Arboriculture & Urban Forestry 47(5): September 2021 the average position of the sensor was recorded (EM50G, METER Group Inc., Pullman, Washington, USA). The installation method and hardware have been extensively tested against other commercially available dendrometers and were found to be robust with no significant relationships between air tempera- ture, relative humidity (RH), VPD, wind speed, wind direction or wind gusts, and sensor output (Kendall’s coefficient 0.039, 0.003, −0.207, 0.095, −0.177, 0.047, respectively; all P < 0.001). While the single point of attachment could result in disturbance by animals, these would be easily detectable as distinct rapid changes in diameter unrelated to observed trends in the biology of the stem or the current ambi- ent environmental conditions and therefore could be easily identified and removed from the data. No such disturbances were detected. Furthermore, by making only a single penetration of the stem, offset from the column of vascular tissue influencing the water trans- port beneath the sensor, we feel this mounting system has some potential advantages over other multipoint attachment methods. Each potentiometer was inde- pendently calibrated at the time of installation, and output is considered linear over the very small annual change (< 3 mm). Each sensor’s initial voltage was related to the measured stem diameter at DBH, which allowed us to continuously calculate the stem radius. Local environmental conditions at the experimental site were monitored throughout the experiment using a digital weather station (ATMOS 41, METER Group Inc., Pullman, Washington, USA). This station mea- sures solar radiation, precipitation, air temperature, barometric pressure, vapor pressure, relative humid- ity, wind speed, wind direction, maximum wind gust, lightning strikes, lightning distance, and tilt. In addi- tion, soil moisture, soil temperature, and conductivity were measured in a single location at a depth of 10 cm, approximately 2.5 m from Spruce 2 and Cedar (TEROS 12, METER Group Inc., Pullman, Washing- ton, USA). All environmental, soil, and growth data were recorded as 5-minute averages with a single data logger (see above), and each hour these data were automatically uploaded to the Zentra Cloud (METER Group Inc., Pullman, Washington, USA). From here, the data were transferred to the Eco Sensor Network (ESN, Hise Scientific Instrumentation, Somers, New York, USA), where the data are publicly available in near-real time (https://ecosensornetwork.com). 217 To convert changes in stem radius to biomass, bio- mass increments, and rates of aboveground carbon sequestration, standard geometric relationships were assumed so that allometric biomass equations could be applied to the calculated DBH. White spruce above- ground biomass (kg) was calculated as 0.0777 × DBH2.4720 (Harding and Grigal 1985). No allometric equation specific to Cryptomeria japonica was found, so biomass was calculated as exp(−2.0336 + 2.2592 × ln[DBH]), a general equation for cedar and larch (Jenkins et al. 2003). Root mass for both species was conservatively estimated at 30% of the aboveground mass based on the results of white spruce total bio- mass harvest performed by Ker and van Raalte (1981). Carbon sequestration was calculated as the increment in dry mass accumulation, assuming the carbon content of woody biomass is 50% (Thomas and Martin 2012). By extension, CO2 culated based on the atomic ratio of one carbon atom to two oxygen atoms in each molecule of CO2 can then be cal- with atomic weights of 12 and 16 grams per mole (a total of 44 grams per mole of CO2 bon was multiplied by 3.67. ), thus the weight of car- Statistical Analysis R version 3.4.4 was used for all statistical analyses (R Development Core Team 2018). Due to occasional low battery levels, not every 5-minute interval was recorded during a 24-hour period. Days missing more than 25% of their data were removed. Growth Models Growing seasons for each tree were determined by using a piecewise regression, which iteratively searched for a breakpoint by minimizing the mean squared error of the segments (Crawley 2012). This was done separately for each spruce at the end of each season, and the cedar at the beginning and end of each sea- son. The beginning of the growing seasons for the spruces were determined by the day they reached the previous year’s maximum stem radius. These indi- vidual growth seasons were used for subsequent sta- tistical analysis. A zero-growth model (ZG)(Zweifel et al. 2016), where “growth” began when the current dendrometer exceeded the last maximum and ended at the first decreasing reading, determined periods of irreversible radial growth within the growing season. Since the ZG model is sensitive to any change in the dendrometer ©2021 International Society of Arboriculture
September 2021
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