Paper Push: 2026-08-03
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每日论文推送：BGC-Argo、海色/海洋光学、海洋热浪与碳泵Daily Paper Push: BGC-Argo, ocean colour/ocean optics, marine heatwaves and carbon pump
本期由 GitHub Actions 自动检索生成：Nature/Science 系列优先，其次是用户指定重点期刊，再补充重点关注团队的新论文，最后纳入其他相关期刊；历史去重后保留 7 篇，不超过每日 50 篇上限。 This issue was generated automatically by GitHub Actions: Nature and Science series first, then the user-defined priority journals, then new papers from the focused team, followed by other relevant journals as topical supplements. After deduplication, 7 papers remain, below the daily limit of 50.
Download Word summary
无 mechanism sketch 图。今天的意大利语卡片： No mechanism sketch figure today. Daily Italian card:
每日一句意大利语Daily Italian
Non ragioniam di lor, ma guarda e passa.
Dante, Commedia, Inferno III, 51; Italian original from Kalliope
这句大意是“不必谈论他们，只看一眼，然后走过去”。现代语境中常用来提醒自己不要被无意义的噪声拖住。
The line means, roughly, do not dwell on them; look and pass on. It is often used as advice not to be trapped by empty noise.
趋势总结Trend Summary
本期重点关注 BGC-Argo、海色遥感/海洋光学、海洋热浪、浮游植物垂向结构和碳泵过程。筛选逻辑不再只限于重点期刊；当高影响力期刊当天新增较少时，会额外检索重点关注团队作者的新论文，并用海洋、海色/光学和碳循环关键词过滤，再从其他相关期刊补充候选论文。
This issue focuses on BGC-Argo, ocean-colour remote sensing, ocean optics, marine heatwaves, vertical phytoplankton structure and carbon-pump processes. The selection is no longer limited to priority journals; when few high-impact papers are newly available, the workflow also checks focused-team authors and filters those papers with ocean, ocean-colour/optics, and carbon-cycle keywords before adding other relevant journals as supplements.
重点期刊：按影响力和相关性排序Key journals: ordered by impact and relevance
1. Integrating Multi-Source Environmental Variables with Sentinel-3 OLCI Imagery for Interpretable Retrieval of Eutrophication Parameters in Bohai
作者Authors: Qiguang Xing; Zhen Sun; Jingping Xu; Siwen Gao; Shanwei Liu; Yanlong Chen
发表月份Publication month: 2026-08 2026-08
Remote Sensing · DOI: 10.3390/rs18152527
关键词Tags: ocean colour ocean colour
摘要：卫星遥感技术具有时空分辨率高、长期连续观测等特点，已成为水质监测的重要工具。向海洋环境中过量输入营养物质，特别是氮和磷，会引起富营养化和一系列相关的生态问题。溶解无机氮 (DIN) 和可溶性活性磷 (SRP) 是控制水质的关键参数。然而，它们固有的弱光谱响应对构建精确的卫星反演模型提出了持续的挑战。将环境变量与光谱反射率一起纳入模型输入特征是提高反演性能的一种有前途的方法。 以渤海为例，将多源环境变量与遥感光谱特征相结合，利用贝叶斯优化和迭代特征重要度筛选策略识别最优特征组合和相应模型。 Bayes-CatBoost 在估计 DIN 和 SRP 方面表现出卓越的性能，分别实现了 0. 82 和 0. 68 的 R2 值。纳入多源环境变量后，相对于仅基于多光谱遥感数据的模型，DIN 反演误差减少了 17. 41%，SRP 反演误差减少了 16. 79%。将所提出的模型应用于 Sentinel-3 OLCI 图像可以生成渤海的每日 DIN 和 SRP 分布。 结果表明，2018年至2023年，渤海DIN和SRP浓度呈现总体稳定但略有下降的趋势，季节性变化明显，水质逐渐改善。
Abstract: Satellite remote sensing technology, characterized by high spatiotemporal resolution and long-term continuous observations, has become a critical tool for water quality monitoring. Excessive inputs of nutrients, particularly nitrogen and phosphorus, into marine environments can induce eutrophication and a range of associated ecological problems. Dissolved Inorganic Nitrogen (DIN) and Soluble Reactive Phosphorus (SRP) are key parameters governing water quality. However, their inherently weak spectral response poses a persistent challenge for the construction of accurate satellite-based inversion models. Incorporating environmental variables into model input features alongside spectral reflectance represents a promising approach to improving inversion performance. Taking the Bohai Sea as a case study, multi-source environmental variables were integrated with remote sensing spectral features, and the optimal feature combination and corresponding model were identified using Bayesian optimization and an iterative feature-importance screening strategy. Bayes-CatBoost demonstrated superior performance in estimating DIN and SRP, achieving R2 values of 0.82 and 0.68, respectively. After incorporating multi-source environmental variables, inversion errors decreased by 17.41% for DIN and 16.79% for SRP relative to models based solely on multispectral remote sensing data. Application of the proposed model to Sentinel-3 OLCI imagery enabled the generation of daily DIN and SRP distributions for the Bohai Sea. The results indicate that from 2018 to 2023, DIN and SRP concentrations in the Bohai Sea exhibited an overall stable but slightly declining trend with pronounced seasonal variability, accompanied by a gradual improvement in water quality.
重点关注团队Focused team
2. A Dual-Branch Encoder–Decoder Network with Convolutional Long Short-Term Memory and Efficient Channel Attention for Forecasting Summer Marine Heatwaves in the East China Sea
作者Authors: Yinjing Zhang; An Yi; Yang Yu; Boni Wang; Wenjin Sun; Haixia Shan
发表月份Publication month: 2026-08 2026-08
Journal of Marine Science and Engineering · DOI: 10.3390/jmse14151421
关键词Tags: marine heatwaves marine heatwaves
摘要：频繁的海洋热浪（MHW）威胁着海洋生态系统和经济。为了准确预测东海（ECS）MHW发生概率，本文提出了深度学习模型MHW-NET。该模型使用编码器-瓶颈-解码器双分支架构、ConvLSTM、高效通道注意力 (ECA) 以及具有焦点 Tversky 和 SSIM 损失的复合损失函数。该模型使用 1982 年至 2011 年的数据进行训练，独立测试期为 2016 年至 2022 年。在第 1 至 7 天期间，MHW-NET 在黄海的表现相对较好，而在复杂的近岸区域（如渤海湾、浙江沿海和台湾北部海域）的表现则明显较差。 该模型准确刻画了重灾区的空间分布特征，再现了2016年和2022年两次极端重灾区事件的空间格局，空间相关性超过0. 85。特征重要性分析表明，海面温度和2米气温是东海地区重灾区的主要驱动因素。本研究的消融实验表明，ConvLSTM和ECA是核心模块，噪声和细化是辅助的。与基线模型的基准比较进一步证实了 MHW-NET 的优越性，展示了其改善 ECS MHW 预测和预警的潜力。
Abstract: Frequent marine heatwaves (MHWs) threaten marine ecosystems and economies. To accurately anticipate MHW occurrence probability in the East China Sea (ECS), this work proposes MHW-NET, a deep learning model. The model uses an encoder–bottleneck–decoder dual-branch architecture, ConvLSTM, efficient channel attention (ECA), and a composite loss function with focal Tversky and SSIM losses. The model is trained on data from 1982 to 2011, with an independent test period of 2016–2022. Over lead days 1 to 7, MHW-NET performs relatively well in the Yellow Sea, while exhibiting substantially weaker performance in complex nearshore regions such as Bohai Bay, the Zhejiang coast, and the waters off northern Taiwan. The model accurately characterizes the spatial distribution of MHWs and reproduces the spatial patterns of the two extreme MHW events in 2016 and 2022, with spatial correlations exceeding 0.85. Feature importance analysis indicates that sea surface temperature and 2-m air temperature are the main driving factors of MHWs in the ECS. This study’s ablation experiments show that ConvLSTM and ECA are core modules and noise and refinement are auxiliary. Benchmark comparisons with baseline models further confirm the superiority of MHW-NET, demonstrating its potential for improving MHWs forecasting and early warning in the ECS.
3. Contrasting Soil Organic Carbon Fractions in Woody Versus Herbaceous Coastal Riparian Habitats by Integrating Litter-Derived DOM and Edaphic Properties
作者Authors: Baohua Li; Qi Jia; Mujun Han; Xinxin Liu; Weidong Qu; Yan Fang; Fude Liu; Hailong Wu
发表月份Publication month: 2026-08 2026-08
Agronomy · DOI: 10.3390/agronomy16151462
关键词Tags: carbon pump; microbial carbon carbon pump; microbial carbon
摘要：沿海河岸带是陆地和水生生态系统碳循环的重要过渡区。然而，不同栖息地的凋落物来源的溶解有机物 (DOM)、土壤 DOM 组成和土壤有机碳 (SOC) 分数之间的关联仍不清楚。本研究旨在阐明木本和草本生境中的 SOC 分数分布，并评估其与凋落物来源的 DOM、土壤 DOM 组成以及沿海河岸带不同季节土壤环境因素的关系。在本研究中，木本生境在 3 月份的 SOC 含量较高，而草本生境在 11 月份的 SOC 含量较高。不同栖息地的颗粒有机碳（POC）和矿物相关有机碳（MAOC）普遍较高。 MAOC 在测量的 SOC 相关池中占很大比例，并且与 SOC 含量呈一致的正相关。 3月份土壤DOM由类蛋白质和类腐殖质成分组成，草本生境表现出较强的类蛋白质成分，木本生境表现出较强的类腐殖质成分。木质凋落物比草本凋落物渗滤液表现出更大的 DOC 和 DON 释放潜力，而凋落物中的类腐殖质 DOM 与土壤中的类腐殖质成分密切相关。不稳定SOC库主要与植被类型和电导率相关，而MAOC与土壤含水量和总磷正相关。 总体而言，沿海河岸生境中 SOC 分数的分布是由生境特定的环境因素决定的，包括植物碳输入、凋落物淋溶和土壤理化性质。这一发现对于制定有针对性的管理策略以促进沿海地区 SOC 积累至关重要。
Abstract: Coastal riparian zones are important transitional areas for carbon cycling between terrestrial and aquatic ecosystems. However, the associations among litter-derived dissolved organic matter (DOM), soil DOM composition, and soil organic carbon (SOC) fractions across habitats remain insufficiently understood. This study aimed to clarify SOC fraction distribution in woody and herbaceous habitats and evaluate its associations with litter-derived DOM, soil DOM composition, and soil environmental factors in different seasons from a coastal riparian zone. In this study, woody habitats had higher SOC content in March, whereas herbaceous habitats showed greater SOC content in November. Particulate organic carbon (POC) and mineral-associated organic carbon (MAOC) were generally higher in different habitats. MAOC accounted for a large proportion of the measured SOC-related pools and showed a consistent positive association with SOC content. Soil DOM consisted of protein-like and humic-like components, with herbaceous habitats showing a stronger protein-like component and woody habitats showing a stronger humic-like component in March. Woody litter showed greater DOC and DON release potential than herbaceous litter leachates, while litter-derived humic-like DOM was closely associated with a soil humic-like component. The labile SOC pool was mainly associated with vegetation type and electrical conductivity, whereas MAOC was positively associated with soil moisture content and total phosphorus. Overall, the distribution of SOC fractions in coastal riparian habitats is shaped by habitat-specific environmental factors, including vegetative carbon inputs, litter leaching and soil physicochemical properties. This finding is critical for developing targeted management strategies to facilitate SOC accumulation in coastal zones.
4. Divergent Blue Carbon Trajectories in the Yellow River Delta Post‐1976 Diversion: Hydrological Stability and Human Disturbance Contrasts Revealed by Multi‐Source Remote Sensing (1984–2023)
作者Authors: Mengqian Jiang; Haotian Liu; Zhenfang He; Zhaosheng Wang; Xuanjie Gai; Qingchun Guo; Shaowei Su
发表月份Publication month: 2026-08 2026-08
Land Degradation & Development · DOI: 10.1002/ldr.70842
关键词Tags: ocean colour; bio-optics ocean colour; bio-optics
摘要：沿海湿地是重要的蓝色碳汇，但其在环境变化下的时空动态仍未充分量化。本研究以黄河三角洲（YRD）为天然实验室，综合了1984年至2023年的多源遥感数据，包括光学和雷达图像，以探索1976年河流改道后蓝色碳储量的演变。确定了两个不同的区域：A 区，其特点是废弃河道和沉积物匮乏；B 区，代表水文稳定的活跃河口。结果表明：（1）植被轨迹不同：从1984年到2023年，两个区域之间观察到不同的植被动态。 (2) 碳轨迹不同：1984年至2023年间，A区碳储量波动较大，范围为9. 90 × 10 4 t至407。 35×10 4 t，主要是由于土地开垦和水文条件改变。相比之下，B 区在稳定的水文投入下保持了植被动态平衡，碳储量从 33. 80 × 10 4 t 上升至 547. 01 × 10 4 t。 (3)差异性入侵影响：2010年后互花米草的入侵使B区碳储量显着增加46. 60×10 4 t。相反，A区的主要驱动因素是河流改道后的水文变化，导致盐碱化加剧。这一条件限制了互花米草的入侵。 （4）空间重组：高碳区从1984-2010年集中在芦苇为主的河岸区域转变为2010-2020年B区内互花米草入侵区。 在盐沼湿地中，水文条件是蓝碳动态的关键调节因素，主要通过控制植被覆盖和演替轨迹。
Abstract: Coastal wetlands are critical blue carbon sinks, yet their spatiotemporal dynamics under environmental change remain insufficiently quantified. Taking the Yellow River Delta (YRD) as a natural laboratory, this study synthesizes multi‐source remote sensing data, including optical and radar imagery spanning from 1984 to 2023, to explore the evolution of blue carbon stocks following the 1976 river diversion. Two distinct zones were identified: Zone A, characterized by an abandoned channel and sediment starvation, and Zone B, representing an active estuary with hydrological stability. Results show that: (1) Divergent vegetation trajectories: From 1984 to 2023, distinct vegetation dynamics were observed between the two zones. (2) Divergent carbon trajectories: Between 1984 and 2023, Zone A experienced fluctuations in carbon stocks, ranging from 9.90 × 10 4 t to 407.35 × 10 4 t, primarily due to land reclamation and altered hydrological conditions. In contrast, Zone B maintained a dynamic vegetation equilibrium under stable hydrological inputs, with carbon stocks rising from 33.80 × 10 4 t to 547.01 × 10 4 t. (3) Differential invasion impacts: The invasion of Spartina alterniflora after 2010 significantly increased carbon storage in Zone B by 46.60 × 10 4 t. Conversely, the primary driver in Zone A was the hydrologic alteration following the river diversion, leading to heightened salinization. This condition limited the invasion of Spartina alterniflora . (4) Spatial reorganization: High‐carbon zones transitioned from being concentrated in Phragmites australis ‐dominated riverbanks during 1984–2010 to encompassing Spartina alterniflora ‐invaded areas within Zone B during 2010–2020. In salt marsh wetlands, hydrological conditions act as a critical regulator of blue carbon dynamics, primarily by governing vegetation cover and succession trajectories.
其他相关期刊：按主题相关性补充Other relevant journals: topical supplements
5. The ASTE‐BGC Data‐Assimilative Regional Ocean Biogeochemical Model
作者Authors: L. A. Moseley; G. A. McKinley; D. Carroll; D. Menemenlis; R. Dussin; A. T. Nguyen
发表月份Publication month: 2026-08 2026-08
Journal of Advances in Modeling Earth Systems · DOI: 10.1029/2025ms004976
关键词Tags: phytoplankton phytoplankton
摘要：我们提出了一个数据同化区域海洋生物地球化学模型 ASTE-BGC，它模拟了 2002 年至 2017 年北大西洋的物理和生物地球化学状态。模型物理由物理状态估计 (ASTE) 提供，它同化了模型域和时间段内的原位 O(10 9 ) 和基于卫星的观测结果。模型生物地球化学由中等复杂性生物地球化学模块 (BLING) 模拟，该模块模拟九种预测生物地球化学示踪剂和三个生态类别。通过结合非正式调整和正式数学优化的三步优化过程，我们将“旋转”模拟生物地球化学状态与 O(10 5 ) BGC-Argo 以及 O 2 、NO 3 、PO 4 、溶解无机碳 (DIC) 和碱度的船基瓶数据之间的模型数据失配最小化了 43%。 首先，我们摆脱传统的生物地球化学模型启动过程，直接从 GLODAPv2 初始化这五个生物地球化学变量。 2016b 1° × 1° 气候图（失配减少 22%）。其次，我们调整太阳辐照度和光合作用之间的经验关系，以延迟模拟的春季浮游植物繁殖（错配减少 19%）。最后，我们使用格林函数方法通过敏感性实验（2% 失配减少）正式优化 7 个 BLING 生物地球化学模型参数。这一过程给所有地区带来了明显的改善，特别是在北大西洋副极地地区。 我们将无约束和优化的模型与独立卫星数据、全球海洋生物地球化学模型和基于观测的产品进行比较，以进一步证明拉布拉多海模拟 O 2 、表面海洋 pCO 2 和叶绿素-a 的改进。最后，我们对生物地球化学数据同化的挑战以及推进该领域所需的未来工作提出了看法。
Abstract: We present a data‐assimilative regional ocean biogeochemical model, ASTE‐BGC, which simulates the physical and biogeochemical state of the North Atlantic Ocean from 2002 to 2017. Model physics are provided by a physical state estimate (ASTE), which assimilates O(10 9 ) in situ and satellite‐based observations over the model domain and time period. Model biogeochemistry is simulated by a medium‐complexity biogeochemical module (BLING), which simulates nine prognostic biogeochemical tracers and three ecological classes. Through a three‐step optimization process which combines informal adjustments and formal mathematical optimization, we minimize model‐data misfit between a “spun‐up” simulated biogeochemical state and O(10 5 ) BGC‐Argo and ship‐based bottle data of O 2 , NO 3 , PO 4 , dissolved inorganic carbon (DIC), and alkalinity by 43%. First, we move away from the traditional biogeochemical model spin‐up process to initialize these five biogeochemical variables directly from the GLODAPv2.2016b 1° × 1° mapped climatology (22% misfit reduction). Second, we tune the empirical relationship between solar irradiance and photosynthesis to delay the simulated spring phytoplankton bloom (19% misfit reduction). Finally, we use a Green's Functions approach to formally optimize seven BLING biogeochemical model parameters using sensitivity experiments (2% misfit reduction). This process leads to demonstrable improvements in all regions, particularly in the subpolar North Atlantic. We compare the unconstrained and optimized models against independent satellite data, global ocean biogeochemical models, and observation‐based products to further demonstrate improvements in simulated O 2 , surface ocean pCO 2 , and chlorophyll‐a in the Labrador Sea. We conclude by offering our perspective on the challenges of biogeochemical data assimilation and the future work needed to advance this field.
6. Potential Drivers of Northwest Pacific Marine Heatwaves Inferred from Adjoint Sensitivities
作者Authors: Xiaoxue Wang
发表月份Publication month: 2026-08 2026-08
Weather and Climate Extremes · DOI: 10.1016/j.wace.2026.100942
关键词Tags: marine heatwaves marine heatwaves
摘要：Crossref 未提供该 DOI 的摘要。
Abstract: Crossref did not provide an abstract for this DOI.
7. Geomorphic and Remote Sensing‐Based Evaluation of Active Faults and Geological Hazards in the Muzaffarabad Region, NW Himalaya
作者Authors: Waqar Ayub; Ahmed Nabi; Muhammad Jabran; Dawar Abbas; Rahat Ullah; Muhammad Nadeem
发表月份Publication month: 2026-08 2026-08
Geological Journal · DOI: 10.1002/gj.70422
关键词Tags: ocean colour ocean colour
摘要：地貌特征、排水模式和地形是活动构造的关键指标。这项研究研究了穆扎法拉巴德地区的地貌特征和地质灾害，特别是地震和山体滑坡。研究结果有助于减少灾害风险和实现可持续发展目标（SDG）。利用实地地貌研究和卫星图像分析该地区的地貌特征。利用航天飞机雷达地形任务数字高程模型（SRTM DEM）计算了五种地貌指数，即不对称因子（AF）、流域形状指数（Db）、坡度分析、谷底宽高比（V f ）和测高曲线。 杰赫勒姆断层和穆扎法拉巴德断层附近的排水偏移、河流偏转、刻面山刺、地震活动、变形的近期沉积物和点坝解剖等特征表明存在左旋斜滑运动，表明这些断层的构造活动性质。地貌和新构造学分析得出的结论是，穆扎法拉巴德地区极易发生地震和山体滑坡，特别是在受断层影响的地区。使用 ArcGIS 中的多标准决策分析 (MCDA) 进行洪水敏感性分析，通过识别洪水易发区域来增强气候适应能力和备灾 (SDG 13) 和支持 (SDG 6)。确定了三个高风险洪水区：尼勒姆河与沙瓦伊纳拉河交汇处、杰赫勒姆河与尼勒姆河在多梅尔交汇处以及洛哈尔加利滑坡附近的低洼地区。 这项研究强调了整合形态测量、地貌和地理空间技术对于有效减少灾害风险（可持续发展目标 11 和 13）、气候适应型基础设施（可持续发展目标 9）、实现可持续发展目标 6 和可持续城市发展、确保构造活跃地区的长期安全的重要性。此外，本研究中的方法整合了多种现有技术，可以扩展到其他地区的危害评估。
Abstract: Geomorphic features, drainage patterns and topography are key indicators of active tectonics. This study examines geomorphological characteristics and geological hazards, specifically earthquakes and landslides, in the Muzaffarabad region. The findings contribute to disaster risk reduction and achievement of sustainable development goals (SDGs). Field‐based geomorphological studies and satellite imagery were used to analyse the geomorphological characteristics of the region. Five geomorphic indices, namely asymmetry factor (AF), drainage basin shape index (Db), slope analysis, valley floor width‐to‐height ( V f ) ratios and hypsometric curves, were calculated using shuttle radar topography mission digital elevation model (SRTM DEM). Features such as drainage offsets, stream deflections, faceted spurs, seismicity, deformed recent sediments and point bars dissection near the Jhelum and Muzaffarabad faults suggest left‐lateral oblique‐slip motion, indicating the tectonically active nature of these faults. The geomorphic and neotectonics analysis concludes that the Muzaffarabad region is highly susceptible to earthquakes and landslides, particularly, in fault‐affected areas. A flood susceptibility analysis using multi‐criteria decision analysis (MCDA) in ArcGIS was conducted to enhance climate resilience and disaster preparedness (SDG 13) and support (SDG 6) by identifying flood‐prone areas. Three high‐risk flood zones were identified: Neelum River–Shawai Nala confluence, Jhelum–Neelum rivers convergence at Domel and a low‐lying area near the Lohargali landslide. This study highlights the importance of integrating morphometric, geomorphological and geospatial techniques for effective disaster risk reduction (SDGs 11 and 13), climate‐resilient infrastructure (SDG 9), addressing SDG 6 and sustainable urban development, ensuring long‐term safety in tectonically active regions. Additionally, the methodology in this study, integrating multiple existing techniques, can be expanded for hazard assessment in other regions.
