Agricultural and Forest Meteorology最新文献_第3页

Net ecosystem carbon balance and greenhouse gas budget of a canola-wheat cropping system in the northern prairies 北方草原油菜-小麦种植系统净生态系统碳平衡与温室气体收支

IF 5.7 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2026-03-15 Epub Date: 2026-02-07 DOI: 10.1016/j.agrformet.2026.111044

D. Ferland , C. Wagner-Riddle , P․K․C Pow , S․E. Brown , K․A. Congreves

Arable croplands are critical in the context of climate change, acting as both sources and potential sinks of greenhouse gases (GHG) in the form of carbon dioxide (CO₂) and nitrous oxide (N₂O). However, there is limited data on the carbon (C) balance and GHG budget (GHGB) from canola-wheat rotations in the northern Prairies of North America, an important agricultural region. We present micrometeorological GHG fluxes measured from January 2021 to April 2025 through two rotations of canola-wheat in Saskatchewan, Canada, to evaluate the interannual C dynamics and GHGB of the 4-year cropping sequence. Net ecosystem exchange (NEE) ranged from 87 to -239 g C m^-2, driven by variable meteorological conditions. Annual cumulative gross primary production (GPP) exceeded the cumulative ecosystem respiration (R_e) in all years except 2021—the second driest year on record for this region. The GHGB values were between 60 and 156 CO₂-eq m^-2 yr^-1 in the first 3 crop years, but were negative (i.e., GHG sink) in Year 4. Overall, this study presents the first multi-year, measurement-based assessment of canola-wheat rotations in the northern Prairies, showing that over a 4-year period, the cropping system was C neutral (net ecosystem carbon balance [NECB] = 2 ± 35 g C m^-2 yr^-1). The dataset provides the region-specific information needed to inform C policy and evaluate the agricultural sustainability of the northern Prairies. It also provides valuable information for canola and wheat crops, particularly the impact of harvest removals and N fertilizer application—practices that can be targeted for agricultural GHG emissions mitigation.

可耕地在气候变化的背景下至关重要，既是二氧化碳（CO2）和一氧化二氮（N2O）形式的温室气体（GHG）的来源，也是潜在的汇。然而，关于北美北部草原油菜-小麦轮作的碳(C)平衡和温室气体收支（GHGB）数据有限。本文利用加拿大萨斯喀彻温省油菜-小麦两个轮作在2021年1月至2025年4月测量的微气象温室气体通量，评估了4年种植序列的年际碳动态和温室气体排放量。净生态系统交换（NEE）在87 ~ -239 g C m-2之间，受不同气象条件的驱动。除2021年（该地区有记录以来第二干旱的年份）外，所有年份的年累积初级生产总值（GPP）均超过累积生态系统呼吸（Re）。前3个作物年的GHGB值在60 ~ 156 co2当量m-2年-1之间，但在第4年为负（即温室气体汇）。总体而言，本研究首次提出了对北部草原油菜-小麦轮作的多年期、基于测量的评估，表明在4年期间，种植系统是C中性的（净生态系统碳平衡[NECB] = 2±35 g C m-2年-1）。该数据集提供了为气候政策提供信息和评估北部草原农业可持续性所需的特定区域信息。它还为油菜籽和小麦作物提供了宝贵的信息，特别是可作为减缓农业温室气体排放目标的收获和氮肥施用方法的影响。

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引用次数: 0

Improved simulation of gross primary production and evapotranspiration in a drought-prone temperate deciduous forest with the BEPS-EcoHydro 利用BEPS-EcoHydro改进的干旱易发温带落叶森林的总初级生产量和蒸散量模拟

IF 5.7 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2026-03-15 Epub Date: 2026-01-22 DOI: 10.1016/j.agrformet.2026.111031

Lu Hu , Mousong Wu , Weimin Ju , Xiuli Xing , Jing M. Chen , Huajie Zhu

Climate extremes, particularly drought, severely affect ecosystem functions. Most terrestrial biosphere models use empirical soil moisture stress factors to represent the impacts of drought on stomatal conductance and photosynthesis, which lack a mechanistic representation of water flow in the soil-plant-atmosphere continuum (SPAC) and result in uncertainties in simulated carbon and water fluxes. In this study, a plant hydraulics module was integrated into the process-based Biosphere-atmosphere Exchange Process Simulator, i.e., the BEPS-EcoHydro, and comprehensively evaluated in a drought-prone temperate deciduous forest in the central USA. BEPS-EcoHydro considers SPAC water flow driven by the soil-leaf water potential gradient, potential transpiration, and plant water storage. Building on these hydraulic processes, the effect of water stress on photosynthesis in BEPS-EcoHydro was quantified via a linkage to leaf water potential. The results showed that BEPS-EcoHydro effectively captured variations in predawn leaf water potential at the ecosystem scale with a coefficient of determination (R²) of 0.54 (p < 0.01), and outperformed the original BEPS in simulating soil moisture with an improvement of R² by 34%. Additionally, evapotranspiration (ET) and gross primary production (GPP) simulation performance has been improved with BEPS-EcoHydro, especially at the hourly scale. Importantly, BEPS-EcoHydro captured drought impact better than the original BEPS and detected the hysteretic responses of GPP and ET to leaf water potential during drought intensification and recovery periods. These results suggest that consideration of plant hydraulics in process-based ecosystem models is necessary to better understand mechanisms in vegetation responses to climate extremes.

极端气候，特别是干旱，严重影响生态系统功能。大多数陆地生物圈模型使用经验土壤水分胁迫因子来表示干旱对气孔导度和光合作用的影响，缺乏土壤-植物-大气连续体（SPAC）中水流的机制表示，导致模拟的碳和水通量存在不确定性。在本研究中，将植物水力学模块集成到基于过程的生物圈-大气交换过程模拟器（BEPS-EcoHydro）中，并在美国中部一个易干旱的温带落叶森林中进行了综合评估。BEPS-EcoHydro考虑由土壤-叶片水势梯度、潜在蒸腾和植物储水量驱动的SPAC水流量。在这些水力过程的基础上，通过与叶片水势的联系，量化了水分胁迫对BEPS-EcoHydro光合作用的影响。结果表明，BEPS- ecohydro有效捕获了生态系统尺度上黎明前叶片水势的变化，决定系数（R2）为0.54 (p < 0.01)，在模拟土壤水分方面优于原BEPS， R2提高了34%。此外，BEPS-EcoHydro的蒸散发（ET）和总初级生产量（GPP）模拟性能也得到了改善，尤其是在小时尺度上。重要的是，BEPS- ecohydro比原始BEPS更好地捕捉了干旱影响，并检测了干旱加剧和恢复期间GPP和ET对叶片水势的滞后响应。这些结果表明，为了更好地理解植被对极端气候的响应机制，在基于过程的生态系统模型中考虑植物水力学是必要的。

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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 : 2026-03-15 Epub 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

Multi-layer model requires accurate information of vertical structure to realize its full potential in simulating gross primary production 多层模型需要准确的垂直结构信息，才能充分发挥其模拟初级生产总量的潜力

IF 5.7 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2026-03-15 Epub Date: 2026-02-03 DOI: 10.1016/j.agrformet.2026.111036

Jiangliu Xie , Gaofei Yin , Shangrong Lin , Xiaozhou Xin , Hu Zhang , Xinjie Liu , Qinhuo Liu , Aleixandre Verger , Adrià Descals , Iolanda Filella , Josep Peñuelas

Photosynthesis, a vital process for carbon exchange between biosphere and atmosphere, has been integrated into terrestrial biosphere models (TBMs). TBMs employ upscaling methods such as big-leaf (BL), two-leaf (TL), or multi-layer (MTL) models to simulate canopy-scale photosynthesis, with MTL model theoretically offering the highest accuracy due to its detailed canopy representation. The comparative efficacy of these models in simulating gross primary production (GPP), however, remains uncertain. This study provides a systematic assessment of how the MTL differs from the BL and TL models in GPP estimation across global flux tower sites.

The results indicate that both the MTL and TL models performed better than BL model in simulating canopy GPP, reducing root mean square error (RMSE) by 32.23% and 26.51%, respectively, with the MTL (2.25 g C m⁻² d⁻¹) demonstrating a slightly improved accuracy compared to the TL model (2.44 g C m⁻² d⁻¹). Incorporating foliar clumping reduced the overestimation of GPP with mean error (ME) decreasing by 32%, 28.74%, and 6.94% for MTL, TL, and BL models, respectively; however, the specific impact varied among the models. The MTL model excelled in enabling layered simulations of photosynthesis, allowing for the identification of vertical heterogeneity in environmental responses. Nonetheless, its improvement in accuracy over simpler models like the TL model was limited without highly precise data on vertical structure. This study highlights that improved canopy structure data from LiDAR technologies, such as GEDI, is crucial for realizing the full potential of MTL models for accurately simulating carbon fluxes.

光合作用是生物圈与大气之间碳交换的重要过程，已被纳入陆地生物圈模型（tbm）。tbm采用大叶（BL）、两叶（TL）或多层（MTL）模型等升级方法来模拟冠层尺度的光合作用，其中MTL模型由于其详细的冠层表示，理论上提供了最高的精度。然而，这些模型在模拟初级生产总值（GPP）方面的比较功效仍然不确定。本研究对全球通量塔站点的GPP估算中MTL与BL和TL模式的差异进行了系统评估。结果表明，MTL模型和TL模型在模拟林冠GPP方面均优于BL模型，RMSE分别降低了32.23%和26.51%，其中MTL模型（2.25 g C m−2 d−1）的精度略高于TL模型（2.44 g C m−2 d−1）。加入叶面团块后，MTL、TL和BL模型的平均误差（ME）分别降低了32%、28.74%和6.94%；然而，具体影响因模型而异。MTL模型在实现光合作用的分层模拟方面表现出色，允许识别环境响应的垂直异质性。尽管如此，在没有高度精确的垂直结构数据的情况下，其精度比TL模型等简单模型的提高受到限制。这项研究强调了来自激光雷达技术（如GEDI）的改进的冠层结构数据对于实现MTL模型精确模拟碳通量的全部潜力至关重要。

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引用次数: 0

Evaluating surface fluxes in WRF using eddy-covariance flux measurements in the Western and Eastern U.S. 利用美国西部和东部涡旋协方差通量测量评估WRF的地表通量

IF 5.7 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2026-03-15 Epub Date: 2026-02-03 DOI: 10.1016/j.agrformet.2026.111029

Fan Wu , Kenneth J. Davis , Li Zhang , Ray G. Anderson , Jason P. Horne , Sarah Goslee , William Munger , Chenxia Cai , Yu Yan Cui , Zhan Zhao , Min Zhong

Atmospheric boundary layer simulations in weather models, important elements of air quality simulations, are coupled with land surface parameterizations. The San Joaquin Valley (SJV) of California and the Multi-state Mid-Atlantic (MMA) feature diverse land uses, including agriculture, urban areas, and forests, which pose challenges for simulating surface fluxes. This study evaluates surface fluxes in the Weather Research and Forecasting (WRF) model using physical configurations adopted by state air quality agencies in California and Pennsylvania. We compared WRF simulations with year-long eddy-covariance flux measurements from 16 sites across the two regions. Results show that the Pleim-Xiu land surface model (PX LSM) exhibits substantial heat flux biases in the SJV but lacks systematic biases in the MMA. In the SJV, the model overestimates daytime (10:00-16:00 LST) sensible heat flux (H) by 260 W m^-2 (274%) and underestimates latent heat flux (LE) by 200 W m^-2 (68%) at irrigated croplands and orchards during spring and summer. In the MMA, PX LSM moderately overestimates both H and LE, with stronger partitioning into H over urban surfaces and into LE over vegetation. Daytime momentum fluxes are overestimated in both regions, while nighttime biases are inconsistent. Our findings suggest that in the SJV, heat flux biases are strongly associated with irrigation during the growing season, while in the MMA, model-data residuals are limited to modest errors in the Bowen ratio and depend on land cover. Improving WRF’s representation of irrigation and land use, potentially through satellite remote sensing, may enhance surface flux simulation accuracy.

天气模式中的大气边界层模拟是空气质量模拟的重要元素，它与陆地表面参数化相耦合。加利福尼亚州的圣华金河谷（SJV）和多州大西洋中部（MMA）具有不同的土地用途，包括农业、城市地区和森林，这对模拟地表通量构成了挑战。本研究使用加州和宾夕法尼亚州州空气质量机构采用的物理配置来评估天气研究与预报（WRF）模型中的地表通量。我们将WRF模拟与两个地区16个站点的一年涡旋协方差通量测量结果进行了比较。结果表明，Pleim-Xiu陆面模式（PX LSM）在SJV中存在较大的热通量偏差，而在MMA中缺乏系统偏差。在SJV中，春夏季灌溉农田和果园白天（10:00-16:00 LST）感热通量(H)高估260 W m-2(274%)，潜热通量（LE）低估200 W m-2（68%）。在MMA中，PX LSM对H和LE均有适度高估，对城市地表上的H和植被上的LE的划分更强。这两个地区白天的动量通量都被高估了，而夜间的偏差则不一致。我们的研究结果表明，在SJV中，热通量偏差与生长季节的灌溉密切相关，而在MMA中，模型数据残差仅限于Bowen比的适度误差，并取决于土地覆盖。可能通过卫星遥感改善水资源循环系统对灌溉和土地利用的反映，可以提高地表通量模拟的准确性。

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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 : 2026-03-15 Epub 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

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

IF 5.7 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2026-03-15 Epub 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

Land-atmosphere coupling (LAC) directly influences the occurrence of extreme climate events. Traditionally, the studies of LAC strength have primarily used soil moisture as a proxy for land conditions. However, recent research has highlighted the significant role of vegetation–atmosphere coupling (VC) in the evolution of extreme climate events through its regulation of the water and energy cycles. Despite this progress, the global patterns and driving mechanisms of VC remain unclear. In this study, the index with a clear physical meaning, ω, defined as the relationship between the canopy conductance (g_c) and aerodynamic conductance (g_a), was introduced to represent VC values. Long-term (1981–2018) global annual VC values were derived using two high-quality reanalysis datasets (ERA5 and MERRA2) based on two different g_c models. Both g_c models exhibited similar spatial distributions that the highest VC values in Arid regions, the lowest in Humid regions, and intermediate values in Transition zones. Results showed 38.84–61.98 % of global land with decreasing VC trend. An attribution analysis using a nonlinear machine learning approach revealed that leaf area index (LAI) and wind speed dominated the VC changes across different climate zones. An increase in LAI reduced VC strength, whereas enhanced wind speed increased VC values. LAI was the dominant factor influencing VC through transpiration regulation (i.e., g_c) over Transition and Arid regions, while wind speed controlled VC variations via g_a over Humid regions. Our study analyzed the spatiotemporal changes in VC values and their driving mechanisms across global land areas. These findings contribute to a deeper understanding of vegetation-climate feedback and its role in amplifying extreme climate events.

陆地-大气耦合直接影响极端气候事件的发生。传统上，LAC强度的研究主要使用土壤湿度作为土地条件的代理。然而，近年来的研究强调了植被-大气耦合（VC）通过调节水和能量循环在极端气候事件演变中的重要作用。尽管取得了这些进展，但风险投资的全球模式和驱动机制仍不清楚。本文引入具有明确物理意义的指标ω，定义为冠层导度（gc）与空气动力导度（ga）之间的关系，来表示VC值。基于两种不同的gc模型，使用两个高质量的再分析数据集（ERA5和MERRA2）获得了长期（1981-2018）全球年度VC值。两种gc模型的空间分布相似，均表现为干旱区VC值最高，湿润区最低，过渡区处于中间值。结果表明，全球38.84 ~ 61.98%的土地呈下降趋势。利用非线性机器学习方法进行归因分析发现，叶面积指数（LAI）和风速在不同气候带的VC变化中起主导作用。LAI的增加降低了VC强度，而风速的增加增加了VC值。在过渡区和干旱区，LAI是通过蒸腾调节（即gc）影响VC的主导因子，而在湿润区，风速通过ga控制VC的变化。本研究分析了全球陆地区域VC值的时空变化及其驱动机制。这些发现有助于更深入地了解植被-气候反馈及其在放大极端气候事件中的作用。

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引用次数: 0

Regulatory mechanisms of spatiotemporal variations in aboveground and belowground net primary production in global terrestrial ecosystems 全球陆地生态系统地上、地下净初级生产量时空变化的调控机制

IF 5.7 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2026-03-15 Epub Date: 2026-02-06 DOI: 10.1016/j.agrformet.2026.111055

Tao Zhou , Yanting Xiong , Zhihan Yang , Yuting Hou , Yuqing Zhang , Dan Liao , Xiaodong Wang , Dinghui Xu , Pingfeng Li , Peng Hou , Wenji Zhao , Guo Chen , Benjamin Laffitte , Xiaolu Tang

Net primary productivity is a critical component of terrestrial carbon cycling and an essential indicator of ecosystem carbon sequestration capacity. However, separating aboveground and belowground net primary productivity (ANPP and BNPP) and understanding the driving mechanisms of their spatial patterns remain challenging across global terrestrial ecosystems. Here, we used a modified multilayer perceptron network (MLP) built upon an updated database containing 5184 field observations to predict the spatiotemporal patterns of ANPP and BNPP and identify their driving mechanisms across global terrestrial ecosystems at 0.05° resolution. Results indicated that the MLP model satisfactorily predicted ANPP (R² = 0.74) and BNPP (R² = 0.73). Spatially, both ANPP and BNPP exhibited strong spatial heterogeneity, with a decreasing trend from the tropics toward the poles. Temporally, ANPP showed an increasing trend of 0.02 Pg C yr⁻², with a global mean of 33.4 ± 0.5 (mean ± standard error) Pg C yr⁻¹ from 1981 to 2018. Similarly, the mean total BNPP was 19.2 ± 0.73 Pg C yr⁻¹, with an increasing trend of 0.05 Pg C yr⁻². Quantitatively, significant trends were observed, with 65.4% and 60.8% of land areas showing increasing trend of ANPP and BNPP (P < 0.01), respectively. The spatial patterns of ANPP were mainly influenced by temperature and precipitation, while BNPP was controlled by soil properties. These findings highlight the importance of distinguishing ANPP and BNPP to better understand the driving mechanisms of carbon allocation strategies. These findings are crucial for advancing the understanding of vegetation dynamics in response to global climate change and improving terrestrial ecosystem carbon modeling.

净初级生产力是陆地碳循环的重要组成部分，也是生态系统固碳能力的重要指标。然而，在全球陆地生态系统中，分离地上和地下净初级生产力（ANPP和BNPP）并理解其空间格局的驱动机制仍然具有挑战性。本文基于5184个野外观测数据，采用改进的多层感知器网络（MLP）在0.05°分辨率下预测了全球陆地生态系统ANPP和BNPP的时空格局，并确定了它们的驱动机制。结果表明，MLP模型对ANPP （R2 = 0.74）和BNPP （R2 = 0.73）的预测较好。在空间上，ANPP和BNPP均表现出较强的空间异质性，从热带向两极呈下降趋势。时间上，ANPP呈增加趋势，为0.02 Pg C yr - 2, 1981 - 2018年全球平均值为33.4±0.5（平均±标准误差）Pg C yr - 1。同样，平均总BNPP为19.2±0.73 Pg C yr - 1，并有0.05 Pg C yr - 2的增加趋势。在数量上，有显著的趋势，65.4%和60.8%的土地面积呈现ANPP和BNPP增加的趋势（P < 0.01）。ANPP的空间格局主要受温度和降水的影响，而BNPP受土壤性质的控制。这些发现强调了区分ANPP和BNPP对于更好地理解碳分配策略的驱动机制的重要性。这些发现对于提高对全球气候变化下植被动态的认识和改进陆地生态系统碳模型至关重要。

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引用次数: 0

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 5.7 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2026-03-15 Epub 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

Tropical forests store substantial carbon stocks and play important roles in biogeochemical carbon cycling. Understanding the drivers of carbon fluxes in tropical forests and how they respond to extreme events are crucial for predicting future global carbon dynamics. Utilizing a 12-year CO₂ flux dataset and meteorological variables from a tropical montane rainforest ecosystem in southern China. This study assessed the effects of climatic drivers on the seasonal and interannual variations in gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem productivity (NEP), as well as the responses of carbon fluxes to extreme climate events. The ecosystem functioned as a strong carbon sink (NEP = 368 ± 121 g C m⁻²) across the study period. Both GPP and ER were generally higher in the wet season. Compared to the dry season, NEP values decreased by 18% during the wet season, primarily due to a temperature-induced increase in ER surpassing GPP. Annual GPP, ER, and NEP showed increasing trends of 32.32 g C m^-2 year^-1 (P < 0.1), 24.4 g C m^-2 year^-1 (P > 0.1), and 12.78 g C m^-2 year^-1 (P > 0.1), respectively. For seasonal fluxes, GPP was mainly controlled by solar-induced chlorophyll fluorescence (SIF), air temperature (T_a), and solar radiation (R_s); ER was predominantly influenced by the SIF and T_a; and NEP was primarily driven by T_a and R_s. On the interannual scale, T_a was the most important factor affecting GPP, ER, and NEP, followed by SIF, precipitation (PPT), and R_s. Extreme climate events, such as typhoons, significantly reduced GPP and NEP via physical pathways, while having a minimal effect on ER. Droughts notably enhanced GPP and ER (P < 0.05). In contrast, a severe drought in 2006 led to reductions in GPP, ER, and NEP of 11%, 12%, and 8%, respectively. Overall, this study addresses the lack of long-term research on CO₂ fluxes in the tropical rainforest of China and will improve the understanding and prediction of the forest carbon dynamics.

热带森林蕴藏着丰富的碳储量，在生物地球化学碳循环中发挥着重要作用。了解热带森林碳通量的驱动因素以及它们如何对极端事件作出反应，对于预测未来全球碳动态至关重要。利用中国南方热带山地雨林生态系统12年CO2通量数据和气象变量。本研究评估了气候驱动因素对总初级生产力（GPP）、生态系统呼吸（ER）和净生态系统生产力（NEP）的季节和年际变化的影响，以及碳通量对极端气候事件的响应。在整个研究期间，生态系统作为一个强大的碳汇（NEP = 368±121 g C m−2）。GPP和ER在雨季普遍较高。与旱季相比，雨季NEP值下降了18%，这主要是由于温度引起的ER增加超过了GPP。年GPP、ER和NEP分别增加32.32 g C m-2 （P > 0.1）、24.4 g C m-2 （P > 0.1）和12.78 g C m-2 （P > 0.1）。在季节通量上，GPP主要受太阳诱导的叶绿素荧光（SIF）、气温（Ta）和太阳辐射（Rs）的控制；ER主要受SIF和Ta的影响；在年际尺度上，Ta是影响GPP、ER和NEP的最重要因子，其次是SIF、降水（PPT）和Rs。台风等极端气候事件通过物理途径显著降低GPP和NEP，而对ER的影响最小。干旱显著提高了GPP和ER （P < 0.05）。相比之下，2006年的严重干旱导致GPP、ER和NEP分别下降了11%、12%和8%。总体而言，该研究解决了中国热带雨林二氧化碳通量长期研究的不足，将提高对森林碳动态的认识和预测。

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引用次数: 0

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

IF 5.7 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2026-03-15 Epub Date: 2026-02-02 DOI: 10.1016/j.agrformet.2026.111052

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

This study aims to obtain fundamental information on birch pollen deposition data by field observation for the high-resolution, accurate pollen modeling. On the peak dispersal day in 2024, simple pollen collectors were installed just below and at three downwind points of an isolated birch tree line in Ebetsu, Hokkaido, Japan. Meteorological observations were also conducted at the site during the days. The birch pollen captured on slide glasses was imaged by a microscope. We automatically counted birch pollen grains by applying a machine learning algorithm You Only Look Once (YOLO) v5 to the images. The results suggested that the pollen count was highest in the point 200 m downstream from the tree line and diurnal variations were observed at all distances. The pollen counts in the downstream was correlated with air temperature with a statistical significance, but was correlated with wind speed with a marginal significance. The large-eddy simulation with the pollen advection supported the observation results, though the pollen deposition was more concentrated near the tree in the simulation.

本研究旨在通过野外观测获取白桦花粉沉积数据的基础信息，为高分辨率、准确的花粉建模提供依据。在2024年的传播高峰日，在日本北海道的Ebetsu，一个孤立的桦树线的下方和三个下风点安装了简单的花粉收集器。此外，天文台亦在该处进行气象观测。在载玻片上捕获的桦树花粉用显微镜成像。我们通过对图像应用机器学习算法You Only Look Once (YOLO) v5来自动计数桦树花粉颗粒。结果表明，花粉数量在距林木线下游200 m处最高，且各距离均有明显的日变化。下游花粉数与气温的相关性有统计学意义，与风速的相关性有边际显著性。具有花粉平流的大涡模拟支持观测结果，但模拟中花粉沉积更集中在树附近。

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引用次数: 0