Research Trends in the Remote Sensing of Phytoplankton Blooms: Results from Bibliometrics

Advances in the integration of microalgal communities for biomonitoring of metal pollution in aquatic ecosystems of sub-Saharan Africa

This review elucidated the recent advances in integrating microalgal communities in monitoring metal pollution in aquatic ecosystems of sub-Saharan Africa (SSA). It also highlighted the potential of incorporating microalgae as bioindicators in emerging technologies, identified research gaps, and suggested directions for further research in biomonitoring of metal pollution. Reputable online scholarly databases were used to identify research articles published between January 2000 and June 2023 for synthesis. Results indicated that microalgae were integrated either individually or combined with other bioindicators, mainly macroinvertebrates, macrophytes, and fish, alongside physicochemical monitoring. There was a significantly low level of integration (< 1%) of microalgae for biomonitoring aquatic metal pollution in SSA compared to other geographical regions. Microalgal communities were employed to assess compliance (76%), in diagnosis (38%), and as early-warning systems (38%) of aquatic ecological health status. About 14% of biomonitoring studies integrated microalgal eDNA, while other technologies, such as remote sensing, artificial intelligence, and biosensors, are yet to be significantly incorporated. Nevertheless, there is potential for the aforementioned emerging technologies for monitoring aquatic metal pollution in SSA. Future monitoring in the region should also consider the standardisation and synchronisation of integrative biomonitoring and embrace the "Citizen Science" concept at national and regional scales.

Remote sensing retrieval and driving analysis of phytoplankton density in the large storage freshwater lake: A study based on random forest and Landsat-8 OLI

Remote sensing monitoring of seasonal changes in phytoplankton density and analyses of the driving factors of phytoplankton densities are necessary for assessing the health of aquatic ecosystems, controlling lake eutrophication, and formulating ecological restoration policies. Building upon the satellite-ground synchronization experiment that involves the in situ aquatic ecological monitoring conducted in Nansi Lake, which is the largest storage lake situated along the eastern route of the South-to-North Water Diversion Project, we developed a phytoplankton density retrieval model utilizing the random forest (RF) method and Landsat-8 OLI data. On this basis, we mapped the seasonal fluctuations and spatial disparities in the phytoplankton densities from 2013 to 2023. Subsequently, we conducted a detailed analysis of the driving factors and considered both the natural and anthropogenic aspects. The results indicate that (1) the RF model, when utilizing three band combinations, yielded favorable results with R2, RMSE and MAE values of 0.67, 1.31 × 106 cells/L and 1.18 × 106 cells/L, respectively. (2) The phytoplankton densities exhibited both seasonal and spatial variations, with higher concentrations in summer and autumn than in spring and winter. Significantly, the northwestern region of Zhaoyang Lake and the southeastern region of Weishan Lake had substantially greater phytoplankton densities than did the other areas. Furthermore, overarching upward trends were observed from 2013 to 2023, reflecting an annual rate of increase of 3.32%. (3) An analysis of the causal factors indicated that temperatures and gross agricultural production levels are the primary drivers influencing the seasonal variations and distributions of phytoplankton densities. In the future, we will delve into the potential of deep learning and utilize various satellite sensors to explore the intricacies of phytoplankton monitoring, as well as the complex mechanisms that influence aquatic ecological health.

Urbanization shifts long-term phenology and severity of phytoplankton blooms in an urban lake through different pathways

Climate change can induce phytoplankton blooms (PBs) in eutrophic lakes worldwide, and these blooms severely threaten lake ecosystems and human health. However, it is unclear how urbanization and its interaction with climate impact PBs, which has implications for the management of lakes. Here, we used multi-source remote sensing data and integrated the Virtual-Baseline Floating macroAlgae Height (VB-FAH) index and OTSU threshold automatic segmentation algorithm to extract the area of PBs in Lake Dianchi, China, which has been subjected to frequent PBs and rapid urbanization in its vicinity. We further explored long-term (2000-2021) trends in the phenological and severity metrics of PBs and quantified the contributions from urbanization, climate change, and also nutrient levels to these trends. When comparing data from 2011-2021 to 2000-2010, we found significantly advanced initiation of PBs (28.6 days) and noticeably longer duration (51.9 days) but an insignificant trend in time of disappearance. The enhancement of algal nutrient use efficiency, likely induced by increased water temperature and reduced nutrient concentrations, presumably contributed to an earlier initiation and longer duration of PBs, while there was a negative correlation between spring wind speed and the initiation of PBs. Fortunately, we found that both the area of the PBs and the frequency of severe blooms (covering more than 19.8 km2 ) demonstrated downward trends, which could be attributed to increased wind speed and/or reduced nutrient levels. Moreover, the enhanced land surface temperature caused by urbanization altered the thermodynamic characteristics between the land and the lake, which, in turn, possibly caused an increase in local wind speed and water temperature, suggesting that urbanization can differently regulate the phenology and severity of PBs. Our findings have significant implications for the understanding of the impacts of urbanization on PB dynamics and for improving lake management practices to promote sustainable urban development under global change.

Cinacalcet use in secondary hyperparathyroidism: a machine learning-based systematic review

Introduction

This study aimed to systematically review research on cinacalcet and secondary hyperparathyroidism (SHPT) using machine learning-based statistical analyses.

Methods

Publications indexed in the Web of Science Core Collection database on Cinacalcet and SHPT published between 2000 and 2022 were retrieved. The R package "Bibliometrix," VOSviewer, CiteSpace, meta, and latent Dirichlet allocation (LDA) in Python were used to generate bibliometric and meta-analytical results.

Results

A total of 959 articles were included in our bibliometric analysis. In total, 3753 scholars from 54 countries contributed to this field of research. The United States, Japan, and China were found to be among the three most productive countries worldwide. Three Japanese institutions (Showa University, Tokai University, and Kobe University) published the most articles on Cinacalcet and SHPT. Fukagawa, M.; Chertow, G.M.; Goodman W.G. were the three authors who published the most articles in this field. Most articles were published in Nephrology Dialysis Transplantation, Kidney International, and Therapeutic Apheresis and Dialysis. Research on Cinacalcet and SHPT has mainly included three topics: 1) comparative effects of various treatments, 2) the safety and efficacy of cinacalcet, and 3) fibroblast growth factor-23 (FGF-23). Integrated treatments, cinacalcet use in pediatric chronic kidney disease, and new therapeutic targets are emerging research hotspots. Through a meta-analysis, we confirmed the effects of Cinacalcet on reducing serum PTH (SMD = -0.56, 95% CI = -0.76 to -0.37, p = 0.001) and calcium (SMD = -0.93, 95% CI = -1.21to -0.64, p = 0.001) and improving phosphate (SMD = 0.17, 95% CI = -0.33 to -0.01, p = 0.033) and calcium-phosphate product levels (SMD = -0.49, 95% CI = -0.71 to -0.28, p = 0.001); we found no difference in all-cause mortality (RR = 0.97, 95% CI = 0.90 to 1.05, p = 0.47), cardiovascular mortality (RR = 0.69, 95% CI = 0.36 to 1.31, p = 0.25), and parathyroidectomy (RR = 0.36, 95% CI = 0.09 to 1.35, p = 0.13) between the Cinacalcet and non-Cinacalcet users. Moreover, Cinacalcet was associated with an increased risk of nausea (RR = 2.29, 95% CI = 1.73 to 3.05, p = 0.001), hypocalcemia (RR = 4.05, 95% CI = 2.33 to 7.04, p = 0.001), and vomiting (RR = 1.90, 95% CI = 1.70 to 2.11, p = 0.001).

Discussion

The number of publications indexed to Cinacalcet and SHPT has increased rapidly over the past 22 years. Literature distribution, research topics, and emerging trends in publications on Cinacalcet and SHPT were analyzed using a machine learning-based bibliometric review. The findings of this meta-analysis provide valuable insights into the efficacy and safety of cinacalcet for the treatment of SHPT, which will be of interest to both clinical and researchers.

Shifts in periphyton research themes over the past three decades

It has been well documented that periphyton communities play a key role in primary productivity, nutrient cycling, and food web interactions. However, a worldwide overview of research on the key themes, current situation, and major trends within the field is lacking. In this study, we applied the machine learning technique (latent Dirichlet allocation, LDA) to analyze the abstracts of 6690 publications related to periphyton from 1991 to 2020 based on the Web of Science database. The relative frequency of classical and basic research on periphyton related to colonization, biomass, growth rate, and habitats has been clearly decreasing. The increasing trends of research on periphyton are embodied in the periphyton function in freshwater ecosystems (e.g., application as ecological indicators, function in the removal of nutrients, and application in paleolimnology), the research at macroscales (e.g., spatial-temporal variation, and functional and taxonomic diversity), and the anthropogenic themes (e.g., climate warming, response to multiple stressors, and land use type). The keyword and title analysis showed that the periphyton studies are concentrated mainly on diatom aspects, especially with respect to streams relative to lakes. The thematic space based on non-metric multidimensional scaling (NMDS) showed that the classical themes such as growth rate, colonization, and environmental factors (e.g., multiple stressors and climate warming) were most linked to other research themes. We proposed that future trends in the periphyton should focus on the function of periphyton in lakes and their response to multiple environmental pressures with the increasingly extensive eutrophication in lakes and the increasingly significant change in the climate.

Satellite Altimetry: Achievements and Future Trends by a Scientometrics Analysis

Scientometric reviews, facilitated by computational and visual analytical approaches, allow researchers to gain a thorough understanding of research trends and areas of concentration from a large number of publications. With the fast development of satellite altimetry, which has been effectively applied to a wide range of research topics, it is timely to summarize the scientific achievements of the previous 50 years and identify future trends in this field. A comprehensive overview of satellite altimetry was presented using a total of 8541 publications from the Web of Science Core Collection covering the years from 1970 to 2021. We begin by presenting the fundamental statistical results of the publications, such as the annual number of papers, study categories, countries/regions, afflictions, journals, authors, and keywords, in order to provide a comprehensive picture of satellite altimetry research. We discuss the co-occurrence of the authors in order to reveal the global collaboration network of satellite altimetry research. Finally, we utilised co-citation networks to detect the development trend and associated crucial publications for various specific topics. The findings show that satellite altimetry research has been changed immensely during the last half-century. The United States, France, China, England, and Germany made the most significant contributions in the field of satellite altimetry. The analysis reveals a clear link between technology advancements and the trend in satellite altimetry research. As a result, wide swath altimetry, GNSS-reflectometry, laser altimetry, terrestrial hydrology, and deep learning are among the most frontier study subjects. The findings of this work could guide a thorough understanding of satellite altimetry’s overall development and research front.