LP-80, Decagon Devices, Inc., Pullman, WA, USA). Each PAR value consisted of the Sellers (1985) Green normalized difference vegetation index GNDVI NIR-Green NIR+Green Gitelson et al. (1996) Red ratio vegetation index RVI NIR Red Birth and McVey (1968) Green ratio vegetation index GVI NIR Green Birth and McVey (1968) 1 3
average of two measurements, taken at the beginning and at the end of optical sensor measurements each time. Measurements were made by placing the linear quantum sensor horizontally over a line of plants located in the center of each replicate plot per treatment.
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8

Infrared Imaging of Ice Dynamics in Picea abies Buds

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Ice nucleation, propagation, and supercooling within and around vegetative buds of P. abies were monitored with a digital infrared camera (T650SC, FLIR Systems, Danderyd, Sweden). This infrared camera has a thermal resolution of 0.2 mK. We used a close‐up lens (magnifying factor: 1.5×, working distance: 46 mm) to obtain a spatial resolution of 25 μm. Infrared images were recorded at an interval of 10 frames per second. Subsequent processing of the images by infrared differential thermal analysis (IDTA; Hacker & Neuner, 2008; Neuner & Kuprian, 2014) was conducted with FLIR ResearchIR Max (version 4.20.2.74, FLIR Systems). Image overlay was done with After Effects (Adobe Systems Inc., San Jose, USA).
A longitudinal section of the terminal part of a twig of P. abies, bearing three vegetative buds, was mounted on a small lift table by double‐sided adhesive tape. In the image field of the camera (16 mm × 12 mm), the three buds were arranged in a focal plane. Additionally, six thermocouples were mounted close to the buds. Thermocouple output was recorded every 10 s by a data logger (CR10X, Campbell Scientific).
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9

Soil CO2 Flux Measurement Protocol

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Soil CO2 concentration measurements were made during the growing season of 2009 using Vaisala CARBOCAP solid‐state CO2 sensors (model GMT 221, Vaisala, Helsinki, Finland) at depths of 10 and 5 cm and the Li‐8150 system (Li‐Cor, Lincoln, NE, USA) at 0 cm. At the same depths, soil temperature (averaging soil thermocouple probe TCAV; Campbell Scientific) and moisture (ML2x; Delta‐T Devices, Cambridge, UK) were measured, and incident photosynthetically active radiation (PAR) (BF2H; Delta‐T Devices) was measured above the canopy at 2 m height. Continuous recordings at 0.05 Hz were averaged and half‐hourly values recorded using an automated station (CR10X; Campbell Scientific). Values of soil CO2 concentration were corrected for temperature and pressure using the ideal gas law according to the manufacturer (Vaisala, Helsinki, Finland). Soil CO2 efflux at the soil surface was measured using an automated soil respiration system (Li‐8100 and Li‐8150; Li‐Cor, Lincoln, NE, USA) over measurement intervals of 2 min. The chambers were white to minimize heating. Possible pressure changes due to a Venturi effect are largely eliminated by the design of the vent used with the chamber [Xu et al., 2006].
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10

Microclimatic Data Collection for Agricultural Research

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Each site was equipped with a meteorological station. The station was supplied with a shielded air temperature and relative humidity sensor (HMP50, Vaisala, Helsinki, Finland), PAR sensors (Li 190 Campbell Scientific, Logan, UT, USA), pluviometer, and three soil temperature sensors placed at three soil depth (10, 20, and 30 cm). Data were continuously recorded hourly throughout the growing season of 2013 and 2014 (from 152 to 273 day of year) using datalogger (CR10X, Campbell Scientific, Logan, UT, USA) (Figure 2).
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