Retention of fish larvae in an optimal habitat is essential for successful recruiting fish populations. Atoll lagoons may serve as ideal retention areas for fish larvae. We used plankton nets to investigate larval fish assemblages during flooding and ebbing tides in a water-passage inside the Yongle Atoll Lagoon in the South China Sea in May 2022 to reveal the patterns of fish larvae exchanges between the lagoon and the ocean. We collected a total of 186 species/taxa, which were mainly composed of Pomacentridae (21 taxa, 12.3 % total individuals), followed by Apogonidae (18, 6.2 %), Gobiidae (17, 7.4 %), Lutjanidae (15, 5.8 %), Labridae (11, 16.9 %), and Myctophidae (9, 12.6 %). Species richness and density were higher during flooding tide at night (140 taxa, 129.5 ind. / 100 m3) than that during ebbing tide at night (99 taxa, 22.7 ind. / 100 m3), followed by flooding tide at day (42 taxa, 10.0 ind. / 100 m3) and ebbing tide at day (5 taxa, 1.6 ind. / 100 m3). Thus, more fish larvae were transported into the lagoon through flooding tides than those washed out through ebbing tides, as well as at night compared to during daytime. This demonstrated the retention function of the lagoon driven by a combination of flooding tide and the nocturnal activity of fish larvae. Our results suggested that the protection of atoll lagoons in open oceans should be further emphasized not only for their high biodiversity but also for their potential role in providing retention habitats and consequently enhancing recruitment of fish populations.

Materials science plays an irreplaceable role in driving societal progress and technological innovation. With the rapid development of artificial intelligence (AI) and big data technologies, the research paradigm in materials science is undergoing profound transformations. This review discusses how the integration of AI and big data is reshaping the research paradigm in materials science (AI for materials science), accelerating the advancement of computational materials science, and innovating the experimental process. It begins by outlining the infrastructure development of material databases in the context of big data, which serve as the cornerstone of scientific work by providing robust support for the storage, management, and analysis of material data. These databases facilitate efficient data handling, enabling researchers to extract valuable insights from vast amounts of experimental and simulation data. Subsequently, the review explores the application of AI technologies across different stages of the material discovery cycle, including theoretical calculations, experimental design, data collection, and synthesis. AI algorithms, particularly deep learning, have revolutionized these stages by enhancing the ability to process and analyze complex datasets, revealing intricate relationships between material structures and their properties. A significant highlight of this review is the introduction of self-driving laboratories (SDLs). Resulting from the integration of AI with laboratory automation and robotics technology, SDLs have realized a complete closed-loop process for material discovery, promoting a significant shift towards autonomous scientific discovery models. These laboratories can independently design and execute experiments, analyze results, and iteratively refine hypotheses, greatly increasing the efficiency and accuracy of material discovery. Furthermore, the development of large language models (LLMs) has brought about revolutionary changes in natural language understanding, leading to the emergence of scientific LLMs, thus expanding the capabilities from text understanding to scientific exploration. The review provides an overview of the latest advancements in LLMs within materials science, emphasizing their critical role in expediting the material discovery process. These models can parse and understand vast amounts of scientific literature, enabling researchers to stay abreast of the latest developments and identify novel research directions. The review concludes by evaluating the challenges involved in building an intelligent ecosystem for material research. These challenges include the need for high-quality, standardized data, the integration of diverse AI tools, and the development of robust methodologies for cross-disciplinary collaboration. Despite these challenges, the substantial potential of AI in materials science is evident. AI technologies promise to transform material research, enabling the discovery of new materials with unprecedented speed and precision. In summary, this review aims to inform researchers about the significance of AI in materials science, highlighting the transformative impact of AI and big data on the research paradigm. It underscores the importance of developing intelligent systems and methodologies to harness the full potential of AI, thereby advancing the field of materials science and contributing to technological innovation and societal progress.

AimSurf zones are crucial nursery habitats for the early life stages of fish species associated with typical coastal ecosystems. However, little is known about the temporal patterns and drivers of fish assemblages in tropical surf zones. This study aimed to assess the (1) main changes in fish community structure throughout 1 year, (2) seasonal dynamic patterns in fish assemblages, and (3) key factors influencing fish assemblages in the tropical surf zones.LocationGaolong Bay, Wenchang City, Hainan Island, China.MethodsFish sampling was conducted monthly from June 2021 to May 2022 using a beach seine net. Fish species were identified using both morphological and molecular analyses. Kruskal-Wallis test, analysis of similarity, non-metric multidimensional scaling analysis, and similarity percentage analysis were used to investigate the temporal fish assemblage patterns. Generalised additive models and canonical correspondence analysis were used to assess how environmental variables influence fish assemblages.ResultsWe identified 83 fish species, which were grouped into three ecotypes based on their primary habitat: coral reef-seagrass-associated species (CS) (35), mangrove-estuarine-associated species (ME) (30), and common coastal-estuarine-associated species (CE) (18). Most captured individuals were juveniles, and fish abundance and diversity were highest in May. Most CS species were abundant between March and May. ME and most CE species were dominant from June to August, and Mugilidae (CE) was abundant between October and February. Furthermore, surf fish assemblages were substantially influenced by tidal level, water temperature, conductivity, pH, turbidity, and dissolved oxygen.ConclusionsJuvenile fish were abundant in May and fish species with three ecotypes alternate in the surf zones throughout the year. Counter to much current thinking, March maybe the spawn peak of most fish species in the studied area, and we suggest that the fishing ban period could start from March instead of May in the inshore areas of Hainan Island.

为探讨湖泊内部阻隔引发的生态问题,阐释鱼类群落聚合对湖泊内部阻隔的响应,研究选取长江中游典型阻隔湖泊保安湖为研究对象,于2019-2020年夏季和秋季对其肖四海湖区(完全阻隔)、扁担塘湖区(半阻隔)、桥墩湖区(半阻隔)和主体湖区的鱼类群落结构进行了调查,应用单因素方差分析、置换多元方差分析和非度量多维尺度等多重统计方法分析了湖区间鱼类群落组成和多样性的差异.结果表明,完全阻隔湖区肖四海鱼类群落结构发生了明显变化,其种类数[(15±3)种]显著低于半阻隔湖区[(22±3)种]和主体湖区[(23±3)种,P<0.05],鱼类丰度高而生物量低,物种丰富度指数、Shannon指数和Simpson指数显著低于主体湖区(P<0.05),功能丰富度指数、功能分散度指数和功能均匀度指数也显著较低(P<0.05);而半阻隔湖区鱼类群落结构与主体湖区无显著性差异.置换多元方差分析和非度量多维尺度分析也显示出完全阻隔湖区鱼类群落与半阻隔湖区和主体湖区鱼类群落具有显著性差异(P<0.05),半阻隔湖区与主体湖区无显著性差异.研究发现湖泊内部水文阻隔对鱼类群落组成也有着重要影响,恢复湖泊内部水文自由连通对湖泊生态管理和生物多样性保护有着重要作用.

The source region of the Yangtze River, located in the heart of the Tibetan Plateau, is sensitive to climate change, holding a tendency of river runoff increase and lake area expansion and desalination.Investigation on aquatic organisms is helpful to understand impacts of climate change on ecosystems of this region.We investigated benthic macroinvertebrate communities in Yangtze’s western source TuoTuoHe River and southern source DangQu River and 5 surrounding typical lakes（i.e.BanDeHu, YaXiCuo, MaZhangCuoQin, GeLeCuo, AngCuoQin） with salinity ranging from 0.96‰ to 14.72‰,and pH ranging from 8.89 to 9.63.In both rivers and lakes, altogether 25 taxa of macroinvertebrates belonging to 5 classes, 7 orders and 10 families were identified.Results showed that average density and biomass of macroinvertebrates were 36 individuals/m~2 and 0.22 g/m~2 in rivers, and 647 individuals/m~2 and 5.34 g/m~2 in lakes, respectively.The dominant species were Einfeldia sp.in rivers and Orthocladius sp.in lakes.Out of all the species in lakes, 83.3% were special to one single lake.Monte Carlo permutation test indicated that the most important factors influencing macroinvertebrate assemblage were alkalinity, total suspended solids, turbidity, pH, total dissolved solids, salinity and chlorophyll a.The ordination plot by Canonical Correspondence Analysis indicated that macroinvertebrates tended to cluster in the environment with relatively low alkalinity, high water clarity, low salinity, and high chlorophyll a.Our results suggest that the abundance and richness of macroinvertebrates in the source region of the Yangtze River may decrease with increasing turbidity caused by climate-driven runoff increase.Future macroinvertebrates studies in the source region of the Yangtze River may need to pay more attention on long-term ecological monitoring and assessment, and responses of macroinvertebrates to climate change.

Background The application of index of biotic integrity (IBI) to evaluate river health can be an essential method for river ecosystem management. However, these types of methods were developed in small, low-order streams, and are therefore, infrequently applied to large rivers. To that end, phytoplankton communities and environmental variables were monitored in 30 sampling segments of the middle and lower reaches of the Yangtze River, China during the wet (July–August) and dry (November–December) seasons in 2017–2018. We developed a phytoplankton-based index of biotic integrity (P-IBI) and used the index to assess the ecological health of the Yangtze River. Relationships among P-IBI, its component metrics, and environmental factors were analyzed across different seasons. Results Results obtained from the P-IBI indicated that the phytoplankton-based ecological health of the Yangtze River was rated as “good” during both seasons, with an overall better condition in the dry season. During the wet season, there were scattered river segments with P-IBI ratings of “fair” or below. Water quality and land use appeared to shape the patterns of P-IBI. In the wet season, P-IBI negatively correlated with total phosphorus, nitrate, total suspended solids, turbidity, conductivity, and dissolved oxygen. In the dry season, P-IBI positively correlated with total nitrogen, ammonium, and nitrite, and negatively correlated with water temperature. Conclusions The ecological health of the Yangtze River as reflected by the P-IBI exhibited spatial and temporal variability, with the effect of water quality being greater than that of local land use. This study indicated the importance of considering seasonal effects in detecting large river ecological health. These findings enhanced our understanding of the ecological health and characterized potential benchmarks for management of the Yangtze River. These findings also may be applicable to other large rivers elsewhere.

[目的/意义]明确科学数据服务产品体系能够指导科学数据服务工作的开展,推动数据规范化使用与质量控制的进程,提升科学数据利用效率与效益.[方法/过程]梳理国内外科学数据服务现状与不足,从数据服务阶段与用户两个角度分析科学数据服务需求,探究图书馆提供科学数据服务的优势能力与条件.[结果/结论]基于供需对应的视角构建包括政策规划、技术支撑、知识情报等在内的十种图书馆科学数据服务产品,推动科学数据服务系统化发展.

Regional sea level rise in the southeast Indian Ocean (SEIO) exerts growing threats to the surrounding Australian and Indonesian coasts, but the mechanisms of sea level rise have not been firmly established. By analyzing observational datasets and model results, this study investigates multidecadal steric sea level (SSL) rise of the SEIO since the mid-twentieth century, underscoring a significant role of ocean salinity change. The average SSL rising rate from 1960 through 2018 was 7.4 +/- 2.4 mm decade(-1), and contributions of the halosteric and thermosteric components were similar to 42% and similar to 58%, respectively. The notable salinity effect arises primarily from a persistent subsurface freshening trend at 400-1000 m. Further insights are gained through the decomposition of temperature and salinity changes into the heaving (vertical displacements of isopycnal surfaces) and spicing (density-compensated temperature and salinity change) modes. The subsurface freshening trend since 1960 is mainly attributed to the spicing mode, reflecting property modifications of the Subantarctic Mode Water (SAMW) and Antarctic Intermediate Water (AAIW) in the southern Indian Ocean. Also noteworthy is a dramatic acceleration of SSL rise (20.3 +/- 7.0 mm decade(-1)) since similar to 1990, which was predominantly induced by the thermosteric component (16.3 +/- 5.5 mm decade(-1)) associated with the heaving mode. Enhanced Ekman downwelling by surface winds and radiation forcing linked to global greenhouse gas warming mutually caused the depression of isopycnal surfaces, leading to the accelerated SSL rise through thermosteric effect. This study highlights the complexity of regional sea level rise in a rapidly changing climate, in which the role of ocean salinity is vital and time-varying.

对截止至2021年6月报道的长江源区气候、水资源、水质、藻类、大型无脊椎动物和鱼类资源等水生态系统健康相关研究进行了综述,以期为进一步开展长江源区水生态系统健康研究与生态保护提供参考和依据.研究结果表明:①长江源区水生态相关研究主要关注于气候变化,其次为水资源变化和草地退化.②1948—2019年,长江源区全年平均气温呈上升趋势,增长速度为0.2～0.5℃/10 a;春季和冬季降水量呈增加趋势,增长速度分别为1.1～26.6 mm/10 a和0.2～9.1 mm/10 a;全年平均径流量呈增加趋势,增长速度为11.8～79.6 m3/(s·10 a);蒸发量呈增加趋势,增长速度为7.6～71.6 mm/10 a.③1969—2002年,冰川面积减少了68.1 km2,年均减少2.0 km2.1969—2015年,格拉丹东冰川面积减少了14.9～79.0 km2,减少速度为0.5～10.0 km2/a.1975—2015年,湖泊面积增加了2.7～831.6 km2,增速为0.3～96.2 km2/a.④1986—2015年,大部分河段水质为Ⅱ类及以上,且无明显年际变化.⑤针对水生生物的调查和研究非常匮乏.总体而言,长江源区水生态系统健康状况良好.近年来其气象因子以及水资源状况有所改变,未来气候变化可能会进一步影响长江源区水生态系统健康状况.今后亟须加强对长江源区的本底调查,完善基础数据,关注气候变化对水资源和水质的影响,并探索气候变化对水生生物的影响.

[目的/意义]研究提出学科服务3.0模式,为科学大数据环境下学科馆员团队创新发展提供可借鉴的理论模型和实践参考.[方法/过程]面向科学大数据环境下科学研究新范式新形势,分析学科馆员代际演进趋势,从"创新组织方式""提高能力素质""转变工作方式""拓展服务内容""提升服务层次""完善目标追求"6个维度设计新型组织服务模式,建立"矩阵式+网状式"学科服务团队"双协同"协作体系,创新组织方式,按照"能力专业化""工作精准化"提高能力素质,根据"团队协同化""过程嵌入化""合作有温度""品牌高价值"转变工作方式,围绕"四重对象"、沿着科技创新产业链拓展服务内容、提升服务层次,支撑科技管理与决策.在此基础上,以中国科学院某研究所为例开展实证研究.[结果/结论]本研究所构建的学科服务3.0模式在当前科学大数据环境发展下,能有效提升学科服务建设效果,为学科用户提供更好的研究服务与决策支撑.

面向科学数据知识产权保护的服务,是图书馆开展科学数据服务的重要方向.本文从科学数据生命周期的角度出发,分析不同生命周期阶段和图书馆自身发展对科学数据知识产权服务的主要影响因素,从供给侧和需求侧两端揭示不同因素的相互影响关系,并从能力建设机制、团队协同机制、产品建设机制、决策咨询服务机制以及宣传机制5个方面提出建议,以提升图书馆科学数据知识产权服务水平.

How various peoples crossed geographical barriers,were affected by climate change and human-made technologies comprise some of the most interesting quandaries in the history of cultures.This paper con-siders the Hu line,which is a major boundary between population centres and different environments in China.The boundary became evident approximately 11,400 years ago;however,evidence suggests that people crossed through at 5200,3800,and 2800 cal a BP,facilitating the increases of the trans-Eurasian exchange.The timings of the crossings correspond to the weakening of the East Asian summer monsoon that triggers seesaw changes of precipitation in western and eastern China.This analysis demonstrates that climate change on a millennial-to-centennial scale can have a profound influence on population dis-tribution with long-term consequences.

为加强长江源区水生态研究,于2017年丰水期调查了长江源区5个湖泊、5条河流的水质和鱼类资源状况,并研究了其空间格局.水质综合指数(WQI)计算结果显示,长江源区WQI范围为41～87,评价等级介于差到良好之间,大部分采样点的水质评价等级为一般,其中,班德湖的水质评价等级为良好.主成分分析结果显示,长江源区河流、淡水湖、微咸水湖和咸水湖的水质指标呈现出明显的空间差异.河流水质呈现出较高的总磷、总氮、硝态氮、总悬浮物和浊度,淡水湖呈现出较高的水温、溶解氧及WQI,咸水湖呈现出较高的总碱度、总硬度、盐度、电导率和pH.长江源区鱼类多样性较低,共调查到5种鱼类,包括小头高原鱼(Herzensteinia microcephalus)、裸腹叶须鱼(Ptychobarbus kaznakovi)、斯氏高原鳅(Triplophysa stoliczkae)、细尾高原鳅(Triplophysa stenura)和梭形高原鳅(Triplophysa leptosoma).对长江源区水质因子和鱼类群落进行皮尔逊相关分析显示,长江源区鱼类群落主要与水质指标中的浊度和盐度有关.为切实保护好长江源区水质和鱼类资源,建议加强科研监测,建立长江源区水生态数据库,建立土著鱼类种质资源库和基因库,预防和控制外来鱼类的引入,同时要加强鱼类栖息地保护.

城镇化背景下,河流生态系统退化趋势明显,有效评价河流生境状况是修复和保护河流生态系统健康的重要基础.深圳市作为全国经济发展的窗口城市,河流生境的调查研究十分匮乏.因此,为阐明深圳市不同城镇化程度的流域河流生境的差异与主要影响因素,对深圳市两个代表性流域的河流生境展开了研究.针对深圳市河流的生境特点,于2019年丰水期(8月)和枯水期(11月)对城镇化程度较高的深圳河流域的13个样点和城镇化程度较低的坪山河流域12个样点河段的生境状况进行定量调查与评价.采用综合评价法,从河床、河道和河岸带3个方面选取10个生境指标,构建深圳市河流生境评价指标体系和评价方法.结果 表明:深圳河流域河流生境质量总体较差,生境评价等级为"良"、"中"、"差"的样点河段分别占7.7％、38.5％、53.8％;坪山河流域河流生境质量总体较好,生境评价等级为"优"、"良"、"中"、"差"的样点河段分别占8.3％、41.7％、41.7％、8.3％.方差分析结果表明两次调查河流生境状况无显著性差异,短时间跨度内河流生境状况变化较小;两个流域河流生境状况差异显著,城镇化程度较低的坪山河流域河流生境质量显著好于城镇化程度较高的深圳河流域.河流生境评估指标主成分分析结果表明人类活动强度、河岸稳定性、河道变化、底质、河岸土地利用及植被多样性是影响深圳市河流生境变化的主要因子.本文对河床、河道、河岸带3个方面分别提出针对性的修复建议,对深圳市河流的生境修复和保护具有重要的指导作用.

Untangling relationships between landscape patterns shaped by human stressors and related response of fish communities is important for identifying biodiversity patterns and conservation targets, yet in large rivers this knowledge is extremely limited. Our study focuses on how human stressors within a riparian landscape zone, including both riparian land use and in-channel stressors, explained the fish community structure in a large river. We studied fish community patterns along the upstream-downstream gradient of the Yangtze River, China. The curve estimation was used to test correlations between fish metrics and the distance from the estuary. We linked human stressors to fish metrics by multivariate generalized linear models. We collected a total of 63 freshwater fish species from 6,147 specimens. Limnophilic species had the highest richness, represented by 30 specie. The predominant riparian land uses in the studied reaches were cropland (65.3% ± 13.1%) and urban land (19.7% ± 13.6%). There were strong negative correlations between riparian land use (e.g., urban land) and in-channel stressors (e.g., shoreline modification, navigation, and fishing pressure) and fish assemblages, especially limnophilic fish abundance, biomass, and richness. These results demonstrate influences of both riparian land use and in-channel stressors on fish communities, and highlight the use of landscape descriptors as a valuable approach to assess linkages between human pressures and fish diversity in large river systems. Management recommendations include: establishing or rehabilitating riparian buffers, improving commercial navigation management, implementing shoreline protection measures, and reinforcing fishing laws and regulations.

科研数据是科研创新的核心,因此,如何更好地管理科研数据已成为科研管理的重要工作.基于此,服务科研数据管理将成为学科服务创新发展的重要方向之一.本文总结了国内外高校图书馆开展科研数据管理服务的实践工作,通过对比研究,剖析我国高校图书馆基于科研数据管理的学科服务存在的问题,并从协同组织架构、服务能力建设、产品体系构建、服务推广宣传4个层面出发,结合我国学科服务发展现状,提出了面向科研数据管理的高校图书馆学科服务建议策略,以期推动我国高校图书馆学科服务发展完善.

从多个层面对基于文献数据与科学数据融合的图书馆服务开展调研,针对各文献数据与科学数据融合服务中的用户与学科服务之间关系,提出合作、支撑、服务以及共享互动关系.基于文献与科学数据融合的学科服务主要的服务内容与机制包括基础服务、技术关联服务、数据计量学服务、服务机制等,因此,从组织机制建设、专业能力建设、服务产品体系建设、服务宣传营销、理论方法研究等层面总结文献与科学数据融合的学科服务发展路径.

[目的/意义]设计我国科技信息多维贫困指标体系,开展实证研究并制定帮扶策略,为推动贫困地区农民科技信息素养提升与可持续发展,也为我国科技信息贫困研究提供可供参考的方法与数据.[方法/过程]围绕我国科技扶贫总体目标,结合贫困地区农民的科技信息需求,从图书馆提升农民科技信息素养及贫困地区科技信息能力的角度,探索构建一套包含"教育""医疗""产业""人员""管理"5项维度15个指标的我国科技信息多维贫困测度指标体系.在此基础上,运用A-F法以秦巴山区为例开展实证研究.[结果/结论]所构建的我国科技信息多维贫困指标体系及测度方法能够有效反映秦巴山区的科技信息多维贫困现状,发现科技信息多维贫困的程度、分布及关键点,从而有效制定相应的帮扶路径和策略,推动秦巴山区农民科技信息素养及区域科技信息能力提升.

科学数据传播是科学数据生命周期中的重要阶段,涉及科研工作者、数据管理、政府主管部门、科研机构、科普组织、企业等参与者.有效地面向科学数据传播过程中不同利益相关者开展图书馆数据服务,成为我国图书馆发展的重要方向.文章总结了国内外面向科学数据传播开展图书馆科学数据服务的研究与实践,剖析不同参与者与图书馆科学数据服务之间的关系与需求,确定"正面关系""中性关系""负面关系"三类关系,并从三个方面提出图书馆科学数据服务发展建议,包括发展优势、内容建设、团队建设、服务模式等,构建有针对性的图书馆科学数据服务发展路径,为我国进一步开展基于科学数据传播的图书馆科学数据服务提供智力支持.

评价体系建设是衡量科普支撑大众创业、万众创新("双创")成效实现程度和科普能力的重要手段.通过梳理、分析当前我国科普评价的研究方向与制度等现状,围绕科普条件、科普过程、科普成果、经济融合四个层面进行指标设计,并通过专家调研对指标进行征询、调整与完善,构建符合当前"双创"发展的科普工作评价指标,进一步提出构建支撑"双创"的科研机构科普成效评价体系建议,为我国科普工作服务国家"双创"战略提供政策建议.