Geographical Distribution Research Articles

Temperature extremes nip invasive macrophyte Cabomba caroliniana A. Gray in the bud: potential geographic distributions and risk assessment based on future climate change and anthropogenic influences

Cabomba caroliniana A. Gray, an ornamental submerged plant indigenous to tropical America, has been introduced to numerous countries in Europe, Asia, and Oceania, impacting native aquatic ecosystems. Given this species is a popular aquarium plant and widely traded, there is a high risk of introduction and invasion into other environments. In the current study the potential global geographic distribution of C. caroliniana was predicted under the effects of climate change and human influence in an optimised MaxEnt model. The model used rigorously screened occurrence records of C. caroliniana from hydro informatic datasets and 20 associated influencing factors. The findings indicate that temperature and human-mediated activities significantly influenced the distribution of C. caroliniana. At present, C. caroliniana covers an area of approximately 1531×104 km2 of appropriate habitat, especially in the south-eastern parts of South, central and North America, Southeast Asia, eastern Australia, and most of Europe. The suitable regions are anticipated to expand under future climate scenarios; however, the dynamics of the changes vary between different extents of climate change. For example, C. caroliniana is expected to expand to higher latitudes, following global temperature increases under SSP1–2.6 and SSP2–4.5 scenarios, however, intolerance to temperature extremes may mediate invasion at higher latitudes under future extreme climate scenarios, e.g., SSP5–8.5. Owing to the severe impacts its invasion causes, early warning and stringent border quarantine processes are required to guard against the introduction of C. caroliniana especially in the invasion hotspots such as, Peru, Italy, and South Korea.

Examining dynamic developmental trends: the interrelationship between age-friendly environments and healthy aging in the Chinese population—evidence from China Health and Retirement Longitudinal Study, 2011–2018

BackgroundThe objective of this research is to investigate the dynamic developmental trends between Age-Friendly Environments (AFE) and healthy aging in the Chinese population.MethodsThis study focused on a sample of 11,770 participants from the CHARLS and utilized the ATHLOS Healthy Aging Index to assess the level of healthy aging among the Chinese population. Linear mixed model (LMM) was used to explore the relationship between AFE and healthy aging. Furthermore, a cross-lagged panel model (CLPM) and a random-intercept cross-lagged panel model (RI-CLPM) were used to examine the dynamic developmental trends of healthy aging, taking into account both Between-Person effects and Within-Person effects.ResultsThe results from LMM showed a positive correlation between AFE and healthy aging (β = 0.087, p < 0.001). There was a positive interaction between the geographic distribution and AFE (central region * AFE: β = 0.031, p = 0.038; eastern region * AFE: β = 0.048, p = 0.003). In CLPM and RI-CLPM, the positive effect of healthy aging on AFE is a type of Between-Person effects (β ranges from 0.147 to 0.159, p < 0.001), while the positive effect of AFE on healthy aging is Within-Person effects (β ranges from 0.021 to 0.024, p = 0.004).ConclusionFirstly, individuals with high levels of healthy aging are more inclined to actively participate in the development of appropriate AFE compared to those with low levels of healthy aging. Furthermore, by encouraging and guiding individuals to engage in activities that contribute to building appropriate AFE, can elevate their AFE levels beyond the previous average level, thereby improving their future healthy aging levels. Lastly, addressing vulnerable groups by reducing disparities and meeting their health needs effectively is crucial for fostering healthy aging in these populations.

Square the Circle: Diversity of Viral Pathogens Causing Neuro-Infectious Diseases

Neuroinfections rank among the top ten leading causes of child mortality globally, even in high-income countries. The crucial determinants for successful treatment lie in the timing and swiftness of diagnosis. Although viruses constitute the majority of infectious neuropathologies, diagnosing and treating viral neuroinfections remains challenging. Despite technological advancements, the etiology of the disease remains undetermined in over half of cases. The identification of the pathogen becomes more difficult when the infection is caused by atypical pathogens or multiple pathogens simultaneously. Furthermore, the modern surge in global passenger traffic has led to an increase in cases of infections caused by pathogens not endemic to local areas. This review aims to systematize and summarize information on neuroinvasive viral pathogens, encompassing their geographic distribution and transmission routes. Emphasis is placed on rare pathogens and cases involving atypical pathogens, aiming to offer a comprehensive and structured catalog of viral agents with neurovirulence potential.

V4RIN: visual analysis of regional industry network with domain knowledge.

The regional industry network (RIN) is a type of financial network derived from industry networks that possess the capability to describe the connections between specific industries within a particular region. For most investors and financial analysts lacking extensive experience, the decision-support information provided by industry networks may be too vague. Conversely, RINs express more detailed and specific industry connections both within and outside the region. As RIN analysis is domain-specific and current financial network analysis tools are designed for generalized analytical tasks and cannot be directly applied to RINs, new visual analysis approaches are needed to enhance information exploration efficiency. In this study, we collaborated with domain experts and proposed V4RIN, an interactive visualization analysis system that integrates predefined domain knowledge and data processing methods to support users in uploading custom data. Through multiple views in the system panel, users can comprehensively explore the structure, geographical distribution, and spatiotemporal variations of the RIN. Two case studies were conducted and a set of expert interviews with five domain experts to validate the usability and reliability of our system.

Exploring Chemical Variability in the Essential Oils of the Thymus Genus.

Thyme remains an indispensable herb today, finding its place in gastronomy, medicine, cosmetics, and gardens worldwide. It is highly valued in herbal remedies and pharmaceutical formulations for its antibacterial, antifungal, and antioxidant properties derived from the richness of its essential oil, which comprises various volatile components. However, climate change poses a significant challenge today, potentially affecting the quality of thyme, particularly the extracted essential oil, along with other factors such as biotic influences and the plant's geographical distribution. Consequently, complex diversity in essential oil composition was observed, also influenced by genetic diversity within the same species, resulting in distinct chemotypes. Other factors contributing to this chemodiversity include the chosen agrotechnology and processing methods of thyme, the extraction of the essential oil, and storage conditions. In this review, we provide the latest findings on the factors contributing to the chemovariability of thyme essential oil.

New Discovery of Calamitaceae from the Cisuralian in Northwest China: Morphological Evolution of Strobilus.

Calamitaceae was the predominant arborescent element of the Late Paleozoic plant assemblages. However, there is currently controversy surrounding the evolutionary relationships of their four reproductive organs, and there is no unified understanding of the geographical distribution and species richness characteristics. This paper is based on the detailed description of the macro- and microstructures of Calamites and Macrostachya discovered in the Shanxi Formation of the Cisuralian in the eastern Hexi Corridor of northwestern China, and it discusses the evolutionary patterns of calamitean reproductive organs. The results indicate that the current specimens can be identified as the Calamites cistii and Macrostachya sp., and the in situ spores should exhibit distinct trilete marks, indicating that they belong to the Punctatisporites punctatus. The abundant fossil records suggest that the "Calamostachys" type should be considered as the ancestral type of strobili. Additionally, Calamitaceae was widely distributed in mid to low latitudes globally from the Pennsylvanian to the Cisuralian and coupled with paleogeographic distribution characteristics.

Potential historically intertropical stable areas during the Late Quaternary of South America

AbstractSouth America is a pivotal paleontological setting for Late Quaternary megafaunal research. Nonetheless, its paleobiogeography and paleoecology, and the causes for the recent extinction of megafauna in the Late Pleistocene/Early Holocene are not yet fully understood. This study aimed to investigate the potential geographical distribution and historically intertropical stable areas (HISAs) of South American megafauna. We generated maps using Paleo‐Species Distribution Models for 12 megafaunal taxa (11 herbivores and one carnivore) during interglacial and glacial periods in the Late Quaternary: 120 and 21 ka. Our models, together with isotopic data, show that the HSIAs occurred mainly in low‐altitude plains (&lt;1000 m) and were superimposed on seasonal dry forest biomes. We propose the occurrence of two HSIAs: the West Intertropical Region and the Brazilian Intertropical Region, the latter being redefined. We suggest that the Brazilian Intertropical Region is much smaller than previously proposed, but was still a key zoogeographical region for megafauna in South America during the Late Pleistocene.

New records of Dipsas welborni Arteaga &amp;amp; Batista, 2023, Gelanesaurus flavogularis (Altamirano-Benavides, Zaher, Lobo, Grazziotin, Sales-Nunes &amp;amp; Rodrigues, 2013), and Synophis insulomontanus Torres-Carvajal, Echevarr&amp;iacute;a, Venegas, Ch&amp;aacute;vez &amp;amp; Camper, 2015 in the Cordillera de Col&amp;aacute;n, Peru

A herpetological survey during recent expeditions to the foothills of the Cordillera de Col&amp;aacute;n in the Amazonas region of Peru resulted in new records and extensions of the geographical distribution of three poorly known species of reptiles: Dipsas welborni (family Colubridae), Gelanesaurus flavogularis (family Gymnophthalmidae), and Synophis insulomontanus (family Colubridae).

Geographic and Racial/Ethnic Differences in Access to Methamphetamine Detoxification Services, United States, 2021.

Methamphetamine detoxification before entering formal and longer term treatment may have a positive impact on treatment retention and success. Understanding geographic distribution of methamphetamine specialty detox services and differential access by race/ethnicity is critical for establishing policies that ensure equitable access across populations. We used the Mental health and Addiction Treatment Tracking Repository to identify treatment facilities that offered any substance use detoxification in 2021 (N=2346) as well as the census block group in which they were located. We sourced data from the US Census Bureau to identify the percentage of a census block group that was White, Black, and Hispanic. We used logistic regression to model the availability of methamphetamine-specific detox, predicted by the percentage of a block group that was Black and Hispanic. We adjusted for relevant covariates and defined state as a random effect. We calculated model-based predicted probabilities. Over half (60%) of detox facilities offered additional detox services specifically for methamphetamine. Sixteen states had <10 methamphetamine-specific detox facilities. The predicted probability of methamphetamine-specific detox availability was 60% in census block groups with 0%-9% Black residents versus only 46% in census block groups with 90%-100% Black residents, and was 61% in census block groups with 0%-9% Hispanic residents versus 30% in census block groups with 90%-100% Hispanic residents. During an unprecedented national methamphetamine crisis, access to a critical health care service was disproportionately lower in communities that were predominately Black and Hispanic. We orient our findings around a discussion of health disparities, residential segregation, and the upstream causes of the systematic exclusion of minoritized communities from health care.

Species boundaries of the whiptail catfish Rineloricaria (Siluriformes: Loricariidae) from the Paraíba do Sul River drainage, southeastern Brazil, with species redescriptions and description of a new species.

Species of the catfish genus Rineloricaria are common in the Paraíba do Sul River basin, in southeastern Brazil; here we present a revision of the taxonomic diversity and geographic distribution of the species of the genus inhabiting the basin, based on novel morphologic and molecular data. Five species delimitation methods based on cytochrome C oxidase subunit 1 nucleotide sequences yielded comparable molecular operational taxonomic units. The automatic barcode gap discovery, assemble species by automatic partitioning, barcode index number, and Bayesian implementation of the Poisson tree process methods supported the recognition of five evolutionary lineages. These taxonomic units were assigned to the previously described Rineloricaria nigricauda, Rineloricaria steindachneri, Rineloricaria zawadzkii, and Rineloricaria nudipectoris, and an additional undescribed species. R. zawadzkii was further divided into two intraspecific geographically structured lineages using the generalized mixed Yule coalescent delimitation method. A maximum likelihood phylogenetic analysis revealed that the five lineages from the Paraíba do Sul have closer relationships to different species from southern and southeastern Brazil (Ribeira de Iguape, Lagoa dos Patos, Uruguay, Paraguay, and Parana river basins) than to each other. Based on the analysis of lectotypes, recently collected material, and specimens from ichthyological collections, the poorly described R. nigricauda and R. steindachneri are redescribed following current descriptive standards. The undescribed species from the middle and upper Paraíba do Sul River basin is formally described. The description of a new species, along with the description of species boundaries in R. nigricauda and R. steindachneri, contributes to the knowledge of the ichthyofauna of the Paraíba do Sul River basin and adjacent coastal drainages of southeastern Brazil. An identification key for the species of Rineloricaria occurring in the Paraíba do Sul River basin is provided.

Wildfire Ashes from the Wildland-Urban Interface Alter Vibrio vulnificus Growth and Gene Expression.

Climate change-induced stressors are contributing to the emergence of infectious diseases, including those caused by marine bacterial pathogens such as Vibrio spp. These stressors alter Vibrio temporal and geographical distribution, resulting in increased spread, exposure, and infection rates, thus facilitating greater Vibrio-human interactions. Concurrently, wildfires are increasing in size, severity, frequency, and spread in the built environment due to climate change, resulting in the emission of contaminants of emerging concern. This study aimed to understand the potential effects of urban interface wildfire ashes on Vibrio vulnificus (V. vulnificus) growth and gene expression using transcriptomic approaches. V. vulnificus was exposed to structural and vegetation ashes and analyzed to identify differentially expressed genes using the HTSeq-DESeq2 strategy. Exposure to wildfire ash altered V. vulnificus growth and gene expression, depending on the trace metal composition of the ash. The high Fe content of the vegetation ash enhanced bacterial growth, while the high Cu, As, and Cr content of the structural ash suppressed growth. Additionally, the overall pattern of upregulated genes and pathways suggests increased virulence potential due to the selection of metal- and antibiotic-resistant strains. Therefore, mixed fire ashes transported and deposited into coastal zones may lead to the selection of environmental reservoirs of Vibrio strains with enhanced antibiotic resistance profiles, increasing public health risk.

Ciliate symbionts of bivalves with notes on their worldwide geographic distribution

The shells, mantle cavities and various organs of mollusks serve as suitable habitats for symbiotic ciliates, as commensal, epibiotic and parasitic. With about 80,000 species, molluscans are distributed in freshwater, marine and terrestrial habitats; symbiotic ciliates have been recorded in bivalves, gastropods and polyplacophorans; however these records have not been integrated in comprehensive revisions. The goal of this work is to provide an updated checklist of the ciliates involved as symbionts of bivalve molluscs worldwide. Available records of symbiotic species of ciliates were compiled and checked, along with their molluscan hosts and localities. We obtained data for 165 species of ciliates as symbionts of 158 bivalve hosts, distributed in 31 countries, regions and seas. This is the first comprehensive study to review the biodiversity of ciliates associated with bivalves and show that only a small fraction of this class of molluscs has been studied in terms of their symbiotic relationships with ciliates.

Research trends in aerobic gymnastics in school settings: A bibliometric analysis

This study presents a bibliometric analysis of 5335 articles published between 2013 and 2023, aimed at exploring the research landscape of aerobic gymnastics in school settings. The study aims to identify key research categories, publication trends, and geographic distribution of publications. A bibliometric analysis was conducted using data from the Dimensions database, focusing on peer-reviewed journal articles, conference papers, and scholarly outputs related to aerobic gymnastics in school-based physical education. The analysis reveals a multidisciplinary approach, with key research categories including education, health sciences, and public health. Publication trends indicate a significant increase in publications, particularly during the COVID-19 pandemic, demonstrating a growing interest in aerobic gymnastics as a flexible physical activity adaptable to various contexts, including remote learning. The United States, the United Kingdom, and Australia lead in publication productivity, while countries like Indonesia exhibit lower productivity, suggesting a need for increased research efforts and collaborations. The sources with the highest number of citations offer insights into the relationship between physical activity and health outcomes in relation to aerobic gymnastics. An analysis of co-authorship highlights the key researchers and collaborations that have made significant contributions to the field. This study emphasizes the importance of ongoing research and collaboration to gain a better understanding of the benefits and challenges of implementing aerobic gymnastics programs in schools. Suggestions for future research include longitudinal, comparative, intervention, and qualitative studies to enhance our understanding of the impact of aerobic gymnastics on education, health, and society.

Incorporating physiological knowledge into correlative species distribution models minimizes bias introduced by the choice of calibration area

AbstractCorrelative species distribution models (SDMs) are important tools to estimate species’ geographic distribution across space and time, but their reliability heavily relies on the availability and quality of occurrence data. Estimations can be biased when occurrences do not fully represent the environmental requirement of a species. We tested to what extent species’ physiological knowledge might influence SDM estimations. Focusing on the Japanese sea cucumber Apostichopus japonicus within the coastal ocean of East Asia, we compiled a comprehensive dataset of occurrence records. We then explored the importance of incorporating physiological knowledge into SDMs by calibrating two types of correlative SDMs: a naïve model that solely depends on environmental correlates, and a physiologically informed model that further incorporates physiological information as priors. We further tested the models’ sensitivity to calibration area choices by fitting them with different buffered areas around known presences. Compared with naïve models, the physiologically informed models successfully captured the negative influence of high temperature on A. japonicus and were less sensitive to the choice of calibration area. The naïve models resulted in more optimistic prediction of the changes of potential distributions under climate change (i.e., larger range expansion and less contraction) than the physiologically informed models. Our findings highlight benefits from incorporating physiological information into correlative SDMs, namely mitigating the uncertainties associated with the choice of calibration area. Given these promising features, we encourage future SDM studies to consider species physiological information where available.

A systematic review and meta-analysis of artificial neural network, machine learning, deep learning, and ensemble learning approaches in field of geotechnical engineering

AbstractArtificial neural networks (ANN), machine learning (ML), deep learning (DL), and ensemble learning (EL) are four outstanding approaches that enable algorithms to extract information from data and make predictions or decisions autonomously without the need for direct instructions. ANN, ML, DL, and EL models have found extensive application in predicting geotechnical and geoenvironmental parameters. This research aims to provide a comprehensive assessment of the applications of ANN, ML, DL, and EL in addressing forecasting within the field related to geotechnical engineering, including soil mechanics, foundation engineering, rock mechanics, environmental geotechnics, and transportation geotechnics. Previous studies have not collectively examined all four algorithms—ANN, ML, DL, and EL—and have not explored their advantages and disadvantages in the field of geotechnical engineering. This research aims to categorize and address this gap in the existing literature systematically. An extensive dataset of relevant research studies was gathered from the Web of Science and subjected to an analysis based on their approach, primary focus and objectives, year of publication, geographical distribution, and results. Additionally, this study included a co-occurrence keyword analysis that covered ANN, ML, DL, and EL techniques, systematic reviews, geotechnical engineering, and review articles that the data, sourced from the Scopus database through the Elsevier Journal, were then visualized using VOS Viewer for further examination. The results demonstrated that ANN is widely utilized despite the proven potential of ML, DL, and EL methods in geotechnical engineering due to the need for real-world laboratory data that civil and geotechnical engineers often encounter. However, when it comes to predicting behavior in geotechnical scenarios, EL techniques outperform all three other methods. Additionally, the techniques discussed here assist geotechnical engineering in understanding the benefits and disadvantages of ANN, ML, DL, and EL within the geo techniques area. This understanding enables geotechnical practitioners to select the most suitable techniques for creating a certainty and resilient ecosystem.

The influence of manual segmentation strategies and different phases selection on machine learning-based computed tomography in renal tumors: a systematic review and meta-analysis.

Delineating the region/volume of interest (ROI/VOI) and selecting the phases are of importance in developing machine learning (ML). The results will change when choosing different methods of drawing the ROI/VOI and selecting different phases. However, there is no related standard for delineating the ROI/VOI and selecting the phases in renal tumors to develop ML based on computed tomography (CT). The PubMed and Web of Science were searched for related studies published until March 1, 2023. Inclusion criteria were studies that developed ML models in renal tumors from CT images. And the binary diagnostic accuracy data were extracted to obtain the outcomes, such as sensitivity (SE), specificity (SP), accuracy (ACC), and area under the curve (AUC). Twenty-three papers were included in the meta-analysis with a pooled SE of 87% (95% CI 85-88%), SP of 82% (95% CI 79-85%), and AUC of 91% (95% CI 89-93%) in phases; a pooled SE of 82% (95% CI 80-84%), SP of 85% (95% CI 83-86%), and AUC of 90% (95% CI 88-93%) in phases combined with delineating strategies, respectively. In all different combinations, the contour-focused and single phase produce the highest AUC of 93% (95% CI 90-95%). In subgroup analyses (sample size, year of publication, and geographical distribution), the performance was acceptable on phases and phases combined strategies. To explore the effect of manual segmentation strategies and different phases selection on ML-based CT, we find that the method of single phase (CMP or NP) combined with contour-focused was considered a better strategy compared to the other strategies.

Assessing the conservation and restoration potential of biotopes in a central European region

AbstractChanging environmental conditions and land use are threatening biodiversity on a large scale, making successful conservation and restoration essential for maintaining biodiversity. Planning of such efforts profits from information about where conditions are suitable for biotopes, to evaluate how likely successful conservation or restoration is at these sites. This study uses the distribution model Maxent to identify varying levels of conservation and restoration potential for 29 different biotopes in the central European region of Bavaria, Germany, by comparing the environmentally suitable areas identified by models with the current distribution of each biotope. We identified a conservation potential when a biotope occurred under suitable environmental conditions and a restoration potential when suitable environmental conditions were present at a site where the biotope was not observed. We found that 69.57% of biotope observations occurred under suitable environmental conditions representing a large conservation potential. Also, 22 biotopes showed more restoration potential than their current distribution and both conservation and restoration potential showed a similar geographical distribution. The approach used in this study can provide valuable insights for conservation and restoration decision-making by suggesting priority areas for the conservation and restoration of multiple biotopes. Further, it could be applied in other regions globally and by incorporating future climate projections it could identify particularly resilient locations for biotope conservation or restoration.

Heavy Metals In Bivalves From Coastal Municipalities Of C apiz,P hilippines

This research study is based on the current status of heavy metal contamination in bivalves within the coastal areas of Capiz, Philippines, drawing insights from accessible data. The findings shed light on the contamination’s extent, potential threats to human health, and the pollution’s origins. The researchers acknowledge the study’s limitations. As per the findings, elevated levels of heavy metals, such as lead, mercury, cadmium, arsenic, and chromium, in bivalves collected from Capiz’s coastal regions. Variations in metal concentrations are observed among different bivalve species and sampling sites, with identified geographical distribution patterns and potential contamination hotspots. An assessment of conformity to regulatory limits and guidance for heavy metal levels in shellfish consumption is conducted, identifying any exceedances or areas of concern. The research aims to establish the extent to which bivalves from Capiz aligns with legal requirements. Potential health risks allied to the bivalve consumption are evaluated based on the detected heavy metal levels, considering various exposure routes, population characteristics, and toxicity reference values. The research scrutinizes the impact of human activities, including industrial discharges, agricultural practices, and urban runoff, on heavy metal contamination in coastal ecosystems. The ongoing discussion underscores the need for further investigation and underscores the importance of addressing the issue to ensure the environmental sustainability and safety of coastal resources in Capiz.

Risk Assessment of Spodoptera exempta against Food Security: Estimating the Potential Global Overlapping Areas of Wheat, Maize, and Rice under Climate Change.

Spodoptera exempta, known as the black armyworm, has been extensively documented as an invasive agricultural pest prevalent across various crop planting regions globally. However, the potential geographical distribution and the threat it poses to host crops of remains unknown at present. Therefore, we used an optimized MaxEnt model based on 841 occurrence records and 19 bioclimatic variables to predict the potential suitable areas of S. exempta under current and future climatic conditions, and the overlap with wheat, rice, and maize planting areas was assessed. The optimized model was highly reliable in predicting potential suitable areas for this pest. The results showed that high-risk distribution areas for S. exempta were mainly in developing countries, including Latin America, central South America, central Africa, and southern Asia. Moreover, for the three major global food crops, S. exempta posed the greatest risk to maize planting areas (510.78 × 104 km2), followed by rice and wheat planting areas. Under future climate scenarios, global warming will limit the distribution of S. exempta. Overall, S. exempta had the strongest effect on global maize production areas and the least on global wheat planting areas. Our study offers a scientific basis for global prevention of S. exempta and protection of agricultural crops.

A Gaussian Function Model of Mesoscale Eddy Temperature Anomalies and Research of Spatial Distribution Characteristics

Mesoscale eddies are ubiquitous oceanic phenomena and play an important role in ocean circulation, ocean dynamics, and the transport of material energy. Temperature anomalies are a crucial parameter that reflects the state of mesoscale eddies. This study proposes a Gaussian function model to fit the vertical temperature anomaly (TA) profile to facilitate the analysis of variations, and the principle of the model is based on the fact that each TA profile tends to fluctuate around one or more peaks. The model is extracted and validated using Argo profiles within cyclonic and anticyclonic eddies in the Northwest Pacific Ocean spanning over the period from 2002 to 2021. The validation demonstrates that the model can accurately recover the vertical TA profiles with a limited number of parameters. This makes it suitable for analysing the spatial distribution patterns that require a large sample count. The analysis indicates that eddies with different TA profiles have a spatial aggregation effect in geographic distribution. Eddies with lower extreme temperature anomalies, at depths of 200–300 m, are mainly distributed along two bands on the north side of the Kuroshio Extension (KE) and the North Equatorial Current. Eddies with extreme TAs at the deepest depth (500–600 m) are distributed along the KE.