Agricultural and Forest Meteorology最新文献_第8页

Corrigendum to “Responses of methane emissions to global wetland restoration and influencing factors” [Agricultural and Forest Meteorology, 364 (2025), 110459] “甲烷排放对全球湿地恢复的响应及其影响因素”的勘误表[农林气象，364 (2025),110459]

IF 5.7 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2025-11-25 DOI: 10.1016/j.agrformet.2025.110943

Shangqi Xu , Meng Na , Yuqing Miao , Chunjie Tian , Jihai Zhou , Xia Liu

引用次数: 0

Temporally extending long-term forest productivity dynamics using Landsat-derived vegetation index and phenology 利用landsat衍生的植被指数和物候学，在时间上扩展长期森林生产力动态

IF 5.7 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2025-11-25 DOI: 10.1016/j.agrformet.2025.110952

Yi Cen , Lu Hou , Xiaojie Gao , Kai Liu , Yao Li , Yu Shen , Yingpin Yang , Zongbin Wang , Jinnian Wang

Interannual variation of gross primary productivity (GPP), its annual maximum (GPPmax), and growing season length (GSL) are crucial indicators for assessing forest ecosystem responses to climate change. Coarse-resolution satellite observations (e.g., MODIS, 250–500 m) have been widely used to upscale GPP metrics measured by eddy-covariance (EC) flux towers during 2000-present. However, primarily due to data sparsity, studies that use Landsat data to upscale GPP metrics and investigate long-term carbon dynamics are rare, despite its finer resolution (30 m) and extended temporal coverage (1980s-present), which align well with most EC measurements. Here, by using a recently developed Bayesian land surface phenology (BLSP) method that addresses data sparsity of Landsat and a vegetation photosynthesis model (VPM), we explored the potential of Landsat in upscaling long-term GPP metrics. We found that Landsat had comparable performance (R² = 0.9, RMSE = 1.32 g C m^-2d^-1, Bias = -0.3 g C m^-2d^-1) with MODIS (R² = 0.92, RMSE = 1.13 g C m^-2d^-1, Bias = -0.22 g C m^-2d^-1) in estimating GPP validated by EC measurements. Both data sources had higher performance in deciduous (Landsat R² = 0.89; MODIS R² = 0.91) than in evergreen forests (Landsat R² = 0.79; MODIS R² = 0.88). More importantly, Landsat substantially extended the temporal coverage of GPP, especially prior the MODIS era. This extension enabled a more robust assessment of long-term GPP dynamics, as evidenced by our result that long-term trends of GPP metrics derived from Landsat aligned more closely with EC measurements than those derived from MODIS. Therefore, our study shows that Landsat, coupled with the BLSP model, offers a powerful tool to temporally extend EC-measurements and investigate long-term vegetation ecosystem carbon dynamics.

总初级生产力（GPP）、年最大值（GPPmax）和生长季长度（GSL）的年际变化是评价森林生态系统对气候变化响应的重要指标。2000年至今，粗分辨率卫星观测（例如，MODIS， 250-500米）已被广泛用于提高涡流协方差（EC）通量塔测量的GPP指标。然而，主要由于数据稀疏，使用Landsat数据来提高GPP指标和调查长期碳动态的研究很少，尽管它的分辨率更高（30米），时间覆盖范围更广（1980年代至今），与大多数EC测量结果很好地吻合。在这里，通过使用最近开发的贝叶斯陆地表面物候（BLSP）方法来解决Landsat的数据稀疏性和植被光合作用模型（VPM），我们探索了Landsat在提高长期GPP指标方面的潜力。我们发现Landsat在估计EC测量验证的GPP方面与MODIS （R2 = 0.92, RMSE = 1.13 g C m-2d-1, Bias = -0.22 g C m-2d-1）具有相当的性能（R2 = 0.9, RMSE = 1.32 g C m-2d-1, Bias = -0.3 g C m-2d-1）。两种数据源在落叶林中（Landsat R2 = 0.89, MODIS R2 = 0.91）均优于常绿林中（Landsat R2 = 0.79, MODIS R2 = 0.88）。更重要的是，Landsat极大地扩展了GPP的时间覆盖范围，特别是在MODIS时代之前。这一扩展使我们能够对长期GPP动态进行更稳健的评估，正如我们的结果所证明的那样，从Landsat得出的GPP指标的长期趋势比从MODIS得出的GPP指标更接近EC测量值。因此，我们的研究表明，Landsat与BLSP模型相结合，提供了一个强大的工具来暂时扩展ec测量和研究长期植被生态系统碳动态。

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引用次数: 0

Shifting optimal preseason length alters temperature effects on leaf senescence 改变最佳季前长度可以改变温度对叶片衰老的影响

IF 5.7 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2025-11-25 DOI: 10.1016/j.agrformet.2025.110953

Zhendong Guo , Zhaofei Wu , Shouzhi Chen , Zitong Jia , Yongshuo H. Fu

Global warming has shifted the timing of leaf senescence, influencing water and carbon cycles in terrestrial ecosystems. Climate conditions preceding leaf senescence play a critical role in regulating senescence timing, yet the temporal variation in the effect of temperature on leaf senescence remain unclear, hindering accurate predictions of growing season length. Based on 321,639 in situ phenological records of four dominant European tree species (Aesculus hippocastanum, Betula pendula, Fagus sylvatica, and Quercus robur) collected from 1950 to 2021, we found that leaf senescence has significantly delayed by 5.7 days over the past seven decades, primarily driven by preseason temperature and the timing of spring leaf-out. Rising preseason temperatures delayed leaf senescence (β = 0.37, P < 0.05), whereas earlier leaf-out timing advanced it (β = 0.32, P < 0.05). More importantly, the effects of temperature on leaf senescence have shifted significantly, with the delaying effect of temperature becoming stronger, especially in cold regions. This variation could be explained by the divergent effects of early- and late-season temperature on leaf senescence, as well as by the shortened optimal preseason length of temperature (−2.3 days per decade). Our study highlights the importance of the optimal preseason length of temperature in regulating leaf senescence and emphasizes the need to incorporate its variation into senescence models to improve predictions of growing season length and carbon-cycle dynamics.

全球变暖改变了叶片衰老的时间，影响了陆地生态系统中的水和碳循环。叶片衰老前的气候条件在调节衰老时间中起着关键作用，但温度对叶片衰老影响的时间变化尚不清楚，阻碍了生长季节长度的准确预测。基于1950 ~ 2021年欧洲4种优势树种（Aesculus hippocastanum、Betula pendula、Fagus sylvatica和Quercus robur）的321639个原位物候记录，我们发现在过去70年里，叶片衰老显著延迟了5.7天，主要受季前温度和春季落叶时间的驱动。季前温度升高延缓了叶片衰老（β = 0.37, P < 0.05），提早退叶提前了叶片衰老（β = 0.32, P < 0.05）。更重要的是，温度对叶片衰老的影响发生了明显的变化，温度的延迟效应变得更强，特别是在寒冷地区。这种差异可以解释为季节前期和后期温度对叶片衰老的不同影响，以及季节前最佳温度长度缩短（- 2.3天/ 10年）。我们的研究强调了最佳季前温度长度在调节叶片衰老中的重要性，并强调需要将其变化纳入衰老模型，以改进生长季节长度和碳循环动态的预测。

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引用次数: 0

Understanding forest wind damage during mountain wave events: Insights from a case study in Norway 了解山浪事件期间的森林风害：来自挪威案例研究的见解

IF 5.7 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2025-11-24 DOI: 10.1016/j.agrformet.2025.110951

Peter Zubkov , Harold McInnes , Eirik Mikal Samuelsen , Kristina Blennow

Forest wind damage models are typically based on the assumption that windstorm damage results from the interaction between horizontal wind forces and forest stand properties. In complex terrain, mountain waves caused by stably stratified air flowing over mountains can generate standing waves and severe downslope windstorms on the leeward side. Using the windstorm of 19 November 2021 in a mountain valley in southeastern Norway as a case study, we tested two hypotheses:

1. Forest stand properties do not significantly contribute to explaining forest damage during a mountain wave event.

2. Meteorological variables related to atmospheric stratification, turbulence, and non-horizontal airflow significantly contribute to explaining forest damage during a mountain wave event.

To test these hypotheses, we combined forest damage observations with a high-resolution numerical weather prediction model and Random Forest modeling. We used SHapley Additive exPlanations (SHAP) values to quantify the contributions of individual model features. Incorporating forest stand variables did not significantly improve predictive performance, whereas potential temperature gradient, vertical airflow velocity, and wind gust speed, capturing turbulence, did. SHAP analysis showed that although wind gust speed helped explain damage, its influence was secondary to that of potential temperature gradient, which had the strongest explanatory power. The model demonstrated good discriminative power between damage and no damage in the test set. Our findings underscore the limitations of conventional models reliant on horizontal wind speed, highlighting the need for high-resolution numerical weather prediction models that resolve three-dimensional flow in complex terrain, especially during mountain wave events.

森林风害模型通常基于水平风力和林分特性相互作用的假设。在地形复杂的情况下，由稳定的分层空气在山上流动而产生的山波可以在背风侧产生驻波和剧烈的下坡风暴。以2021年11月19日挪威东南部山谷中的风暴为例，我们测试了两个假设：1。林分性质对山波事件中森林破坏的解释不显著。与大气分层、湍流和非水平气流有关的气象变量对解释山波事件期间的森林破坏有重要作用。为了验证这些假设，我们将森林破坏观测与高分辨率数值天气预报模型和随机森林模型相结合。我们使用SHapley加性解释（SHAP）值来量化各个模型特征的贡献。纳入林分变量并不能显著提高预测性能，而潜在温度梯度、垂直气流速度和捕捉湍流的阵风速度却能显著提高预测性能。SHAP分析结果表明，虽然阵风风速有助于解释灾害，但其影响次于势温梯度，势温梯度的解释能力最强。在测试集中，该模型对损伤和无损伤具有良好的判别能力。我们的研究结果强调了依赖水平风速的传统模式的局限性，强调了高分辨率数值天气预报模式的必要性，该模式可以解决复杂地形中的三维流动，特别是在山波事件期间。

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引用次数: 0

Nitrogen limitation reduces CO₂ emissions from land use change primarily by decreasing CO₂ and climate interactions 氮限制主要通过减少二氧化碳与气候的相互作用来减少土地利用变化带来的二氧化碳排放

IF 5.7 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2025-11-24 DOI: 10.1016/j.agrformet.2025.110940

Xinyu Zou , Ying-Ping Wang , Yuanyuan Huang

Estimates of CO₂ emissions from land-use change strongly influence the inferred land carbon sink but remain highly uncertain. One key source of this uncertainty is nitrogen (N) limitation and its interactions with climate and CO₂ emissions from land-use change. Here we developed and implemented a land-use change scheme into the Australian Community Atmosphere Biosphere Land Exchange model (CABLE) and conducted simulations using a full factorial design combining changes in land use, climate, and atmospheric CO₂, both with and without nitrogen limitation. CABLE with nitrogen limitation simulates global gross primary production (GPP), soil respiration, plant biomass, and soil carbon, with correlation coefficients from 0.6 to 0.9 against the benchmark data. From 1960 to 2020, estimated cumulative CO₂ emissions from land-use change were 119 Pg C without nitrogen limitation and 73 Pg C with nitrogen limitation, compared to 100 ± 35 Pg C from 20 dynamic global vegetation models and 87 ± 24 Pg C from three bookkeeping approaches reported in the Global Carbon Budget 2023. We further partitioned total emissions into direct emissions from land-use change and indirect emissions arising from interactions with climate, nitrogen deposition, and atmospheric CO₂. Nitrogen limitation reduced global direct CO₂ emissions from land-use change by 0.12 Pg C yr⁻¹ and indirect emissions by 0.24 Pg C yr⁻¹ during 1701–1959, and by 0.4 Pg C yr⁻¹ for both emissions during 1960–2020. Nitrogen limitation reduced soil carbon inherited from lands when converted to secondary forests, which contributed over 75 % of the total emission reduction, while reduced regrowth of secondary forests contributed < 25 % of the total reduction. Furthermore, nitrogen limitation had the strongest effect on the interaction between land-use change and atmospheric CO₂. Therefore, accounting for nitrogen limitation in both direct and indirect emissions from land-use change is critical for understanding emission drivers, improving model accuracy, and informing climate policy.

对土地利用变化产生的CO 2排放量的估计强烈影响推断的土地碳汇，但仍然高度不确定。这种不确定性的一个关键来源是氮(N)限制及其与气候和土地利用变化产生的二氧化碳排放的相互作用。在这里，我们开发并实施了一个土地利用变化方案到澳大利亚社区大气生物圈土地交换模型（CABLE）中，并使用全因子设计结合土地利用、气候和大气CO 2的变化进行了模拟，包括氮限制和不限制。具有氮限制的CABLE模拟了全球初级生产总值（GPP）、土壤呼吸、植物生物量和土壤碳，与基准数据的相关系数为0.6至0.9。从1960年到2020年，土地利用变化的累积CO₂排放量估计为无氮限制的119 Pg C和氮限制的73 Pg C，而全球碳预算2023报告的20个动态全球植被模型的累积CO₂排放量为100±35 Pg C，三种簿记方法的累积CO₂排放量为87±24 Pg C。我们进一步将总排放量划分为土地利用变化产生的直接排放和与气候、氮沉降和大气CO 2相互作用产生的间接排放。在1701-1959年期间，氮素限制使土地利用变化造成的全球直接二氧化碳排放减少了0.12 Pg - C /年的毒发展，间接排放减少了0.24 Pg - C /年的毒发展，1960-2020年期间，这两种排放分别减少了0.4 Pg - C /年的毒发展。氮素限制减少了土地转化为次生林时继承的土壤碳，占总排放量的75%以上，而次生林再生减少占总排放量的25%。氮素限制对土地利用变化与大气CO₂的交互作用影响最大。因此，考虑土地利用变化直接和间接排放中的氮限制对于理解排放驱动因素、提高模型准确性和为气候政策提供信息至关重要。

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引用次数: 0

Hemispherical imaging of canopy light interception: A ceptometer alternative for precision irrigation in orchards and vineyards 冠层光拦截的半球形成像：果园和葡萄园精确灌溉的一种替代方案

IF 5.7 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2025-11-24 DOI: 10.1016/j.agrformet.2025.110958

Mohamed Ibrahim Belaid , Alexandre Escolà Agustí , Jaume Casadesús Brugués

The amounts of solar radiation absorbed or intercepted by canopies are key parameters for determining gas exchange rates and for estimating water requirements and yield potential in precision agriculture. Measurements with portable ceptometers around midday are the most widespread field method for assessing light interception. However, in orchards and vineyards, light interception varies during the day depending on tree spacing, training system, and tree size, so a single midday measurement may not represent the daily integrated value. This study proposes a cost-effective approach based on hemispherical imaging for rapidly and reliably assessing both the diurnal pattern and the daily fraction of Intercepted Photosynthetically Active Radiation (fIPAR). The method uses hemispherical images representing the fraction of radiation reaching the ground across tree spacing, including alleys between rows. Images were processed automatically to analyse canopy occlusion along the sun’s trajectory. Application of this method, using either still camera or video recordings, was compared with concurrent ceptometer measurements in orchard and vineyard canopies, showing high agreement (R² between 0.88–0.92) and consistency across lighting conditions. The results highlight that, particularly when employing action cameras, this method offers a practical, scalable, and labour-efficient assessment of diurnal fIPAR, providing an operational alternative to traditional ceptometer measurements. Its adaptability to different orchard canopies and robustness under various lighting conditions and configurations, including anti-hail nets, make it a suitable method for precision agriculture.

被冠层吸收或截获的太阳辐射量是确定气体交换率和估计精准农业需水量和产量潜力的关键参数。正午前后用便携式光强计测量是评估光拦截最广泛的野外方法。然而，在果园和葡萄园中，白天的光拦截因树木间距、训练系统和树木大小而异，因此单一的中午测量可能无法代表每日综合值。本研究提出了一种基于半球成像的经济有效的方法，用于快速可靠地评估日模式和截获光合有效辐射（fIPAR）的日分数。该方法使用半球形图像，表示穿过树间距到达地面的辐射的比例，包括行与行之间的小巷。图像被自动处理以分析沿太阳轨迹的冠层遮挡。该方法的应用，使用静止相机或视频记录，与果园和葡萄园树冠上的同步ceptometer测量结果进行了比较，显示出高一致性（R²在0.88-0.92之间）和不同光照条件下的一致性。结果强调，特别是当使用运动相机时，这种方法提供了一种实用的、可扩展的、劳动效率高的日fIPAR评估方法，为传统的压差计测量提供了一种可操作的替代方法。它对不同果园树冠的适应性和在各种光照条件和配置（包括防雹网）下的稳健性，使其成为一种适合精准农业的方法。

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引用次数: 0

Impact of vertical and seasonal variation in leaf traits on simulating soybean canopy photosynthesis via 1D and 3D modeling 叶片性状垂直和季节变化对一维和三维模拟大豆冠层光合作用的影响

IF 5.7 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2025-11-22 DOI: 10.1016/j.agrformet.2025.110941

Xinlei Wang , Kaiyu Guan , Sheng Wang , Brian N. Bailey , Elizabeth A. Ainsworth , Zhao Jiang , Kaiyuan Li

Accurate modeling of photosynthesis is crucial for predicting crop productivity and quantifying the carbon cycle in agroecosystems. Leaf traits are essential inputs for modeling canopy photosynthesis. Yet, many existing models still use fixed plant functional type (PTF)-based values to parameterize leaf traits under a big-leaf or two-big-leaf assumption, neglecting their vertical profiles and seasonal changes. This simplification may introduce significant uncertainties in estimating gross primary productivity (GPP). In this study, we simulated soybean GPP and tested the effects of vertical and seasonal variation in three key leaf photosynthetic traits: the maximum carboxylation rate at 25 °C (Vcmax₂₅), leaf chlorophyll content (LCC), and leaf mass per area (LMA) in the 1D-SCOPE and 3D-Helios models. Weekly field measurements were conducted during the growing season of 2024 to support the simulation. We designed ten leaf trait parameterization schemes by incorporating different combinations of vertical profiles and seasonal changes, while assuming homogeneous canopy architecture in both models. Our results revealed that Vcmax₂₅ vertical and seasonal variation had the strongest influence on simulated GPP in both 1D and 3D models, while LCC and LMA effects were minimal. Particularly, the scheme with an empirically parameterized Vcmax₂₅ profile achieved comparable performance to the scheme with the measured Vcmax₂₅ profile. Both 1D-SCOPE and 3D-Helios accurately modeled GPP (SCOPE: R² = 0.87, Bias = 0.55 µmol m⁻² s⁻¹; Helios: R² = 0.9, Bias = 0.22 µmol m⁻² s⁻¹) under the most complex scheme, and their responses to vertical and seasonal variation in leaf traits were consistent, demonstrating the robustness of our findings. Based on our findings, we propose a scalable framework for parameterizing leaf traits to improve GPP simulations. This study contributes to improving the representation of leaf trait dynamics in canopy-level photosynthesis models, potentially enhancing our ability to predict crop productivity and understand agroecosystem carbon dynamics.

准确的光合作用模型对于预测作物产量和量化农业生态系统中的碳循环至关重要。叶片性状是模拟冠层光合作用的重要输入。然而，现有的许多模型仍然使用基于固定植物功能类型（PTF）的值来参数化大叶或双叶假设下的叶片性状，而忽略了叶片的垂直剖面和季节变化。这种简化可能在估计总初级生产力（GPP）时引入重大的不确定性。在本研究中，我们模拟了大豆GPP，并在1D-SCOPE和3D-Helios模型中测试了垂直和季节变化对三个关键叶片光合性状的影响：25°C时最大羧化率（Vcmax25）、叶片叶绿素含量（LCC）和叶面积质量（LMA）。在2024年的生长季节进行了每周的实地测量，以支持模拟。我们设计了10种叶片性状参数化方案，通过考虑不同的垂直剖面和季节变化组合，同时假设两种模型的冠层结构均匀。结果表明，Vcmax25垂直和季节变化对一维和三维模式模拟GPP的影响最大，而LCC和LMA的影响最小。特别是，经验参数化Vcmax25剖面的方案与实测Vcmax25剖面方案的性能相当。2d -SCOPE和3D-Helios都准确地模拟了最复杂方案下的GPP （SCOPE: R2 = 0.87, Bias = 0.55µmol m⁻²s⁻¹；Helios: R2 = 0.9, Bias = 0.22µmol m⁻²s⁻¹），它们对叶性状垂直和季节变化的反应是一致的，证明了我们的发现的稳稳性。基于我们的研究结果，我们提出了一个可扩展的叶片特征参数化框架，以改进GPP模拟。该研究有助于改善叶片性状动态在冠层水平光合作用模型中的表现，潜在地提高我们预测作物生产力和了解农业生态系统碳动态的能力。

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引用次数: 0

Increasing pathlength resistance and within-canopy shading similarly attenuate transpiration in accruing collocated stands of five pine species 增加径长阻力和冠内遮荫同样会减弱五种松林的蒸腾作用

IF 5.7 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2025-11-21 DOI: 10.1016/j.agrformet.2025.110928

Chainey A. Boroski , Chris A. Maier , Sari Palmroth , Jean-Christophe Domec , Yi Wang , Ram Oren

In forested regions dominated by management for timber production, quantifying biosphere-atmosphere exchange of mass and energy over accruing forests is essential for accurate estimates of water yield and carbon sequestration. Environmental conditions drive transpiration rates, a dominant portion of evapotranspiration in forests. However, differences among species and stand characteristics set limits to canopy-scale transpiration. Both canopy leaf area and height increase rapidly as stands develop, increasing within-canopy shading and pathlength resistance of water flow to leaves, respectively. Understanding these dynamics is important to accurately quantifying water use and informing forest and watershed management strategies.

We measured sap-flux in five co-occurring Southeastern U.S. pine species for nearly five years at a common garden site on a sandy loam soil in the Duke Forest, Durham, NC. Despite significant differences among these species in crown architecture, sapwood area per unit of ground area, and canopy leaf area, their leaf-scale transpiration rate displayed similar sensitivity to vapor pressure deficit. Sensitivity to soil moisture decline varied among species. Under standard conditions, leaf and canopy transpiration declined with increased pathlength resistance (greater height), ostensibly dominating over the impact of within-canopy shading (higher leaf area).

The results suggest that transpiration of these pine species on sandy soil can be approximated assuming a similar physiology, but that accurately estimating it during the rapid phase of stand development requires not only accounting for the effect of increasing canopy leaf area, but also for increasing hydraulic resistance with tree height, especially in open or thinned stands.

在以木材生产管理为主的森林地区，量化累积森林的质量和能量的生物圈-大气交换对于准确估计水量和碳固存至关重要。环境条件驱动蒸腾速率，这是森林蒸散的主要部分。然而，树种和林分特征的差异限制了冠层尺度蒸腾作用。随着林分的发育，冠层叶面积和高度迅速增加，分别增加了冠层内遮阳和叶片的路径阻力。了解这些动态对于准确量化水资源利用以及为森林和流域管理战略提供信息至关重要。我们在北卡罗来纳州达勒姆杜克森林的沙质壤土上的一个普通花园地点测量了近五年美国东南部五种共同发生的松树的树液通量。尽管这些树种在冠状结构、单位地面面积边材面积和冠层叶面积上存在显著差异，但它们的叶尺度蒸腾速率对蒸汽压亏缺表现出相似的敏感性。不同物种对土壤水分下降的敏感性不同。在标准条件下，叶片和冠层蒸腾随路径长度阻力增大（高度增大）而减小，表面上优于冠层内遮阳（叶面积增大）的影响。结果表明，这些松林在沙质土壤上的蒸腾作用可以在类似的生理条件下进行近似计算，但在林分发育的快速阶段，要准确估算其蒸腾作用，不仅需要考虑冠层叶面积增加的影响，还需要考虑随着树高的增加而增加的水力阻力，特别是在开阔或稀疏的林分中。

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引用次数: 0

Cross-scale convergence in the carbon balance of managed boreal forests in Northern Sweden 瑞典北部管理的北方森林碳平衡的跨尺度收敛

IF 5.7 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2025-11-20 DOI: 10.1016/j.agrformet.2025.110926

Matthias Peichl , Eduardo Martínez-García , Jinshu Chi , Natascha Kljun , Anne Klosterhalfen , Johannes Larson , Hjalmar Laudon , Tomas Lundmark , Guillaume Monteil , Mats B. Nilsson , Anusha Sathyanadh , Marko Scholze , Jörgen Wallerman , Peng Zhao

Boreal forests are globally important carbon (C) sinks, but strategies for maximising their climate benefit remain under debate. Major uncertainties in this discussion arise from contrasting sink-source estimates, which largely emanate from inherent limitations of standard measurement techniques to distinct spatio-temporal scales. Here, we use a spatially-nested measurement framework that integrates bottom-up (forest-plot inventory and chamber-based fluxes) and top-down (eddy-covariance; atmospheric observations and atmospheric transport modelling) approaches to reconcile the C balance of actively managed boreal forests in Northern Sweden across plot-, ecosystem-, landscape-, and regional scales during 2016–2018. We found that 3-year mean estimates of the net ecosystem production (NEP) across plot-, landscape-, and regional scales did not differ significantly, converging into a mean (± 95 % confidence interval) C sink of 118 ± 27 g C m^-2 yr^-1. We also noted a convergence across these scales for the 3-means of the NEP components, i.e., gross primary production (908 ± 48 g C m^-2 yr^-1) and ecosystem respiration (790 ± 40 g C m^-2 yr^-1). However, estimates of the inter-annual variations in NEP and its components were inconsistent among most scales and measurement approaches. Furthermore, our results indicate a scale-dependency in the NEP response to the 2018 European summer drought, with a greater reduction of NEP observed in bottom-up compared to top-down estimates. Thus, this study consolidates the C sink-strength of managed boreal forests and advocates the need for cross-scale assessments to constrain forest C cycle-climate feedbacks.

北方针叶林是全球重要的碳汇，但将其气候效益最大化的策略仍存在争议。本讨论中的主要不确定性来自不同的汇源估计，这在很大程度上源于标准测量技术对不同时空尺度的固有限制。在这里，我们使用了一个空间巢式测量框架，该框架整合了自下而上（森林样地清查和基于室的通量）和自上而下（涡旋协方差；大气观测和大气输送模型）的方法，以协调2016-2018年瑞典北部积极管理的北方森林在样地、生态系统、景观和区域尺度上的碳平衡。研究发现，在样地、景观和区域尺度上，净生态系统产量（NEP）的3年平均值没有显著差异，趋近于平均（±95%置信区间）碳汇为118±27 g C m-2年-1。我们还注意到，在这些尺度上，NEP组成部分的3个平均值(即初级生产总值（908±48 g C m-2年-1）和生态系统呼吸（790±40 g C m-2年-1）具有收敛性。然而，在大多数尺度和测量方法中，对新经济政策及其组成部分年际变化的估计是不一致的。此外，我们的研究结果表明，新能源政策对2018年欧洲夏季干旱的响应存在规模依赖性，与自上而下的估计相比，自下而上的估计所观察到的新能源政策减少幅度更大。因此，本研究巩固了管理的北方针叶林的碳汇强度，并提倡需要跨尺度评估来约束森林碳循环-气候反馈。

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引用次数: 0

Co-regulation of water use and canopy temperature in desert trees 荒漠乔木水分利用与冠层温度的协同调节

IF 5.7 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2025-11-19 DOI: 10.1016/j.agrformet.2025.110929

Bryn E. Morgan , Anna T. Trugman , Kelly K. Caylor

Plants employ a range of water-use strategies to withstand limitations in water supply and increases in atmospheric demand. At the same time, water-use strategies alter canopy energy balance, leading to changes in canopy temperature that can impact photosynthesis, creating distinct tradeoffs between water and temperature regulation. However, the extent of these tradeoffs is a key uncertainty in understanding plant responses to hydroclimatic stress. Here, we use a unique dataset of near-surface remotely sensed retrievals of canopy conductance, transpiration, and temperature to assess how desert trees co-regulate their water status and temperature. We leverage a moisture gradient and seasonality in temperature to evaluate species-specific plant responses to both isolated (cool, dry and hot, wet) and combined (hot, dry) water and temperature stress and compare them to reference (cool, wet) conditions. We find that species exhibit different water-use strategies in response to supply- and demand-driven water stress, but exhibit similar responses to thermal stress. Under most conditions, plants face tradeoffs between hydraulic function and avoiding thermal stress. However, when both supply and demand are high, water and canopy temperature regulation can become decoupled. Altogether, our findings reveal two unexpected plant behaviors that may be particularly vulnerable to climate change.

植物采用一系列的用水策略来抵御水供应的限制和大气需求的增加。与此同时，水利用策略改变了冠层能量平衡，导致冠层温度的变化，从而影响光合作用，在水和温度调节之间产生明显的权衡。然而，这些权衡的程度是理解植物对水文气候胁迫反应的关键不确定性。本研究利用独特的近地表遥感数据集获取树冠导度、蒸腾和温度，以评估沙漠树木如何共同调节其水分状态和温度。我们利用湿度梯度和温度的季节性来评估物种特异性植物对孤立（冷、干、热、湿）和联合（热、干）水和温度胁迫的反应，并将它们与参考（冷、湿）条件进行比较。研究发现，不同物种对供需驱动的水胁迫表现出不同的用水策略，但对热胁迫表现出相似的响应。在大多数情况下，植物面临着水力功能和避免热应力之间的权衡。然而，当供应和需求都很高时，水和冠层温度调节可能会脱钩。总之，我们的发现揭示了两种意想不到的植物行为，它们可能特别容易受到气候变化的影响。

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