The photochemical reflectance index provides an optical indicator of spring photosynthetic activation in evergreen conifers.
The photochemical reflectance index provides an optical indicator of spring photosynthetic activation in evergreen conifers.
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DOI：
10.1111/nph.13251
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发表时间：
2015-04
期刊：
影响因子：
--
通讯作者：
Christopher Y. S. Wong;J. Gamon
中科院分区：
文献类型：
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作者：
Christopher Y. S. Wong;J. Gamon
在常绿植物中，光合作用的季节性下调和重新激活在很大程度上是不可见的，难以用遥感进行评估。由于气候变化，这种看不见的物候可能正在发生变化。为了更好地了解这些隐藏的生理转变的机制和时间，我们探讨了几种测定和光学指标春季光合作用激活针叶树暴露于北方气候。光化学反射指数（PRI），叶绿素荧光，和万年青针叶树幼苗叶色素进行了监测超过1年的北方气候，除了在春季的气体交换。PRI，电子传递速率，色素水平，光利用效率和光合作用都表现出显着的季节变化，不同的动力学和强度的相关性，这是用来评估的机制和时间的春天激活。PRI和色素池密切定时与光合作用的气体交换测量的复活。PRI提供了一个明确的光学指标春季光合作用的激活，是在针叶树叶和林分尺度检测。我们建议，PRI可能提供一个有用的度量有效的生长季节长度适合遥感，并可以改善遥感驱动的模型中的万年青生态系统的碳吸收。
In evergreens, the seasonal down-regulation and reactivation of photosynthesis is largely invisible and difficult to assess with remote sensing. This invisible phenology may be changing as a result of climate change. To better understand the mechanism and timing of these hidden physiological transitions, we explored several assays and optical indicators of spring photosynthetic activation in conifers exposed to a boreal climate. The photochemical reflectance index (PRI), chlorophyll fluorescence, and leaf pigments for evergreen conifer seedlings were monitored over 1 yr of a boreal climate with the addition of gas exchange during the spring. PRI, electron transport rate, pigment levels, light-use efficiency and photosynthesis all exhibited striking seasonal changes, with varying kinetics and strengths of correlation, which were used to evaluate the mechanisms and timing of spring activation. PRI and pigment pools were closely timed with photosynthetic reactivation measured by gas exchange. The PRI provided a clear optical indicator of spring photosynthetic activation that was detectable at leaf and stand scales in conifers. We propose that PRI might provide a useful metric of effective growing season length amenable to remote sensing and could improve remote-sensing-driven models of carbon uptake in evergreen ecosystems.