Agricultural and Forest Meteorology最新文献

{"title":"Carbon dynamics, emission mitigation, and yield optimization in farmlands: A machine learning framework for multi-variable prediction","authors":"Beibei Wang ,&nbsp;Xiao Huang ,&nbsp;Hongxing He ,&nbsp;Conrad Zorn ,&nbsp;Jiangnan Wang ,&nbsp;Wenzhou Guo ,&nbsp;Jiarui Wu ,&nbsp;Shengchao Qiao ,&nbsp;Lingling Kong ,&nbsp;Peifang Wang ,&nbsp;Chaoqing Yu","doi":"10.1016/j.agrformet.2025.110740","DOIUrl":"10.1016/j.agrformet.2025.110740","url":null,"abstract":"<div><div>Machine learning (ML) has become a promising approach in agro-ecosystem applications to simulate different fertilization management practices (FMP) and their impact on crop yield, soil organic carbon (SOC) concentration, and greenhouse gas (GHG) emissions. However, existing ML-based studies often focus on predicting single variables and lack a systematic framework, limiting model reliability and practical application. This study addresses these gaps by proposing a systematic, modular framework for ML-based multi-variable prediction in agro-ecosystems. Utilizing a comprehensive field-measured dataset, we developed a multi-variable system to predict crop yield, SOC accumulation, and GHG emissions (N₂O, CH₄) for three staple crops in China. The study evaluates a range of preprocessing techniques and algorithms on model performance and demonstrates the model’s application in the North China Plain (NCP) to identify FMPs that balance productivity with carbon mitigation. Our results show that k-Nearest Neighbors missing data imputation, Local Outlier Factor outlier detection, and the Random Forest ML algorithm combined to deliver the best performance for yield (R² = 0.83), SOC (R² = 0.91), and N₂O emissions (R² = 0.83). These models outperformed other candidates across all environmental, soil, and management subgroups. Notably, models with similar accuracy when evaluated with measured variables can show substantial variability in predicting the effects of FMPs compared to conventional practices, highlighting the importance of robust model selection for providing reliable guidance in optimizing FMPs. Partial Dependence Plot (PDP) analysis revealed distinct phases in SOC accumulation, underscoring the need for input datasets with broad temporal coverage to capture both short-term dynamics and long-term trends in SOC dynamics. Overall across the case study area, we identify that 50% Manure-N substitution can reduce global warming potential by 29.5% for maize and 19.5% for wheat while increasing SOC concentration more than fivefold over 30 years.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"373 ","pages":"Article 110740"},"PeriodicalIF":5.6,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144701679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Grazing mitigates soil GHG emissions while optimizes forage production of annual cereal grasses in an arid saline-alkali land","authors":"Jiao Ning ,&nbsp;Kaili Xie ,&nbsp;Yarong Guo ,&nbsp;Shanning Lou ,&nbsp;Shenghua Chang ,&nbsp;Wanhe Zhu ,&nbsp;Xiong Z. He ,&nbsp;Fujiang Hou","doi":"10.1016/j.agrformet.2025.110743","DOIUrl":"10.1016/j.agrformet.2025.110743","url":null,"abstract":"<div><div>Livestock production faces the challenge of feed shortage due to the escalating demand for livestock products and the continued degradation of grasslands. The cultivation of annual forage crops may be an alternative option in the forthcoming decades. However, the impact of grassland utilization method (grazing vs. mowing) on forage yield and associated soil greenhouse gas (GHG) emissions of annual sown pastures remains uncertain. A 4-year experiment was conducted in a saline-alkali cropland with irrigation of 560 mm yr^-1 in Northwest China. Annual forage crops were rotationally sown to elucidate the impact of grassland utilization methods on forage productivity (hay, crude protein (CP)) and soil GHG (CO₂, N₂O, and CH₄) fluxes, aiming to optimize the trade-off between forage production and soil GHG emissions. Results show that compared to mowing, grazing increased the mean yields of hay and CP by 44.7 % and 50.2 %, respectively; however, grazing had no significant impact on the cumulative soil N₂O emissions and CH₄ uptake but significantly reduced cumulative soil CO₂ emissions during the last two study years. For both grazing and mowing, soil water content was the primary influencing factor of soil N₂O emissions, and soil temperature was the primary influencing factor of soil CH₄ uptakes and CO₂ emissions. Cumulative soil N₂O emissions and CH₄ uptakes had upward trends with the increasing forage hay and CP yields under grazing. Cumulative soil CO₂ emission under mowing had a downward-curving relationship with the hay and CP yields. Overall, compared to mowing, grazing decreased hay and CP yield-scaled soil GHG intensity by 36.3 % and 38.6 % respectively. Grazing presents an effective strategy for optimizing forage production and environmental performance of annual cereal grasses in arid regions.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"373 ","pages":"Article 110743"},"PeriodicalIF":5.6,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144684636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Decreasing annual pollen loads in evergreen needleleaf species (Pinaceae) by the earlier end of the spring pollen season","authors":"Jongho Kim ,&nbsp;Kyu Rang Kim ,&nbsp;Mae Ja Han ,&nbsp;Yoori Cho ,&nbsp;Sujong Jeong","doi":"10.1016/j.agrformet.2025.110753","DOIUrl":"10.1016/j.agrformet.2025.110753","url":null,"abstract":"<div><div>Globally, the annual pollen integral (APIn) of allergenic plant species has increased owing to climate-induced ecosystem changes; however, the role of phenology in APIn changes remains underexplored. This study examined the direct and indirect effects of climate variables and pollen phenology on APIn in Korean <em>Pinus</em> spp. using 23 years of ground-based data from seven stations. Phenological stages—start (SPS), end (EPS), and length (LPS) of the pollen season—were estimated using two different methods: percentage-based and threshold-based. At the same time, various meteorological indicators related to temperature and precipitation were calculated from daily observation data. Despite interannual warming, APIn significantly declined at most stations by about 2 % per year, independent of temperature trends. Path analysis revealed that temperature sequentially influenced pollen phenology: higher seasonal temperatures advanced SPS (β = –1.19, <em>p</em> &lt; 0.01) and EPS (β = –0.73, <em>p</em> &lt; 0.05), leading to significant indirect reductions in APIn. Bootstrapped mediation models confirmed adverse indirect effects through EPS (β = –204.21) and multi-step paths involving SPS and LPS.</div><div>In contrast, early-season rainfall showed limited influence, with a single significant path through EPS (β = 110.90). These findings reveal that phenological advancement can suppress pollen production under favorable climatic conditions. Climate-pollen interactions in coniferous forests are thus better understood through a phenological mediation framework, which captures the cascading effects of shifting seasonal timing. Monitoring phenological change offers a critical tool for predicting ecosystem-level responses to climate change and informing forest management in temperate regions.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"373 ","pages":"Article 110753"},"PeriodicalIF":5.6,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144684637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Measuring tree sway frequency with videos for ecohydrologic applications: Assessing the efficacy of Eulerian processing algorithms","authors":"Joseph H. Ammatelli ,&nbsp;Ethan D. Gutmann ,&nbsp;Sidney A. Bush ,&nbsp;Holly R. Barnard ,&nbsp;Dominick M. Ciruzzi ,&nbsp;Steven P. Loheide II ,&nbsp;Mark S. Raleigh ,&nbsp;Jessica D. Lundquist","doi":"10.1016/j.agrformet.2025.110751","DOIUrl":"10.1016/j.agrformet.2025.110751","url":null,"abstract":"<div><div>Measurements of tree sway frequency can be used to quantify important ecohydrologic processes, such as drought stress and canopy interception, that otherwise require expensive measurement techniques. However, existing instruments used to measure tree sway lack spatial scalability. We investigate whether the virtual vision sensor and multilevel binary thresholding video processing algorithms can be used to accurately extract tree sway frequency at multiple points in a video camera field of view to enable scalable measurements of ecohydrologic processes. Comparing sway frequencies extracted from video and accelerometer data at three sites, we show that for 30–60 second videos, the video processing algorithms can reproduce 30-minute accelerometer sway frequencies with ±0.02 Hz accuracy. The results suggest that video processing algorithms may be suitable for applications where changes in sway frequency are on the order of tenths of hertz or larger, for example the measurement of snow intercepted in tree canopies. Further work is needed to clarify the accuracy of the algorithms when applied to longer videos, which may be required to monitor processes that result in more subtle changes in sway frequency, such as diurnal changes in tree water content and impacts from drought stress.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"373 ","pages":"Article 110751"},"PeriodicalIF":5.6,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144677903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Attributing future changes in terrestrial evapotranspiration: The combined impacts of climate change, rising CO2, and land use change","authors":"Haiyan Hou ,&nbsp;Xia Li ,&nbsp;Yuanzhi Yao ,&nbsp;Guohua Hu ,&nbsp;Cheng Wang ,&nbsp;Nan Chu","doi":"10.1016/j.agrformet.2025.110747","DOIUrl":"10.1016/j.agrformet.2025.110747","url":null,"abstract":"<div><div>Evapotranspiration (ET) is a crucial component of ecohydrological processes that can be significantly influenced by environmental drivers, including climate variability, elevating CO₂ concentration, and human-induced land use/land cover changes (LULCC). However, the mechanism and specific quantitative contributions of these drivers in shaping terrestrial ET remain highly uncertain within the context of future global changes. Here, we employed an integrated modeling framework that combines a process-based land surface model and a land use simulation model to comprehensively estimate and attribute future changes in global terrestrial ET for different Shared Socioeconomic Pathways and Representative Concentration Pathways (SSP-RCP) for the first time. We projected an increase in terrestrial ET of 0.17 to 0.60 mm yr⁻² from 2020 to 2100 under three SSP-RCPs. Specifically, climate change and CO₂ suppression effects exert primary (78.14 % – 78.37 %) and secondary (17.99 % – 21.44 %) influences on this increase, respectively. LULCC has a relatively minor impact on terrestrial ET variations (0.19 % to 3.88 %), and dominates ET across 0.64 % to 4.74 % of the global land area. In tropical regions like South America, LULCC can account for up to 17.77 % of ET changes under a medium development scenario (SSP2–4.5). Our study enhances the comprehension of combined and individual impacts of climate change, rising atmospheric CO₂ concentration, and LULCC on future terrestrial ET, and underscores the crucial role of LULCC at regional scales.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"373 ","pages":"Article 110747"},"PeriodicalIF":5.6,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144678171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Forcing experiment and model integration to validate an olive tree phenological model","authors":"Omar Abou-Saaid ,&nbsp;Bouchaib Khadari","doi":"10.1016/j.agrformet.2025.110752","DOIUrl":"10.1016/j.agrformet.2025.110752","url":null,"abstract":"<div><div>Accurate assessment of chill and heat requirements is a fundamental challenge in phenological modeling of perennial fruit species, especially in the current climate change setting. Such models are typically calibrated and validated on the basis of long-term phenological and temperature records, without the integration of forcing experiments to highlight endodormancy release dates. Here we investigated olive tree flowering date modeling by combining a statistical approach and forcing experiments on the Picholine Marocaine cultivar with the aim of developing an olive phenological model for accurate assessment of chill and heat requirements. We initially assessed the endodormancy release date using a forcing experiment in 2021 and 2022 by comparing floral bud fresh weights under natural field conditions and after forcing conditions in a climate-controlled growing chamber. Subsequently, we used the PhenoFlex framework to calibrate and validate the model based on 31 years of flowering date and temperature data. We obtained an optimal model following nine calibrations with distinct season onset dates, and the latter were similar to the chilling onset date determined through a previous partial least squares regression approach. We also used endodormancy release dates to improve our model calibration by fitting the predicted flowering date to the observed value according to the recalibrated chill and heat requirement values. Finally, we validated the model based on six years of flowering date and temperature data. Our findings highlighted that the model calibrated solely via phenological records was less accurate than that calibrated based on a combination of phenological records and forcing experiment data. Our investigations broaden the scope for future applications of phenological olive tree modeling to accurately assess chill and heat requirements, which is currently a challenging issue facing olive growing in Mediterranean areas under climate warming.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"373 ","pages":"Article 110752"},"PeriodicalIF":5.6,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144677904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Carbon partitioning as a drought-tolerance strategy in clonal eucalyptus under thermal and water stress","authors":"Fernanda Leite Cunha ,&nbsp;Otávio Camargo Campoe ,&nbsp;Cléber Rodrigo de Souza ,&nbsp;Isaira Leite & Lopes ,&nbsp;Clayton Alcarde Alvares ,&nbsp;Jose Luiz Stape","doi":"10.1016/j.agrformet.2025.110719","DOIUrl":"10.1016/j.agrformet.2025.110719","url":null,"abstract":"<div><div>The increase in the frequency, duration, and intensity of drought associated with climate change may alter the current productivity rates of planted forests and the risk of tree mortality associated with physiological stress. In this context, we aim to understand carbon allocation strategies in fast-growing (FG) and drought-tolerant (DT) clonal <em>Eucalyptus</em> plantations under different water and thermal stress. We used carbon balance data from two DT and three FG clones at four climatically contrasting sites, covering an area of 3185 km in Brazil. With the aid of a generalized linear mixed model (GLMM), we observed that under extreme conditions of water and thermal stress, the clones tended to reduce gross primary production (GPP) and the partitioning of aboveground carbon, in detriment in increase in root growth. FG clones showed more significant reductions in GPP and carbon fluxes compared to DT clones, which demonstrates that FG clones are more sensitive to climate change. Our work contributes to elucidating carbon allocation strategies for the main groups of clones planted in Brazil, producing reference values that can be used in sustainable management projects and ecophysiological modeling aimed at more productive plantations that are tolerant to climatic adversity.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"373 ","pages":"Article 110719"},"PeriodicalIF":5.6,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144678169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cross-regional validation of the PhenoFlex framework for flowering date prediction in apple: A study across Germany and Spain","authors":"Hajar Mojahid ,&nbsp;Lars Caspersen ,&nbsp;Alvaro Delgado ,&nbsp;Enrique Dapena ,&nbsp;Eike Luedeling ,&nbsp;Katja Schiffers ,&nbsp;Eduardo Fernandez","doi":"10.1016/j.agrformet.2025.110746","DOIUrl":"10.1016/j.agrformet.2025.110746","url":null,"abstract":"<div><div>Modeling the dormancy period in temperate fruit trees is essential to assessing the impacts of climate change on tree phenology and spring frost events. Whereas cultivar-specific parametrization of phenology models may provide accurate predictions, it offers limited outlook at the species level. Using shared parameters for apple species alongside cultivar-specific parameters would improve phenology projections, provide insights into future risks, and inform strategies for adapting temperate orchards to climate change. In this study, we assessed the performance of PhenoFlex when used to estimate a common set of model parameters for apple trees from Germany and Spain. We used historical phenology and weather data for 5 German and 11 Spanish cultivars, testing two calibration approaches: location-specific (data grouped by country) and species-specific (combining data for all 16 cultivars), under two fitting procedures: a global optimization and an enhanced global optimization. Overall, species-specific calibration increased the PhenoFlex model accuracy, especially for the Spanish cultivars under the enhanced global optimization (RMSE of 4.6 vs. 5.4 days, respectively for ‘Clara’). On the other hand, location-specific calibration performed better for German cultivars. The enhanced global optimization reduced maximum errors from 12.0 to 7.5 days (‘Collaos’ in the species-specific fit), outperforming the global optimization procedure. Analysis of chill and heat response curves revealed variation across calibration approaches, with the species-specific calibration showing moderate responses. Our results highlight the trade-offs between generalizability and specificity in phenology modeling. Integrating multi-site data for the same cultivar could improve species-level parameter reliability and inform climate-resilient orchard management.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"373 ","pages":"Article 110746"},"PeriodicalIF":5.6,"publicationDate":"2025-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144664518","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Contribution of aboveground and belowground biomass of Robinia pseudoacacia trees to total plant carbon stocks in a young agroforestry system","authors":"Soline Martin-Blangy ,&nbsp;Christophe Jourdan ,&nbsp;Isabelle Bertrand ,&nbsp;Marion Forest ,&nbsp;Ezzeddine Abbessi ,&nbsp;Rémi Dugué ,&nbsp;Gabin Piton ,&nbsp;Jérôme Ngao","doi":"10.1016/j.agrformet.2025.110749","DOIUrl":"10.1016/j.agrformet.2025.110749","url":null,"abstract":"<div><div>Allocation to aboveground and belowground compartments of tree biomass in Mediterranean agroforestry systems (AFS) is poorly documented, especially for young trees. This work aimed at (i) characterizing the effects of land use (Agroforestry, AF vs. Tree Plantation, TP) on 5-year-old black locust tree growth, tree biomass allocation, and tree C stocks at plot scale, and (ii) assessing the effect of land use on total carbon stocks (AF vs. TP vs. Crop Monoculture). Allometric equations were built for upscaling tree biomass at the plot scale. Biomass of understory vegetation and crops were estimated at the plot scale in the three land uses. Tree diameter was 19 % higher in the AF than in TP, likely due to different light microclimate, while tree height did not vary significantly between land uses. Tree biomass allocation to aboveground and belowground compartments (70 % and 30 % of total tree biomass, respectively) did not vary between land uses. Higher efficiency in building tree carbon stock was shown in agroforestry than in tree plantation per area unit. Trees accounted for 39 % and 66 % of total carbon stocks in biomass in AF and TP, respectively. Understory vegetation accounted for 8 % and 34 % of total carbon stocks in biomass in AF and TP, respectively. Land equivalent ratio values, which involved tree, crop and understory vegetation carbon stocks, did not yet indicate a synergetic effect on accumulation of plant carbon compared to sole crop or tree plantations. This study provides new reference values of carbon stocks in biomass in a young AFS.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"373 ","pages":"Article 110749"},"PeriodicalIF":5.6,"publicationDate":"2025-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144663669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"New allometric models for Eucalyptus tereticornis using terrestrial laser scanning show increased carbon storage in larger trees","authors":"Louise Terryn ,&nbsp;David Ellsworth ,&nbsp;Belinda E. Medlyn ,&nbsp;Matthias Boer ,&nbsp;Tom E. Verhelst ,&nbsp;Kim Calders","doi":"10.1016/j.agrformet.2025.110708","DOIUrl":"10.1016/j.agrformet.2025.110708","url":null,"abstract":"<div><div>Accurate aboveground woody biomass (AGB) estimates are crucial for assessing the impact of elevated CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> (eCO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span>) on net carbon sequestration in trees. Estimating AGB essentially involves developing allometric models using destructively harvested data. Due to the costs and restrictions of harvesting, models from other regions are often used. In the past two decades, terrestrial laser scanning (TLS) has become a widely accepted, non-destructive method for measuring tree structure. We provide new TLS-based allometric AGB models for <em>Eucalyptus tereticornis</em>, the dominant tree species at EucFACE, a replicated, ecosystem-scale mature forest free-air CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> enrichment (FACE) experiment in Australia. Based on TLS-derived diameter at breast height (DBH), tree height (H), and crown area (CA) of 116 trees, we developed both an AGB:DBH model and an AGB:(CA<span><math><mo>×</mo></math></span>H) model. Our TLS-based AGB:DBH model (uncertainty = 19 %, bias &lt;−1 %), shows substantially larger AGB growth compared to the previously-used allometric model at EucFACE. Although this new model does not change previous conclusions about the impact of eCO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> on tree-level AGB increments at EucFACE, it does indicate a notable increase in AGB increment, particularly for larger trees. This highlights the need to recalculate net primary productivity and carbon partitioning at EucFACE. Additionally, we present a TLS-based AGB:(CA<span><math><mo>×</mo></math></span>H) model (uncertainty = 27 %, bias &lt;1 %). These models improve accuracy in assessing carbon storage at EucFACE and offer scalable methods for monitoring AGB in <em>E. tereticornis</em> across broader landscapes. By enabling reliable, landscape-level carbon estimates, this work supports targeted forest management and conservation strategies under rising CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> conditions.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"373 ","pages":"Article 110708"},"PeriodicalIF":5.6,"publicationDate":"2025-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144663668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}