Agricultural and Forest Meteorology最新文献

{"title":"Degradation mechanisms and restoration strategies of Haloxylon ammodendron Forests: Insights from water use and environmental stress","authors":"Yuquan Qiang ,&nbsp;Mingjun Zhang ,&nbsp;Yu Zhang ,&nbsp;Xianying Xu ,&nbsp;Jinchun Zhang ,&nbsp;Guiquan Fu ,&nbsp;Peng Zhao ,&nbsp;Shengjie Wang","doi":"10.1016/j.agrformet.2025.110629","DOIUrl":"10.1016/j.agrformet.2025.110629","url":null,"abstract":"<div><div><em>Haloxylon ammodendron</em> as a key sand - fixing tree species in the oasis - desert ecotone of arid regions, its degradation seriously threatens regional ecological security. In this study, by integrating heat diffusion technology, isotope tracing, and multi - environmental factor monitoring, the water - use strategies of <em>H. ammodendron</em> forests with different degradation degrees and their response mechanisms to environmental stresses were systematically analyzed. The results showed that net radiation was the core driving factor regulating the transpiration water consumption of <em>H. ammodendron</em>. Under high - temperature and drought stress, <em>H. ammodendron</em> reduced water consumption by decreasing the number of branches and assimilating branches. However, the shrinkage of the canopy aggravated surface wind erosion, resulting in the exposure and damage of shallow roots. Isotope analysis indicated that degraded <em>H. ammodendron</em> relied on water from thick roots to repair fine roots, but the water supply to the above - ground parts was limited, forming a vicious cycle of “root damage - canopy degradation - aggravated wind erosion”. Based on this, a hierarchical restoration strategy was proposed: for mildly degraded forests, pruning the canopy to optimize water distribution; for moderately degraded forests, removing secondary dead branches to reduce ineffective water consumption; for severely degraded forests, cutting the trunk and setting up sand barriers to block the sand - wind flow. The field restoration experiment in 2023 showed that the above - mentioned strategies significantly improved the survival rate and functional restoration of <em>H. ammodendron</em>. This study revealed the multi - scale driving mechanisms of <em>H. ammodendron</em> degradation, providing a scientific paradigm for ecological restoration in global arid regions.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"371 ","pages":"Article 110629"},"PeriodicalIF":5.6,"publicationDate":"2025-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144067406","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 the impact of weather variability on maize yield fluctuation for different sowing dates","authors":"Yuan-Chih Su ,&nbsp;Ping-Wei Sun ,&nbsp;Hung-Yu Dai ,&nbsp;Bo-Jein Kuo","doi":"10.1016/j.agrformet.2025.110625","DOIUrl":"10.1016/j.agrformet.2025.110625","url":null,"abstract":"<div><div>Frequent and intense adverse weather resulting from climate change can lead to high fluctuations in crop yields. However, sowing dates can be adjusted to avoid adverse weather and thereby mitigate crop yield fluctuation. To elucidate the relationship between the sowing date and fluctuations in maize (<em>Zea mays</em> L.) yield, this study evaluated the effect of weather conditions, including adverse weather, on maize yield during different growth periods. The primary difference in weather conditions between sowing dates was the temperature during the whole growth period and precipitation during specific growth periods; notably, precipitation exhibited higher annual fluctuations. Furthermore, a low relative yield (&lt;70 %) and high coefficient of variation (&gt;15 %) were noted for sowing dates with high annual fluctuation in precipitation and adverse precipitation events frequency. In simulations, the lowest yield and yield stability were those for the sowing dates with high temperature during the crop season and high annual fluctuation in adverse precipitation events frequency during the vegetative stage. In both crop seasons, adverse weather significantly affected maize yield and explained &gt;50 % of observed yield variation. Under the weather scenario of adverse high temperature and precipitation, an approximate 2500-kg/ha reduction in yield was predicted. This study first evaluated the effect of sowing dates on the variation of weather conditions, then correlated these variations to yield fluctuation to identify factors contributing to maize yield fluctuation. The results indicate that adverse precipitation during the vegetative stage affects crop yield fluctuation and sowing dates must be reevaluated under climate change.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"371 ","pages":"Article 110625"},"PeriodicalIF":5.6,"publicationDate":"2025-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144067405","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":"Assessing the impact of climate indices on corn yield in the continental USA using machine learning approach","authors":"Amitesh Sabut ,&nbsp;Kumar Puran Tripathy ,&nbsp;Ashok Mishra ,&nbsp;Martha Anderson ,&nbsp;Michael Cosh ,&nbsp;Simon kraatz ,&nbsp;Feng Gao ,&nbsp;Richard Cirone","doi":"10.1016/j.agrformet.2025.110632","DOIUrl":"10.1016/j.agrformet.2025.110632","url":null,"abstract":"<div><div>Climate has a profound impact on crop productivity, but its effects are difficult to measure due to significant spatial and temporal variability. This study explores a wide range of climatic indices that represent the various conditions affecting corn growth across the United States. By employing clustering techniques, we categorized rainfed corn-growing regions into distinct zones based on similar climatic characteristics to evaluate how each index influences crop yields. We identified the most effective combinations of these indices and used machine learning models at the county level to map the relationships between climatic factors and crop yields. Our analysis reveals that temperature-related indices, such as the number of days with temperatures exceeding 30 °C (HD30), Temperature Variance (Tvar), and Extreme Temperature Range (ETR), are the top three factors that negatively impact yields, while SU (number of summer days) has a positive effect. Precipitation-related indices also contribute positively, highlighting the critical role of balanced water availability during key growth stages. Notably, temperature-related indices emerged as the most effective predictors of yield in most regions, demonstrating stronger influence and higher predictive accuracy compared to precipitation indices. At the county level, machine learning models were used to map these relationships, with XGBoost emerging as the most reliable model. It consistently outperformed alternatives like Random Forest, Support Vector Machine, and LASSO, demonstrating superior accuracy and robustness. This was particularly evident during the extreme climatic conditions of 2012, marked by severe drought and heatwaves, where XGBoost accurately captured yield losses without overestimation. Among all factors, HD30 was identified as the most influential climatic driver of yield reductions under heat stress. This study not only enhances our understanding of climatic influences on crop production but also empowers stakeholders like farmers, policymakers, insurers, and agribusinesses to adopt optimized agricultural practices and develop strategic initiatives that enhance agricultural resilience and food security.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"371 ","pages":"Article 110632"},"PeriodicalIF":5.6,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144066293","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":"Mature biocrust-covered soil carbon fluxes are dependent on their types: Moss-covered soils still serve as sinks while cyanobacteria-covered soils become sources","authors":"Weiqiang Dou ,&nbsp;Bo Xiao","doi":"10.1016/j.agrformet.2025.110627","DOIUrl":"10.1016/j.agrformet.2025.110627","url":null,"abstract":"<div><div>Soil carbon (C) fluxes in drylands are crucial for predicting future global climate change. Biocrusts covering dryland surfaces have been recognized for their roles in ecosystem functions. However, the contributions of biocrusts to soil C fluxes may vary depending on the crust-forming organisms, but evidence remains limited. In the semiarid climate of the Northern Chinese Loess Plateau, we conducted continuous measurements of soil C fluxes, including biocrust photosynthesis (<em>P</em>_n), soil respiration (<em>R</em>_s), and net C fluxes (NCF = <em>R</em>_s – <em>P</em>_n, where a positive value refers to a C source, and a negative value refers to a C sink), on two representative types of mature biocrust-covered (cyanobacteria and mosses; ∼40 years old) and bare soil over two growing seasons (2022–2023). Our results showed that mature moss crusts significantly increased <em>P</em>_n and <em>R</em>_s compared with cyanobacterial crusts. The NCF for cyanobacterial crusts was positive, whereas that for moss crusts was negative, with moss crusts showing significant net C uptake (–0.32 μmol m^–2 s^–1). Both linear regression and structural equation modelling showed that soil water content was the first determinant factor driving seasonal changes in C fluxes in biocrust-covered soil. Notably, the estimated average annual NCF from the random forest model indicated that mature moss-crusted soils had a slight net C uptake (–66 g C m^–2 yr^–1), whereas mature cyanobacteria-crusted soils (551 g C m^–2 yr^–1) exhibited remarkable net C emissions. In conclusion, mature biocrusts are important contributors to soil C fluxes in drylands; however, their contributions are highly dependent on the type of biocrust. Our study highlights that mature moss-crusted soils could increase dryland C uptake over extended periods (potentially decades or even centuries), and thus they may serve as potential ‘permanent’ C sinks in drylands, whereas cyanobacteria-crusted soils would reach C saturation sooner and subsequently act as C sources by reducing dryland C uptake. These divergent changes in dryland soil C fluxes caused by biocrusts, especially the differences among mature biocrust types, should be thoroughly considered to accurately assess dryland or global C fluxes for mitigating climate change.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"371 ","pages":"Article 110627"},"PeriodicalIF":5.6,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144066011","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":"Temporal patterns in root water uptake and intrinsic water-use efficiency of overstory and understory tree species in a subtropical humid pine forest","authors":"Lu Li ,&nbsp;Wei Ren ,&nbsp;Lide Tian","doi":"10.1016/j.agrformet.2025.110626","DOIUrl":"10.1016/j.agrformet.2025.110626","url":null,"abstract":"<div><div>Root water uptake and leaf-level intrinsic water-use efficiency (WUEi) and their temporal variations are important determinates of plant water balance and carbon fixation, yet these processes in humid forest trees are much less explored. We investigated the monthly variations in xylem and soil water isotopes (δ¹⁸O, δ²H), leaf carbon isotope (δ¹³C), soil, xylem and leaf water contents as well as the seasonal variations in leaf oxygen isotope (δ¹⁸O) and N contents for the dominant overstory species (<em>Pinus massoniana</em>) and a neighboring common understory species (<em>Camellia japonica</em>) in a subtropical humid pine forest within April 2021-June 2022. Water stable isotopes revealed that the two species exhibited similar water uptake patterns over time and both shifted water uptake toward deeper and shallow soil layers during the wet and relatively dry seasons, respectively. Evident soil water partitioning only occurred during a spring drought when only <em>C. japonica</em> shifted water uptake toward deeper soil layers, indicating high interspecific competition for shallow water. For <em>P. massoniana</em>, the reliance on shallow water positively correlated with WUEi (leaf δ¹³C) through negatively affecting leaf relative (to xylem) water content and stomatal conductance (proxied by leaf ¹⁸O enrichment above source water). In contrast, <em>C. japonica</em> exhibited non-sensitive WUEi response to temporal changes in water uptake depth, and its low leaf N contents indicate severe N limitation on photosynthesis and WUEi. Our results highlight the tight coupling between water uptake depth and WUEi for the overstory species, but not for the understory species likely associated with the stronger water and particularly N limitation it was experiencing. Our analysis of temporal changes in water uptake depth and WUEi (leaf δ¹³C) provides a useful framework to evaluate belowground constraints on resource acquisition and leaf-level water use strategies for plants in humid forests.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"371 ","pages":"Article 110626"},"PeriodicalIF":5.6,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144066292","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":"Validation of the vertical plant area index profile product derived from GEDI over global forest sites","authors":"Yao Wang ,&nbsp;Hongliang Fang ,&nbsp;Yu Li ,&nbsp;Sijia Li ,&nbsp;Hao Tang","doi":"10.1016/j.agrformet.2025.110612","DOIUrl":"10.1016/j.agrformet.2025.110612","url":null,"abstract":"<div><div>Knowledge of the vertical plant area index (PAI) profile is critical for understanding the forest structural and functional characteristics. Vertical PAI profile has been retrieved by the Global Ecosystem Dynamics Investigation (GEDI) spaceborne LiDAR. However, large-scale validation of the GEDI PAI profile products is limited, and their performance has yet to be clearly established. This study aims to systematically assess the performance of GEDI PAI profile product and investigate the impact factors on PAI profile estimates. The digital hemispherical photography (DHP) of vertical measurement and airborne laser scanning (ALS) data were collected to derive the reference PAI profiles. The results indicate that adjusting footprint geolocation before GEDI validation is essential for enhancing product assessment. The GEDI PAI profile moderately agrees with the DHP and ALS (R² = 0.84 and 0.58, respectively) but underestimates the reference (bias = −0.14 and −0.28, respectively). The needleleaf forest exhibits the highest agreement with ALS (R² = 0.60 and bias = −0.16), while shrubland shows the lowest agreement (R² = 0.38 and bias = 0.21). The agreement between GEDI and ALS increases with the canopy height but decreases with the canopy cover. Low vegetation height and steep slopes affect the GEDI PAI accuracy owing to the difficulty in decomposing the mixed ground and canopy returns. Additionally, the limited penetration of GEDI in dense vegetation with high canopy cover contributes to the underestimation. The performance of GEDI PAI profile can be improved by applying a specific canopy and ground reflectance ratio (<span><math><msub><mi>ρ</mi><mi>v</mi></msub></math></span>/<span><math><msub><mi>ρ</mi><mi>g</mi></msub></math></span>) value derived from the linear regression of return energy. The discrepancies between GEDI and ALS PAI profiles were partially attributed to the sub-optimal waveform processing algorithm settings and differences in LiDAR specifications. Further improvement to the GEDI PAI product may be achieved by implementing a customized waveform processing algorithm and using realistic <span><math><msub><mi>ρ</mi><mi>v</mi></msub></math></span>/<span><math><msub><mi>ρ</mi><mi>g</mi></msub></math></span> values.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"371 ","pages":"Article 110612"},"PeriodicalIF":5.6,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144066070","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":"Local and downwind precipitation has been boosted by evapotranspiration change-induced moisture recycling in the Chinese Loess Plateau","authors":"Chao Gao ,&nbsp;Jinxia Fu ,&nbsp;Zhiming Han ,&nbsp;Wangjia Ji ,&nbsp;Liu Zhao ,&nbsp;Xiaohua Wei ,&nbsp;Zhi Li","doi":"10.1016/j.agrformet.2025.110623","DOIUrl":"10.1016/j.agrformet.2025.110623","url":null,"abstract":"<div><div>The Grain for Green Project in the Chinese Loess Plateau (CLP) has greatly increased vegetation cover and altered land use patterns. However, the effects of evapotranspiration (ET) from different vegetation types on local and downwind precipitation remain unclear. In this study, we employed a moisture tracking model to quantify the contributions of ET-driven moisture recycling to precipitation change for 1990–2019. We found the ET moisture over CLP flows northeastward to contribute to local and downwind precipitation. On average, 21 % of the ET moisture contributed to 14 % of local precipitation. The remaining ET moisture contributed unevenly to downwind precipitation of different regions: 38 % of ET for rest of China, 17 % for other countries, and 24 % for the ocean. The increased ET over the past three decades has greatly contributed to the increases in local precipitation. A 1 mm rise in ET can increase local precipitation by 0.15 mm, among which ∼70 % of the precipitation increase (0.1 mm) is attributed to transpiration. Collectively, a 60-mm increase in ET resulted in a net precipitation increase of 9 mm, accounting for 16 % of the total precipitation increase over the past three decades. The increased ET from grassland and cropland respectively contributed 61 % and 21 % to the increase of local precipitation. We conclude that the increased ET over the past three decades has greatly contributed to the increases in local precipitation, and grassland played a dominant role because of its larger area proportion. This finding has important implications for vegetation restoration and water resource management in the water-limited areas.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"371 ","pages":"Article 110623"},"PeriodicalIF":5.6,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144066291","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":"Rice water requirement exacerbates groundwater depletion in Northeast China under a changing climates","authors":"Yuanbo Zhao ,&nbsp;Tao Li ,&nbsp;Jin Zhao ,&nbsp;Zhentao Zhang ,&nbsp;Runze Liu ,&nbsp;Yanying Shi ,&nbsp;Haoyu Ma ,&nbsp;Chuang Zhao ,&nbsp;Zhijuan Liu ,&nbsp;Xiaoguang Yang","doi":"10.1016/j.agrformet.2025.110624","DOIUrl":"10.1016/j.agrformet.2025.110624","url":null,"abstract":"<div><div>In recent years, Northeast China (NEC) has emerged as a key rice production region. However, the region’s scarce precipitation and surface water availability raise concerns about groundwater over intensive rice cultivation. Using the process-based rice model ORYZA (v3), we assessed irrigation water demand and groundwater depletion under two irrigation regimes - Flood (FLD) Irrigation and Alternative Wet-dry (AWD) Irrigation - across two climate change scenarios (SSP1–2.6 and SSP5–8.5). Results indicated a substantial increase in irrigation water demand (28.6 % to 52.3 %) and groundwater depletion ratio (23.6 % to 53.0 %) under future climate scenarios, with higher impacts under the more extreme SSP5–8.5 pathway. Spatial analysis revealed that regions with larger rice cultivation areas, particularly in Sanjiang Plain, are more vulnerable to groundwater depletion. Furthermore, the benefits of AWD irrigation in mitigating water stress decline under climate change, with reductions in groundwater extraction alleviation (by 7.6 % to 7.9 %) and water use efficiency improvement (by 8.1 % to 8.3 %). These findings underscore the urgent need for spatially optimized rice cultivation and adaptive irrigation strategies tailored to ensure long-term groundwater sustainability and regional food security.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"371 ","pages":"Article 110624"},"PeriodicalIF":5.6,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143947672","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":"Improved uncertainty estimates for eddy covariance-based carbon dioxide balances using deep ensembles for gap-filling","authors":"Henriikka Vekuri ,&nbsp;Juha-Pekka Tuovinen ,&nbsp;Liisa Kulmala ,&nbsp;Mika Aurela ,&nbsp;Tea Thum ,&nbsp;Jari Liski ,&nbsp;Annalea Lohila","doi":"10.1016/j.agrformet.2025.110558","DOIUrl":"10.1016/j.agrformet.2025.110558","url":null,"abstract":"<div><div>Eddy covariance (EC) measurements of carbon dioxide (CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span>) fluxes are commonly used to determine CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> balances of ecosystems. However, comparisons between experimental treatments, environmental controls or measurement sites are not meaningful without proper uncertainty estimates for the balances. We studied how random and systematic errors depend on the amount of missing data and whether the uncertainty estimates produced by popular gap-filling methods, including tree-based machine learning methods, neural networks and marginal distribution sampling (MDS), are in line with these errors. Using synthetic data created for European forest sites, we found that when the proportion of missing data increased from 30% to 90%, the random uncertainty related to gap-filling (2<span><math><msub><mrow><mi>σ</mi></mrow><mrow><mtext>rnd</mtext></mrow></msub></math></span>, computed from observed model errors) increased from approximately 10 g C m⁻² y⁻¹ up to 25–75 g C m⁻² y⁻¹ depending on the site and gap-filling method. Ensembles of neural networks (deep ensembles) had smaller random errors than the standard EC gap-filling method MDS, and also produced improved uncertainty estimates for the CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> balances. Long gaps of up to one month caused random uncertainty of mostly less than 50 g C m⁻² y⁻¹; however, a long gap during a dry and warm period that was inadequately represented in the measurements caused random uncertainty of up to 99 g C m⁻² y⁻¹. Deep ensembles produced well-calibrated uncertainty estimates also for the long gaps, except for the most difficult cases when long gaps occurred during periods of active change in the ecosystem. The uncertainty estimates produced by MDS for long gaps were clearly too small. Tree-based machine learning methods produced well-calibrated uncertainty estimates for short-term fluxes but not for balances and, unlike deep ensembles, did not extrapolate outside the training data.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"371 ","pages":"Article 110558"},"PeriodicalIF":5.6,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144066290","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":"Pioneering insights into the global and local origins of Betula spp. pollen in Iceland: Tracing long-distance transport pathways","authors":"Ewa Przedpelska-Wasowicz ,&nbsp;Paweł Bogawski ,&nbsp;Katarzyna Piotrowicz ,&nbsp;Beata Bosiacka ,&nbsp;Agnieszka Grinn-Gofroń ,&nbsp;Dorota Myszkowska","doi":"10.1016/j.agrformet.2025.110607","DOIUrl":"10.1016/j.agrformet.2025.110607","url":null,"abstract":"<div><div>Iceland’s natural woodlands are dominated by the downy birch (<em>Betula pubescens</em>), while the dwarf birch (<em>B. nana</em>) is common in shrublands. These two species are the local sources of allergenic pollen that, however, may also be transported from outside Iceland (distant sources). This study aims to detect long-distance pollen transport, elucidate its mechanisms, and assess the relative contributions of local and distant sources to Iceland’s birch pollen pool.</div><div>Pollen records (1998–2023) for Akureyri and Reykjavik were investigated using surface meteorological data, back-trajectories calculated by the Hybrid Single Particle Lagrangian Integrated Trajectory model (HYSPLIT) and transformed into Potential Source Contribution Function (PSCF), complemented with Sea Level Pressure (SLP) and 500 hPa geopotential height (z500) patterns. Moreover, distributions of <em>Betula</em> spp. were modelled using random forest models to show the location of potential birch pollen sources.</div><div>We evidenced that birch pollen was transported across the Atlantic Ocean to Iceland, especially before the local pollen season, from Eastern Europe and Scotland, sometimes in large quantities (max:456 pollen m^-3). The SPIn in Akureyri was higher when pollen transported from the eastern part of Iceland or Scandinavia overlapped with the local pollen pool. In Reykjavik, pollen was transported from northern, western Iceland, but probably also from Greenland and Labrador. <em>Betula</em> spp. distribution maps in Iceland can aid future species distribution modelling under climate change. This research enhances the understanding of Arctic pollen transport dynamics and highlights the need for further research on high-latitude pollen dispersion mechanisms.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"371 ","pages":"Article 110607"},"PeriodicalIF":5.6,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143942230","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}