Paper Push: 2026-06-07
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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 3 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, 3 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
O insensata cura de' mortali.
Dante, Commedia, Paradiso XI, 1; Italian original from Kalliope
这句感叹凡人的忧虑多么无理。它从天堂视角回看世俗焦虑，带有强烈反讽。
This line laments the senseless cares of mortals. From Paradiso's height, ordinary anxieties look painfully misplaced.
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. Riverine Particulate Organic Matter Exported to the Adjacent Coastal Ocean: Implications for Marine Zooplankton in a Highly Productive Coastal Upwelling Area
作者Authors: Alexander Galán; Marcus Sobarzo; Gonzalo S. Saldías; Elizabeth Curra‐Sánchez; Victor M. Aguilera; Valentina Manriquez; Alberto Araneda; Cristian A. Vargas
发表月份Publication month: 2026-06 2026-06
Biogeosciences · DOI: 10.1029/2025jg008810
关键词Tags: carbon pump; phytoplankton; microbial carbon carbon pump; phytoplankton; microbial carbon
这项研究关注有机碳输出和生物碳泵过程。 研究结合观测、模型或实验结果来刻画海洋生态和生物地球化学过程。 研究主要分析变化趋势、事件响应、驱动机制或方法表现，并把观测结果与生态和生物地球化学过程联系起来。 核心结果或实现为该主题提供了新的观测约束、方法基准或过程解释。 它有助于解释观测现象、比较方法差异，并为后续海洋生物地球化学分析提供线索。
The study examines organic carbon export and biological carbon-pump processes. The study combines observations, models, or experimental results to characterize ocean ecological and biogeochemical processes. The main task is to analyse trends, event responses, drivers, or method performance, linking observations with ecological or biogeochemical processes. The main result or implementation provides new observational constraints, methodological benchmarks, or process interpretation for this topic. It is useful for interpreting observations, comparing methods, and designing follow-up analyses in marine biogeochemistry.
2. Reversible Regime Change: Climate‐Driven Phytoplankton Community Shifts in the Cariaco Basin, Venezuela
作者Authors: Benjamin Post; Esteban Acevedo‐Trejos; Subhendu Chakraborty; Andrew D. Barton; Agostino Merico
发表月份Publication month: 2026-06 2026-06
Biogeosciences · DOI: 10.1029/2025jg009360
关键词Tags: phytoplankton phytoplankton
这项研究关注浮游植物群落、生理状态和生产力变化。 研究结合观测、模型或实验结果来刻画海洋生态和生物地球化学过程。 研究主要分析变化趋势、事件响应、驱动机制或方法表现，并把观测结果与生态和生物地球化学过程联系起来。 核心结果或实现为该主题提供了新的观测约束、方法基准或过程解释。 它有助于解释观测现象、比较方法差异，并为后续海洋生物地球化学分析提供线索。
The study examines changes in phytoplankton communities, physiology, and productivity. The study combines observations, models, or experimental results to characterize ocean ecological and biogeochemical processes. The main task is to analyse trends, event responses, drivers, or method performance, linking observations with ecological or biogeochemical processes. The main result or implementation provides new observational constraints, methodological benchmarks, or process interpretation for this topic. It is useful for interpreting observations, comparing methods, and designing follow-up analyses in marine biogeochemistry.
其他相关期刊：按主题相关性补充Other relevant journals: topical supplements
3. Rainfall-Runoff Modelling: A Review of Empirical, Physically-Based and Machine Learning Approaches and Climate Change Applications
作者Authors: Dasari Omkar; S. Selvakumar; S. Pazhanivelan; M. Raju; K. P. Ragunath; V. Ravikumar
发表月份Publication month: 2026-06 2026-06
International Journal of Environment and Climate Change · DOI: 10.9734/ijecc/2026/v16i65499
关键词Tags: ocean colour ocean colour
这项研究关注海色遥感中的浮游植物和光学信号变化。 数据上主要面向卫星海色、叶绿素或遥感反射率记录，并在需要时结合原位或剖面观测进行约束。 方法上使用机器学习、深度学习或神经模拟器来提取信号、反演变量或识别驱动机制。 核心实现是提出可复用的框架、流程或数据产品，使类似观测、反演、验证或趋势分析可以更系统地开展。 它有助于解释观测现象、比较方法差异，并为后续海洋生物地球化学分析提供线索。
The study examines phytoplankton and optical signals in ocean-colour remote sensing. The data emphasis is satellite ocean-colour, chlorophyll, or remote-sensing reflectance records, with in-situ or profile constraints where relevant. Methodologically, it uses machine learning, deep learning, or a neural emulator to extract signals, retrieve variables, or identify drivers. The main contribution is a reusable framework, workflow, or data product that makes similar observation, retrieval, validation, or trend-analysis tasks more systematic. It is useful for interpreting observations, comparing methods, and designing follow-up analyses in marine biogeochemistry.
