Alexander J.V. Buzacott , Merit van den Berg , Bart Kruijt , Jeroen Pijlman , Christian Fritz , Pascal Wintjen , Ype van der Velde
{"title":"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","authors":"Alexander J.V. Buzacott , Merit van den Berg , Bart Kruijt , Jeroen Pijlman , Christian Fritz , Pascal Wintjen , Ype van der Velde","doi":"10.1016/j.agrformet.2024.110179","DOIUrl":null,"url":null,"abstract":"<div><p>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 <em>Typha latifolia</em> paludiculture experiment and the surrounding area (SA) which is primarily a dairy meadow. We used a Bayesian inference approach to predict carbon dioxide (CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span>) and methane (CH<span><math><msub><mrow></mrow><mrow><mn>4</mn></mrow></msub></math></span>) 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 <em>Typha</em> was a net sink of CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> for both simulation years (−18.5 ± 2.9 and −17.8 ± 2.9<!--> <!-->t<!--> <!-->CO<span><math><mrow><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub><mspace></mspace><msup><mrow><mi>ha</mi></mrow><mrow><mo>−</mo><mn>1</mn></mrow></msup><mspace></mspace><msup><mrow><mi>yr</mi></mrow><mrow><mo>−</mo><mn>1</mn></mrow></msup></mrow></math></span>) while SA was a net source (16.8 ± 2.9 and 17.4 ± 2.9 <!--> <!-->t<!--> <!-->CO<span><math><mrow><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub><mspace></mspace><msup><mrow><mi>ha</mi></mrow><mrow><mo>−</mo><mn>1</mn></mrow></msup><mspace></mspace><msup><mrow><mi>yr</mi></mrow><mrow><mo>−</mo><mn>1</mn></mrow></msup></mrow></math></span>). Using the 100-year global warming potential of CH<span><math><msub><mrow></mrow><mrow><mn>4</mn></mrow></msub></math></span>, even though CH<span><math><msub><mrow></mrow><mrow><mn>4</mn></mrow></msub></math></span> emissions were higher for paludiculture in both years (13.6 ± 0.6 and 15.9 ± 1.0<!--> <!-->t<!--> <!-->CO<span><math><mrow><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub><mtext>-eq</mtext><mspace></mspace><msup><mrow><mi>ha</mi></mrow><mrow><mo>−</mo><mn>1</mn></mrow></msup><mspace></mspace><msup><mrow><mi>yr</mi></mrow><mrow><mo>−</mo><mn>1</mn></mrow></msup></mrow></math></span>) than SA (7.1 ± 0.6 and 6.8 ± 1.2 <!--> <!-->t<!--> <!-->CO<span><math><mrow><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub><mtext>-eq</mtext><mspace></mspace><msup><mrow><mi>ha</mi></mrow><mrow><mo>−</mo><mn>1</mn></mrow></msup><mspace></mspace><msup><mrow><mi>yr</mi></mrow><mrow><mo>−</mo><mn>1</mn></mrow></msup></mrow></math></span>), the net GHG balance indicates that <em>Typha</em> paludiculture is a viable strategy to limit GHG emissions from drained peatlands.</p></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":null,"pages":null},"PeriodicalIF":5.6000,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0168192324002922/pdfft?md5=d803f6f52e0e5d265659ba001a84ff8f&pid=1-s2.0-S0168192324002922-main.pdf","citationCount":"0","resultStr":"{\"title\":\"A Bayesian inference approach to determine experimental Typha latifolia paludiculture greenhouse gas exchange measured with eddy covariance\",\"authors\":\"Alexander J.V. Buzacott , Merit van den Berg , Bart Kruijt , Jeroen Pijlman , Christian Fritz , Pascal Wintjen , Ype van der Velde\",\"doi\":\"10.1016/j.agrformet.2024.110179\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>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 <em>Typha latifolia</em> paludiculture experiment and the surrounding area (SA) which is primarily a dairy meadow. We used a Bayesian inference approach to predict carbon dioxide (CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span>) and methane (CH<span><math><msub><mrow></mrow><mrow><mn>4</mn></mrow></msub></math></span>) 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 <em>Typha</em> was a net sink of CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> for both simulation years (−18.5 ± 2.9 and −17.8 ± 2.9<!--> <!-->t<!--> <!-->CO<span><math><mrow><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub><mspace></mspace><msup><mrow><mi>ha</mi></mrow><mrow><mo>−</mo><mn>1</mn></mrow></msup><mspace></mspace><msup><mrow><mi>yr</mi></mrow><mrow><mo>−</mo><mn>1</mn></mrow></msup></mrow></math></span>) while SA was a net source (16.8 ± 2.9 and 17.4 ± 2.9 <!--> <!-->t<!--> <!-->CO<span><math><mrow><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub><mspace></mspace><msup><mrow><mi>ha</mi></mrow><mrow><mo>−</mo><mn>1</mn></mrow></msup><mspace></mspace><msup><mrow><mi>yr</mi></mrow><mrow><mo>−</mo><mn>1</mn></mrow></msup></mrow></math></span>). Using the 100-year global warming potential of CH<span><math><msub><mrow></mrow><mrow><mn>4</mn></mrow></msub></math></span>, even though CH<span><math><msub><mrow></mrow><mrow><mn>4</mn></mrow></msub></math></span> emissions were higher for paludiculture in both years (13.6 ± 0.6 and 15.9 ± 1.0<!--> <!-->t<!--> <!-->CO<span><math><mrow><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub><mtext>-eq</mtext><mspace></mspace><msup><mrow><mi>ha</mi></mrow><mrow><mo>−</mo><mn>1</mn></mrow></msup><mspace></mspace><msup><mrow><mi>yr</mi></mrow><mrow><mo>−</mo><mn>1</mn></mrow></msup></mrow></math></span>) than SA (7.1 ± 0.6 and 6.8 ± 1.2 <!--> <!-->t<!--> <!-->CO<span><math><mrow><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub><mtext>-eq</mtext><mspace></mspace><msup><mrow><mi>ha</mi></mrow><mrow><mo>−</mo><mn>1</mn></mrow></msup><mspace></mspace><msup><mrow><mi>yr</mi></mrow><mrow><mo>−</mo><mn>1</mn></mrow></msup></mrow></math></span>), the net GHG balance indicates that <em>Typha</em> paludiculture is a viable strategy to limit GHG emissions from drained peatlands.</p></div>\",\"PeriodicalId\":50839,\"journal\":{\"name\":\"Agricultural and Forest Meteorology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.6000,\"publicationDate\":\"2024-08-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S0168192324002922/pdfft?md5=d803f6f52e0e5d265659ba001a84ff8f&pid=1-s2.0-S0168192324002922-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Agricultural and Forest Meteorology\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0168192324002922\",\"RegionNum\":1,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AGRONOMY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Agricultural and Forest Meteorology","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0168192324002922","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRONOMY","Score":null,"Total":0}
A Bayesian inference approach to determine experimental Typha latifolia paludiculture greenhouse gas exchange measured with eddy covariance
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 (CO) and methane (CH) 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 CO for both simulation years (−18.5 ± 2.9 and −17.8 ± 2.9 t CO) while SA was a net source (16.8 ± 2.9 and 17.4 ± 2.9 t CO). Using the 100-year global warming potential of CH, even though CH emissions were higher for paludiculture in both years (13.6 ± 0.6 and 15.9 ± 1.0 t CO) than SA (7.1 ± 0.6 and 6.8 ± 1.2 t CO), the net GHG balance indicates that Typha paludiculture is a viable strategy to limit GHG emissions from drained peatlands.
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.