Agricultural and Forest Meteorology最新文献

{"title":"Assessing evapotranspiration in rainfed and irrigated Alfalfa in the U.S. southern great plains using eddy covariance measurements and OpenET products","authors":"Pradeep Wagle ,&nbsp;Afshin Shayeghi ,&nbsp;Nishan Bhattarai ,&nbsp;Brian K. Northup ,&nbsp;Corey Moffet ,&nbsp;Stacey A. Gunter ,&nbsp;Rudra Baral","doi":"10.1016/j.agrformet.2026.111032","DOIUrl":"10.1016/j.agrformet.2026.111032","url":null,"abstract":"<div><div>Understanding the annual dynamics of water use by rainfed and irrigated alfalfa (<em>Medicago sativa</em> L.) can support its sustainable management. Changes in evapotranspiration (ET) and plant growth patterns of alfalfa across years are scarce and are not well understood in the Southern Great Plains (SGP) of the United States (U.S.). The objectives of this study were to investigate the dynamics of eddy covariance (EC) measured ET (ET_EC) and its controlling factors in rainfed and irrigated alfalfa and to compare ET_EC dynamics with OpenET products that provide several established remote sensing-based ET model products (METRIC, PTJPL, SIMS, SSEBop, SEBAL, and DisALEXI) across the western U.S. The ET_EC showed notable seasonal and interannual dynamics driven by meteorological conditions, vegetation dynamics, and water availability. Warmer and wetter conditions in April 2019 promoted initial alfalfa growth. Alfalfa’s water use (ET) mirrored its growth pattern throughout the year. Daily ET_EC rates and cumulative ET_EC at annual and seasonal scales were substantially lower than those reported for highly productive irrigated alfalfa in past studies. Satellite-derived enhanced vegetation index (EVI) and solar radiation (SR) explained 75% and 88% of variations in ET_EC for all sites combined at 8-day and monthly scales, respectively. It indicates the potential of developing empirical models using readily available EVI and SR data to monitor alfalfa ET across large areas. When compared to ET_EC, the performance of OpenET models varied widely, depending on field scenarios and criteria applied to model evaluations. SIMS and SSEBop demonstrated consistency and reliability in estimating ET for rainfed and irrigated alfalfa. DisALEXI and SEBAL performed poorly in irrigated alfalfa. METRIC and PTJPL exhibited poor performances under rainfed and irrigated conditions. By examining water use dynamics by alfalfa and the reliability of OpenET products, this study provides crucial information for effective water management practices for alfalfa.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"379 ","pages":"Article 111032"},"PeriodicalIF":5.7,"publicationDate":"2026-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145996210","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":"Improving the MCWLA agroecosystem model to better simulate methane emissions from paddy rice fields","authors":"Hong Zhou ,&nbsp;Fulu Tao ,&nbsp;Yi Chen ,&nbsp;Lichang Yin ,&nbsp;Yibo Li","doi":"10.1016/j.agrformet.2026.111053","DOIUrl":"10.1016/j.agrformet.2026.111053","url":null,"abstract":"<div><div>Rice cultivation stands out as a major greenhouse gas source, emitting 10–20% of global CH₄ emissions. How to accurately estimate CH₄ emissions from paddy rice and their mitigation potential has been key concerns. Agroecosystem models have unique advantages in understanding CH₄ processes, simulating CH₄ emissions dynamics, optimizing management practices, and quantifying mitigation potentials. However, current agroecosystem models need to be substantially improved for these purposes. In this study, we develop a comprehensive agroecosystem model, MCWLA-Rice 2.0, to better depict the production, oxidation, and emission processes of CH₄ and improve the simulation of root exudates, the effect of nitrate fertilizer on CH₄ emissions, and the decomposition of external organic carbon. We calibrate and validate the model and demonstrate its performance in simulating the rice cultivation system under different fertilizer and irrigation treatments at seven sites across Asia. Elaborating on both aboveground and belowground carbon-nitrogen coupling processes, MCWLA-Rice 2.0 is a valuable tool for simulating rice productivity and CH₄ emissions under various environments and managements, effectively supporting the development of climate-smart agriculture.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"379 ","pages":"Article 111053"},"PeriodicalIF":5.7,"publicationDate":"2026-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146129310","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":"Temperature and photoperiod interactions influence the cessation of wood growth in three temperate and boreal conifers","authors":"Jianhong Lin ,&nbsp;Cyrille B.K. Rathgeber ,&nbsp;Patrick Fonti ,&nbsp;Sergio Rossi ,&nbsp;Henri Cuny ,&nbsp;Edurne Martinez del Castillo ,&nbsp;Katarina Čufar ,&nbsp;J. Julio Camarero ,&nbsp;Alessio Giovannelli ,&nbsp;Harri Mäkinen ,&nbsp;Peter Prislan ,&nbsp;Walter Oberhuber ,&nbsp;Hanuš Vavrčík ,&nbsp;Jianguo Huang ,&nbsp;Andreas Gruber ,&nbsp;Vladimír Gryc ,&nbsp;Václav Treml ,&nbsp;Martin de Luis ,&nbsp;Jožica Gričar ,&nbsp;Nicolas Delpierre","doi":"10.1016/j.agrformet.2026.111056","DOIUrl":"10.1016/j.agrformet.2026.111056","url":null,"abstract":"<div><div>Cambium phenology is a crucial process in wood production and carbon sequestration of forest ecosystems. Although cambium phenology has been widely studied, research specifically focusing on the cessation of wood formation remains limited. To better understand the influence of environmental and intrinsic factors on the cessation of wood formation, we built and compared three ecophysiological models (<em>temperature sum</em> model, <em>photoperiod-influenced temperature sum</em> model and <em>soil moisture- and photoperiod-influenced temperature sum</em> model) in their ability to predict the date of cessation of xylem cell enlargement (cE) in three major Northern Hemisphere conifer species (Black spruce, Norway spruce and Scots pine). We developed these models based on xylogenesis data collected for 130 site‐years across Europe and Canada. Our results demonstrate that the <em>photoperiod-influenced temperature sum</em> model is well-supported by data across all conifer species, with a RMSE of 9.2 days, suggesting that both temperature and photoperiod are critical drivers of wood growth cessation. However, incorporating soil moisture effects does not improve model performance. Our model effectively captures the inter-site variability in cE across a wide environmental gradient, with a fair model efficiency (ME = 0.51 ± 0.22), but performed less well for annual anomalies (ME = 0.10 ± 0.09). Additionally, we found that the total ring cell number also affected prediction accuracy. Using this model, we reconstructed historical trends in cE over the past six decades and found a trend to delayed cessation dates. This delay varied geographically, with slower shifts at higher latitudes and elevations, likely due to constrained cambial responses and conservative growth strategies in colder regions. Our model framework offers a simple yet accurate approach for predicting wood growth cessation at large spatial scales, providing a basis for integrating cambium phenology into land surface models and forest productivity assessments.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"379 ","pages":"Article 111056"},"PeriodicalIF":5.7,"publicationDate":"2026-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146129311","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":"Net ecosystem carbon balance and greenhouse gas budget of a canola-wheat cropping system in the northern prairies","authors":"D. Ferland ,&nbsp;C. Wagner-Riddle ,&nbsp;P․K․C Pow ,&nbsp;S․E. Brown ,&nbsp;K․A. Congreves","doi":"10.1016/j.agrformet.2026.111044","DOIUrl":"10.1016/j.agrformet.2026.111044","url":null,"abstract":"<div><div>Arable croplands are critical in the context of climate change, acting as both sources and potential sinks of greenhouse gases (GHG) in the form of carbon dioxide (CO₂) and nitrous oxide (N₂O). However, there is limited data on the carbon (C) balance and GHG budget (GHGB) from canola-wheat rotations in the northern Prairies of North America, an important agricultural region. We present micrometeorological GHG fluxes measured from January 2021 to April 2025 through two rotations of canola-wheat in Saskatchewan, Canada, to evaluate the interannual C dynamics and GHGB of the 4-year cropping sequence. Net ecosystem exchange (NEE) ranged from 87 to -239 g C m^-2, driven by variable meteorological conditions. Annual cumulative gross primary production (GPP) exceeded the cumulative ecosystem respiration (<em>R</em>_<em>e</em>) in all years except 2021—the second driest year on record for this region. The GHGB values were between 60 and 156 CO₂-eq m^-2 yr^-1 in the first 3 crop years, but were negative (i.e., GHG sink) in Year 4. Overall, this study presents the first multi-year, measurement-based assessment of canola-wheat rotations in the northern Prairies, showing that over a 4-year period, the cropping system was C neutral (net ecosystem carbon balance [NECB] = 2 ± 35 g C m^-2 yr^-1). The dataset provides the region-specific information needed to inform C policy and evaluate the agricultural sustainability of the northern Prairies. It also provides valuable information for canola and wheat crops, particularly the impact of harvest removals and N fertilizer application—practices that can be targeted for agricultural GHG emissions mitigation.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"379 ","pages":"Article 111044"},"PeriodicalIF":5.7,"publicationDate":"2026-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146135047","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":"The efficiency-level inconsistency of the SIF–GPP relationship in a subtropical evergreen forest in Okinawa, Japan","authors":"Junjie Fu ,&nbsp;Tomomichi Kato ,&nbsp;Tomoki Morozumi ,&nbsp;Kazuho Matsumoto ,&nbsp;Shingo Taniguchi ,&nbsp;Masahito Ueyama ,&nbsp;Kanokrat Buareal ,&nbsp;Tatsuya Miyauchi ,&nbsp;Naohisa Nakashima ,&nbsp;Tomoko Kawaguchi Akitsu","doi":"10.1016/j.agrformet.2026.111050","DOIUrl":"10.1016/j.agrformet.2026.111050","url":null,"abstract":"<div><div>Monitoring of photosynthetic activity is essential for understanding forest carbon dynamics, particularly in structurally stable but physiologically dynamic ecosystems such as subtropical evergreen broadleaf forests. This study investigated the seasonal and diurnal dynamics of far-red and red solar-induced chlorophyll fluorescence (SIF), gross primary productivity (GPP), and related metrics in a subtropical evergreen broadleaf forest in Okinawa, Japan, on the basis of ground-based observations from 2020 to 2022. Far-red SIF consistently exhibited stronger and more stable correlations with GPP than red SIF, especially under overcast conditions and at daily temporal resolution. However, a significant environmental divergence was observed in the efficiency metrics. Environmental binning analyses revealed that light-use efficiency (LUE) responded strongly to changes in vapor pressure deficit (VPD), whereas SIF yield exhibited much weaker sensitivity<strong>.</strong> Random forest analysis further supported this divergence, showing a distinct, time-dependent sensitivity of SIF yield and LUE to VPD. Consistent with these environmental sensitivities, diurnal patterns showed that a pronounced inconsistency emerged at the efficiency level: the relationship between far-red SIF yield and LUE was generally weak or non-significant, indicating asynchronous regulation of fluorescence efficiency and carbon assimilation. Diurnal analyses showed that this decoupling could become more pronounced under certain conditions, such as during the afternoon. These findings refine the interpretation of SIF-based indicators in dense evergreen canopies and underscore the importance of the efficiency-level asynchronous recovery for improving SIF-based GPP models in subtropical ecosystems.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"379 ","pages":"Article 111050"},"PeriodicalIF":5.7,"publicationDate":"2026-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146071842","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":"Multi-layer model requires accurate information of vertical structure to realize its full potential in simulating gross primary production","authors":"Jiangliu Xie ,&nbsp;Gaofei Yin ,&nbsp;Shangrong Lin ,&nbsp;Xiaozhou Xin ,&nbsp;Hu Zhang ,&nbsp;Xinjie Liu ,&nbsp;Qinhuo Liu ,&nbsp;Aleixandre Verger ,&nbsp;Adrià Descals ,&nbsp;Iolanda Filella ,&nbsp;Josep Peñuelas","doi":"10.1016/j.agrformet.2026.111036","DOIUrl":"10.1016/j.agrformet.2026.111036","url":null,"abstract":"<div><div>Photosynthesis, a vital process for carbon exchange between biosphere and atmosphere, has been integrated into terrestrial biosphere models (TBMs). TBMs employ upscaling methods such as big-leaf (BL), two-leaf (TL), or multi-layer (MTL) models to simulate canopy-scale photosynthesis, with MTL model theoretically offering the highest accuracy due to its detailed canopy representation. The comparative efficacy of these models in simulating gross primary production (GPP), however, remains uncertain. This study provides a systematic assessment of how the MTL differs from the BL and TL models in GPP estimation across global flux tower sites.</div><div>The results indicate that both the MTL and TL models performed better than BL model in simulating canopy GPP, reducing root mean square error (RMSE) by 32.23% and 26.51%, respectively, with the MTL (2.25 g C m⁻² d⁻¹) demonstrating a slightly improved accuracy compared to the TL model (2.44 g C m⁻² d⁻¹). Incorporating foliar clumping reduced the overestimation of GPP with mean error (ME) decreasing by 32%, 28.74%, and 6.94% for MTL, TL, and BL models, respectively; however, the specific impact varied among the models. The MTL model excelled in enabling layered simulations of photosynthesis, allowing for the identification of vertical heterogeneity in environmental responses. Nonetheless, its improvement in accuracy over simpler models like the TL model was limited without highly precise data on vertical structure. This study highlights that improved canopy structure data from LiDAR technologies, such as GEDI, is crucial for realizing the full potential of MTL models for accurately simulating carbon fluxes.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"379 ","pages":"Article 111036"},"PeriodicalIF":5.7,"publicationDate":"2026-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146110719","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":"Evaluating surface fluxes in WRF using eddy-covariance flux measurements in the Western and Eastern U.S.","authors":"Fan Wu ,&nbsp;Kenneth J. Davis ,&nbsp;Li Zhang ,&nbsp;Ray G. Anderson ,&nbsp;Jason P. Horne ,&nbsp;Sarah Goslee ,&nbsp;William Munger ,&nbsp;Chenxia Cai ,&nbsp;Yu Yan Cui ,&nbsp;Zhan Zhao ,&nbsp;Min Zhong","doi":"10.1016/j.agrformet.2026.111029","DOIUrl":"10.1016/j.agrformet.2026.111029","url":null,"abstract":"<div><div>Atmospheric boundary layer simulations in weather models, important elements of air quality simulations, are coupled with land surface parameterizations. The San Joaquin Valley (SJV) of California and the Multi-state Mid-Atlantic (MMA) feature diverse land uses, including agriculture, urban areas, and forests, which pose challenges for simulating surface fluxes. This study evaluates surface fluxes in the Weather Research and Forecasting (WRF) model using physical configurations adopted by state air quality agencies in California and Pennsylvania. We compared WRF simulations with year-long eddy-covariance flux measurements from 16 sites across the two regions. Results show that the Pleim-Xiu land surface model (PX LSM) exhibits substantial heat flux biases in the SJV but lacks systematic biases in the MMA. In the SJV, the model overestimates daytime (10:00-16:00 LST) sensible heat flux (H) by 260 W m^-2 (274%) and underestimates latent heat flux (LE) by 200 W m^-2 (68%) at irrigated croplands and orchards during spring and summer. In the MMA, PX LSM moderately overestimates both H and LE, with stronger partitioning into H over urban surfaces and into LE over vegetation. Daytime momentum fluxes are overestimated in both regions, while nighttime biases are inconsistent. Our findings suggest that in the SJV, heat flux biases are strongly associated with irrigation during the growing season, while in the MMA, model-data residuals are limited to modest errors in the Bowen ratio and depend on land cover. Improving WRF’s representation of irrigation and land use, potentially through satellite remote sensing, may enhance surface flux simulation accuracy.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"379 ","pages":"Article 111029"},"PeriodicalIF":5.7,"publicationDate":"2026-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146110944","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":"The influence of spatial correlations in crop production on global crop failures in model simulations","authors":"Sifang Feng ,&nbsp;Jakob Zscheischler ,&nbsp;Zengchao Hao ,&nbsp;Jonas Jägermeyr ,&nbsp;Christoph Müller ,&nbsp;Emanuele Bevacqua","doi":"10.1016/j.agrformet.2026.111021","DOIUrl":"10.1016/j.agrformet.2026.111021","url":null,"abstract":"<div><div>Spatial correlation between climate variables may modulate concurrent regional crop failures and reduce global crop production. However, the influence of spatial correlation in crop production fields on globally aggregated production remains poorly understood. Systematically addressing this gap using observed crop production is challenging, as such observational datasets typically suffer from limited sample sizes and/or coarse spatial information. Here, using gridded global simulations from the Global Gridded Crop Model Intercomparison Phase 3 (GGCMI3), we quantify how spatial correlation between regional crop productions influences global production across different spatial scales for maize, wheat, soybean, and rice. By employing the mean of crop production from multiple crop models forced with reanalysis climate data, we find minimal influence of the correlations between the productions of major breadbasket regions on global breadbasket-aggregated production. This aligns with the fact that global major breadbasket regions are generally non-large and distant from each other, whereas spatial correlations in the crop production field influence global crop production through correlations between small and nearby areas. The correlation between crop production of areas characterized by small spatial scales (100–1000 km) enhances extremely low (5th percentile) global production by about 0.9-1.1 standard deviation of the global production on average. This correlation effect at small spatial scales is less important for weaker extremes of low global crop production. Finally, crop model simulations forced with bias-corrected climate simulations often are not able to reproduce the correlation effects seen in crop model simulations forced with reanalysis climate data, suggesting that bias-corrected climate model input may degrade correlation effects in GGCMI3 crop simulations. These model-based results highlight that spatial correlations are a critical driver of global production risk, stressing the need for improved cross-regional processes representation in crop models to enhance future food security risk assessments.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"379 ","pages":"Article 111021"},"PeriodicalIF":5.7,"publicationDate":"2026-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146080637","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":"Observed declining strength of vegetation-atmosphere coupling","authors":"Shijie Li ,&nbsp;Guojie Wang ,&nbsp;Shanlei Sun ,&nbsp;Zefeng Chen ,&nbsp;Matteo Mura ,&nbsp;Jiao Lu ,&nbsp;Qi Liu ,&nbsp;Ji Li ,&nbsp;Daniel Fiifi Tawia Hagan ,&nbsp;Almudena García-García ,&nbsp;Jian Peng","doi":"10.1016/j.agrformet.2026.111051","DOIUrl":"10.1016/j.agrformet.2026.111051","url":null,"abstract":"<div><div>Land-atmosphere coupling (LAC) directly influences the occurrence of extreme climate events. Traditionally, the studies of LAC strength have primarily used soil moisture as a proxy for land conditions. However, recent research has highlighted the significant role of vegetation–atmosphere coupling (VC) in the evolution of extreme climate events through its regulation of the water and energy cycles. Despite this progress, the global patterns and driving mechanisms of VC remain unclear. In this study, the index with a clear physical meaning, ω, defined as the relationship between the canopy conductance (g_c) and aerodynamic conductance (g_a), was introduced to represent VC values. Long-term (1981–2018) global annual VC values were derived using two high-quality reanalysis datasets (ERA5 and MERRA2) based on two different g_c models. Both g_c models exhibited similar spatial distributions that the highest VC values in Arid regions, the lowest in Humid regions, and intermediate values in Transition zones. Results showed 38.84–61.98 % of global land with decreasing VC trend. An attribution analysis using a nonlinear machine learning approach revealed that leaf area index (LAI) and wind speed dominated the VC changes across different climate zones. An increase in LAI reduced VC strength, whereas enhanced wind speed increased VC values. LAI was the dominant factor influencing VC through transpiration regulation (i.e., g_c) over Transition and Arid regions, while wind speed controlled VC variations via g_a over Humid regions. Our study analyzed the spatiotemporal changes in VC values and their driving mechanisms across global land areas. These findings contribute to a deeper understanding of vegetation-climate feedback and its role in amplifying extreme climate events.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"379 ","pages":"Article 111051"},"PeriodicalIF":5.7,"publicationDate":"2026-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146110945","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":"Regulatory mechanisms of spatiotemporal variations in aboveground and belowground net primary production in global terrestrial ecosystems","authors":"Tao Zhou ,&nbsp;Yanting Xiong ,&nbsp;Zhihan Yang ,&nbsp;Yuting Hou ,&nbsp;Yuqing Zhang ,&nbsp;Dan Liao ,&nbsp;Xiaodong Wang ,&nbsp;Dinghui Xu ,&nbsp;Pingfeng Li ,&nbsp;Peng Hou ,&nbsp;Wenji Zhao ,&nbsp;Guo Chen ,&nbsp;Benjamin Laffitte ,&nbsp;Xiaolu Tang","doi":"10.1016/j.agrformet.2026.111055","DOIUrl":"10.1016/j.agrformet.2026.111055","url":null,"abstract":"<div><div>Net primary productivity is a critical component of terrestrial carbon cycling and an essential indicator of ecosystem carbon sequestration capacity. However, separating aboveground and belowground net primary productivity (ANPP and BNPP) and understanding the driving mechanisms of their spatial patterns remain challenging across global terrestrial ecosystems. Here, we used a modified multilayer perceptron network (MLP) built upon an updated database containing 5184 field observations to predict the spatiotemporal patterns of ANPP and BNPP and identify their driving mechanisms across global terrestrial ecosystems at 0.05° resolution. Results indicated that the MLP model satisfactorily predicted ANPP (<em>R</em>² = 0.74) and BNPP (<em>R</em>² = 0.73). Spatially, both ANPP and BNPP exhibited strong spatial heterogeneity, with a decreasing trend from the tropics toward the poles. Temporally, ANPP showed an increasing trend of 0.02 Pg C yr⁻², with a global mean of 33.4 ± 0.5 (mean ± standard error) Pg C yr⁻¹ from 1981 to 2018. Similarly, the mean total BNPP was 19.2 ± 0.73 Pg C yr⁻¹, with an increasing trend of 0.05 Pg C yr⁻². Quantitatively, significant trends were observed, with 65.4% and 60.8% of land areas showing increasing trend of ANPP and BNPP (<em>P</em> &lt; 0.01), respectively. The spatial patterns of ANPP were mainly influenced by temperature and precipitation, while BNPP was controlled by soil properties. These findings highlight the importance of distinguishing ANPP and BNPP to better understand the driving mechanisms of carbon allocation strategies. These findings are crucial for advancing the understanding of vegetation dynamics in response to global climate change and improving terrestrial ecosystem carbon modeling.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"379 ","pages":"Article 111055"},"PeriodicalIF":5.7,"publicationDate":"2026-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146135056","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}