Agricultural and Forest Meteorology最新文献

{"title":"Carbon fluxes controlled by land management and disturbances at a cluster of long-term ecosystem monitoring sites in Central Europe","authors":"Thomas Grünwald,&nbsp;Luise Wanner,&nbsp;Uwe Eichelmann,&nbsp;Markus Hehn,&nbsp;Uta Moderow,&nbsp;Heiko Prasse,&nbsp;Ronald Queck,&nbsp;Christian Bernhofer,&nbsp;Matthias Mauder","doi":"10.1016/j.agrformet.2025.110533","DOIUrl":"10.1016/j.agrformet.2025.110533","url":null,"abstract":"<div><div>Terrestrial ecosystems play a crucial role in carbon sequestration and provide vital ecosystem services such as food, energy, and raw materials. Climate change, through rising temperatures, altered precipitation patterns, and extreme events, threatens the carbon sink potential of these ecosystems, with forests and grasslands particularly at risk. Long-term data from flux tower networks offer valuable insights into how different ecosystems respond to climate change and management interventions, helping to develop strategies to mitigate greenhouse gas emissions and maintain ecosystem resilience. In this study, we present such data from a &lt;10 km cluster of long-term FLUXNET/ICOS sites in Central Europe, comprising an old spruce forest (DE-Tha), a young oak plantation after a cleared windthrow (DE-Hzd), a permanent grassland site (DE-Gri), and an agricultural site with a crop rotation typical for this region (DE-Kli). By analysing decades of data from these eddy covariance measurement sites, the research highlights the influence of drought, management, and land cover changes on CO₂ and H₂O fluxes. The interannual variability of evapotranspiration depends less on land use than the CO₂ exchange. Our findings show that intact forests can act as larger carbon sinks than previously estimated. DE-Tha is a consistent carbon sink, with thinning helping to maintain the CO₂ sequestration at a stable level of 350 gC <em>m</em>⁻² <em>a</em>⁻¹. In contrast, disturbances like clear cutting or windthrow can cause ecosystems to become carbon sources for several years, with recovery delayed due to soil carbon losses from increased respiration (DE-Hzd). While DE-Hzd was resilient to drought, the carbon uptake of DE-Tha was significantly reduced by around 50 % during dry years compared to wet years. Furthermore, sustainable management maintains carbon sequestration and land-use practices, such as crop selection, significantly impact net ecosystem productivity. These insights are valuable for optimizing land management strategies to enhance carbon sinks in similar regions.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"369 ","pages":"Article 110533"},"PeriodicalIF":5.6,"publicationDate":"2025-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143844727","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":"Predicting fire risk in colombia tropical savannas: A multi-scenario approach","authors":"Tania Marisol González ,&nbsp;Juan David González-Trujillo ,&nbsp;María Meza Elizalde ,&nbsp;Dolors Armenteras","doi":"10.1016/j.agrformet.2025.110566","DOIUrl":"10.1016/j.agrformet.2025.110566","url":null,"abstract":"<div><div>Climate change amplifies the frequency and severity of fires in tropical regions, particularly in savanna ecosystems. Amidst these changes, we provide the first comprehensive analysis of future fire risks in northern South American tropical savanna ecosystems under diverse climate scenarios. Utilizing a compounded-event framework, we not only assess but also predict fire risks in savannas under varying carbon mitigation scenarios (SSP 1–2.6, 3–7.0, 5–8.5). Our approach integrated the individual and compounded effects of eight key climatic variables to unveil the intricate dynamics of heat and drought on fire risk. A Poisson bivariate model focused on maximum temperature and accumulated precipitation robustly explained 75 % of the monthly burned area variability. We used this model to forecast fire risks from 1980 to 2100, revealing a concerning 5–8 % increase in risk during 2000–2020, with projections showing a potential 40 % surge under low mitigation scenarios. This underscores the critical need for aggressive carbon emission mitigation and effective localized fire management strategies, highlighting their vital role, even in optimistic climate scenarios.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"369 ","pages":"Article 110566"},"PeriodicalIF":5.6,"publicationDate":"2025-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143844725","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":"Divergent responses of canopy and ecosystem water use efficiency to environmental conditions over a decade in a shrubland ecosystem dominated by Artemisia ordosica","authors":"Peng Liu ,&nbsp;Tianshan Zha ,&nbsp;Xin Jia ,&nbsp;Yun Tian ,&nbsp;Shaorong Hao ,&nbsp;Xinhao Li","doi":"10.1016/j.agrformet.2025.110551","DOIUrl":"10.1016/j.agrformet.2025.110551","url":null,"abstract":"<div><div>Canopy and ecosystem water use efficiency (WUE_T and WUE_E) measure the trade-off between carbon gain and water loss at canopy and ecosystem scale respectively, and provide vital information for water resource management in drylands. But the assessment of environmental controls on WUE_T and WUE_E on the decadal scale in drylands remains limited. Here, using eddy covariance (2014–2023) and sap-flow measurements (2022–2023), we investigated the environmental controls of WUE_T, WUE_E, and their components (i.e. gross ecosystem production GPP, evapotranspiration ET, and transpiration T) in a shrubland ecosystem dominated by <em>Artemisia ordosica</em> of northern China. Results showed that WUE_E (variation coefficient, CV=12.5 %) exhibited a larger interannual variation than WUE_T (CV=8.2 %), due to similar responses of GPP and T to environmental factors. As a result, the interannual variation in WUE_T seems to be independent of both canopy greenness (i.e. normalized difference vegetation index NDVI) and climatic factors (soil water content SWC and vapor pressure deficit VPD). While interannual variation in WUE_E was mainly controlled by NDVI through changing the ratio of T to ET. The interannual variation in GPP and ET was significantly affected by SWC in spring, which impacted canopy greenness in summer (NDVI_{_summer}). We further found that a decrease in SWC is not universally associated with reductions in GPP and ET. By contrast, the sensitivity of GPP and ET to an increase of VPD is always negative across the full SWC range. Our results suggested that the response of WUE_E to environmental factors does not necessarily reflect changes in canopy water use efficiency. Despite the predominant VPD stress on GPP and ET, SWC is a key factor in determining interannual variation in GPP and ET and need to be taken into account when studying long term trends in GPP or ET.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"368 ","pages":"Article 110551"},"PeriodicalIF":5.6,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143838910","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":"Declining soil evaporation on a drying earth","authors":"Han Chen ,&nbsp;Yizhao Wei","doi":"10.1016/j.agrformet.2025.110550","DOIUrl":"10.1016/j.agrformet.2025.110550","url":null,"abstract":"<div><div>Rising vapor pressure deficit (VPD) due to warming has increased global land surface soil evaporation (E), whereas reduced soil moisture (SM) from global drying has suppressed E. However, the relative contributions of these two factors to global E remain poorly understood, creating significant uncertainty regarding its long-term trends. This study constructed an E model that integrated physical processes with machine learning and validated its performance using in-situ E data from 368 global flux sites. The trained hybrid model was then employed to create a dataset of global land surface E for both historical and future periods, enabling the identification of long-term trends and drivers of E across these timeframes. Our findings revealed that the negative impact of SM decline on global E outweighed the positive effects of increased VPD, resulting in a long-term downward trend in global land surface E from 1982 to 2023 (–0.28 ± 0.07 mm/year²). Under future climate change scenarios, global land surface E was projected to continue its decline at a faster rate than observed in historical periods (average –0.42 ± 0.11 mm/year² under three climate change scenarios from 2024 to 2100), with SM playing a dominant role in this trend. The long-term downward trend was further corroborated by nine additional E datasets. These results underscored the critical role of global drying in driving the persistent decline in global E and highlighted how climate change was exacerbating risks to global water resources.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"368 ","pages":"Article 110550"},"PeriodicalIF":5.6,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143838908","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 continuous learning framework based on physics-guided deep learning for crop phenology simulation","authors":"Junji Ou ,&nbsp;Fangzheng Chen ,&nbsp;Min Zhang ,&nbsp;William David Batchelor ,&nbsp;Bin Wang ,&nbsp;Dingrong Wu ,&nbsp;Xiaodong Ma ,&nbsp;Zengguang Zhang ,&nbsp;Kelin Hu ,&nbsp;Puyu Feng","doi":"10.1016/j.agrformet.2025.110562","DOIUrl":"10.1016/j.agrformet.2025.110562","url":null,"abstract":"<div><div>Process-based models (PBMs) and artificial intelligence models (AIMs) are both widely used to simulate crop growth under various environmental conditions and farm management practices. PBMs offer the advantage of interpretable simulations due to their mechanistic underpinnings, but the latest insights from crop growth mechanism research are often not promptly incorporated into PBMs. Further, while AIMs can directly extract potential patterns from data, they struggle to generate temporally continuous simulations due to their lack of consideration for crop growth processes, thus limiting the interpretability of their simulations. To synergize the strengths of PBMs and AIMs, we developed a continuous learning framework, AGLPF (APSIM Guided LSTM Phenology Framework), to dynamically simulate the changes in maize phenology across the Chinese Maize Belt. The AGLPF consists of a PBM (APSIM), its phenology dataset, and an AIM based on attention-Long short-term memory (LSTM). When initially training the AIM in AGLPF by the PBM output dataset, the AGLPF was capable of replicating the PBM outcomes, with an average RMSE of 0.8 days for the vegetative growth phase and flowering phase, 1.4 days for the grain filling phase and 2.0 days for the full growing cycle. With incremental actual phenology data from 0 to 12 years being used for self-tuning training, the simulations of the AGLPF increasingly aligned with actual data. Notably, the RMSE of the full growing cycle steadily declined from 27.8 days to 5.5 days. Moreover, the self-tuning training method performed better than the from-scratch training method in the simulation of all the phenological phases. The development of AGLPF has provided a framework to consider physics-guided AIM to simulate crop phenology and even other crop-related variables while being easy to upgrade and easily interpret outputs.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"368 ","pages":"Article 110562"},"PeriodicalIF":5.6,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143838907","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":"Extending genomic prediction to future climates through crop modelling. A case study on heading time in barley","authors":"Livia Paleari ,&nbsp;Alessandro Tondelli ,&nbsp;Luigi Cattivelli ,&nbsp;Ernesto Igartua ,&nbsp;Ana M. Casas ,&nbsp;Andrea Visoni ,&nbsp;Alan H. Schulman ,&nbsp;Laura Rossini ,&nbsp;Robbie Waugh ,&nbsp;Joanne Russell ,&nbsp;Roberto Confalonieri","doi":"10.1016/j.agrformet.2025.110560","DOIUrl":"10.1016/j.agrformet.2025.110560","url":null,"abstract":"<div><div>Integrating genomic prediction (GP) and biophysical crop models has the potential to support plant breeding in defining adapting strategies to climate change. However, whether this integrated approach can actually broaden the prediction domain to unexplored environments is still unclear. We showed how crop models can extend GP to new environments and capture genotype-specific response to future climate conditions.</div><div>Days to heading (HD) in spring barley was used as a case study, given the primary role of phenology for crop adaptation. Phenotypic and genomic (50 K Illumina SNP array) data for 151 two-row genotypes were used, with HD determined on 17 site × season combinations spread from the Mediterranean basin to Northern Europe. A dedicated modelling solution was developed by integrating approaches from the WARM and WOFOST crop models, with optimization algorithms used to derive accession-specific values of most relevant model parameters. GP was carried out on the model parameters with the R package rr-BLUP, and the resulting markers-derived parameters were used to simulate heading date with the crop model explicitly reproducing <em>G</em> × <em>E</em> × <em>M</em> interactions. Prediction accuracy for unknown genotypes was evaluated through ten-fold cross validation, whereas the capability of crop models to extend GP to unexplored environments was evaluated with a leave-one site-out cross validation.</div><div>Results were encouraging, with average R², RMSE and Nash-Sutcliffe efficiency for unknown genotypes in unexplored environments equal to 0.97, 9.27, and 0.94, respectively. Accession-specific HD under future climates (20 seasons centred on 2060 generated for the IPSL-CM6A-LR realization of SSP3–7.0) highlighted large <em>G</em> × <em>E</em> × <em>M</em> interactions, confirming the potential of integrating crop modelling and GP to supporting breeding programs targeting adaptation to climate change.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"368 ","pages":""},"PeriodicalIF":5.6,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143838270","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":"Hydrothermal drivers of seasonal and interannual dynamics of soil respiration and its temperature sensitivity in a temperate semiarid shrubland","authors":"Shengjie Gao ,&nbsp;Xin Jia ,&nbsp;Xiaoyan Jiang ,&nbsp;Yanmei Mu ,&nbsp;Charles P.-A. Bourque ,&nbsp;Peng Liu ,&nbsp;Shugao Qin ,&nbsp;Yun Tian ,&nbsp;Wenjing Chen ,&nbsp;Tianshan Zha","doi":"10.1016/j.agrformet.2025.110564","DOIUrl":"10.1016/j.agrformet.2025.110564","url":null,"abstract":"<div><div>Despite the importance of soil respiration (<em>R_s</em>) in the global carbon (C) cycle, our understanding of the dynamics of <em>R_s</em> and its temperature sensitivity (<em>Q</em>₁₀) over time and across timescales remains to be improved for dryland ecosystems. We measured <em>R_s</em> continuously in a temperate semiarid shrubland in northern China during 2013–2019 to examine seasonal and interannual variations in <em>R_s</em> and <em>Q</em>₁₀. Daily mean <em>R_s</em> ranged from values close to zero in winter to 1–3 µmol CO₂ m⁻² s⁻¹ in summer. Daily mean <em>R_s</em> increased exponentially with soil temperature (<em>T_s</em>) at 10-cm depth in spring and autumn, being greater in autumn at a given <em>T_s</em>, but decoupled from <em>T_s</em> in summer. Summertime <em>R_s</em> increased with soil water content (<em>SWC</em>) at 10-cm depth up to about 0.16 m³ m⁻³, beyond which it levelled off or decreased. Annual <em>R_s</em> ranged from 231.8 to 334.9 g C m⁻² yr⁻¹ and increased with summer rainfall amount. Estimates of <em>Q</em>₁₀ were generally lower in spring than in autumn, and this difference was more obvious for seasonal <em>Q</em>₁₀ (estimated from seasonal <em>R_s</em>−<em>T_s</em> relationships) than for diel <em>Q</em>₁₀ (estimated from diel <em>R_s</em>−<em>T_s</em> relationships over a five-day moving window). Synchronizing the diel oscillations in <em>R_s</em> and <em>T_s</em> enhanced diel <em>Q</em>₁₀ from 1.8 ± 0.4 (mean ± SD) to 2.5 ± 0.6, suggesting the need to consider the diel hysteresis between <em>R_s</em> and <em>T_s</em> for accurate modeling of hourly <em>R_s</em> dynamics. Both seasonal and diel <em>Q</em>₁₀ decreased with increasing <em>T_s</em>, and diel <em>Q</em>₁₀ increased with increasing <em>SWC</em>. Our findings demonstrate that hydrothermal controls on <em>R_s</em> and <em>Q</em>₁₀ vary across seasons and timescales, and highlight the role of seasonal hydrothermal drivers in regulating long-term ecosystem C balance.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"368 ","pages":"Article 110564"},"PeriodicalIF":5.6,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143834508","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":"Incorporation of needleleaf traits improves estimation of light absorption and gross primary production of evergreen needleleaf forests","authors":"Baihong Pan ,&nbsp;Xiangming Xiao ,&nbsp;Li Pan ,&nbsp;Cheng Meng ,&nbsp;Peter D. Blanken ,&nbsp;Sean P. Burns ,&nbsp;Jorge A. Celis ,&nbsp;Chenchen Zhang ,&nbsp;Yuanwei Qin","doi":"10.1016/j.agrformet.2025.110526","DOIUrl":"10.1016/j.agrformet.2025.110526","url":null,"abstract":"<div><div>The seasonal dynamics and interannual variation of gross primary production (GPP, g C/m²/day) of evergreen needleleaf forest (ENF) are important but most of models underestimate ENF GPP. In this work, we selected three ENF sites with 10+ years of data from the eddy flux towers and investigated temporal dynamics of GPP, climate, and vegetation greenness (as measured by vegetation indices from MODIS surface reflectance data) during 2000–2020. We found that the seasonal dynamics of GPP and vegetation indices were correlated highly at two sites (US-Ho2, US-NR1) under Warm Summer Continental climate (Dfb) and Subarctic climate (Dfc), where the seasonality of air temperature, radiation and rainfall are synchronized, but weakly at the site (US-Me2) under Mediterranean climate (Csb), where the seasonality of air temperature and radiation is asynchronized with that of rainfall and trees have deep roots for access to deep soil water in a year. We incorporated the needleleaf traits and modified the equation that estimates light absorption by chlorophyll of needleleaf in the data-driven Vegetation Photosynthesis Model (VPM), which resulted in substantial improvement of GPP estimates. Daily GPP estimates over 2000–2020 from the VPM (v3.0) agreed well with the GPP estimates provided by AmeriFlux. As ENF at the US-Me2 site under the Mediterranean climate has deep roots for access water in the deep soils, we incorporated no-water stress in the wet season for the VPM (v3.0) simulations, which further improved GPP estimates of ENF at the site. This study highlights the importance of needleleaf traits and plant root traits in the VPM v3.0 for estimating GPP of evergreen needleleaf forests under different types of climate systems.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"368 ","pages":"Article 110526"},"PeriodicalIF":5.6,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143834507","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":"Dynamic changes and regional differences in permafrost active layer thickness along the Qinghai-Tibet Highway from 2004 to 2023","authors":"Ren Li ,&nbsp;Shenning Wang ,&nbsp;Tonghua Wu ,&nbsp;Junjie Ma ,&nbsp;Wenhao Liu ,&nbsp;Xiaodong Wu ,&nbsp;Guojie Hu ,&nbsp;Jimin Yao ,&nbsp;Yao Xiao ,&nbsp;Yongliang Jiao ,&nbsp;Shengfeng Tang ,&nbsp;Xiaofan Zhu ,&nbsp;Jianzong Shi ,&nbsp;Yongping Qiao","doi":"10.1016/j.agrformet.2025.110547","DOIUrl":"10.1016/j.agrformet.2025.110547","url":null,"abstract":"<div><div>The active layer thickness (ALT) is a critical indicator of permafrost response to climate change, holding important implications for ecological and hydrological systems. This study analyzed ALT trends and assessed dominant influencing factors along the Qinghai-Tibet Highway from 2004 to 2023, using observational data from 9 sites. Results showed a warming trend of 0.25 °C/10 a across the study sites, with an average ALT increase of 64.7 cm (2.84 cm/a). The surface energy budget, particularly the annual global radiation accumulation and net longwave radiation, was identified as the predominant factor influencing ALT changes. Although soil moisture and vegetation cover did not show significant correlations with ALT across all sites, a significant negative correlation was observed when analyzed by underlying surface type, with alpine swamp meadows having the thinnest ALT and alpine desert steppes the thickest. An empirical model developed with readily available meteorological data demonstrated satisfactory accuracy, offering an effective tool for ecological and infrastructure planning in permafrost regions. The findings of this study contribute to the understanding of permafrost degradation due to climate change.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"368 ","pages":"Article 110547"},"PeriodicalIF":5.6,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143829714","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 practical approach for grading cotton Verticillium wilt severity for remote sensing monitoring","authors":"Yaohui Gui ,&nbsp;Changping Huang ,&nbsp;Junru Zhou ,&nbsp;Mi Yang ,&nbsp;Xiaofeng Qiu ,&nbsp;Ze Zhang ,&nbsp;Yaokai Liu ,&nbsp;Yu Gao ,&nbsp;Weiling Shen ,&nbsp;Wenjiang Huang ,&nbsp;Bhaskar Shrestha ,&nbsp;Lifu Zhang","doi":"10.1016/j.agrformet.2025.110559","DOIUrl":"10.1016/j.agrformet.2025.110559","url":null,"abstract":"<div><div>Disease severity grading is a key prerequisite and major aspect of the integrated management of cotton <em>Verticillium</em> wilt (VW). However, the application of current VW severity grading methods requires an investigation into the disease status of all cotton leaves. It is time-consuming, unrelated to yield, and difficult to reflect the actual severity, especially when it comes to large-scale remote-sensing monitoring. We integrated the cotton VW progression mechanism exploring the potential of leaf VW severity in various leaf types at different layers of cotton to indicate yield loss. Based on all main stem leaves (MLs) in cotton leaf layers 1–3 and fruit branch leaves (FLs) in layers 1–5, we proposed a practical grading method for cotton VW associated with yield loss and suitable for remote sensing monitoring, termed the Eight-Position Grading method (EPG). The results indicated FL exhibited stronger correlation with yield compared to ML, and MLs in layers 1–3 and FLs in layers 1–5 effectively indicated yield loss due to VW. EPG was compared with the technical specifications for VW severity assessment in China (GB) and its associated grading methods, demonstrating performance with a 12 % yield loss gradient while correcting overestimation in GB grading. The remote sensing applicability of EPG was theoretically validated using PROSPECT_D and mSCOPE. Field remote sensing experiment confirmed that EPG achieved preferable accuracies in estimating VW severity (R² = 0.76, RPD = 2.06) and demonstrated a strong correlation with yield (R² = 0.53). This study offers a simple and practical method for scientifically assessing VW severity and estimating yield loss.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"368 ","pages":"Article 110559"},"PeriodicalIF":5.6,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143833827","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}