Agricultural and Forest Meteorology最新文献

{"title":"Contribution of drought-avoidant strategy to gross primary productivity of three forest ecosystems in China","authors":"Caiyi Zhang ,&nbsp;Xingfei Jiang ,&nbsp;Minyue Si ,&nbsp;Junjiong Shao","doi":"10.1016/j.agrformet.2025.110698","DOIUrl":"10.1016/j.agrformet.2025.110698","url":null,"abstract":"<div><div>As drought events become more frequent and intense around the world, ecosystem gross primary productivity (GPP) is greatly associated with the responses of plants to drought stress. Drought avoidance is a critical strategy for plants to maintain internal water status under water deficit. However, the relative importance of this strategy to GPP has yet to be investigated. In this study, we first developed a theoretical framework to quantify the relative contribution of drought-avoidant strategy to GPP (Imp) based on the relationship between predawn and midday vegetation optical depth (VOD) and the relationship between midday VOD and GPP, and then applied this framework to three forest ecosystems in China. The results showed that the Imp was much smaller in a subtropical evergreen broadleaf forest (CN-Din, 2.3 ± 0.1 % and 6.6 ± 0.1 % for the original and the resolution mismatch corrected Imp, respectively) and a subtropical evergreen needleleaf forest (CN-Qia, 23.6 ± 0.8 % and 3.1 ± 0.1 %, respectively) than in a typical temperate mixed forest (CN-Cha, 58.2 ± 3.7 % and 66.4 ± 0.7 %, respectively). This difference may primarily come from the differential water conditions among the three forests, as the available water was much higher and the drought intensity was much weaker in CN-Din and CN-Qia than in CN-Cha. This work, for the first time, quantified the relative importance of drought-avoidant strategy to GPP, which might be critical to ecosystem functioning under climate change, especially for ecosystems that had not developed effective drought-tolerant strategies in the past geological times.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"372 ","pages":"Article 110698"},"PeriodicalIF":5.6,"publicationDate":"2025-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144335957","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":"Urban tree architectural modifications over the growing season and water restriction significantly contribute to variations in climate services","authors":"Dorine Canonne ,&nbsp;Sophie Herpin ,&nbsp;Julien Thierry ,&nbsp;Camille Le Bras ,&nbsp;Bénédicte Dubuc ,&nbsp;Lydie Ledroit ,&nbsp;Denis Cesbron ,&nbsp;Marc Saudreau ,&nbsp;Pierre-Emmanuel Bournet ,&nbsp;Sabine Demotes-Mainard","doi":"10.1016/j.agrformet.2025.110694","DOIUrl":"10.1016/j.agrformet.2025.110694","url":null,"abstract":"<div><div>Street trees have gained attention for improving thermal comfort in cities, yet seasonal changes in tree services in relation to the evolution of tree architecture are not well understood. This study hypothesizes that over a growing season and for sunny days, changes in climate services primarily rely on tree architecture influence on cast-shadow, especially during summer droughts. Two alignments of ornamental apple trees were grown in a reduced-scale street canyon, with a non-vegetated control zone. All trees were well watered until July 5th, 2022, after which one alignment experienced moderate water restriction while the other remained well-watered. The street microclimate was characterized, the universal thermal climate index (UTCI) calculated, and tree architecture at the organ and crown scales was measured. On sunny days, well-watered trees improved thermal comfort from 5.8°C UTCI in mid-May to 7.9°C in late August, while water restriction reduced this benefit by up to 2.7°C UTCI after 8 weeks. The changes in thermal comfort were primarily linked to tree architectural development and cast-shadow, although these effects were moderate due to leaf area index high enough in May to ensure 87.5 % of interception of radiation. Increases in crown projected area and volume enhanced tree services, with larger effects on the side than just below the tree canopy. Water restriction diminished thermal comfort by inhibiting stem growth and accelerating leaf fall, thus reducing light interception. This study highlights the significant role of architectural plasticity in tree climate services under water restriction, warranting further research in other species.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"372 ","pages":"Article 110694"},"PeriodicalIF":5.6,"publicationDate":"2025-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144335956","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":"Calculation of the fraction of sunlit and shaded leaf area in heterogeneous canopies with discontinuous plant crowns","authors":"Brian N. Bailey","doi":"10.1016/j.agrformet.2025.110680","DOIUrl":"10.1016/j.agrformet.2025.110680","url":null,"abstract":"<div><div>The fraction of sunlit leaf area, <span><math><msub><mrow><mi>f</mi></mrow><mrow><mi>s</mi><mi>u</mi><mi>n</mi></mrow></msub></math></span>, is a critical parameter for simple scaling of plant biophysical models from leaf to canopy, and is a useful bulk parameter describing interactions between canopy structure and function. Because of the highly non-linear response of many plant biophysical processes (e.g., photosynthesis) to light, using canopy-averaged light fluxes as the basis for scaling calculations does not yield correct whole-canopy fluxes. Accurate scaling requires calculation of the fraction of sunlit and shaded leaf area, the equations for which have been available in the literature for many decades for homogeneous canopies. However, when canopies become heterogeneous, such as in the case of many agricultural crops, the assumptions inherent in traditional approaches for estimating <span><math><msub><mrow><mi>f</mi></mrow><mrow><mi>s</mi><mi>u</mi><mi>n</mi></mrow></msub></math></span> are violated. In this work, a simple geometric model for the sunlit leaf area fraction in discontinuous canopies is presented and evaluated against a detailed 3D leaf-resolving model for simplified plant geometries and realistic tree reconstructions derived from LiDAR data. Results illustrated that the proposed model closely matched the 3D model. An alternative definition of <span><math><msub><mrow><mi>f</mi></mrow><mrow><mi>s</mi><mi>u</mi><mi>n</mi></mrow></msub></math></span> is presented and evaluated that can be easily applied within any model that calculates the fraction of canopy absorbed radiation, which was shown to produce <span><math><msub><mrow><mi>f</mi></mrow><mrow><mi>s</mi><mi>u</mi><mi>n</mi></mrow></msub></math></span> values that were nearly identical to the 3D model even in the presence of foliage clumping and woody branch elements.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"372 ","pages":"Article 110680"},"PeriodicalIF":5.6,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144321441","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":"Regional scale multi-crop water footprint quantification based on improved WOFOST model and remote sensing data assimilation","authors":"Xi Chen ,&nbsp;Shuqing Yang ,&nbsp;Xiaoyu Wen ,&nbsp;Wei Wang","doi":"10.1016/j.agrformet.2025.110691","DOIUrl":"10.1016/j.agrformet.2025.110691","url":null,"abstract":"<div><div>Addressing global water scarcity and food security, quantifying crop water footprints is essential for improving agricultural water use efficiency. Field trials in Horqin Left Wing Middle Banner, Inner Mongolia (2021–2022) explored efficient water use. A C-WOFOST model with a water balance module was developed, achieving Nash-Sutcliffe Efficiency (NSE) values over 0.8 for maize, beet, and sunflower’s LAI and soil moisture. Using Ensemble Kalman Filter (EnKF) for data assimilation, the coefficient of determination (R²) for maize, beet, and sunflower yields increased by 32.7 %, 69.4 %, and 43.6 %, respectively. Integrated with ArcGIS and U-Net for high-resolution analysis, the model showed maize had the highest water footprint, followed by sunflower and sugar beet. Maize’s WFgreen was 11.6 % higher than its WFblue, while sugar beet had the lowest water footprint, with nearly equal contributions from WFgreen and WFblue. Environmental conditions influenced water footprint distribution, with higher WFblue in the east and higher WFgreen in the west. The study suggests prioritizing crops with lower irrigation needs, such as sugar beet, in water-scarce areas and optimizing irrigation or selecting salt-tolerant varieties for high-demand crops like maize. The findings provide insights for sustainable water resource management in salinized regions.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"372 ","pages":"Article 110691"},"PeriodicalIF":5.6,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144321440","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":"Tropospheric ozone alters solar-induced chlorophyll fluorescence and its relationship with gross primary production in a subtropical evergreen forest","authors":"Jinghua Chen ,&nbsp;Shaoqiang Wang ,&nbsp;Kai Zhu ,&nbsp;Bin Chen ,&nbsp;Qinyi Wang ,&nbsp;Leiming Zhang ,&nbsp;Yuelin Li ,&nbsp;Chen Zheng","doi":"10.1016/j.agrformet.2025.110695","DOIUrl":"10.1016/j.agrformet.2025.110695","url":null,"abstract":"<div><div>Tropospheric ozone (O₃), as a harmful air pollutant and greenhouse gas, is globally increasing in concentration, raising concerns about its detrimental effects on ecosystems. To develop scientific strategies for protecting vegetation from O₃ damage, a comprehensive understanding of vegetation responses to O₃ is essential. Solar-induced chlorophyll fluorescence (SIF) offers a novel approach to studying how plants respond to stress, yet the extent and mechanism by which SIF reflects vegetation changes under varying ambient O₃ remain unclear. Using continuous and simultaneous observations of O₃, SIF, and carbon fluxes in a subtropical evergreen forest, we investigated the response of canopy SIF to ambient O₃ exposure and explored the underlying mechanisms of vegetation’s response to O₃. Our findings reveal that high ambient O₃ alters both the canopy SIF and its relationship with GPP in the subtropical evergreen forest. Specifically, canopy SIF decreases when O₃ concentrations exceed 60 ppb, but the threshold for a decrease in canopy SIF differs between the dry season (75 ppb) and the wet season (45 ppb), probably due to reduced stomatal conductance in the dry season, which limits O₃ uptake by leaf. Furthermore, extremely high O₃ concentrations decouple the linear SIF-GPP relationship (especially in wet season), indicating that high O₃ exposure more strongly affects SIF and thus weakens the ability of SIF to track GPP dynamics. Our analysis of the decomposed radiative, structural, and physiological components shows that plant physiology is more vulnerable to O₃ damage. This results in high O₃ concentrations influencing the SIF-GPP relationship primarily through structure in the dry season and through plant physiology in the wet season. These findings highlight the ability of SIF for plant O₃ stress detection and the different responses of structure and physiology under varying water conditions, which could effectively advance our understanding of plant O₃ stress mechanisms across different climates.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"372 ","pages":"Article 110695"},"PeriodicalIF":5.6,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144314016","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":"Wheat leaf area index retrieval from drone-derived hyperspectral and LiDAR imagery using machine learning algorithms","authors":"Gabriel Mulero ,&nbsp;David J. Bonfil ,&nbsp;David Helman","doi":"10.1016/j.agrformet.2025.110648","DOIUrl":"10.1016/j.agrformet.2025.110648","url":null,"abstract":"<div><div>Leaf Area Index (LAI) is a key parameter that reflects canopy structure and influences photosynthetic activity. Traditional remote sensing methods using spectral indices usually struggle with saturation at LAI &gt; 3.0 m² m^–2 in crop fields. Light detection and ranging (LiDAR) systems offer a solution by capturing detailed canopy structures.</div><div>This study used drone-based LiDAR and hyperspectral imagery to predict LAI across 60 plots in five wheat fields in Israel. Field LAI, assessed using a handheld optical sensor, ranged from 0.25 to 7.7 m² m^–2. LiDAR-derived metrics, including height, gap fraction, and canopy volume features, were combined with spectral indices for LAI prediction. These metrics were used in simple linear regression (SLR) and five machine learning (ML) models: artificial neural network (ANN), random forest, ridge regression, relevance vector machine, and extreme gradient boosting. Shapley’s additive explanations identified key predictive features.</div><div>Results show that ML models significantly improved prediction performance (R² = 0.59–0.90) compared to single metric SLR models (R² = 0.09–0.67). Combined LiDAR-spectral models outperformed spectral- and LiDAR-only models. ANN achieved the best results, with a mean R² of 0.90, normalized RMSE of 6 %, and residual prediction deviation (RPD) score of 3.34, accurately predicting LAI up to 5.5 m² m^–2. LiDAR alone or in combination with spectral metrics improved LAI predictions. While some spectral metrics ranked high, LiDAR-derived metrics, particularly canopy volume-related, consistently emerged among the most important features, with gap fraction and height metrics also contributing to the models. This study demonstrates the efficacy of drone-based LiDAR for non-destructively predicting LAI in wheat fields, offering a valuable tool for crop model calibration and evaluation and addressing the challenge of scaling from leaf to canopy.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"372 ","pages":"Article 110648"},"PeriodicalIF":5.6,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144314017","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":"Amazon deforestation intensifies atmospheric aridity through locally dominant biophysical mechanisms","authors":"Mengqi Cheng ,&nbsp;Qinglong You ,&nbsp;Zhiyan Zuo ,&nbsp;Mingcai Li ,&nbsp;Deliang Chen ,&nbsp;Niklas Boers","doi":"10.1016/j.agrformet.2025.110693","DOIUrl":"10.1016/j.agrformet.2025.110693","url":null,"abstract":"<div><div>The Amazon basin has experienced severe deforestation in recent decades; however, the impact of this deforestation on vapor pressure deficit (VPD) remains unclear. VPD is a key variable used to characterize atmospheric aridity. Here, we analyze idealized deforestation experiments with coupled Earth system models, exploring the bidirectional relationship between deforestation and increased VPD. In simulations, Amazon deforestation causes a substantial increase in VPD, and initiated a positive feedback mechanism. We find that 40 % of the deforestation-induced increase in VPD in the Amazon basin is contributed by increasing atmospheric vapor demand, while 60 % is contributed by decreasing atmospheric vapor supply. Specifically, increased local radiative forcing due to changes in shortwave transmissivity and aerodynamic resistance results in local warming, which plays a dominant role in the increase in atmospheric vapor demand. Meanwhile, reduced evapotranspiration caused by deforestation dominates the decrease in atmospheric vapor supply. Our results show a possible existence of a positive feedback mechanism between deforestation and VPD increase in the Amazon, and suggest that large-scale Amazon deforestation may trigger uncontrollable increases in atmospheric aridity.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"372 ","pages":"Article 110693"},"PeriodicalIF":5.6,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144307737","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":"Light grazing tends to enhance ecosystem carbon sequestration and resource use efficiency in a meadow steppe of northern China","authors":"Hongliang Yu,&nbsp;Xu Wang,&nbsp;Yiqian Wu,&nbsp;Chongwei Wang,&nbsp;Ruirui Yan,&nbsp;Dawei Xu,&nbsp;Yuchun Yan,&nbsp;Xiaoping Xin","doi":"10.1016/j.agrformet.2025.110690","DOIUrl":"10.1016/j.agrformet.2025.110690","url":null,"abstract":"<div><div>Grassland ecosystems are particularly sensitive to human disturbances due to their relatively simple structure and limited resource availability. However, the responses of ecosystem carbon and water exchanges to grazing, the dominant human activity in grasslands, remain insufficiently understood. During growing seasons in 2023 and 2024, a grazing gradient experiment was conducted in a meadow steppe of northern China, incorporating four intensity levels: no grazing (CK), light grazing (LG), moderate grazing (MG), and heavy grazing (HG). Using the static chamber method, we assessed ecosystem carbon fluxes (GPP: gross primary production; ER: ecosystem respiration; NEE: net ecosystem CO₂ exchange; Rh: soil heterotrophic respiration), water exchanges (ET: evapotranspiration; EP: soil evaporation), and resource use efficiencies (CUE: carbon use efficiency; WUE: water use efficiency). Results indicated that light grazing significantly enhanced NEE, CUE, and WUE compared to other treatments. In contrast, increasing grazing intensity markedly reduced carbon and water fluxes in MG and HG plots. Under grazing stress, aboveground biomass (AGB) was the primary determinant of GPP and ET changes, while ER was mainly influenced by soil microclimate and nutrients. GPP emerged as the key driver of NEE, CUE, and WUE variations. These findings highlight the contrasting roles of biotic and abiotic factors in regulating ecosystem functions and provide comprehensive evidence that light grazing could benefit carbon sequestration and resource use efficiency in the meadow steppe. Our study can offer practical and theoretical support for determining appropriate grazing intensity and promoting the sustainable management of grasslands in northern China.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"372 ","pages":"Article 110690"},"PeriodicalIF":5.6,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144307736","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":"Long-term variations in the ratio of transpiration to evapotranspiration and their drivers in a humid subalpine forest","authors":"Yuhao Xiang ,&nbsp;Genxu Wang ,&nbsp;Arthur Gessler ,&nbsp;Xiangyang Sun ,&nbsp;Shan Lin ,&nbsp;Zishu Tang ,&nbsp;Shouqin Sun ,&nbsp;Zhaoyong Hu","doi":"10.1016/j.agrformet.2025.110692","DOIUrl":"10.1016/j.agrformet.2025.110692","url":null,"abstract":"<div><div>Identifying the temporal variations in transpiration (T) and its contribution to evapotranspiration (ET) (T/ET) is of great significance for understanding the mechanisms of ecosystem water distribution and energy partitioning. However, there is a lack of knowledge on the long-term variations in T and ET in high-altitude subalpine regions with low temperature and high humidity. Therefore, the T and ET of a subalpine coniferous forest in Mount Gongga was simulated during the growing season from 2005 to 2021 using three machine learning models and a generalized nonlinear complementary principle model. Results showed that the machine learning models performed better in simulating T than the often-applied Penman-Monteith model. The mean daily and growing season T were 1.18 ± 0.14 mm d^-1 and 217.60 ± 17.76 mm yr^-1, respectively. There was a decreasing trend of T during 2005–2021, with a rate of -2.46 mm yr^-1 (<em>P &lt;</em> 0.05). Variation in T was mainly influenced by net radiation, wind speed, vapor pressure deficit, and relative humidity, and the magnitude of these effects varied at different temporal scales (daily, monthly, and annual). Mean growing season T/ET was 0.46 ± 0.03. There was no significant trend in T/ET before 2016 (<em>P &gt;</em> 0.05), but the T/ET significantly decreased thereafter with a rate of 0.01 yr^-1 (<em>P &lt;</em> 0.05). There was no significant difference in T/ET among years with different precipitation at our study site which had always abundant precipitation of &gt;1400 mm. Changes in T/ET were more sensitive to air temperature, and the effect of meteorological factors on T/ET varied at daily, monthly and annual time scales. The decrease in T/ET was primarily due to the continuous increase in temperature in recent years. Our findings indicate that future climate warming will lead to an increase in water resources in subalpine humid regions.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"372 ","pages":"Article 110692"},"PeriodicalIF":5.6,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144305253","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":"Evaluation of a novel approach to partitioning respiration and photosynthesis using eddy covariance, wavelets and conditional sampling","authors":"Pedro Henrique H. Coimbra ,&nbsp;Benjamin Loubet ,&nbsp;Olivier Laurent ,&nbsp;Matthias Mauder ,&nbsp;Bernard Heinesch ,&nbsp;Jonathan Bitton ,&nbsp;Nicolas Delpierre ,&nbsp;Daniel Berveiller ,&nbsp;Jérémie Depuydt ,&nbsp;Pauline Buysse","doi":"10.1016/j.agrformet.2025.110684","DOIUrl":"10.1016/j.agrformet.2025.110684","url":null,"abstract":"<div><div>The eddy covariance (EC) technique remains a cornerstone for direct, continuous monitoring of greenhouse gases fluxes, particularly for carbon dioxide (CO₂). Traditionally, EC-derived net ecosystem exchange (NEE) is partitioned into gross primary productivity (GPP) and ecosystem respiration (<em>R</em>_eco) using model-based approaches. Here, we present a novel, fully empirical partitioning method that applies conditional sampling to wavelet-decomposed signals, isolating positive and negative contributions of the wavelet co-spectrum of vertical wind velocity and CO₂ dry molar fraction, conditioned by the water vapour flux. This method was evaluated across two French ICOS sites, a mixed forest (FR-Fon) and a cropland (FR-Gri), over multiple years.</div><div>The approach is grounded in the hypothesis that wavelet decomposition enables separation of oppositely signed turbulent structures across scales, a claim supported by co-spectral analysis. The resulting flux components exhibited distinct frequency signatures under neutral and unstable atmospheric conditions, though not under stable stratification.</div><div>Daily partitioned fluxes derived from this method aligned well with GPP and <em>R</em>_eco estimates from established nighttime- and daytime-based partitioning, with inter-method differences smaller than those observed between the conventional approaches themselves. Conceptually the method approximates net photosynthesis and offered improved coherence with site-specific ecological and management dynamics, capturing events such as growing season, harvest, and manure application at FR-Gri, more reliably than standard methods. It also avoided spurious GPP estimates common error in the night-time approach. Moreover, the diel <em>R</em>_eco cycle revealed a bimodal pattern, suggestive of combined influences from solar radiation and soil temperature, in contrast to the predominantly single temperature-driven dynamics inferred by conventional models.</div><div>Our findings demonstrate that wavelet-based conditional sampling offers a promising alternative for CO₂ flux partitioning, one that is entirely empirical, calibration-free, and grounded in the physical co-emission dynamics and transport from surface to the atmosphere.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"372 ","pages":"Article 110684"},"PeriodicalIF":5.6,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144297118","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}