Agricultural and Forest Meteorology最新文献

{"title":"Quantifying forest structural attributes and aboveground carbon dynamics with terrestrial laser scanning in a temperate deciduous forest","authors":"Shilin Chen ,&nbsp;Hans Verbeeck ,&nbsp;Louise Terryn ,&nbsp;Wout Cherlet ,&nbsp;Chang Liu ,&nbsp;Mathias Disney ,&nbsp;Yadvinder Malhi ,&nbsp;Niall Origo ,&nbsp;Joanne Nightingale ,&nbsp;Kim Calders","doi":"10.1016/j.agrformet.2025.110995","DOIUrl":"10.1016/j.agrformet.2025.110995","url":null,"abstract":"<div><div>Quantifying forest structure and aboveground biomass carbon (AGBC) dynamics over time is crucial for evaluating climate change impact on carbon stocks, and providing key insights into changes in the terrestrial carbon cycle. To date, the use of multi-temporal terrestrial laser scanning (TLS) to detect temporal dynamics of forest structure and AGBC remains largely unexplored. In this study, we demonstrate the use of bi-temporal TLS data to quantify fine-scale dynamics of forest structure and AGBC. A total of 831 live trees were extracted and manually aligned from two leaf-off datasets collected in a 1.4 ha area of temperate woodland (Wytham Woods, UK) in 2016 and 2022. Results indicated that, at the individual tree level, most trees exhibited positive growth in structural attributes between 2016 and 2022, including diameter at breast height (DBH, 60.2 % of trees), tree height (H, 75.8 %), crown projection area (CPA, 64.7 %), crown volume (CV, 60.5 %), and aboveground volume (V, 50.5 %). At the plot level, all structural attributes also increased, including basal area (1.8 m²/ha, 4.8 % growth), H (128.9 m/ha, 1.4 %), CPA (411.9 m²/ha, 3.0 %), DBH (1.5 m/ha, 1.1 %), CV (181.7 m³/ha, 0.3 %), and V (7.9 m³/ha, 1.0 %). The total AGBC of the study area saw a net carbon gain of 0.4 Mg C/ha/year over the six-year period. Notably, trees with DBH greater than 60 cm contributed over 40 % of the total AGBC. Moreover, our results reveal that branch dynamics play a crucial role in AGBC dynamics, underscoring the added value of TLS for tracking AGBC changes over time.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"378 ","pages":"Article 110995"},"PeriodicalIF":5.7,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145785329","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 gap-filling of eddy covariance CO2 fluxes using remote sensing and environmental variables via XGBoost","authors":"Simon De Cannière ,&nbsp;Sebastian Wieneke ,&nbsp;Thomas Servotte ,&nbsp;Adrià Descals ,&nbsp;Tim Verdonck ,&nbsp;Ivan Janssens","doi":"10.1016/j.agrformet.2025.110987","DOIUrl":"10.1016/j.agrformet.2025.110987","url":null,"abstract":"<div><div>Gap-filling of eddy covariance (EC) CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> flux data is critical for quantifying ecosystem carbon balances, yet traditional methods like Marginal Distribution Sampling (MDS) do not adequately represent sub-daily carbon fluxes and it fails to leverage vegetation dynamics, which is especially problematic for filling in gaps longer than one week. This study evaluates the potential of eXtreme Gradient Boosting (XGBoost), a machine learning approach, to improve gap-filling of net ecosystem exchange (NEE) and gross primary production (GPP) by integrating remote sensing (RS) data and environmental data, both from in-situ measurements and from the ERA5 reanalysis model over a temperate pine forest (ICOS site BE-Bra). We compare three XGBoost models: (1) in-situ (meteorological, soil moisture, and tower-based sun-induced chlorophyll fluorescence (SIF)), (2) large-scale (ERA5 and Sentinel-2-derived vegetation indices), and (3) hybrid (combining ERA5 and Sentinel-2-derived vegetation indices with in-situ radiation). The results show XGBoost outperforms MDS for NEE gap-filling in all of its scenarios, with minimal performance degradation for gaps up to 56 days. Soil moisture and SIF improved predictions during warm periods (Air Temperature <span><math><mo>&gt;</mo></math></span> 25° C), when these data were taken from in-situ sources. SHAP analysis revealed light-related drivers as dominant controls. During heatwaves, typically co-occurring with high-light conditions, soil water content became an important driver. Overall, the hybrid model achieved comparable model performance as the models with in-situ data, demonstrating the viability of satellite RS and reanalysis for operational gap-filling. However, in-situ irradiation turned out notably more useful compared to irradiation from a reanalysis. Our findings advocate for XGBoost as a robust tool to integrate multi-source data, advancing carbon flux quantification beyond traditional methods, espescially when it comes to modeling the sub-daily carbon fluxes, which is important when using EC data for evaluating remote sensing based carbon flux estimations.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"378 ","pages":"Article 110987"},"PeriodicalIF":5.7,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145785326","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-year water and carbon flux contrasts between high-yielding and conventional rice cultivars","authors":"Keisuke Ono ,&nbsp;Hiroki Ikawa ,&nbsp;Akira Miyata","doi":"10.1016/j.agrformet.2025.110983","DOIUrl":"10.1016/j.agrformet.2025.110983","url":null,"abstract":"<div><div>Cultivation of high-yielding indica rice varieties has been spreading in Japan. This trend raises concerns about their potential impacts on water use and the carbon cycle. To this end, eddy covariance flux measurements were conducted from transplanting to harvest over three years for a high-yielding rice variety, Oonari, and compared with a conventional japonica rice variety, Koshihikari, in farmers’ fields under actual management practices. Evapotranspiration (ET) was higher for Oonari in 2018 and 2019, being 9.6 % higher than Koshihikari (2018: Oonari, 549.6 mm; Koshihikari, 501.2 mm; 2019: Oonari, 472.0 mm; Koshihikari, 430.5 mm). In 2020, ET for Oonari was 6.0 % smaller due to a shorter growth period (Oonari, 426.5 mm; Koshihikari, 453.9 mm). Gross primary production (GPP) was significantly higher for Oonari, averaging 24 % more than Koshihikari (Oonari: 1175.2±76.5 g C m^–2, Koshihikari: 946.5±32.7 g C m^–2). Higher ET and GPP of Oonari were reflected in greater crop coefficients and radiation use efficiency. These characteristics are mainly due to Oonari's higher leaf area index and extended photosynthetic period, highlighting the importance of field-scale evaluations throughout the entire growth period. Although both ET and GPP were greater in Oonari than in Koshihikari, the more pronounced difference in GPP indicates that cultivating Oonari has a greater impact on the carbon cycle than on water use.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"378 ","pages":"Article 110983"},"PeriodicalIF":5.7,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145785325","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":"Daily global transpiration estimation (2001–2018) by integrating satellite solar-induced fluorescence and spatially heterogeneous slope parameter in a conductance-photosynthesis model","authors":"Jiaxin Jin ,&nbsp;Linan Dong ,&nbsp;Guojing Gan ,&nbsp;Xingwang Fan ,&nbsp;Ying Wang ,&nbsp;Qiuan Zhu ,&nbsp;Russell Doughty ,&nbsp;Yuanwei Qin ,&nbsp;Guishan Yang","doi":"10.1016/j.agrformet.2025.110993","DOIUrl":"10.1016/j.agrformet.2025.110993","url":null,"abstract":"<div><div>Plant transpiration (<em>T_c</em>) is a key element of the water cycle. The conductance-photosynthesis (G_s-A) model, which assumes a linear relationship between stomatal conductance (<em>G_s</em>) and photosynthetic rate (<em>A</em>) under specific environmental conditions, is widely used to estimate <em>G_s</em> for the remote sensing of <em>T_c</em>. Nevertheless, the key parameter of the G_s-A model, the slope parameter, is typically assigned a biome-specific constant value, despite significant spatial heterogeneity observed within individual biomes. Moreover, the G_s-A model may introduce uncertainties into <em>T_c</em> estimation due to the broad-scale GPP simulated by empirical or complex process models. In this study, <em>G_s</em> was estimated using a typical G_s-A model (i.e., Ball-Berry model) enhanced by integrating daily satellite-observed solar-induced chlorophyll fluorescence (SIF), with a corresponding slope parameter (termed <em>m_sif</em>) that varies spatially with the local leaf area index (<em>LAI</em>) and air temperature (<em>TEM_a</em>). Subsequently, a daily global <em>T_c</em> product (named <strong>T_sif</strong>) at a 0.05^° spatial resolution (2001–2018) was generated, utilizing the Penman-Monteith equation combined with the improved <em>G_s</em>-<em>A</em> model. Observation data of 56 flux sites from the FLUXNET2015 were used to assess the performance and uncertainty of <em>T_c</em> across major vegetation types. Results demonstrated that daily-scale <em>T_c</em> estimation using the dynamic parameterization scheme of <em>m_sif</em> (DYN) outperformed the fixed scheme (FIX), reducing the root mean square error (RMSE) by an average of 10.89 % compared with flux observations. Furthermore, the spatiotemporal variations in <em>T_c</em> from our product showed good agreement with widely used <em>T_c</em> products, such as GLEAM, SiTHv2, and PML_v2. Notably, compared with flux observations, <strong>T_sif</strong> exhibited superior performance for Evergreen Broadleaf Forest, Deciduous Broadleaf Forest &amp; Woody Savannas (DW), Savannas &amp; Shrubland, and Grass, achieving the lowest RMSE values (0.88, 0.85, 0.55, and 0.74 mm day⁻¹, respectively). The <strong>T_sif</strong> dataset provides a novel, independent product valuable for analyses of the water cycle and ecohydrology at large scales.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"378 ","pages":"Article 110993"},"PeriodicalIF":5.7,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145785335","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":"Using point dendrometers to improve forest transpiration estimation accuracy at stand scales","authors":"Ryan M. Bright ,&nbsp;Danielle Creek ,&nbsp;Holger Lange ,&nbsp;Helge Meissner ,&nbsp;Morgane Merlin ,&nbsp;Junbin Zhao","doi":"10.1016/j.agrformet.2025.110986","DOIUrl":"10.1016/j.agrformet.2025.110986","url":null,"abstract":"<div><div>Forest transpiration is often quantified by scaling up stem sap flow measured on a few trees within a stand. This procedure carries uncertainty related to the (ill)representativeness of the sampled trees for the entire stand, often comprising several thousand transpiring trees. Here, we explored the uncertainty reduction potential afforded by increasing the number of sampled trees within the stand – not by costly sap flow monitoring equipment – but by point dendrometers measuring sub-daily fluctuations in stem radii which partially correlate with xylem water movement (i.e., sap flow). Using measurements collected in a forest dominated by even-aged spruce trees over two growing seasons, we built an empirical model for estimating hourly sap flow from individual trees equipped with point dendrometers, then applied it to estimate the daily transpiration of the stand both with and without trees equipped with point dendrometers. We found that the expanded tree sample size reduced the uncertainty of the stand-level estimate by 31–37 %, suggesting that the benefit afforded by increasing the stand representativeness outweighed the cost of introducing modeling error. Given their relative simplicity and affordability, we encourage additional investigations into the use of point dendrometers for studying tree water relations and water consumption patterns of entire forested stands.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"378 ","pages":"Article 110986"},"PeriodicalIF":5.7,"publicationDate":"2025-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145785293","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":"Critical snowpack thresholds and escalating risks for extreme decreases in vegetation productivity across Northern Hemisphere ecosystems","authors":"Hao Liu ,&nbsp;Pengfeng Xiao ,&nbsp;Xueliang Zhang ,&nbsp;Xin Miao ,&nbsp;Bo Tang ,&nbsp;Yantao Liu ,&nbsp;Siyong Chen ,&nbsp;Gareth Rees ,&nbsp;Weimin Ju","doi":"10.1016/j.agrformet.2025.110992","DOIUrl":"10.1016/j.agrformet.2025.110992","url":null,"abstract":"<div><div>Seasonal snowpack is a key driver of vegetation productivity dynamics, but it is unclear at which levels of snowpack changes cause extreme decreases in vegetation productivity (EDVP), increasing the uncertainty in assessing the terrestrial carbon cycle. Here, we investigate the impact of different levels of snowpack changes on EDVP and identify the roles of different ecological processes of snowpack changes in the Northern Hemisphere (NH). The results show that over 30 % of snowpack decrease events are followed by EDVP events in ∼10 % of NH areas (<em>p</em> &lt; 0.05), which is mainly attributed to snowpack’s moisture effect (via altering soil moisture). On average, the response of EDVP to snowpack changes increases rapidly when snow water equivalent (SWE) is –0.85 standard deviations (σ) below the mean, peaking at –1.33σ. Moreover, vegetation in warm and dry regions, especially grasslands, is more vulnerable to decreased SWE, and its resistance significantly increases with increasing precipitation. The future risk of EDVP occurrence will significantly increase in more regions owing to decreased snowpack, with ∼8 % of NH areas experiencing EDVP annually after ∼2083 under SSP5-8.5 scenario. Our findings underscore the significance of decreased snowpack in regulating EDVP and provide insights for better projecting and mitigating ecological consequences of snowpack changes.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"378 ","pages":"Article 110992"},"PeriodicalIF":5.7,"publicationDate":"2025-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145785294","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":"Intra-annual density fluctuations in Pinus massoniana across subtropical forests in China: Occurrence patterns and triggering factors","authors":"Qin He ,&nbsp;Paolo Cherubini ,&nbsp;J. Julio Camarero ,&nbsp;Xiaochun Wang ,&nbsp;Yuan Zhang ,&nbsp;Danyang Yuan ,&nbsp;Shuguang Liu ,&nbsp;Liangjun Zhu","doi":"10.1016/j.agrformet.2025.110990","DOIUrl":"10.1016/j.agrformet.2025.110990","url":null,"abstract":"<div><div>Intra-annual density fluctuations (IADFs) are wood cells formed in response to abnormal climatic events during the growing season. They are crucial for evaluating the relationship between extreme climatic events and radial growth, as well as for understanding wood quality. However, most existing research has focused on seasonally dry Mediterranean and semi-arid conifer forests, with limited studies conducted in other regions—particularly subtropical forests, where frequent and severe droughts constrain forest productivity and growth. Here, we investigated the occurrence patterns and triggering factors of IADFs in <em>Pinus massoniana</em> plantations along a climate gradient in southern China. We found that latewood IADFs (IADF-L) are the predominant type formed by <em>P. massoniana</em>, whereas earlywood IADFs (IADF-E) are relatively rare. The frequency of IADFs showed a clear spatial pattern, gradually increasing as climate conditions became warmer and wetter. IADF-L frequency was negatively correlated with elevation but positively correlated with tree-ring width. High precipitation in late summer and early autumn, as well as hot and dry conditions during summer, triggered the formation of IADF-Ls, while spring (May) droughts induced IADF-E. The inferred climatic drivers of IADFs were further confirmed by climate-growth relationships based on seasonal wood data and the VS-Lite tree-ring growth model. Our findings provide a valuable foundation for developing management strategies for drought-prone subtropical pine forests. For example, artificial rainfall or supplemental irrigation during summer-autumn dry spells could stimulate the formation of IADF-Ls, thereby enhancing forest growth and carbon sequestration capacity.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"378 ","pages":"Article 110990"},"PeriodicalIF":5.7,"publicationDate":"2025-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145785296","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":"Unveiling spatial and temporal characteristics of cooling effects of rice paddy expansion in Northeast China","authors":"Tong Yang ,&nbsp;Jinwei Dong ,&nbsp;Jie Wang ,&nbsp;Chao Zhang ,&nbsp;Wenqi Liu ,&nbsp;Yuting Zhou ,&nbsp;Geli Zhang ,&nbsp;Guosong Zhao","doi":"10.1016/j.agrformet.2025.110967","DOIUrl":"10.1016/j.agrformet.2025.110967","url":null,"abstract":"<div><div>Rice paddy expansion in Northeast China can affect land surface temperature (LST) through biophysical mechanisms. However, the temporal and spatial heterogeneity of the LST effects, the variations associated with the area proportions of rice paddy, and the underlying biophysical mechanisms remain poorly understood. In this study, we analyze the differences in LST (dLST), albedo (dAlbedo), and evapotranspiration (dET) between rice paddies and adjacent rainfed croplands using a pair-wise comparison approach. Our results show that the expansion of rice paddies potentially reduces daytime LST (−2.02 ± 1.03 °C) and albedo (−1.02 ± 1.07 %) while increases nighttime LST (0.76 ± 0.41 °C) and ET (0.03 ± 1.20 mm/8 days) in Northeast China during the growing season (May to September). The effects are more pronounced in spring than in summer and autumn. Spatially, Sanjiang Plain exhibits a daytime cooling effect in later months and a nighttime warming effect in earlier months than other regions. For every ten percent increase in the area proportion of rice paddies, daytime dLST decreases by 1.60 °C, nighttime dLST increases by 0.64 °C, and dAlbedo decreases by 1.40 %. Using a decomposed temperature metric approach, we confirmed that non-radiative mechanisms dominate the cooling effects during the growing season. These findings emphasize the need to consider spatial heterogeneity and biophysical mechanisms of land cover changes in model simulations, crop planting plans, and regional climate mitigation strategies.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"378 ","pages":"Article 110967"},"PeriodicalIF":5.7,"publicationDate":"2025-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145785295","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":"Carbon fluxes and partitioning in Eucalyptus and Pinus plantations across a climatic gradient in Brazil","authors":"Fernanda Leite Cunha ,&nbsp;Otávio Camargo Campoe ,&nbsp;Cléber Rodrigo de Souza ,&nbsp;Isaira Leite & Lopes ,&nbsp;Yann Nouvellon ,&nbsp;Timothy Albaugh ,&nbsp;David R. Carter ,&nbsp;Rafael Rubilar ,&nbsp;Isabel Deliberari ,&nbsp;Rachel Cook ,&nbsp;Joannès Guillemot ,&nbsp;Guerric Le Maire ,&nbsp;Jean-Paul Laclau ,&nbsp;Jose Luiz Stape ,&nbsp;Clayton Alcarde Alvares","doi":"10.1016/j.agrformet.2025.110977","DOIUrl":"10.1016/j.agrformet.2025.110977","url":null,"abstract":"<div><div>Brazilian <em>Eucalyptus</em> and <em>Pinus</em> forests are the most productive forests worldwide. The growth rates of these intensively managed plantations depend strongly on environmental conditions and matching genotypes to local environments. Changing climates underscore the value of understanding the intricacies of how these plantations can fix high amounts of carbon (C) and grow so much wood. We measured the full C budgets of <em>Eucalyptus</em> and <em>Pinus</em> forests across climate gradients in Brazil, focusing on the rates of C uptake, the allocation of C to belowground roots and mycorrhizae, and stem growth. We found that gross primary production (GPP) varied more than sixfold across the climate conditions in Brazil. Maximum temperature was the main climatic driver of productivity, where extreme temperatures reduced fluxes to stem production while increasing fluxes to root production. Net ecosystem production varied with management and age across the sites. The ecophysiological investigation presented in this work is fundamental for understanding C partitioning behavior under extreme temperature conditions. In this way, our results provide tools for forest managers to support their decision-making processes as well as starting points for strategies to be implemented in projects aimed at mitigating the effects of climate change.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"378 ","pages":"Article 110977"},"PeriodicalIF":5.7,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145753299","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 ecosystem water use efficiency and recovery dynamics during flash droughts: insights from observations and model simulations","authors":"Yuefeng Hao ,&nbsp;Jiafu Mao ,&nbsp;Yaoping Wang ,&nbsp;Lianhong Gu ,&nbsp;Jeffrey Wood ,&nbsp;Paul J. Hanson ,&nbsp;Melanie A. Mayes ,&nbsp;Mingzhou Jin ,&nbsp;Peter E. Thornton ,&nbsp;Xiaoying Shi ,&nbsp;Daniel M. Ricciuto","doi":"10.1016/j.agrformet.2025.110982","DOIUrl":"10.1016/j.agrformet.2025.110982","url":null,"abstract":"<div><div>Flash droughts (FD), rapidly emerging in a warming future, disrupt ecosystems, agriculture, and water security. Ecosystem water use efficiency (WUE), the ratio of gross primary production (GPP) to actual evapotranspiration (AET), balances carbon assimilation and water loss. FD rapidly disrupts this balance, making WUE critical for assessing plant stress and recovery. This study investigates the dynamics of landscape-scale WUE, and the components of GPP and AET under FD utilizing both observed data from the Missouri Ozark AmeriFlux site (US-MOz) and version 2 of the U.S. Department of Energy’s Earth, Energy, Exascale System Model (E3SM) Land Model (ELMv2). Observations and simulations reveal GPP as dominant for WUE during earlier FD events (2005, 2007, 2012), shifting to AET in recent events (2014, 2018). This agreement indicates that the ELM can capture the shifting dynamics of GPP and AET in regulating WUE under FD conditions. However, the ELM systematically underestimates both GPP and AET and does so in a manner that does not preserve their ratio. As a result, WUE is also underestimated, suggesting that GPP is more strongly underestimated than AET. Furthermore, the ELM also underestimates the speed of GPP recovery, producing an artificially prolonged GPP recovery time following FD events. Observed environmental drivers such as vapor pressure deficit (VPD), soil moisture (SM), and predawn leaf water potential (PLWP) effectively predict WUE, but ELM primarily highlights SM, underestimating VPD’s role. This study demonstrates that relying solely on soil moisture fails to capture the rapid hydraulic recovery observed in PLWP, underscoring the necessity of integrating plant hydraulics into land surface models to improve flash drought predictability.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"378 ","pages":"Article 110982"},"PeriodicalIF":5.7,"publicationDate":"2025-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145731138","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}