光合作用的缓慢温度适应对总初级生产量估算的影响

IF 5.6 1区 农林科学 Q1 AGRONOMY
Jia Bai , Helin Zhang , Rui Sun , Yuhao Pan
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引用次数: 0

摘要

早期的实地实验和研究已经证实了光合作用的缓慢温度适应性。然而,这种效应难以用一些简单易得的指标来表征和量化。因此,光合作用的慢温适应性对总初级生产力(GPP)估算的影响往往被忽视或未被纳入大多数 GPP 模型中。在本研究中,我们使用了一个理论变量--适应状态(S)来描述缓慢的温度适应。该变量代表光合作用机制适应的温度,被定义为气温(Ta)和植被对温度做出反应所需的时间常数(τ)的函数,以讨论其对 GPP 模拟的影响。我们利用 FLUXNET2015 数据集计算了 S,并基于随机森林算法,利用 S 和短波辐射(SW)建立了 GPP 模型(S 模型)。作为对比,我们直接使用 Ta 和 SW 建立了另一个 GPP 模型(Ta 模型)。此外,植物对不同温度的适应能力对于预测和应对未来可能出现的温度胁迫至关重要。因此,还利用卫星太阳诱导叶绿素荧光(SIF)和 Ta 数据集绘制了 τ 值的空间分布图。结果表明(1)考虑光合作用对温度的缓慢适应,可以更精确地估算 GPP,这主要体现在减少 GPP 预测的过度波动;(2)考虑光合作用对温度的缓慢适应,可以降低植被对温度的敏感性;(3)S 模型对 GPP 估算的改进在不同植被生长阶段是不同的,在春季恢复阶段更为显著;(4)τ 值具有显著的空间分布,受植被生长决定因素和温度季节变化的影响很大。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Effects of slow temperature acclimation of photosynthesis on gross primary production estimation

The slow temperature acclimation of photosynthesis has been confirmed through early field experiments and studies. However, this effect is difficult to characterize and quantify with some simple and easily accessible indicators. As a result, the impact of slow temperature acclimation of photosynthesis on gross primary production (GPP) estimation has often been overlooked or not integrated into most GPP models. In this study, we used a theorical variable-state of acclimation (S), to characterize the slow temperature acclimation. This variable represents the temperature to which the photosynthetic machinery adapts and is defined as a function of air temperature (Ta) and time constant (τ) required for vegetation to respond to temperature, to discuss its impact on GPP simulation. We used FLUXNET2015 dataset to calculate S and established a GPP model using S and shortwave radiation (SW) based on random forest algorithm (S model). As a comparison, we directly used Ta and SW to build the other GPP model (Ta model). Moreover, the divergent temperature acclimation capacities of plants are crucial to predict and make preparations for likely temperature stress in the future. Therefore, the spatial distribution of τ values was also mapped using satellite sun induced chlorophyll fluorescence (SIF) and Ta datasets. The results indicated that: (1) taking into account the slow temperature acclimation of photosynthesis led to a more precise estimation of GPP which mainly reflected in reduction of excessive fluctuations in GPP predictions; (2) considering the slow temperature acclimation of photosynthesis can reduce the sensitivity of vegetation to temperature; (3) the improvement of S model in GPP estimations was different in different vegetation growth stages which was more significant in the springtime recovery stage; (4) τ values had significant spatial distribution which was strongly affected by the determinants of vegetation growth and seasonal variations in temperature.

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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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