Paper Push: 2026-07-27
Back to date list
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 6 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, 6 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
Nel suo profondo vidi che s'interna, legato con amore in un volume.
Dante, Commedia, Paradiso XXXIII, 85-86; Italian original from Kalliope
但丁在终章异象中看见宇宙万物被爱装订成一卷。它是《神曲》关于统一与爱的最高意象之一。
In the final vision, Dante sees all things bound by love into one volume. It is one of the poem's supreme images of unity.
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. A pan-Arctic pigment database for phytoplankton and sea–ice algae
作者Authors: Asta C. Heidemann; Alexander Hayward; Philipp Assmy; Atreya Basu; Astrid Bracher; Giulia Castellani; Giacomo Ditullio; Katarzyna Dragańska-Deja; et al.
发表月份Publication month: 2026-07 2026-07
Earth System Science Data · DOI: 10.5194/essd-18-5505-2026
关键词Tags: phytoplankton; ocean colour phytoplankton; ocean colour
摘要：气候变化极大地改变了北冰洋，海冰范围和厚度显着减少，水温升高。这种变化对北冰洋许多地区的生态影响已经被描述，但生物指标的长期记录仍然缺失。其中，光合和辅助色素是帮助浮游植物和海冰藻生物量定量以及群落组成表征的关键工具之一。为了弥补这一差距，我们提出了第一份全北极原位藻类色素数据汇编，这些数据仅通过高效液相色谱法 (HPLC) 获得，其中包含 2000 年至 2024 年间 77 次北极研究航行收集的 10 798 个样本。 作为大规模协作努力的结果，该数据库涵盖了沿海、大陆架和开放领域的开放水域和海冰环境。该数据库（https://doi.org/10.11583/DTU.29445104，Heidemann 等，2026）包含多达 26 种色素的测量结果，本研究考虑了 8 种主要标记/辅助色素，即四黄素 (Allo)、19'-丁酰氧基岩藻黄素 (But-fuco)、叶绿素 a (Chl) a)、叶绿素 b (Chl b)、岩藻黄质 (Fuco)、19'-己酰氧基岩藻黄质 (Hex-fuco)、多甲素 (Peri) 和玉米黄质 (Zea)。这个公开数据库提供了重要数据，可用于评估浮游植物动态、验证遥感观测结果，并可作为未来北极生态和建模研究的资源。
Abstract: Climate change has dramatically altered the Arctic seas with significant decrease in sea ice extent and thickness and warming water temperature. The ecological impacts of such change have been described for many parts of the Arctic Ocean, but long-term records of biological indicators are still missing. Among those, photosynthetic and accessory pigments are one of the key tools that aid quantification of phytoplankton and sea–ice algae biomass and characterisation of community composition. To address this gap, we present the first pan-Arctic compilation of in situ algal pigment data obtained exclusively by High-Performance Liquid Chromatography (HPLC), containing 10 798 samples collected across 77 Arctic research cruises between 2000 and 2024. As a result of large-scale collaborative effort, this database covers both open water and sea–ice environments across coastal, shelf and open domains. The database (https://doi.org/10.11583/DTU.29445104, Heidemann et al., 2026) includes measures of up to 26 pigments, with 8 major marker/accessory pigments being considered in this study, namely Alloxanthin (Allo), 19'-Butanoyloxyfucoxanthin (But-fuco), Chlorophyll a (Chl a), Chlorophyll b (Chl b), Fucoxanthin (Fuco), 19'-Hexanoyloxyfucoxanthin (Hex-fuco), Peridinin (Peri), and Zeaxanthin (Zea). This publicly available database provides crucial data that can be used to assess phytoplankton dynamics, validating remote sensing observations and can serve as a resource for future Arctic ecological- and modelling studies.
2. PACE satellite detection of marine phytoplankton taxonomic groups based on light absorption
作者Authors: Deyong Sun; Zan Li; Shengqiang Wang; Zixu Ye; hailong zhang
发表月份Publication month: 2026-07 2026-07
Optics Express · DOI: 10.1364/oe.608779
关键词Tags: phytoplankton phytoplankton
摘要：Crossref 未提供该 DOI 的摘要。
Abstract: Crossref did not provide an abstract for this DOI.
重点关注团队Focused team
3. Remote Sensing Dynamic Monitoring and Driving Mechanism of Lake Area in Ebinur Lake, 1992–2024
作者Authors: Xingyu Wang; Decao Niu; Xiaoming Cao; Yongxin Li; Jie Han; Xiaochang Jiang; Zhengwei Han; Changle Yang; et al.
发表月份Publication month: 2026-07 2026-07
Water · DOI: 10.3390/w18151810
关键词Tags: ocean colour ocean colour
摘要：干旱内陆盐湖是流域生态系统的重要组成部分。艾比湖作为新疆最大的盐湖和西北地区重要的生态屏障，其区域动态对区域可持续发展至关重要。本研究将陆地卫星图像（1992-2024）与气象和社会经济数据相结合，以研究最佳取水方法、湖泊面积时空变化和驱动机制。采用了多种方法，包括水分指数比较、Mann-Kendall 检验、Pearson 相关和岭回归。 结果表明：（1）归一化水分指数（NDWI）在历年、历月内均保持较高、稳定的分类精度，适合长期监测； （2）1992年至2024年，湖泊面积呈现显着的波动下降趋势，未出现突变点，呈现持续退化。生长季（4-10月）先减少后增加，早季面积较大，8、9月最小，恰逢农业灌溉需求高峰； (3)从驱动机制来看，社会经济因素占主导地位(约70%)，气象因素的调节作用较弱(约30%)。人口增长和用水量增加是主要驱动因素，季节性差异明显。 气象变化、社会经济发展和生态措施共同影响湖区。尽管极端事件（如异常降水）会引起短期波动，但不会改变人类活动主导的长期退化趋势。该研究为干旱盐湖的长期监测提供了方法学支撑，为艾比湖流域的生态保护和水资源管理提供了科学依据。
Abstract: Arid inland saline lakes are key components of basin ecosystems. As the largest saline lake in Xinjiang and a critical ecological barrier in northwest China, Ebinur Lake’s area dynamics are vital to regional sustainable development. This study integrates Landsat imagery (1992–2024) with meteorological and socio-economic data to investigate optimal water extraction methods, spatio-temporal lake area variations, and driving mechanisms. Multiple methods were employed, including water index comparison, Mann–Kendall test, Pearson correlation, and ridge regression. Results show that: (1) the Normalized Difference Water Index (NDWI) maintains high, stable classification accuracy across years and months, making it suitable for long-term monitoring; (2) from 1992 to 2024, lake area demonstrates a significant fluctuating downward trend without abrupt change points, indicating continuous degradation. During the growing season (April–October), it first decreases and then increases, with larger early-season areas, minima in August and September, coinciding with peak agricultural irrigation demand; (3) regarding driving mechanisms, socio-economic factors dominate (approximately 70%), while meteorological factors play a weakly regulatory role (about 30%). Population growth and increased water consumption are the primary drivers, with obvious seasonal differences. Meteorological changes, socio-economic development, and ecological measures jointly influence lake area. Although extreme events (e.g., anomalous precipitation) induce short-term fluctuations, they do not alter the long-term degradation trend dominated by human activities. This study provides methodological support for long-term monitoring of arid saline lakes and scientific evidence for ecological conservation and water resource management in the Ebinur Lake Basin.
其他相关期刊：按主题相关性补充Other relevant journals: topical supplements
4. Coping with marine heatwaves: Tissue‐specific neuroendocrine and immune adjustments in small‐spotted catsharks
作者Authors: Sandra Martins; Rute Felix; Catarina Pereira Santos; Rui Rosa; Deborah M. Power
发表月份Publication month: 2026-07 2026-07
Journal of Fish Biology · DOI: 10.1111/jfb.70567
关键词Tags: marine heatwaves marine heatwaves
摘要：海洋温度上升扰乱了脊椎动物的神经内分泌-免疫相互作用。研究人员对暴露于 30 天模拟海洋热浪的小斑点猫鲨 (Scyliorhinus canicula) 的肝脏、脾脏、肠道、血细胞和外阴器官中的神经内分泌基因表达进行了检查。神经内分泌基因、免疫和铁相关基因、血浆生化和白细胞测定之间的相关性揭示了组织特异性表达模式、减少了个体间变异性以及跨组织的协调转录调节。总体而言，猫鲨表现出对热应激的综合调整，最有可能平衡代谢需求与免疫恢复能力。
Abstract: Rising ocean temperatures disrupt neuroendocrine–immune interactions in vertebrates. Neuroendocrine gene expression in the liver, spleen, intestine, blood cells and epigonal organ was examined in small‐spotted catsharks ( Scyliorhinus canicula ) exposed to a 30‐day simulated marine heatwave. Correlations among neuroendocrine genes, immune‐ and iron‐related genes, plasma biochemistry and leukocyte assays revealed tissue‐specific expression patterns, reduced inter‐individual variability and coordinated transcriptional modulation across tissues. Overall, catsharks exhibited integrated adjustments to thermal stress, most likely to balance metabolic demands with immune resilience.
5. Biogeochemical signal from marine heatwaves, cold spells, and transient warming events in a coastal upwelling system
作者Authors: Valentina Valdés-Castro; Diego A. Narváez; Laura Farías; Renato A. Quiñones; Camila Fernández; Verónica Molina
发表月份Publication month: 2026-07 2026-07
Scientific Reports · DOI: 10.1038/s41598-026-62941-1
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.
6. A GeoAI framework for coastal flood risk assessment: integrating remote sensing and socioeconomic data
作者Authors: Munshi Khaledur Rahman; Md Sariful Islam; Thomas Crawford; Emma Robinson; Md. Farhad Hossain
发表月份Publication month: 2026-07 2026-07
Frontiers in Climate · DOI: 10.3389/fclim.2026.1831382
关键词Tags: ocean colour ocean colour
摘要：孟加拉国沿海地区被广泛认为是世界上最容易发生灾害的地区之一。在这一脆弱带内，拉克什米布尔地区拥有漫长且高度暴露的海岸线，并且经常遭受水文气象灾害，包括频繁的洪水、潮汐涌动、河流泛滥和强烈的季风降雨。该地区平坦的地形和地理环境进一步加剧了其对季节性和极端洪水事件的敏感性。值得注意的是，2024 年和 2025 年连续发生的两次特大洪水分别影响了约 60 万人和 5 万人，仅 2024 年的一次洪水就造成农作物损失超过 2. 27 亿孟加拉塔卡。 为了应对这些不断升级的风险，本研究开发了一个基于地理空间人工智能 (GeoAI) 的洪水风险绘图框架，该框架集成了多源卫星地球观测数据和社会数据集，以绘制 2024 年和 2025 年的洪水范围，并预测拉克什米普尔地区的洪水风险。洪水范围是使用 Sentinel-1 合成孔径雷达 (SAR) 图像得出的，而洪水风险预测则采用了根据海拔、坡度、到河流的距离、降水量、人口、农田和建成指数进行训练的随机森林分类器。由此产生的概率洪水风险被分为从极低风险到极高风险的五类，并在联盟层面量化人口和农田暴露程度。使用 2025 年洪水数据进行的模型验证的总体准确度为 85. 9%，Cohen’s Kappa 为 0。 71，表现出强大的预测性能。结果突出了关键的洪水风险和暴露热点，强调了基于 GeoAI 的方法在实现及时、高效和可操作的洪水风险评估方面的实用性，特别是对于脆弱社区来说，通过绘图和建模进行早期风险检测对于主动灾害规划和自然灾害管理的有针对性的缓解至关重要。
Abstract: Bangladesh’s coastal zone is widely recognized as one of the most hazard-prone regions of the world. Within this vulnerable belt, Lakshmipur District stands for its long, highly exposed coastline and its recurrent experience of hydrometeorological hazards, including frequent floods, tidal surges, river overflows, and intense monsoon rainfall. The district’s flat topography and geographic setting further amplify its susceptibility to both seasonal and extreme flood events. Notably, two consecutive major floods in 2024 and 2025 affected approximately 600,000 and 50,000 people, respectively, with the 2024 event alone causing crop losses exceeding BDT 2.27 billion. In response to these escalating risks, this study develops a Geospatial Artificial Intelligence (GeoAI)-based flood risk mapping framework that integrates multi-source satellite Earth observation data and social datasets to map flood extents for 2024 and 2025 and to predict flood risk for Lakshmipur District. Flood extents were derived using Sentinel-1 Synthetic Aperture Radar (SAR) imagery, while flood risk prediction employed a Random Forest classifier trained on elevation, slope, distance to rivers, precipitation, population, cropland, and built-up indices. The resulting probabilistic flood risk was classified into five categories ranging from very low to very high risk, with population and cropland exposure quantified at the union level. Model validation using 2025 flood data achieved an overall accuracy of 85.9% and a Cohen’s Kappa of 0.71, demonstrating strong predictive performance. The results highlight critical flood-risk and exposure hotspots, underscoring the utility of GeoAI-based approaches for enabling timely, efficient, and actionable flood risk assessments, particularly for vulnerable communities where early risk detection through mapping and modeling is essential for proactive disaster planning and targeted mitigation for natural disaster management.
