Han Wu , Zhenggang Du , Lingyan Zhou , Guiyao Zhou , Giovanni Coco , Jing Gao , Xuhui Zhou
{"title":"东北地区林龄决定着森林根冠比","authors":"Han Wu , Zhenggang Du , Lingyan Zhou , Guiyao Zhou , Giovanni Coco , Jing Gao , Xuhui Zhou","doi":"10.1016/j.agrformet.2025.110595","DOIUrl":null,"url":null,"abstract":"<div><div>Root: shoot (RS) ratios are widely used to estimate global and regional forest carbon stocks and to model the forest carbon cycle. However, limited knowledge is available regarding factors that determine RS spatial patterns, particularly in high-latitude temperate regions. Therefore, in this study, we compiled 189 measurements of forest RSs across Northeast China to evaluate the main drivers of RS patterns. An optimal machine learning model was selected to upscale the RS data and estimate belowground biomass carbon in Northeast China. The results showed that the stand age had the greatest impact on RS variation (contribution of 17.6 %), exceeding the influence of other predictors and increasing the coefficient of determination of the RS by 41 % in a structural equation model. Regional RS values decreased from 0.22 ± 0.02 to 0.16 ± 0.01 as the stand age increased from less than 20 years to over 60 years. Higher estimated RS values were found in both forests with a stand age of 40–60 years (19.3 %) and over 60 years (22.6 %) when the stand age was not considered. We also found that our RS estimates were lower (mean value = 0.21 ± 0.05) than Earth system models (0.25 ± 0.03) and remote sensing-based estimates (0.5 ± 0.05), resulting in 33.2 % and 62.7 % lower estimates of belowground biomass carbon in Northeast China, respectively. The results of this study highlight the importance of the stand age in forest carbon allocation, representing a factor that should be incorporated when estimating current and future carbon sequestration.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"370 ","pages":"Article 110595"},"PeriodicalIF":5.6000,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The stand age governs forest root: Shoot ratios across northeast China\",\"authors\":\"Han Wu , Zhenggang Du , Lingyan Zhou , Guiyao Zhou , Giovanni Coco , Jing Gao , Xuhui Zhou\",\"doi\":\"10.1016/j.agrformet.2025.110595\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Root: shoot (RS) ratios are widely used to estimate global and regional forest carbon stocks and to model the forest carbon cycle. However, limited knowledge is available regarding factors that determine RS spatial patterns, particularly in high-latitude temperate regions. Therefore, in this study, we compiled 189 measurements of forest RSs across Northeast China to evaluate the main drivers of RS patterns. An optimal machine learning model was selected to upscale the RS data and estimate belowground biomass carbon in Northeast China. The results showed that the stand age had the greatest impact on RS variation (contribution of 17.6 %), exceeding the influence of other predictors and increasing the coefficient of determination of the RS by 41 % in a structural equation model. Regional RS values decreased from 0.22 ± 0.02 to 0.16 ± 0.01 as the stand age increased from less than 20 years to over 60 years. Higher estimated RS values were found in both forests with a stand age of 40–60 years (19.3 %) and over 60 years (22.6 %) when the stand age was not considered. We also found that our RS estimates were lower (mean value = 0.21 ± 0.05) than Earth system models (0.25 ± 0.03) and remote sensing-based estimates (0.5 ± 0.05), resulting in 33.2 % and 62.7 % lower estimates of belowground biomass carbon in Northeast China, respectively. The results of this study highlight the importance of the stand age in forest carbon allocation, representing a factor that should be incorporated when estimating current and future carbon sequestration.</div></div>\",\"PeriodicalId\":50839,\"journal\":{\"name\":\"Agricultural and Forest Meteorology\",\"volume\":\"370 \",\"pages\":\"Article 110595\"},\"PeriodicalIF\":5.6000,\"publicationDate\":\"2025-05-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Agricultural and Forest Meteorology\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0168192325002151\",\"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/S0168192325002151","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRONOMY","Score":null,"Total":0}
The stand age governs forest root: Shoot ratios across northeast China
Root: shoot (RS) ratios are widely used to estimate global and regional forest carbon stocks and to model the forest carbon cycle. However, limited knowledge is available regarding factors that determine RS spatial patterns, particularly in high-latitude temperate regions. Therefore, in this study, we compiled 189 measurements of forest RSs across Northeast China to evaluate the main drivers of RS patterns. An optimal machine learning model was selected to upscale the RS data and estimate belowground biomass carbon in Northeast China. The results showed that the stand age had the greatest impact on RS variation (contribution of 17.6 %), exceeding the influence of other predictors and increasing the coefficient of determination of the RS by 41 % in a structural equation model. Regional RS values decreased from 0.22 ± 0.02 to 0.16 ± 0.01 as the stand age increased from less than 20 years to over 60 years. Higher estimated RS values were found in both forests with a stand age of 40–60 years (19.3 %) and over 60 years (22.6 %) when the stand age was not considered. We also found that our RS estimates were lower (mean value = 0.21 ± 0.05) than Earth system models (0.25 ± 0.03) and remote sensing-based estimates (0.5 ± 0.05), resulting in 33.2 % and 62.7 % lower estimates of belowground biomass carbon in Northeast China, respectively. The results of this study highlight the importance of the stand age in forest carbon allocation, representing a factor that should be incorporated when estimating current and future carbon sequestration.
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.