Estimating tree phenology from high frequency tree movement data
Estimating tree phenology from high frequency tree movement data
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DOI：
10.1016/j.agrformet.2018.08.020
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发表时间：
2018-12
影响因子：
6.2
通讯作者：
A. Gougherty;Stephen R. Keller;A. Kruger;C. Stylinski;A. Elmore;M. Fitzpatrick
中科院分区：
文献类型：
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作者：
A. Gougherty;Stephen R. Keller;A. Kruger;C. Stylinski;A. Elmore;M. Fitzpatrick
林木物候的变化是植物对气候变化最重要和最显著的反应之一。然而，以高时间频率系统地记录大范围内个体树木物候的变化往往是令人望而却步的劳动和资源密集型工作。在这里，我们提出了一种新的方法，使用加速度计来克服在野外测量高频树木物候的挑战。加速计是一种小型便携设备，可以安装在树上记录由于风的强迫而产生的运动。对加速计记录的树木移动数据进行时间序列分析可以得出树木质量的近似值。由于叶片出苗和落叶改变了地上树木的质量，这些物候事件预计可以从加速计数据中检测到。为了测试加速计可以多好地测量物候日期，我们在2016年生长季在不同地点的苦瓜杨树上部署了20个加速计，并评估了加速计得出的物候与公民科学家记录的物候目测结果的匹配程度。我们发现，加速计的测量结果符合理论上的预期，即树木质量的季节性变化与树叶物候有关；具体地说，树木质量在春季增加，在秋季下降。此外，我们发现由加速度计得出的物候与目测的出叶情况相吻合，首次观测到的盛叶日期与由加速度计得出的物候有很强的相关性(r= 0.82，p<； 0.01)。然而，来自加速计的叶片落叶估算值与目测结果没有显著相关性(r= 0.16，p= 0.69)。我们的工作表明，加速度计可以可靠地用于检测林木的春季物候，并有可能克服在野外以高空间和时间分辨率记录春季树木物候的一些挑战。
Shifts in forest tree phenology are one of the most important and conspicuous plant responses to climate variability. However, systematically documenting changes in phenology of individual trees across large areas at high temporal frequency is often prohibitively labor- and resource-intensive. Here we present a new method that uses accelerometers to overcome challenges of measuring high-frequency tree phenology in the field. Accelerometers are small, portable devices that can be attached to trees to record movement due to forcing by wind. Time series analyses of tree movement data recorded by accelerometers can yield an approximation of tree mass. Because leaf emergence and leaf drop alter aboveground tree mass, these phenological events are expected to be detectable from accelerometer data. To test how well accelerometers can be used to measure phenological dates, we deployed 20 accelerometers on balsam poplar (Populus balsamifera) trees across a variety of sites during the 2016 growing season and assessed how well phenology derived from accelerometers matched visual observation of phenology recorded by citizen scientists. We found that accelerometer measurements fit the theoretical expectation for the seasonal change in tree mass associated with leaf phenology; specifically, an increase in tree mass in the spring, and a decline in the autumn. Furthermore, we found that accelerometer-derived phenology matched visual observations for leaf emergence, with a strong correlation between the dates of first observed full leaves and accelerometer-derived phenology (r= 0.82,p< 0.01). Estimates of leaf drop from accelerometers and visual observations, however, were not significantly correlated (r= 0.16,p= 0.69). Our work shows that accelerometers can reliably be used to detect spring phenology of forest trees, and have the potential to overcome some of the challenges related to documenting spring tree phenology at high spatial and temporal resolution in the field.