Agricultural and Forest Meteorology最新文献_第7页

The impact of nonlinear surface energy partitioning on potential evapotranspiration: A machine learning study based on FLUXNET data 非线性表面能量分配对潜在蒸散的影响：基于FLUXNET数据的机器学习研究

IF 5.7 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2026-03-01 Epub Date: 2025-12-31 DOI: 10.1016/j.agrformet.2025.111005

Weiqi Liu , Shaoxiu Ma , Haiyang Xi , Linhao Liang , Kun Feng , Atsushi Tsunekawa

Potential evapotranspiration (PET) is a key variable in drought occurrence and modeling. The no-water-limited Bowen ratio (β_NWL) is widely used to construct energy balance-based PET models by assuming that β_NWL does not vary with climate and vegetation conditions. However, we found that β_NWL varies significantly with climate as well as vegetation conditions based on global-wide observational flux data. Therefore, this study aims to investigate the dominant influence factors of β_NWL and to simulate the nonlinear relationship between β_NWL with environmental factors by leveraging flux observation globally and machine learning models. We then applied the nonlinear β_NWL to develop a PET model (

P E T_{β_{N W L - R F}}

) and evaluated its performance under various conditions, comparing it against commonly used PET models. Our results showed that the gross primary productivity (GPP) had the most significant effect on β_NWL, with a relative importance of 31%. The

P E T_{β_{N W L - R F}}

model significantly improved the accuracy of daily PET estimation (R² ≥ 0.93, TSS ≥ 0.96, RMSE ≤ 0.48 mm/day, -0.04 mm/day ≤ MB ≤ 0.06 mm/day) against observation. Moreover, we also found that the

P E T_{β_{N W L - R F}}

model can effectively reduce the uncertainty (overestimation or underestimation) of PET estimation by commonly used PET models especially under drought conditions and hence significantly enhance the reliability of drought monitoring. This study reveals the influence of nonlinear relationships of surface energy partitioning on PET, which would be insightful for PET estimation as well as drought monitoring.

潜在蒸散发（PET）是干旱发生和模拟的关键变量。无水限波文比（βNWL）被广泛用于构建基于能量平衡的PET模型，假设βNWL不随气候和植被条件变化。然而，基于全球观测通量数据，我们发现βNWL随气候和植被条件变化显著。因此，本研究旨在研究βNWL的主导影响因素，并利用通量全局观测和机器学习模型模拟βNWL与环境因子的非线性关系。然后，我们将非线性βNWL应用于PET模型（PETβNWL−RF），并评估其在各种条件下的性能，并将其与常用的PET模型进行比较。结果表明，总初级生产力（GPP）对βNWL的影响最为显著，相对重要性为31%。PETβ nwl−RF模型较观测值的日PET估计精度显著提高（R2≥0.93,TSS≥0.96,RMSE≤0.48 mm/day, -0.04 mm/day≤MB≤0.06 mm/day）。此外，我们还发现，PETβ nwl−RF模型可以有效降低常用PET模型在干旱条件下对PET估计的不确定性（高估或低估），从而显著提高干旱监测的可靠性。该研究揭示了地表能量分配的非线性关系对PET的影响，对PET估算和干旱监测具有重要意义。

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引用次数: 0

Rainfall partitioning and interception simulation for typical species in the Taihang Mountains, China 太行山典型物种降雨分配与截留模拟

IF 5.7 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2026-03-01 Epub Date: 2026-01-02 DOI: 10.1016/j.agrformet.2025.111004

Bo Guo , Hui Yang , Chunyu Zhu , Zhibang Yan , Jiansheng Cao , Yanjun Shen

Rainfall partitioning plays a key role in the ecosystem water cycle and watershed water balance, and understanding its processes in the Taihang Mountains is essential for optimizing afforestation strategies and improving water resource management. Various afforestation species have been introduced since the implementation of ecological restoration projects, yet their effects on rainfall partitioning remain unclear. In this study, we used field observations and the Revised Gash model to investigate rainfall partitioning and its influencing factors among typical species in the Taihang Mountains. The results showed that the interception percentage, throughfall percentage, and stemflow percentage of different species at the study site ranged from 8.1% to 28.7%, 69.6% to 90.9%, and 0.9% to 10.5% of total rainfall, respectively. Rainfall amount was the most significant factor affecting rainfall partitioning, while rainfall duration and rainfall intensity had less impact on rainfall partitioning. The Revised Gash model was effectively parameterized for this region, with the relative error of the validation model for simulating typical vegetation interception ranging from -11.9% to 10.2%. The calculation method for the average evaporation rate of the canopy in the Revised Gash model affected the accuracy of interception simulations, with the Penman-Monteith method (

{\overline{E}}_{PM}

) providing better interception loss simulations for P. bungeana, while the mean method (

{\overline{E}}_{TF}

) was recommended for other species. Under extreme heavy rainfall events, interception loss ranged from 6.5% to 27.0% among different species. The Revised Gash model parameterized using the mean method (

{\overline{E}}_{TF}

) achieved relative errors ranging from -26.9% to 7.2% in simulating interception loss under extreme heavy rainfall events across different species. For all species, interception loss during and after rainfall accounted for the largest proportion, comprising 92.83% to 98.40% of interception loss. Compared to native species, economic species exhibited higher interception capacities, suggesting their more significant potential to influence rainfall partitioning and hydrological processes in the Taihang Mountains. In summary, evaluating the rainfall partitioning of typical species in this region has scientific significance for assessing hydrological processes and selecting afforestation species.

降雨分配在生态系统水循环和流域水平衡中起着关键作用，了解降雨分配过程对优化造林策略和改善水资源管理具有重要意义。生态修复工程实施以来，引入了多种造林物种，但其对降雨分配的影响尚不清楚。本文采用野外观测和修正Gash模型对太行山典型物种的降雨分配及其影响因素进行了研究。结果表明：研究点不同树种截流率、穿透率和茎流率分别占总降雨量的8.1% ~ 28.7%、69.6% ~ 90.9%和0.9% ~ 10.5%；降雨量是影响降雨分配最显著的因素，而降雨持续时间和降雨强度对降雨分配的影响较小。修正后的Gash模型参数化效果较好，验证模型模拟典型植被截留的相对误差在-11.9% ~ 10.2%之间。订正Gash模型中树冠平均蒸发速率的计算方法影响了拦截模拟的准确性，其中Penman-Monteith方法（E - PM）为白杨提供了更好的拦截损失模拟，而对于其他物种则推荐采用均值方法（E - TF）。在极端强降雨条件下，不同物种的截留损失在6.5% ~ 27.0%之间。采用均值法（E - TF）参数化的修正Gash模型在模拟不同物种极端强降雨事件下的拦截损失时，实现了-26.9% ~ 7.2%的相对误差。在所有物种中，雨中和雨后截留损失所占比例最大，分别为92.83% ~ 98.40%。与本地物种相比，经济物种表现出更高的截流能力，表明其对太行山降水分配和水文过程的影响潜力更大。综上所述，评价该地区典型物种的降雨分配对水文过程评价和造林树种选择具有重要的科学意义。

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引用次数: 0

Beyond surface fluxes: Observational and computational needs of multilayer canopy models – A walnut orchard test case 超越地表通量：多层冠层模型的观测和计算需求——一个核桃园试验案例

IF 5.7 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2026-03-01 Epub Date: 2025-12-02 DOI: 10.1016/j.agrformet.2025.110960

Gordon B. Bonan , Sean P. Burns , Edward G. Patton

Land surface models simulate fluxes exchanged between the land and atmosphere in weather and climate models. The prevailing modeling paradigm uses a big-leaf canopy parameterization that is not vertically-resolved. Multilayer canopy models have received interest over the past several years as a means to improve surface fluxes and enable new science. We present results from a comparison of the Community Land Model (CLM) multilayer canopy model (CLM-ml v2) and observations of air temperature, specific humidity, wind speed, and fluxes (net radiation, sensible heat, latent heat, momentum) at multiple heights in and above a walnut orchard during the Canopy Horizontal Array Turbulence Study (CHATS). The dataset provides a benchmark with which to test multilayer models. Above-canopy sensible heat, latent heat, and momentum fluxes are well simulated under a range of atmospheric regimes spanning strongly unstable, weakly unstable, near-neutral, weakly stable, and strongly stable, as are vertical profiles of fluxes within the canopy. Vertical profiles of wind speed closely match the observations under all stability regimes. Vertical profiles of air temperature and specific humidity are well simulated except for strongly stable conditions, when the first-order turbulence closure cannot represent within-canopy non-local vertical mixing that would otherwise transport the cool air produced by radiative cooling of the upper canopy downward to the lower canopy. Our model–data comparison highlights the potential of multilayer models to simulate the surface air space. The multilayer canopy model is simpler and more consistent with theory than is the CLM big-leaf canopy model, and it modernizes the canopy physics for theoretical and computational advances compared with CLM’s outdated ad-hoc parameterizations. Nonetheless, our analysis points to further modeling needs and identifies observations central to model testing. Measurements of within-canopy micrometeorology and leaf gas exchange are needed in addition to above-canopy fluxes.

在天气和气候模式中，陆地表面模式模拟陆地和大气之间交换的通量。流行的建模范例使用不是垂直解析的大叶冠参数化。多层冠层模型作为一种改善地表通量和促进新科学发展的手段，在过去几年中引起了人们的兴趣。我们将社区陆地模型（CLM）多层冠层模型（CLM-ml v2）与冠层水平阵列湍流研究（CHATS）期间核桃园内外多个高度的气温、比湿、风速和通量（净辐射、感热、潜热、动量）的观测结果进行了比较。该数据集为测试多层模型提供了一个基准。在强不稳定、弱不稳定、接近中性、弱稳定和强稳定的一系列大气状态下，很好地模拟了冠层上感热、潜热和动量通量，以及冠层内通量的垂直剖面。风速的垂直剖面与所有稳定状态下的观测结果非常吻合。空气温度和比湿度的垂直剖面得到了很好的模拟，但在强稳定条件下，一阶湍流闭合不能代表冠层内部的非局部垂直混合，否则会将上层冠层辐射冷却产生的冷空气向下输送到下层冠层。我们的模型与数据对比突出了多层模型模拟地表空气空间的潜力。多层冠层模型比CLM大叶冠层模型更简单，更符合理论，与CLM过时的自组织参数化相比，它在理论和计算方面实现了冠层物理的现代化。尽管如此，我们的分析指出了进一步的建模需求，并确定了模型测试的核心观察结果。除了冠层上通量外，还需要测量冠层内微气象学和叶片气体交换。

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引用次数: 0

Climatic control on soil microbial methane uptake across forest biomes 气候对森林生物群落土壤微生物甲烷吸收的控制

IF 5.7 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2026-03-01 Epub Date: 2025-12-01 DOI: 10.1016/j.agrformet.2025.110942

Yongping Kou , Manuel Delgado-Baquerizo , Wenqiang Zhao , Xiangzhen Li , Yanhong Wu , Xiaohu Wang , Jiangtao Xiao , Haijian Bing , Qing Liu

Soil microbial methane (CH₄) uptake is critical for mitigating global warming and is sensitive to climate change. However, how climatic changes regulate the capacity of forest soils to uptake CH₄ across environmental gradients remains largely unclear. Here, we investigated the distribution and key drivers of the CH₄ oxidation potential (MOP) across 26 forests along a latitudinal gradient of 4000 km with structural equation modeling and multiple regression. We found that climate was a fundamental driver of MOP, with soil MOP peaking in the subtropical zone and being the lowest in the temperate zone. Structural equation modeling provided evidence that soil MOP was directly driven by changes in the aridity index and indirectly by regulating plant biomass, followed by soil properties. We also found that the environmental context influenced MOP within particular biomes and vegetation types. For example, the cold temperate zone exhibited a significant positive correlation between soil copper content and MOP, suggesting copper as a key factor explaining the variation in soil MOP in this region, as the particulate methane monooxygenase that catalyzes the oxidation of CH₄ is a copper-bound membrane metalloenzyme. Within coniferous broad-leaved forests, soil manganese emerged as a significant predictor of soil MOP, because CH₄ oxidation could be coupled to the reduction of manganese oxides, highlighting its biome-specific role in ecosystem functioning. In addition, methanotrophic richness was most important for explaining soil MOP in coniferous forests due to the lower alpha diversity of methanotrophs observed here. Our study provides solid evidence that climate and local environmental conditions regulate CH₄ sinks in forest ecosystems, with implications for predicting terrestrial carbon cycling under global climate change.

土壤微生物对甲烷（CH4）的吸收对减缓全球变暖至关重要，对气候变化非常敏感。然而，气候变化如何调节森林土壤跨环境梯度吸收CH4的能力仍不清楚。利用结构方程模型和多元回归分析方法，在4000 km的纬度梯度上研究了中国26个森林CH4氧化电位（MOP）的分布及其驱动因素。气候是土壤MOP的根本驱动因素，土壤MOP在亚热带最高，在温带最低。结构方程模型表明，土壤MOP直接受干旱指数变化的影响，间接受植物生物量调节的影响，其次是土壤性质的影响。我们还发现，在特定的生物群系和植被类型中，环境背景会影响MOP。例如，冷温带土壤铜含量与MOP呈显著正相关，表明铜是解释该地区土壤MOP变化的关键因素，因为催化CH4氧化的颗粒甲烷单加氧酶是一种铜结合的膜金属酶。在针叶林中，土壤锰是土壤MOP的重要预测因子，因为CH4氧化可能与锰氧化物的还原耦合，突出了其在生态系统功能中的生物群系特异性作用。此外，甲烷营养丰富度是解释针叶林土壤MOP最重要的原因，因为这里观察到的甲烷营养菌α多样性较低。我们的研究为气候和局部环境条件对森林生态系统中CH4汇的调节提供了有力证据，对预测全球气候变化下陆地碳循环具有重要意义。

{"title":"Climatic control on soil microbial methane uptake across forest biomes","authors":"Yongping Kou , Manuel Delgado-Baquerizo , Wenqiang Zhao , Xiangzhen Li , Yanhong Wu , Xiaohu Wang , Jiangtao Xiao , Haijian Bing , Qing Liu","doi":"10.1016/j.agrformet.2025.110942","DOIUrl":"10.1016/j.agrformet.2025.110942","url":null,"abstract":"<div><div>Soil microbial methane (CH<sub>4</sub>) uptake is critical for mitigating global warming and is sensitive to climate change. However, how climatic changes regulate the capacity of forest soils to uptake CH<sub>4</sub> across environmental gradients remains largely unclear. Here, we investigated the distribution and key drivers of the CH<sub>4</sub> oxidation potential (MOP) across 26 forests along a latitudinal gradient of 4000 km with structural equation modeling and multiple regression. We found that climate was a fundamental driver of MOP, with soil MOP peaking in the subtropical zone and being the lowest in the temperate zone. Structural equation modeling provided evidence that soil MOP was directly driven by changes in the aridity index and indirectly by regulating plant biomass, followed by soil properties. We also found that the environmental context influenced MOP within particular biomes and vegetation types. For example, the cold temperate zone exhibited a significant positive correlation between soil copper content and MOP, suggesting copper as a key factor explaining the variation in soil MOP in this region, as the particulate methane monooxygenase that catalyzes the oxidation of CH<sub>4</sub> is a copper-bound membrane metalloenzyme. Within coniferous broad-leaved forests, soil manganese emerged as a significant predictor of soil MOP, because CH<sub>4</sub> oxidation could be coupled to the reduction of manganese oxides, highlighting its biome-specific role in ecosystem functioning. In addition, methanotrophic richness was most important for explaining soil MOP in coniferous forests due to the lower alpha diversity of methanotrophs observed here. Our study provides solid evidence that climate and local environmental conditions regulate CH<sub>4</sub> sinks in forest ecosystems, with implications for predicting terrestrial carbon cycling under global climate change.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"378 ","pages":"Article 110942"},"PeriodicalIF":5.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145625161","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}

引用次数: 0

Unveiling spatial and temporal characteristics of cooling effects of rice paddy expansion in Northeast China 揭示东北地区稻田扩张降温效应的时空特征

IF 5.7 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2026-03-01 Epub Date: 2025-12-16 DOI: 10.1016/j.agrformet.2025.110967

Tong Yang , Jinwei Dong , Jie Wang , Chao Zhang , Wenqi Liu , Yuting Zhou , Geli Zhang , Guosong Zhao

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.

东北地区水稻种植扩展通过生物物理机制影响地表温度。然而，地表温度效应的时空异质性、与稻田面积比例相关的变化及其潜在的生物物理机制尚不清楚。在本研究中，我们采用两两比较的方法分析了稻田和邻近旱作农田的地表温度（dLST）、反照率（dAlbedo）和蒸散量（dET）的差异。结果表明：5 ~ 9月稻田面积的扩大使东北地区白天地表温度（- 2.02±1.03°C）和反照率（- 1.02±1.07%）降低，夜间地表温度（0.76±0.41°C）和ET（0.03±1.20 mm/8 d）升高。这种影响在春季比夏季和秋季更为明显。从空间上看，三江平原较其他地区表现出较晚月份的日间降温效应和较早月份的夜间升温效应。稻田面积比例每增加10%，白天dLST降低1.60°C，夜间dLST增加0.64°C， dAlbedo降低1.40%。利用分解温度度量方法，我们证实了非辐射机制在生长季节的冷却效应中占主导地位。这些发现强调了在模式模拟、作物种植计划和区域气候减缓战略中考虑土地覆盖变化的空间异质性和生物物理机制的必要性。

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引用次数: 0

Intra-annual density fluctuations in Pinus massoniana across subtropical forests in China: Occurrence patterns and triggering factors 中国亚热带森林马尾松年际密度波动：发生模式及触发因素

IF 5.7 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2026-03-01 Epub Date: 2025-12-16 DOI: 10.1016/j.agrformet.2025.110990

Qin He , Paolo Cherubini , J. Julio Camarero , Xiaochun Wang , Yuan Zhang , Danyang Yuan , Shuguang Liu , Liangjun Zhu

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 Pinus massoniana plantations along a climate gradient in southern China. We found that latewood IADFs (IADF-L) are the predominant type formed by P. massoniana, 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.

年际密度波动（IADFs）是指在生长季节因异常气候事件而形成的木细胞。它们对于评估极端气候事件与径向生长之间的关系以及了解木材质量至关重要。然而，大多数现有的研究集中在季节性干燥的地中海和半干旱的针叶林，在其他地区进行的研究有限，特别是在频繁和严重干旱限制森林生产力和生长的亚热带森林。本文以马尾松人工林为研究对象，研究了不同气候梯度马尾松人工林IADFs的发生模式和触发因素。我们发现马尾松形成的晚木型IADFs （IADF-L）占主导地位，而早木型IADFs （IADF-E）相对较少。随着气候条件变暖、变湿，iadf频率呈明显的空间格局，逐渐增加。IADF-L频率与海拔高度呈负相关，与树轮宽度呈正相关。夏末秋初的高降水和夏季的干热条件触发了iadf - l的形成，而春季（5月）干旱诱发了IADF-E的形成。基于季节木材数据和VS-Lite树木年轮生长模型的气候生长关系进一步证实了IADFs的气候驱动因素。本研究结果为制定干旱易发的亚热带松林管理策略提供了有价值的基础。例如，在夏秋干旱期，人工降雨或补充灌溉可以刺激iadf - l的形成，从而提高森林生长和固碳能力。

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引用次数: 0

APAR is a better predictor than LUE of the stem growth differences found between Loblolly pine grown in the United State and Brazil APAR比LUE更能预测美国和巴西火炬松的茎生长差异

IF 5.7 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2026-03-01 Epub Date: 2025-12-13 DOI: 10.1016/j.agrformet.2025.110964

Lorena Oliveira Barbosa , Otávio Camargo Campoe , José Roberto Soares Scolforo , Henrique Ferraço Scolforo , Timothy J. Albaugh , Rachel Cook , Rafael Rubilar , Juscelina Arcanjo Santos

Pinus taeda is a species native to southeastern regions of the United State (USA), but plantations with the highest productivity are found in the southern region of Brazil (BRA). The objective of our study was to determine the higher (Light Use Efficiency) LUE and absorbed photosynthetically active radiation (APAR) of P. taeda genotypes with different spacings in order to evaluate potential strategies that could increase the productivity of intensively managed stands in Brazil and the United States. The experiment was designed as a split-split-plot, and evaluations included 81 trees in BRA and 63 trees in the USA, two genotypes (clone C3 vs. open pollination (OP)) and two spacings (BRA – 2.4 × 6.8 m, 613 trees/ha; USA – 3.66 × 4.42 m, 618 trees/ha) and narrow spacing (BRA – 2.4 × 2.2 m, 1894 trees/ha; USA – 3.66 × 1.47 m, 1853 trees/ha). Individual tree calculations of LUE were made at both locations for each tree by dividing its current annual stem increment (WNPPi) by APAR estimated from MAESTRA, a process-based model. The parameterization of this model included the use of forest inventory data, meteorological data, crown characteristics (average crown radius, height, diameter, and leaf area), leaf area density distribution, leaf transmittance, and leaf and soil reflectance. Results showed that trees growing in Brazil had greater leaf area (32%) and stem biomass growth (5%) and absorbed more light (49%) than trees in the USA. The genotype C3 was more efficient than OP in light use at both locations. Narrow spacing resulted in higher LUE values (0,8 g MJ^-1). APAR explain 80% and 65% of WNPP in BRA and USA, respective. Our results suggest that LUE explained the growth differences between sites, genotypes, and spacings, while APAR provided a better differentiation of WNPP between the sites.

红松原产于美国东南部地区，但产量最高的人工林分布在巴西南部地区（BRA）。本研究的目的是确定不同间距下紫杉树基因型的较高（光利用效率）LUE和吸收光合有效辐射（APAR），以评估提高巴西和美国集约经营林分生产力的潜在策略。试验采用裂裂样地设计，包括81株BRA树和63株美国树，两种基因型（C3无性系vs开放授粉（OP）），两种间距（BRA - 2.4 × 6.8 m， 613株/ha；美国- 3.66 × 4.42 m， 618株/ha）和窄间距（BRA - 2.4 × 2.2 m， 1894株/ha；美国- 3.66 × 1.47 m， 1853株/ha）。通过将每棵树当前的年干增量（WNPPi）除以MAESTRA（一个基于过程的模型）估计的APAR，在两个地点对每棵树的LUE进行了单独的计算。该模型的参数化包括利用森林清查数据、气象数据、树冠特征（平均树冠半径、树冠高度、树冠直径和叶面积）、叶面积密度分布、叶片透光率以及叶片和土壤反射率。结果表明，生长在巴西的树木比生长在美国的树木具有更大的叶面积（32%）和茎生物量（5%），吸收更多的光（49%）。C3基因型在两个地点的光能利用效率均高于OP基因型。较窄的间距导致较高的LUE值（0.8 g MJ-1）。APAR分别解释了BRA和美国80%和65%的WNPP。我们的结果表明，LUE解释了不同位点、基因型和间距之间的生长差异，而APAR提供了更好的WNPP在不同位点之间的分化。

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引用次数: 0

Improved gap-filling of eddy covariance CO2 fluxes using remote sensing and environmental variables via XGBoost 基于XGBoost的基于遥感和环境变量的涡动相关co2通量补隙改进

IF 5.7 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2026-03-01 Epub Date: 2025-12-18 DOI: 10.1016/j.agrformet.2025.110987

Simon De Cannière , Sebastian Wieneke , Thomas Servotte , Adrià Descals , Tim Verdonck , Ivan Janssens

Gap-filling of eddy covariance (EC) CO

_{2}

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

>

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.

涡动相关（EC） CO2通量数据的空白填补对于量化生态系统碳平衡至关重要，但传统的方法，如边际分布采样（MDS）不能充分代表亚日碳通量，也不能充分利用植被动态，这在填补超过一周的空白时尤其成问题。本研究评估了极端梯度提升（XGBoost）的潜力，该方法是一种机器学习方法，通过整合遥感（RS）数据和环境数据，包括现场测量数据和ERA5再分析模型，在温带松林（ICOS站点BE-Bra）上改善净生态系统交换（NEE）和总初级生产（GPP）的缺口填补。我们比较了三种XGBoost模型：(1)原位模型（气象、土壤湿度和基于塔的太阳诱导叶绿素荧光（SIF）），(2)大尺度模型（ERA5和sentinel -2衍生的植被指数），以及(3)混合模型（将ERA5和sentinel -2衍生的植被指数与原位辐射相结合）。结果表明，在所有情况下，XGBoost在NEE缺口填充方面都优于MDS，在长达56天的缺口中，性能下降最小。土壤湿度和SIF改善了在温暖时期（空气温度25°C）的预测，当这些数据来自于原位来源时。SHAP分析显示，与光相关的驱动因素是显性控制因素。在热浪期间，通常与强光条件同时发生，土壤含水量成为重要的驱动因素。总体而言，混合模型的模型性能与具有原位数据的模型相当，证明了卫星遥感和再分析用于业务缺口填补的可行性。然而，原位辐照明显比再分析辐照更有用。我们的研究结果表明，XGBoost是一个强大的工具，可以整合多源数据，超越传统方法推进碳通量量化，特别是在亚日碳通量建模方面，这在使用EC数据评估基于遥感的碳通量估算时非常重要。

{"title":"Improved gap-filling of eddy covariance CO2 fluxes using remote sensing and environmental variables via XGBoost","authors":"Simon De Cannière , Sebastian Wieneke , Thomas Servotte , Adrià Descals , Tim Verdonck , 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>></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":"2026-03-01","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}

引用次数: 0

Hydrological processes govern methane flux fluctuations in a subtropical floodplain 水文过程控制着亚热带洪泛区甲烷通量的波动

IF 5.7 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2026-03-01 Epub Date: 2025-12-02 DOI: 10.1016/j.agrformet.2025.110965

Xueran Wang , Rongrong Wan , Guishan Yang , Xiaosong Zhao , Bing Li , Xingwang Fan , Yixue Hong , Haoran Wang , Jipeng Song , Zhiyu Song , Yu Jiang

Floodplain methane (CH₄) emissions represent a significant component of the global CH₄ budget. However, their response to escalating extreme drought events remains poorly understood, mainly due to high temporal variability under alternating wet-dry conditions. To address this gap, we conducted two years of in-situ CH₄ flux measurements using the chamber technique across alternating hydrological cycles (2022–2023) in the Poyang Lake floodplain, during which the region experienced a prolonged drought. Our results showed that CH₄ emissions during non-flooding periods (1.82 ± 1.36 mg CH₄ m^–2 h^–1) (mean ± standard deviation) were significantly higher than those during flooding periods (1.26 ± 0.96 mg CH₄ m^–2 h^–1). Notably, CH₄ fluxes in the autumn growing period (2.04 ± 1.43 mg CH₄ m^–2 h^–1) were 35 % higher than in the spring (1.51 ± 1.21 mg CH₄ m^–2 h^–1) under drought conditions. Further analysis revealed that, apart from air temperature, CH₄ fluxes were primarily regulated by vegetation during non-flooding periods and by fluctuating water levels and flooding duration that influence biogeochemical processes during flooding periods. The enhanced temperature sensitivity of CH₄ emissions emerged as a key factor for the higher autumn emissions compared to spring, which is directly linked to the shortened flooding period in the Poyang Lake floodplain. These findings underscore the critical role of extreme drought in reshaping hydrological conditions and CH₄ emissions in floodplain wetlands, with important implications for predicting wetland responses under future climate change scenarios.

漫滩甲烷（CH4）排放是全球CH4收支的一个重要组成部分。然而，它们对不断升级的极端干旱事件的反应仍然知之甚少，这主要是由于在干湿交替条件下的高时间变异性。为了解决这一差距，我们在鄱阳湖漫滩上进行了为期两年的CH4通量原位测量，使用了室内技术，跨越交替水文循环（2022-2023），在此期间该地区经历了长期干旱。结果表明：非淹水期CH4排放量（1.82±1.36 mg CH4 m-2 h-1）显著高于淹水期（1.26±0.96 mg CH4 m-2 h-1）；干旱条件下，秋季生育期CH4通量（2.04±1.43 mg CH4 m-2 h-1）比春季生育期（1.51±1.21 mg CH4 m-2 h-1）高35%。进一步分析表明，除气温外，CH4通量主要受非洪涝期植被和洪涝期影响生物地球化学过程的水位波动和洪水持续时间的调节。CH4排放的温度敏感性增强是导致秋季排放高于春季的关键因素，这与鄱阳湖漫滩汛期缩短有直接关系。这些发现强调了极端干旱在重塑洪泛区湿地水文条件和CH4排放中的关键作用，对预测未来气候变化情景下湿地的响应具有重要意义。

{"title":"Hydrological processes govern methane flux fluctuations in a subtropical floodplain","authors":"Xueran Wang , Rongrong Wan , Guishan Yang , Xiaosong Zhao , Bing Li , Xingwang Fan , Yixue Hong , Haoran Wang , Jipeng Song , Zhiyu Song , Yu Jiang","doi":"10.1016/j.agrformet.2025.110965","DOIUrl":"10.1016/j.agrformet.2025.110965","url":null,"abstract":"<div><div>Floodplain methane (CH<sub>4</sub>) emissions represent a significant component of the global CH<sub>4</sub> budget. However, their response to escalating extreme drought events remains poorly understood, mainly due to high temporal variability under alternating wet-dry conditions. To address this gap, we conducted two years of <em>in-situ</em> CH<sub>4</sub> flux measurements using the chamber technique across alternating hydrological cycles (2022–2023) in the Poyang Lake floodplain, during which the region experienced a prolonged drought. Our results showed that CH<sub>4</sub> emissions during non-flooding periods (1.82 ± 1.36 mg CH<sub>4</sub> m<sup>–2</sup> h<sup>–1</sup>) (mean ± standard deviation) were significantly higher than those during flooding periods (1.26 ± 0.96 mg CH<sub>4</sub> m<sup>–2</sup> h<sup>–1</sup>). Notably, CH<sub>4</sub> fluxes in the autumn growing period (2.04 ± 1.43 mg CH<sub>4</sub> m<sup>–2</sup> h<sup>–1</sup>) were 35 % higher than in the spring (1.51 ± 1.21 mg CH<sub>4</sub> m<sup>–2</sup> h<sup>–1</sup>) under drought conditions. Further analysis revealed that, apart from air temperature, CH<sub>4</sub> fluxes were primarily regulated by vegetation during non-flooding periods and by fluctuating water levels and flooding duration that influence biogeochemical processes during flooding periods. The enhanced temperature sensitivity of CH<sub>4</sub> emissions emerged as a key factor for the higher autumn emissions compared to spring, which is directly linked to the shortened flooding period in the Poyang Lake floodplain. These findings underscore the critical role of extreme drought in reshaping hydrological conditions and CH<sub>4</sub> emissions in floodplain wetlands, with important implications for predicting wetland responses under future climate change scenarios.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"378 ","pages":"Article 110965"},"PeriodicalIF":5.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145658196","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}

引用次数: 0

Maturation of encroaching juniper woodland elevates gross primary productivity and water use but reduces net ecosystem exchange relative to native tallgrass prairie 相对于原生高草草原，入侵刺柏林地的成熟提高了总初级生产力和水分利用，但减少了净生态系统交换

IF 5.7 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2026-03-01 Epub Date: 2026-01-03 DOI: 10.1016/j.agrformet.2025.111009

Tian Zhang , Chris B. Zou , Rodney E. Will , Benedict Ferguson , Jia Yang

Woody plant encroachment (WPE) is transforming grassland ecosystems, with important consequences for carbon sequestration and water balance. This study assessed the long-term impacts of eastern redcedar (Juniperus virginiana, juniper) encroachment by comparing ecosystem carbon and water fluxes between a mature juniper‐dominant woodland and an adjacent tallgrass prairie in the Southern Great Plains, USA. Paired eddy covariance systems (2022–2024) revealed that the juniper woodland was a weaker carbon sink, with a mean annual net ecosystem CO₂ exchange (NEE) of -162 g C/m², compared to -182 g C/m² in the tallgrass prairie. This occurred despite higher annual gross primary productivity (GPP: 2164 vs. 1475 g C/m²), aboveground net primary productivity (ANPP: 281 vs. 142 g C/m²), and evapotranspiration (ET: 762 vs. 589 mm) of the woodland because WPE increased ecosystem respiration (R_e: 2001 vs. 1294 g C/m²). These results suggest a decoupling of water loss from carbon gain in juniper woodlands and underscore the importance of evaluating full ecosystem carbon budgets – beyond aboveground biomass – to guide integrated carbon and water management in a transitional landscape in the prairies.

木本植物入侵（WPE）正在改变草原生态系统，对固碳和水平衡产生重要影响。本研究通过比较美国南部大平原以成熟杉木为主的林地和邻近的高草草原的生态系统碳和水通量，评估了东部红杉（Juniperus virginia，杜松）入侵的长期影响。配对涡动相关系统（2022-2024）显示，与高草草原的-182 g C/m2相比，杉木林地的年净生态系统二氧化碳交换（NEE）为-162 g C/m2，是一个较弱的碳汇。尽管由于WPE增加了生态系统呼吸（Re: 2001对1294 g C/m²），林地的年总初级生产力（GPP: 2164对1475 g C/m²）、地上净初级生产力（ANPP: 281对142 g C/m²）和蒸散（ET: 762对589 mm）更高，但这种情况仍发生了。这些结果表明，在杜松林地中，水分损失与碳收益是分离的，并强调了评估整个生态系统的碳预算（超过地上生物量）的重要性，以指导草原过渡景观中碳和水的综合管理。

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引用次数: 0