A Bayesian inference approach to determine experimental Typha latifolia paludiculture greenhouse gas exchange measured with eddy covariance

IF 5.6 1区 农林科学 Q1 AGRONOMY
Alexander J.V. Buzacott , Merit van den Berg , Bart Kruijt , Jeroen Pijlman , Christian Fritz , Pascal Wintjen , Ype van der Velde
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引用次数: 0

Abstract

Measurements of greenhouse gas exchange (GHG) using the eddy covariance method are crucial for identifying strategies to achieve emission reductions and carbon sequestration. There are many sites that have heterogeneous land covers where it would be useful to have balances of particular land areas, such as field trials of emission mitigation strategies, but the flux footprint infrequently covers only the area of interest. Filtering the data based on a footprint area threshold can be done but may result in the loss of a high proportion of observations that contain valuable information. Here, we present a study that uses a single eddy covariance tower on the border of two land uses to compare GHG exchange from a Typha latifolia paludiculture experiment and the surrounding area (SA) which is primarily a dairy meadow. We used a Bayesian inference approach to predict carbon dioxide (CO2) and methane (CH4) fluxes where the relative contribution of the two source areas, derived from a two-dimensional footprint for each timestep, was used to weight and parameterise equations. Distinct differences in flux behaviour were observed when contributions of the two land areas changed and that resulted in clearly different parameter distributions. The annual totals (posterior mean ± 95% confidence interval) from the simulations showed that Typha was a net sink of CO2 for both simulation years (−18.5 ± 2.9 and −17.8 ± 2.9 t CO2ha1yr1) while SA was a net source (16.8 ± 2.9 and 17.4 ± 2.9  t CO2ha1yr1). Using the 100-year global warming potential of CH4, even though CH4 emissions were higher for paludiculture in both years (13.6 ± 0.6 and 15.9 ± 1.0 t CO2-eqha1yr1) than SA (7.1 ± 0.6 and 6.8 ± 1.2  t CO2-eqha1yr1), the net GHG balance indicates that Typha paludiculture is a viable strategy to limit GHG emissions from drained peatlands.

利用贝叶斯推理方法确定利用涡度协方差测量的棕榈科植物实验温室气体交换量
利用涡度协方差法测量温室气体交换量(GHG)对于确定减排和固碳战略至关重要。有许多地点的土地覆盖情况不尽相同,在这种情况下,对特定土地区域(如减排策略的实地试验)进行平衡是非常有用的,但通量足迹往往只覆盖感兴趣的区域。可以根据足迹面积阈值对数据进行筛选,但这样做可能会丢失很大一部分包含有价值信息的观测数据。在此,我们介绍了一项研究,该研究利用位于两种土地用途交界处的单个涡度协方差塔,来比较晚叶香蒲(Typha latifolia)棕榈栽培实验与周边地区(SA)的温室气体交换,后者主要是一片奶牛草地。我们使用贝叶斯推理方法预测二氧化碳(CO2)和甲烷(CH4)通量,其中两个源区的相对贡献(由每个时间步的二维足迹得出)被用于加权和参数化方程。当两块陆地的贡献率发生变化时,通量行为会出现明显差异,从而导致参数分布明显不同。模拟得出的年度总量(后平均值 ± 95% 置信区间)显示,在两个模拟年份中,香蒲是二氧化碳的净吸收汇(-18.5 ± 2.9 吨 CO2ha-1yr-1 和 -17.8 ± 2.9 吨 CO2ha-1yr-1),而南澳是净来源(16.8 ± 2.9 吨 CO2ha-1yr-1 和 17.4 ± 2.9 吨 CO2ha-1yr-1)。利用 CH4 的 100 年全球升温潜能值,尽管这两年棕榈栽培的 CH4 排放量(13.6 ± 0.6 吨 CO2-eqha-1yr-1 和 15.9 ± 1.0 吨 CO2-eqha-1yr-1)均高于 SA(7.1 ± 0.6 吨 CO2-eqha-1yr-1 和 6.8 ± 1.2 吨 CO2-eqha-1yr-1),但温室气体净平衡表明,香蒲栽培是限制排水泥炭地温室气体排放的可行策略。
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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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