Solar-induced fluorescence-based phenology of subtropical forests in China and its response to climate factors

IF 5.6 1区 农林科学 Q1 AGRONOMY Agricultural and Forest Meteorology Pub Date : 2024-08-07 DOI:10.1016/j.agrformet.2024.110182
Jiacong Yu , Xuejian Li , Huaqiang Du , Fangjie Mao , Yanxin Xu , Zihao Huang , Yinyin Zhao , Lujin Lv , Meixuan Song , Lei Huang , Dejin Dong
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Abstract

Vegetation phenology refers to the cyclical changes of plant development in different seasons of the year, and is the result of the interaction between environmental factors and biological internal regulatory mechanisms. Current large-scale phenology studies mainly use vegetation indices for remote sensing retrieval, while the greenness information of subtropical forests is inconspicuous, causing regular vegetation indices to retrieve their phenology ineffectively. SIF (Solar-induced chlorophyll fluorescence) is strongly coupled with GPP (Gross Primary Productivity), and has great potential in vegetation phenology research. In this study, we used m-SG (modified Savitzky-Golay) filter to reconstruct OCO-2 (Orbiting Carbon Observatory 2) GOSIF time-series, and used D-L (Double-Logistic) curve fitting to retrieve subtropical forests phenology in China from 2001 to 2018. Then we used phenology retrieved from GPP products and flux GPP as well as phenology observation data to validate the GOSIF phenology. Finally, we analyzed the spatiotemporal distribution pattern of subtropical forests phenology and the influence of climate factors on it. The results showed that: (1) GOSIF can retrieve subtropical forests phenology, and the R2 of SOS (Start of Growth Season), EOS (End of Growth Season) and LOS (Length of Growth Season) based on GOSIF and GPP products reached 0.50, 0.68, 0.59, respectively, while the R2 of SOS, EOS, and LOS based on GOSIF and flux GPP as well as phenology observation data were 0.20, 0.43, 0.56, respectively. (2) The spatial distribution of subtropical forests phenology showed that SOS gradually delayed, EOS gradually advanced and LOS gradually shortened from southeast to northwest. Moreover, different types of forests showed different trends of advanced SOS, delayed EOS and prolonged LOS over time. (3) The annual average minimum temperature was the main climate factor affecting the subtropical forests phenology while the impact of annual total precipitation also cannot be ignored. For every 1 °C increase in the annual average minimum temperature, the overall SOS advanced by 2.94 days, EOS delayed by 2.14 days and LOS prolonged by 4.91 days.

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基于太阳诱导荧光的中国亚热带森林物候及其对气候因素的响应
植被物候是指一年中不同季节植物生长发育的周期性变化,是环境因子与生物内部调节机制相互作用的结果。目前大规模的物候研究主要使用植被指数进行遥感检索,而亚热带森林的绿度信息不明显,导致常规植被指数无法有效检索其物候。SIF(太阳诱导叶绿素荧光)与 GPP(总初级生产力)具有很强的耦合性,在植被物候学研究中具有很大的潜力。本研究利用m-SG(modified Savitzky-Golay)滤波重建了OCO-2(Orbiting Carbon Observatory 2)GOSIF时间序列,并利用D-L(Double-Logistic)曲线拟合检索了2001-2018年中国亚热带森林物候。然后,我们利用 GPP 产品和通量 GPP 以及物候观测数据检索出的物候来验证 GOSIF 物候。最后,我们分析了亚热带森林物候的时空分布格局以及气候因子对其的影响。结果表明(1)GOSIF 可以检索亚热带森林物候,基于 GOSIF 和 GPP 产品的 SOS(生长季开始)、EOS(生长季结束)和 LOS(生长季长度)的 R 分别达到 0.50、0.68 和 0.59,而基于 GOSIF 和通量 GPP 以及物候观测数据的 SOS、EOS 和 LOS 的 R 分别为 0.20、0.43 和 0.56。(2)亚热带森林物候空间分布显示,SOS 从东南向西北逐渐推迟,EOS 逐渐提前,LOS 逐渐缩短。此外,不同类型的森林随着时间的推移呈现出 SOS 提前、EOS 推迟和 LOS 延长的不同趋势。(3)年平均最低气温是影响亚热带森林物候的主要气候因子,同时年总降水量的影响也不容忽视。年平均最低气温每升高 1℃,总体 SOS 提前 2.94 天,EOS 推迟 2.14 天,LOS 延长 4.91 天。
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来源期刊
CiteScore
10.30
自引率
9.70%
发文量
415
审稿时长
69 days
期刊介绍: Agricultural and Forest Meteorology is an international journal for the publication of original articles and reviews on the inter-relationship between meteorology, agriculture, forestry, and natural ecosystems. Emphasis is on basic and applied scientific research relevant to practical problems in the field of plant and soil sciences, ecology and biogeochemistry as affected by weather as well as climate variability and change. Theoretical models should be tested against experimental data. Articles must appeal to an international audience. Special issues devoted to single topics are also published. Typical topics include canopy micrometeorology (e.g. canopy radiation transfer, turbulence near the ground, evapotranspiration, energy balance, fluxes of trace gases), micrometeorological instrumentation (e.g., sensors for trace gases, flux measurement instruments, radiation measurement techniques), aerobiology (e.g. the dispersion of pollen, spores, insects and pesticides), biometeorology (e.g. the effect of weather and climate on plant distribution, crop yield, water-use efficiency, and plant phenology), forest-fire/weather interactions, and feedbacks from vegetation to weather and the climate system.
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