Agricultural and Forest Meteorology最新文献

{"title":"Decreasing frequency of low and moderate fire weather days may be contributing to large wildfire occurrence in the northern Sierra Nevada","authors":"Brandon M. Collins","doi":"10.1016/j.agrformet.2025.110688","DOIUrl":"10.1016/j.agrformet.2025.110688","url":null,"abstract":"<div><div>Previous analyses identified large-scale climatic patterns contributing to greater fuel aridity as drivers of recent dramatic increases in wildfire activity throughout California. This study revisits an approach to investigate more local fire weather patterns in the northern Sierra Nevada; a region within California that has experienced exceptionally high wildfire activity recently. The annual percentages of fire season days above 90th and 95th percentile Energy Release Component (ERC) values were very low prior to 1994 (Fig. 3). Since 1994, years with noticeable percentages of exceedances (&gt;20 %) occurred more frequently. However, neither the highest nor second highest annual exceedances occurred after 2012. Starting in the late 1990s and early 2000s there was a decreasing trend in number of fire season days below the 80th and 50th percentile ERC thresholds. Linear trend lines indicated strongly negative declines throughout the study period. The most likely impact of these declines is on the effectiveness of fire suppression, which rely on low to moderate fire weather to “gain ground” on containment. That said, even the combination of both fire weather conditions (greater high fire weather days and lesser low fire weather days) provides an imperfect explanation for the recent increases in burned area. Additional influences, such as dense forest structures, greater fuel continuity, and ignitions (both number and timing of) are likely contributing as well.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"372 ","pages":"Article 110688"},"PeriodicalIF":5.6,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144271152","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":"Coupling crop growth models and machine learning for scalable winter wheat yield estimation across major wheat regions in China","authors":"Jiyuan Xie ,&nbsp;Dongyan Zhang ,&nbsp;Ning Jin ,&nbsp;Tao Cheng ,&nbsp;Gang Zhao ,&nbsp;Dong Han ,&nbsp;Zhen Niu ,&nbsp;Weifeng Li","doi":"10.1016/j.agrformet.2025.110687","DOIUrl":"10.1016/j.agrformet.2025.110687","url":null,"abstract":"<div><div>The temperate continental climate, with its combination of ample sunlight and relatively low humidity during key growth stages, provides favorable conditions for wheat cultivation, reducing disease risks and supporting efficient grain filling. However, spatial heterogeneity in soil properties, crop varieties, and agronomic practices complicates large-scale yield prediction. This study focuses on China, the world's largest wheat producer, to develop an adaptable method for estimating yields in major wheat-growing regions. We coupled the WOFOST model with HYDRUS and CASA to simulate crop growth, soil moisture, and carbon cycling, assimilated remote sensing data for model calibration, and trained a machine learning model using multi-modal data to predict regional-scale winter wheat yields. The model, combining a Bagging Regressor with total above ground production (TAGP), gross primary productivity (GPP), and evapotranspiration (ET), achieved optimal performance (R = 0.83, RRMSE = 0.12) and reduced prediction errors compared to Global-WheatYield4km, with an average error of 1.92%. The model also reliably predicted yields across varying conditions, with discrepancies under 1,000 kg/ha in most counties. This integrated approach enhances yield prediction stability and precision, offering a solid foundation for regional-scale agricultural management.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"372 ","pages":"Article 110687"},"PeriodicalIF":5.6,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144271153","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":"Stability and transferability of broadly trained phenology models in a changing climate","authors":"Lynsay Spafford ,&nbsp;J. Jelle Lever ,&nbsp;Arthur Gessler ,&nbsp;Roman Zweifel ,&nbsp;Barbara Pietragalla ,&nbsp;Jan Dirk Wegner ,&nbsp;Vivien Sainte Fare Garnot ,&nbsp;Christian Sigg ,&nbsp;Yann Vitasse","doi":"10.1016/j.agrformet.2025.110685","DOIUrl":"10.1016/j.agrformet.2025.110685","url":null,"abstract":"<div><div>A variety of phenology process-based models have been developed to simulate environmental influences on the timing of spring and autumn phenophases. Similar performances between different types of mechanistic models have raised questions about reliability of their predictions. To assess the biological relevance of phenology models, we used a seven-decade dataset of five species across 170 sites and 1700 m elevation in Switzerland. We evaluated nine leaf emergence and ten senescence models over time and space. We explored how optimal parameter values and influences vary, reflecting transitions in model aptitude and phenology responses to drivers. Leaf emergence models showed improved predictions at external sites over time, while emergence dates converged across Switzerland. In contrast, leaf senescence models often failed to outperform the null model predicting the mean date of training data and showed divergent performance trends. Trends in optimal parameters indicated species-specific responses to emergence drivers, with cold-climate suited species favouring earlier thresholds for warmth accumulation in spring, while the trends were opposite for warm-climate suited species, except for beech showing stable parameters likely due to strong photoperiod constraints. Warming increased the importance of chilling-related parameters for leaf emergence, while senescence parameter sensitivities remained stable. Spatial analyses revealed that complex models were less robust to training and validation at different elevations than simple models, and that phenological responses may vary non-linearly with elevation, likely due to local adaptations. Senescence models performed better with validation at high elevations, where climatic variables such as cooling temperatures play a large role, while predictions were more challenging at other elevations. These findings highlight the need for further refinement of process-based models to account for all driving influences on plant phenology, particularly for leaf senescence models. Our work demonstrates the potential for process-based modelling techniques to better understand phenology responses to climate change.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"372 ","pages":"Article 110685"},"PeriodicalIF":5.6,"publicationDate":"2025-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144262432","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":"Warming temperatures and decreasing soil moisture are increasing tree mortality in mature Douglas-fir forests of western Oregon, USA","authors":"Steven P. Cline,&nbsp;E. Henry Lee,&nbsp;Ronald S. Waschmann,&nbsp;Michael A. Bollman,&nbsp;Peter A. Beedlow","doi":"10.1016/j.agrformet.2025.110681","DOIUrl":"10.1016/j.agrformet.2025.110681","url":null,"abstract":"<div><div>Temporal patterns of tree mortality were determined for naturally regenerated Douglas-fir-dominated (<em>Pseudotsuga menziesii</em> (Mirb.) Franco) conifer stands, aged from about 125 to 500+ years, along an elevational gradient in western Oregon, USA based on periodic mortality surveys. Tree mortality increased from 2000 to 2023, a prolonged period of drought and warming. Soil moisture, air temperature, and vapor pressure deficit (VPD) were the key climatic predictors of tree mortality for all sites, species, and canopy classes based on logistic regression modeling. Increasing trends in annual probability of mortality were associated with decreasing summer available soil water and increasing summer temperature and associated VPD. These trends were most pronounced at mid-elevation (∼600 m) sites west of the Cascade crest, and they were higher for small diameter trees in suppressed and intermediate canopy class positions compared with co-dominant and dominant trees for all sites and species. Competition exacerbated the climate effects on mortality of small trees at drier sites. Insect-induced mortality was evident in large Douglas-fir following prolonged drought and high summer temperatures. In recent decades, long-term soil drying associated with warming temperatures appears to underlie tree mortality in these mesic forests of western Oregon.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"372 ","pages":"Article 110681"},"PeriodicalIF":5.6,"publicationDate":"2025-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144262433","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":"A process model-guided transfer learning framework for mapping global gross primary production","authors":"Xiaobin Guan ,&nbsp;Yuyu Li ,&nbsp;Jing M. Chen ,&nbsp;Yongming Ma ,&nbsp;Huanfeng Shen","doi":"10.1016/j.agrformet.2025.110678","DOIUrl":"10.1016/j.agrformet.2025.110678","url":null,"abstract":"<div><div>Accurate estimation of gross primary production (GPP) is critical for global carbon cycle research. The current mainstream approaches, i.e., process-based models, are limited by insufficient parameter representation and high computing costs, and the burgeoning machine learning methods still suffer from inadequate training samples and poor transferability when applied to GPP estimation. Therefore, in this paper, we propose a process model-guided transfer learning approach for global GPP estimation, taking the low-resolution (0.5°) estimates from the Biosphere-atmosphere Exchange Process Simulator (BEPS) model as the source domain and eddy covariance (EC) data as the target domain. After joint constraint from the two domains, relatively high-accuracy GPP estimation at a resolution of 0.05° can be achieved after downscaled pre-training and fine-tuning based on EC tower data. The results indicate that the proposed framework can significantly improve the accuracy of GPP estimation, compared to a direct machine learning method based on only EC tower data (ΔR² = 0.05, ΔRMSE = −1.02 g C m^-2month^-1) and the original BEPS estimates (ΔR² = 0.05, ΔRMSE = −14.14 g C m^-2month^-1). The results of the temporal validation and regional cross-validation also show consistent results, indicating the superior spatio-temporal expandability of the proposed method. Furthermore, when compared with other global GPP products, the new global GPP product built in this study can effectively correct the underestimation/overestimation in high/low GPP regions in the existing machine learning-based GPP products (e.g., FLUXCOM GPP), especially in the area near the equator, and shows higher consistency with solar-induced chlorophyll fluorescence (SIF)-based and model-based GPP products. In addition to the new global GPP product, the results of this study also prove the reliability of combining a process-based model and a machine learning model in GPP estimation.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"372 ","pages":"Article 110678"},"PeriodicalIF":5.6,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144254341","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-biome assessment of tree water use resilience to drought","authors":"Brenda V. Fatecha ,&nbsp;Jordi Martínez-Vilalta ,&nbsp;Maurizio Mencuccini ,&nbsp;Rafael Poyatos","doi":"10.1016/j.agrformet.2025.110666","DOIUrl":"10.1016/j.agrformet.2025.110666","url":null,"abstract":"<div><div>Drought frequency and severity are increasing in many regions, impacting forest functioning and dynamics, with effects that can result in widespread tree death and ecosystem shifts. These events have been linked to soil and atmospheric hydrological changes, but the causes of different responses in tree water-use are poorly understood at the global scale. We used data from the SAPFLUXNET global database to assess water-use resilience to drought of &gt; 900 trees of 96 different species in 89 plots distributed across the globe. We detected decreases in water-use resilience when soil water availability was lower before, during or after the drought. Atmospheric drought enhanced resilience during the pre-drought period, but diminished it post-drought. Resilience was also favoured by longer recovery periods since the last, previous drought, and in larger diameter trees. Hydraulic and water relations traits also played a role in determining differences in tree water-use resilience across species. Species that were more vulnerable to stem xylem embolism (less negative P50) or had a more negative turgor loss point exhibited higher water-use resilience (and resistance). Our findings help to better understand the drivers of water use resilience and therefore contribute to our understanding of how trees respond to severe droughts at multiple spatio-temporal scales.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"372 ","pages":"Article 110666"},"PeriodicalIF":5.6,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144262434","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":"Daytime water and CO2 exchange within and above the Amazon rainforest","authors":"Raquel González-Armas ,&nbsp;Daniël Rikkers ,&nbsp;Oscar Hartogensis ,&nbsp;Cléo Quaresma Dias-Júnior ,&nbsp;Shujiro Komiya ,&nbsp;Giovanni Pugliese ,&nbsp;Jonathan Williams ,&nbsp;Hella van Asperen ,&nbsp;Jordi Vilà-Guerau de Arellano ,&nbsp;Hugo J. de Boer","doi":"10.1016/j.agrformet.2025.110621","DOIUrl":"10.1016/j.agrformet.2025.110621","url":null,"abstract":"<div><div>We studied the sub-hourly variability of water and CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> fluxes within and above the Amazon tropical forest during the dry season. Our aim was to investigate how forest layers contribute to the net ecosystem exchange (NEE) and evapotranspiration (ET) by accounting for the existing vertical profiles of leaf traits and microclimate, and the presence of clouds. To this end, we estimated NEE and ET with a 3-layer land-surface model driven by vertical profiles observed at the Amazon Tall Tower Observatory (ATTO) site during CloudRoots-Amazon22 field campaign. Our analysis focused on a typical “shallow-convective” day, composed of 6 individual days with similar conditions. The observed vertical profiles characterized microclimatic variables (photosynthetic active radiation, air temperature, humidity, CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span>, wind and turbulence) as well as leaf traits (maximum carboxylation rate, <span><math><msub><mrow><mi>V</mi></mrow><mrow><mi>cmax</mi></mrow></msub></math></span>; maximum electron transport, <span><math><msub><mrow><mi>J</mi></mrow><mrow><mi>max</mi></mrow></msub></math></span>; and ¹³C leaf isotopic composition, <span><math><mrow><msup><mrow><mi>δ</mi></mrow><mrow><mn>13</mn></mrow></msup><msub><mrow><mi>C</mi></mrow><mrow><mi>p</mi></mrow></msub></mrow></math></span>) across three layers that represented the understory, the mid-canopy and the forest top-crown. The modeled NEE and ET were subsequently compared with eddy-covariance (EC) fluxes observed above the canopy.</div><div>We found distinctive vertical profiles of leaf traits and microclimate that were maintained during most of the day. In particular, we observed a persistent inversion of temperature within the canopy which hindered air mixing between the top-crown and the lower layers. Modeled NEE and ET fluxes were comparable in magnitude to the EC-measured fluxes, with flux dynamics dominated by the exchange of the top-crown layer. However, differences between observed and modeled NEE emerged during the morning transition (from 7:30 to 9:00 LT), when CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> stored within the canopy overnight was released. We conclude that tropical forests exhibit complex, distinctive vertical profiles of microclimate and leaf traits that influence the water and CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> vegetation exchange and the transport of air within the canopy.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"372 ","pages":"Article 110621"},"PeriodicalIF":5.6,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144252568","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":"Subtropical vegetation damage and recovery dynamics after the great 2008 Chinese ice storm","authors":"Yujiu Xiong ,&nbsp;Wenjie Yan ,&nbsp;Xu Wang ,&nbsp;Yong Luo ,&nbsp;Hanhua Feng ,&nbsp;Wenli Zhao ,&nbsp;Biqing Zhu ,&nbsp;Zhenhua Ye ,&nbsp;Hao Li","doi":"10.1016/j.agrformet.2025.110683","DOIUrl":"10.1016/j.agrformet.2025.110683","url":null,"abstract":"<div><div>In early 2008, an extreme ice storm struck southern China, including the subtropical Guangdong Province, causing substantial ecological damage and economic losses. Previous evaluations of vegetation damage during this event primarily focused on the immediate physical structure damage caused by ice, overlooking the delayed physiological damage from extreme low-temperature stress, especially in adjacent non-frozen regions. Combining remotely-sensed (i.e., MODIS Gross Primary Productivity (GPP) and Enhanced Vegetation index (EVI)) and in-situ data, we conducted a more complete assessment of subtropical vegetation damage and recovery following the 2008 Chinese ice storm by considering time-lag effects. We found vegetation damage and subsequent recovery exhibited distinct spatial patterns correlated to ice storm severity. Assessments that accounted for time-lag effects were more aligned with ground truth, revealing that vegetation damage signal typically lagged the event onset by 1–2 months. The time-lag effect showed distinct patterns in non-frozen regions experiencing secondary low-temperature stress (without direct ice storm exposure). Physiological damage dominated these areas, reducing GPP by 62 %. In contrast, physical structural damage caused a comparatively smaller decline (51 %) in EVI. We also found a positive correlation between frozen time and the severity of vegetation damage, with 37 % of vegetation damaged in less frozen zone versus 70 % in severe frozen zone. Subsequent recovery of GPP and EVI to pre-ice storm conditions took 4–9 months, with GPP recovering faster than EVI, especially in severe frozen forests. Such positive correlation also existed between damage severity (or recovery time) and elevation and slope, but the pattern varied across different freezing zones. Our findings highlight the delayed physiological damage from extreme low-temperature stress and provide new insights into subtropical vegetation dynamics following extreme ice storms.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"372 ","pages":"Article 110683"},"PeriodicalIF":5.6,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144242039","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":"Water availability regulates the carbon uptake period and amplitude of net ecosystem exchange in alpine grasslands of the Qinghai-Xizang Plateau","authors":"Fuquan He ,&nbsp;Qi Li ,&nbsp;Dongdong Chen ,&nbsp;Caiyun Luo ,&nbsp;Yukun Zhang ,&nbsp;Li Zhang ,&nbsp;Sichen Pan ,&nbsp;Zongjian Zhao ,&nbsp;Liang Zhao","doi":"10.1016/j.agrformet.2025.110656","DOIUrl":"10.1016/j.agrformet.2025.110656","url":null,"abstract":"<div><div>The Qinghai-Xizang Plateau (QZP) alpine ecosystem serves as a critical carbon (C) sink, with its seasonal and interannual variation in C assimilation capacity regulated by climatic factors. The C sequestration process in alpine grasslands on the QZP can be divided into the C uptake period (CUP) and the C emission period. However, the relative contributions of these periods to the interannual variability of net ecosystem exchange (NEE) remain unclear. In this study, we decomposed the annual NEE of QZP alpine ecosystems into phenological and physiological components, focusing on the CUP and the maximum rate of net C uptake (MCU). We analyzed interannual anomalies in seasonal and annual NEE, CUP, and MCU in relation to climatic variables across various alpine ecosystems, including alpine meadows (11 sites), alpine wetlands (seven sites), alpine shrub meadows (two sites), alpine steppes (three sites), and tame grasslands (one site). Our key findings indicate that alpine steppes exhibited the longest CUP but the lowest MCU, whereas tame grasslands had a shorter CUP than natural grasslands. Alpine wetlands demonstrated the highest MCU. Across the 84 site-years studied, we found that NEE was predominantly influenced by CUP, which accounted for 38 % of its variability, whereas MCU explained 18 %. The beginning date of the CUP (BDOY) in natural grasslands was primarily driven by spring precipitation. Summer water availability negatively affected MCU in natural grasslands but had a positive effect in tame grasslands. In contrast, human management practices (e.g., sowing and harvesting) determined the CUP of tame grasslands and, consequently, their interannual NEE variability. Winter ecosystem respiration (RE), which accounted for 15 % of annual RE, was largely controlled by snowfall and net radiation. The length of the CUP was determined by early-season precipitation and grassland type, contributing to interannual NEE variability and ecosystem differences.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"372 ","pages":""},"PeriodicalIF":5.6,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144237876","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":"Beyond meteorological data: Modelling tree growth with ERA5-Land","authors":"Marian Schönauer ,&nbsp;Christoph Pucher ,&nbsp;Jan Altman ,&nbsp;Josef Weißbacher ,&nbsp;Lars Sprengel ,&nbsp;Boris Rewald","doi":"10.1016/j.agrformet.2025.110679","DOIUrl":"10.1016/j.agrformet.2025.110679","url":null,"abstract":"<div><div>Forests are increasingly impacted by climate change, affecting tree growth and carbon sequestration. Tree-ring width, closely related to tree growth, is a key climate proxy, yet models describing ring width or growth often lack comprehensive environmental data. This study assesses ERA5-Land data for tree-ring width prediction compared to automatic weather station observations, emphasizing the value of extended and global climate data.</div><div>We analyzed 723 site-averaged and detrended tree-ring chronologies from two broadleaved and two gymnosperm species across Europe, integrating them with ERA5-Land climate data, CO₂ concentration, and a drought index (SPEI12). A subset was compared with weather station data. For modelling interannual variations of tree-ring width we used linear models to assess parameter importance.</div><div>ERA5-Land and weather-station-based models performed similarly, maintaining stable correlations and consistent errors. Models based on meteorological data from weather stations highlighted SPEI12, sunshine duration, and temperature extremes, while ERA5-Land models emphasized SPEI12, dew-point temperature (humidity), and total precipitation. CO₂ positively influenced the growth of gymnosperm species. ERA5-Land facilitated broader spatial analysis and incorporated additional factors like evaporation, snow cover, and soil moisture. Monthly assessments revealed the importance of parameters for each species.</div><div>Our findings confirm that ERA5-Land is a reliable alternative for modeling tree growth, offering new insights into climate-vegetation interactions. The ready availability of underutilized parameters, such as air humidity, soil moisture and temperature, and runoff, enables their inclusion in future growth models. Using ERA5-Land can therefore deepen our understanding of forest responses to diverse environmental drivers on a global scale.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"372 ","pages":"Article 110679"},"PeriodicalIF":5.6,"publicationDate":"2025-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144230797","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}