Agricultural and Forest Meteorology最新文献

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Carbon exchange in a tropical montane rainforest: Annual budgets, drivers, and anomalies 热带山地雨林的碳交换：年度预算、驱动因素和异常现象

IF 6.2 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2026-02-03 DOI: 10.1016/j.agrformet.2026.111049

Peirong Liu, Zhang Zhou, Guilin Wu, Xiaojuan Tong, Tao Zhang, Jingru Zhang, Fangyuan Wang, Dexiang Chen

引用次数: 0

From past exceptional extremes to frequent future risks: How climate change shapes the fate of common wheat in France 从过去的异常极端天气到未来频繁的风险：气候变化如何影响法国普通小麦的命运

IF 6.2 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2026-02-03 DOI: 10.1016/j.agrformet.2026.111054

Mael Aubry, Benjamin Renard, Thomas Opitz, Renan Le Roux, Marie Launay, Iñaki García de Cortázar-Atauri, Carina Furusho-Percot

引用次数: 0

Observed declining strength of vegetation-atmosphere coupling 观测到植被-大气耦合强度下降

IF 6.2 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2026-02-02 DOI: 10.1016/j.agrformet.2026.111051

Shijie Li, Guojie Wang, Shanlei Sun, Zefeng Chen, Matteo Mura, Jiao Lu, Qi Liu, Ji Li, Daniel Fiifi Tawia Hagan, Almudena García-García, Jian Peng

引用次数: 0

Short-distance dispersion of birch pollen 桦树花粉的短距离分散

IF 6.2 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2026-02-02 DOI: 10.1016/j.agrformet.2026.111052

Towa Yamane, Masaru Inatsu, Jun Kawano, Takuto Sato, Hiroyuki Kusaka

引用次数: 0

Corrigendum to “Interannual climatic sensitivity of surface energy flux densities and evapotranspiration in a disturbed and rewetted ombrotrophic bog” [Agricultural and Forest Meteorology 367 (2025) 110501] “扰动和再湿润的共生沼泽中地表能量通量密度和蒸散的年际气候敏感性”[农林气象367(2025)110501]的勘误表

IF 6.2 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2026-02-01 DOI: 10.1016/j.agrformet.2026.111043

J.L. Exler, J. Skeeter, S.H. Knox, A. Christen, R.D. Moore

引用次数: 0

The influence of spatial correlations in crop production on global crop failures in model simulations 模式模拟中作物生产空间相关性对全球作物歉收的影响

IF 5.7 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2026-01-30 DOI: 10.1016/j.agrformet.2026.111021

Sifang Feng , Jakob Zscheischler , Zengchao Hao , Jonas Jägermeyr , Christoph Müller , Emanuele Bevacqua

Spatial correlation between climate variables may modulate concurrent regional crop failures and reduce global crop production. However, the influence of spatial correlation in crop production fields on globally aggregated production remains poorly understood. Systematically addressing this gap using observed crop production is challenging, as such observational datasets typically suffer from limited sample sizes and/or coarse spatial information. Here, using gridded global simulations from the Global Gridded Crop Model Intercomparison Phase 3 (GGCMI3), we quantify how spatial correlation between regional crop productions influences global production across different spatial scales for maize, wheat, soybean, and rice. By employing the mean of crop production from multiple crop models forced with reanalysis climate data, we find minimal influence of the correlations between the productions of major breadbasket regions on global breadbasket-aggregated production. This aligns with the fact that global major breadbasket regions are generally non-large and distant from each other, whereas spatial correlations in the crop production field influence global crop production through correlations between small and nearby areas. The correlation between crop production of areas characterized by small spatial scales (100–1000 km) enhances extremely low (5th percentile) global production by about 0.9-1.1 standard deviation of the global production on average. This correlation effect at small spatial scales is less important for weaker extremes of low global crop production. Finally, crop model simulations forced with bias-corrected climate simulations often are not able to reproduce the correlation effects seen in crop model simulations forced with reanalysis climate data, suggesting that bias-corrected climate model input may degrade correlation effects in GGCMI3 crop simulations. These model-based results highlight that spatial correlations are a critical driver of global production risk, stressing the need for improved cross-regional processes representation in crop models to enhance future food security risk assessments.

气候变量间的空间相关性可能调节同时发生的区域作物歉收并降低全球作物产量。然而，作物生产领域的空间相关性对全球总产量的影响尚不清楚。利用观测到的作物产量系统地解决这一差距具有挑战性，因为此类观测数据集通常样本量有限和/或空间信息粗糙。本文利用全球网格化作物模型比对阶段3 （GGCMI3）的网格化全球模拟，量化了区域作物生产之间的空间相关性如何影响玉米、小麦、大豆和水稻在不同空间尺度上的全球产量。通过使用再分析气候数据强迫的多种作物模型的作物产量平均值，我们发现主要产粮区产量之间的相关性对全球产粮区总产量的影响最小。这与全球主要产粮区通常面积不大且彼此相距遥远的事实相一致，而作物生产领域的空间相关性通过小区域和附近区域之间的相关性影响全球作物生产。小空间尺度（100-1000 km）区域作物产量的相关性使极低（第5百分位）全球产量平均提高约0.9-1.1个标准差。在小空间尺度上，这种相关效应对全球低作物产量的弱极端不太重要。最后，用偏校正气候模拟强迫的作物模式模拟往往不能再现用再分析气候数据强迫的作物模式模拟所看到的相关效应，这表明偏校正气候模式输入可能会降低GGCMI3作物模拟的相关效应。这些基于模型的结果强调，空间相关性是全球生产风险的关键驱动因素，强调需要改进作物模型中的跨区域过程代表性，以加强未来的粮食安全风险评估。

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引用次数: 0

The efficiency-level inconsistency of the SIF–GPP relationship in a subtropical evergreen forest in Okinawa, Japan 日本冲绳亚热带常绿森林SIF-GPP关系的效率水平不一致性

IF 5.7 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2026-01-29 DOI: 10.1016/j.agrformet.2026.111050

Junjie Fu , Tomomichi Kato , Tomoki Morozumi , Kazuho Matsumoto , Shingo Taniguchi , Masahito Ueyama , Kanokrat Buareal , Tatsuya Miyauchi , Naohisa Nakashima , Tomoko Kawaguchi Akitsu

Monitoring of photosynthetic activity is essential for understanding forest carbon dynamics, particularly in structurally stable but physiologically dynamic ecosystems such as subtropical evergreen broadleaf forests. This study investigated the seasonal and diurnal dynamics of far-red and red solar-induced chlorophyll fluorescence (SIF), gross primary productivity (GPP), and related metrics in a subtropical evergreen broadleaf forest in Okinawa, Japan, on the basis of ground-based observations from 2020 to 2022. Far-red SIF consistently exhibited stronger and more stable correlations with GPP than red SIF, especially under overcast conditions and at daily temporal resolution. However, a significant environmental divergence was observed in the efficiency metrics. Environmental binning analyses revealed that light-use efficiency (LUE) responded strongly to changes in vapor pressure deficit (VPD), whereas SIF yield exhibited much weaker sensitivity. Random forest analysis further supported this divergence, showing a distinct, time-dependent sensitivity of SIF yield and LUE to VPD. Consistent with these environmental sensitivities, diurnal patterns showed that a pronounced inconsistency emerged at the efficiency level: the relationship between far-red SIF yield and LUE was generally weak or non-significant, indicating asynchronous regulation of fluorescence efficiency and carbon assimilation. Diurnal analyses showed that this decoupling could become more pronounced under certain conditions, such as during the afternoon. These findings refine the interpretation of SIF-based indicators in dense evergreen canopies and underscore the importance of the efficiency-level asynchronous recovery for improving SIF-based GPP models in subtropical ecosystems.

监测光合活动对于了解森林碳动态至关重要，特别是在结构稳定但生理动态的生态系统中，如亚热带常绿阔叶林。利用2020 - 2022年的地面观测资料，研究了日本冲绳亚热带常绿阔叶林远红和红光诱导的叶绿素荧光（SIF）、总初级生产力（GPP）及相关指标的季节和日动态。远红色SIF与GPP的相关性一直比红色SIF更强、更稳定，特别是在阴天条件下和在日时间分辨率下。然而，在效率指标中观察到显著的环境差异。环境分仓分析表明，光利用效率（LUE）对蒸汽压差（VPD）的变化响应强烈，而SIF产率的敏感性要弱得多。随机森林分析进一步支持了这种差异，显示出SIF产量和LUE对VPD具有明显的、随时间变化的敏感性。与这些环境敏感性相一致的是，日模式表明，在效率水平上出现了明显的不一致性：远红色SIF产量与LUE之间的关系普遍较弱或不显著，表明荧光效率和碳同化的异步调节。每日分析表明，在某些情况下，这种脱钩可能会变得更加明显，比如在下午。这些发现完善了常绿茂密林冠层中基于sif的指标的解释，并强调了效率级异步恢复对改进亚热带生态系统中基于sif的GPP模型的重要性。

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引用次数: 0

Evaluating the impact of different freezing-point depression equations on permafrost hydrothermal processes in the Arctic and Qinghai-Tibet Plateau with CLM5.0 基于CLM5.0评价不同冰点下降方程对北极和青藏高原冻土热液过程的影响

IF 5.7 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2026-01-28 DOI: 10.1016/j.agrformet.2026.111034

Shenning Wang , Ren Li , Tonghua Wu , Junjie Ma , Wenhao Liu , Shuhua Yang , Yizhen Du , Yao Xiao , Xiaodong Wu , Guojie Hu , Jimin Yao , Shengfeng Tang , Xiaofan Zhu , Jianzong Shi , Yongping Qiao

Soil hydrothermal processes in permafrost regions are critical for land-atmosphere exchange but are challenging to simulate accurately in models, largely due to the parameterization of unfrozen water content. This study evaluated 11 freezing-point depression schemes, derived from combinations of three soil water characteristic curves (SWCCs) and four soil matric potential schemes, using CLM5.0 at six sites across the Arctic and Qinghai-Tibet Plateau (QTP). Results showed regionally dependent optimal schemes. For soil temperature, a combined effective porosity and cryosuction scheme (TEST3) reduced the RMSE by 0.51–0.52°C (7.1–8.3%) in the Arctic, while a cryosuction scheme (TEST10) was best on the QTP, reducing RMSE by 0.04–0.06°C. For soil moisture, a Van Genuchten SWCC scheme with effective porosity (TEST5) reduced RMSE by up to 0.018 m³/m³ (13.2%) in the Arctic, and TEST4/TEST5 performed best on the QTP. The explicit parameterization of residual water content in Brooks & Corey and Van Genuchten SWCCs was a key mechanism, correcting the default scheme's large soil moisture bias by up to 53% during freezing. Cryosuction increased unfrozen water, while effective porosity decreased it. However, model structural limitations caused unreliable matric potential output during freezing. Persistent biases at specific sites were attributed to inaccurate soil texture data, unaccounted lateral flow, and insufficient snow insulation representation. This study highlights the regional applicability of schemes and provides critical insights for improving permafrost simulations.

多年冻土区的土壤热液过程对陆地-大气交换至关重要，但由于未冻水含量的参数化，在模式中难以准确模拟。本研究利用CLM5.0软件对北极和青藏高原6个站点的11个冰点降低方案进行了评价，这些方案由3种土壤水分特征曲线（swcc）和4种土壤基质势方案组合而成。结果显示了区域相关的最优方案。对于土壤温度，有效孔隙度和低温吸力组合方案（TEST3）在北极降低RMSE 0.51 ~ 0.52°C(7.1 ~ 8.3%)，而低温吸力方案（TEST10）在QTP上效果最好，降低RMSE 0.04 ~ 0.06°C。对于土壤水分，具有有效孔隙度（TEST5）的Van Genuchten SWCC方案在北极减少RMSE高达0.018 m3/m3(13.2%)，而TEST4/TEST5在QTP上表现最好。在Brooks & Corey和Van Genuchten swcc中，剩余水分的显式参数化是一个关键机制，它在冻结期间纠正了默认方案中高达53%的土壤水分偏差。低温吸吸增加了未冻水，而有效孔隙率降低了。然而，模型结构的限制导致冻结过程中矩阵电位输出不可靠。特定地点的持续偏差归因于不准确的土壤质地数据、未考虑的横向流动和不充分的雪绝缘表征。这项研究强调了方案的区域适用性，并为改进永久冻土模拟提供了重要的见解。

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引用次数: 0

Cropland evapotranspiration based on Sentinel-2 shortwave infrared data and ensemble Kalman filter 基于Sentinel-2短波红外数据和集合卡尔曼滤波的农田蒸散发

IF 5.7 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2026-01-27 DOI: 10.1016/j.agrformet.2026.111035

Lu Liu , Yunjun Yao , Qingxin Tang , Xueyi Zhang , Yufu Li , Joshua B. Fisher , Jiquan Chen , Jia Xu , Xiaotong Zhang , Ruiyang Yu , Zijing Xie , Jing Ning , Jiahui Fan , Luna Zhang

The latent heat of evapotranspiration (LE) is a vital element of agricultural water resources; accurately estimating cropland LE at a fine spatial resolution is crucial for monitoring agricultural drought and estimating crop water requirements. In this study, we propose a shortwave infrared-transformed reflectance (STR)-and ensemble Kalman filter (EnKF)-based Priestley–Taylor (STR–EnKF–PT) model to simulate daily cropland LE using Sentinel-2 data. To evaluate the STR–EnKF–PT model’ performance, we conducted an assessment using ground observations derived from 10 eddy covariance (EC) sites situated in various regions of the United States over the two-year period from 2019 through 2020.The results revealed that STR–EnKF–PT yielded better performance than the competing methods did at four validation sites; additionally, the coefficient of determination (R²) was 0.54∼0.84 at the 99 % confidence level, the root-mean-square error (RMSE) was 26.1∼38.0 W/m², the Kling–Gupta efficiency (KGE) value was 0.69∼0.91, and the bias was -16.3∼9.4 W/m². Crucially, the ensemble system demonstrated robust probabilistic forecasting capabilities across different validation sites, with an excellent mean reliability score of 0.0010, a mean continuous ranked probability score (CRPS) of 29.91 W/m², and appropriate spread-error relationships with a mean ratio of 1.239, providing reliable probability distributions of LE forecasts beyond deterministic estimates. STR–EnKF–PT was then used to depict the spatial patterns of cropland LE at a 20-m resolution in six different regions across the United States, and the results revealed that it is possible to accurately distinguish the LE status of cultivated land. One innovation is the use of soil moisture (SM) constraints derived from the STR to achieve high-resolution (20-m) cropland LE estimation. Furthermore, the incorporation of EnKF significantly enhances the estimated accuracy of the STR–EnKF–PT model and enables reliable probabilistic forecasting. This approach has significant practical implications for achieving the efficient utilization of cropland irrigation water and agricultural risk management processes.

蒸散发潜热是农业水资源的重要组成部分；在精细空间分辨率下准确估算农田LE对于监测农业干旱和估算作物需水量至关重要。在这项研究中，我们提出了一个基于短波红外变换反射率（STR）和集合卡尔曼滤波（EnKF）的Priestley-Taylor （STR - EnKF - pt）模型，利用Sentinel-2数据模拟农田日LE。为了评估STR-EnKF-PT模型的性能，我们利用2019年至2020年两年期间来自美国不同地区的10个涡动相关（EC）站点的地面观测数据进行了评估。结果表明，STR-EnKF-PT在4个验证位点的性能优于竞争对手的方法；此外，在99%置信水平下，决定系数（R2）为0.54 ~ 0.84，均方根误差（RMSE）为26.1 ~ 38.0 W/m2，克林-古普达效率（KGE）值为0.69 ~ 0.91，偏差为-16.3 ~ 9.4 W/m2。重要的是，该集成系统在不同验证点显示出稳健的概率预测能力，平均可靠度得分为0.0010，平均连续排序概率得分（CRPS）为29.91 W/m2，平均差差比为1.239，提供了可靠的LE预测概率分布，超出确定性估计。利用STR-EnKF-PT在20 m分辨率下对美国6个不同地区的耕地LE进行了空间特征描述，结果表明，STR-EnKF-PT能够准确区分耕地LE状况。其中一个创新是利用STR导出的土壤湿度（SM）约束来实现高分辨率（20米）农田LE估计。此外，EnKF的引入显著提高了STR-EnKF-PT模型的估计精度，实现了可靠的概率预测。这种方法对实现农田灌溉用水的有效利用和农业风险管理过程具有重要的实际意义。

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引用次数: 0

Annual dynamics of net ecosystem carbon dioxide exchange in differently managed tallgrass prairies under variable rainfall 降雨变化下不同管理方式高草草原生态系统净二氧化碳交换的年动态

IF 5.7 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2026-01-24 DOI: 10.1016/j.agrformet.2026.111047

Pradeep Wagle , Brian K. Northup , Xiangming Xiao , Tanka Kandel , Andres Cibils , Stacey A. Gunter

Tallgrass prairies are vital ecosystems that support regional biodiversity and play a crucial role in global carbon cycling. However, the management practices and disturbances they face can significantly alter their roles as carbon sinks or sources. Despite their importance, the carbon source-sink status of differently managed tallgrass prairies, especially under varying weather conditions, remains uncertain. This study utilized eddy covariance measurements of carbon dioxide (CO₂) fluxes from four co-located tallgrass prairie pastures with different management regimes, including prescribed spring burns, intensive and rotational grazing, and haying. The primary objectives were to thoroughly evaluate the dynamics of net ecosystem CO₂ exchange (NEE) and to investigate how diverse weather conditions affected carbon exchange across differently managed tallgrass prairies in central Oklahoma. The study period (2019-2024) experienced substantial variability in rainfall patterns. As expected, aboveground biomass and satellite-derived enhanced vegetation index (EVI) displayed distinct interannual variations. During the growing season (April-October, DOY ∼100-300), pastures generally behaved as net carbon sinks, with NEE ranging from -33 to -478 g C m⁻². However, the magnitude and duration of the carbon sink and the overall annual carbon balance showed considerable interannual variations. Annual NEE ranged from 104 g C m⁻² (carbon source) to -362 g C m⁻² (carbon sink). Interannual variations in forage production, vegetation dynamics, and NEE were mainly influenced by rainfall variability, with growing season rainfall strongly correlating with peak biomass and EVI (R² = 0.67-0.71). Although management practices modulated these rainfall effects on carbon exchange, random forest analysis showed that EVI was the primary predictor of NEE across pastures, reflecting its capacity to integrate the combined effects of meteorological factors on carbon uptake. Our findings emphasize the need for adaptive management strategies tailored to local rainfall patterns and forecasts to optimize forage production, increase carbon sequestration, and strengthen the resilience of grassland ecosystems.

高草草原是支持区域生物多样性和在全球碳循环中发挥关键作用的重要生态系统。然而，它们面临的管理实践和干扰可能显著改变它们作为碳汇或碳源的作用。尽管它们很重要，但不同管理方式的高草草原的碳源-汇状况仍然不确定，特别是在不同的天气条件下。本研究利用涡流相关方差测量了4个共地高草草原的二氧化碳（CO2）通量，这些牧场采用不同的管理制度，包括规定的春季焚烧、集约放牧和轮牧以及干草。主要目标是全面评估净生态系统二氧化碳交换（NEE）的动态，并调查不同天气条件如何影响俄克拉何马州中部不同管理的高草草原的碳交换。在研究期间（2019-2024年），降雨模式发生了实质性变化。正如预期的那样，地上生物量和卫星反演的增强植被指数（EVI）表现出明显的年际变化。在生长季节（4 - 10月，DOY ~ 100-300），牧场通常表现为净碳汇，NEE范围为-33至-478 g C m - 2。然而，碳汇的大小和持续时间以及年总体碳平衡表现出较大的年际变化。年NEE范围为104g cm−2（碳源）~ -362 g cm−2（碳汇）。牧草产量、植被动态和NEE的年际变化主要受降雨变率的影响，生长期降雨量与峰值生物量和EVI呈强相关（R2 = 0.67 ~ 0.71）。尽管管理措施调节了降雨对碳交换的影响，但随机森林分析表明，EVI是整个牧场新能源经济的主要预测因子，反映了其综合气象因子对碳吸收的综合影响的能力。我们的研究结果强调，需要针对当地降雨模式和预测制定适应性管理策略，以优化牧草生产，增加碳固存，增强草地生态系统的恢复力。

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