Spatial-temporal Distribution Pattern Research Articles

Spatial-Temporal Distribution Pattern of Dengue Fever and Spatial Relationship of the Aedes Mosquito Larvae Index in Phuket Province

Spatial-Temporal Distribution Pattern of Dengue Fever and Spatial Relationship of the Aedes Mosquito Larvae Index in Phuket Province

Spatial-temporal Variations and Driving Factors of Surface Ozone over the Qinghai-Xizang Plateau from 2015 to 2021

The spatial-temporal distribution pattern of surface O3 over the Qinghai-Xizang Plateau （QXP） was analyzed based on air quality monitoring data and meteorological data from 12 cities on the QXP from 2015 to 2021. Kolmogorov-Zurbenko （KZ） filtering was employed to separate the original O3-8h series into components at different time scales. Then, multiple linear regression of meteorological variables was used to quantitatively isolate the effects of meteorology and emissions. The results revealed that the annual mass concentrations of surface O3-8h from 2015 to 2021 in 12 cities over the QXP ranged from 78.7 to 156.7 μg·m-3, and the exceedance rates of O3 mass concentrations （National Air Quality Standard of grade II） ranged from 0.7%-1.5%. The monthly O3-8h mass concentration displayed a single-peak inverted "V"-shape and a multi-peak "M"-shape. The maximum monthly concentration of O3 occurred in April to July, and valleys occurred in July, September, and December. The short-term, seasonal, and long-term components of O3-8hdecomposed by KZ filtering contributed 29.6%, 51.4%, and 9.1% to the total variance in the original O3 sequence in 12 cities, respectively. From the whole region, the meteorological conditions were unfavorable for O3 reduction on the QXP from 2015 to 2017, which made the long-term component of O3 increase by 0.2-2.1 μg·m-3. The meteorological conditions were favorable for O3-8h reduction from 2018 to 2021, which led to the long-term component of O3-8h decrease by 0.4-1.1 μg·m-3. The meteorological conditions increased the long-term component of O3-8h in Ngari, Lhasa, Naqu, Nyingchi, Qamdo, Haixi, and Xining, with an average contribution of 30.1%. The meteorological conditions decreased the long-term component of O3-8h in Shigatse and Golog, with contributions of 359.0% and 56.5%, respectively. The increase in the long-term component of O3-8h in Ngari, Shigatse, Nagqu, Haixi, and Xining could be due to the rapid decrease in the long-term component of PM2.5 （4.04 μg·（m3·a）-1）.

Spatial–temporal evaluation of total-factor energy efficiency in Chinese construction industry based on three-stage super-efficiency SBM-DEA model

PurposeThe study aims to enhance energy efficiency within the high-energy consuming construction industry. It explores the spatial-temporal dynamics and distribution patterns of total factor energy efficiency (TFEE) across China’s construction industry, aiming to inform targeted emission reduction policies at provincial and city levels.Design/methodology/approachUtilizing a three-stage super-efficiency SBM-DEA model that integrates carbon emissions, the TFEE in 30 Chinese provinces and cities from 2004 to 2019 is assessed. Through kernel density estimation and exploratory spatial data analysis, the dynamic evolution and spatial patterns of TFEE are examined.FindingsAnalysis reveals that environmental investments positively impact TFEE, whereas Gross Regional Product (GRP) exerts a negative influence. R&D expenditure intensity and marketization show mixed effects. Excluding environmental and random factors, TFEE averages declined, aligning more closely with actual development trends, showing a gradual decrease from east to west. TFEE exhibited fluctuating growth with a trend moving from inefficient clusters to a more even distribution. Spatially, TFEE demonstrated aggregation effects and characteristics of space-time transition.Originality/valueThis research employs the three-stage super-efficiency SBM-DEA model to measure the total factor energy efficiency of the construction industry, taking into account external environment, random disturbances, and multiple effective decision-making units. It also evaluates energy efficiency changes before and after removing disturbances and comprehensively examines regional and temporal differences from static and dynamic, overall and phased perspectives. Additionally, Moran scatter plots and LISA cluster maps are used to objectively analyze the spatial agglomeration and factors influencing energy efficiency.

Driving Factors Analysis for Spatial-Temporal Distribution of Organic Pollutants in the Yangtze River Delta Based on the Optimal-scale Geographical Detector

Site contamination has caused serious harm to human health and the ecological environment, so understanding its spatial and temporal distribution patterns is the basis for contamination assessment and site remediation. For this reason, this study analyzed the spatial-temporal distribution patterns of organic pollutants and their driving factors in the Yangtze River Delta based on site sampling data using the optimal-scale geographical detector. The analysis results showed that:① There was a significant scale effect in the spatial distribution of organic pollutants in the Yangtze River Delta, and its optimal geographic detection scale grid was 8 000 meters. ② The main control factor of the spatial distribution of pollutants in the Yangtze River Delta originated mostly from the biological field, followed by the chemical field. ③ At the depth of 0-20 cm of soil, the explanatory power of sucrase content, urease content, microbial nitrogen amount, total nitrogen content, and cation exchange amount were stronger for the spatial distribution of organic pollutants. At the soil depth of 20-40 cm, the factors with stronger explanatory power on the spatial distribution of organic pollutants were soil moisture, population, and total nitrogen content. With the deepening of soil depth, the explanatory power of the factors of the hydrodynamic field increased. ④ Population, total nitrogen content, and polyphenol oxidase content had stronger explanatory power for the spatial distribution of organic pollutants in the spring. The spatial distribution of organic pollutants was more complex in autumn, and the factors showed stronger enhanced-nonlinear and enhanced-bi phenomena.

Application of pervious concrete pavement in the "breathe in-breathe out" design for sponge cities in China.

Sponge city construction is an ideal approach to mitigate the degradation of urban water environments. Among road materials, permeable concrete pavement stands out due to its unique structure that allows rainwater runoff to flow through its pores. This paper analyzes the current application status and the prospect of different permeable pavement designs in China's sponge cities, aiming to offer valuable insights for urban planning and construction. Statistical analysis summarizes the spatial-temporal distribution patterns of urban flooding disasters in China and their causes. By comparing the characteristics and advantages of pervious concrete pavement with traditional concrete pavement, the potential of permeable concrete pavement in sponge city construction is summarized through case studies. The findings highlight that by adjusting the pore size, permeable concrete pavement can collect rainwater while filtering impurities, thereby purifying surface runoff. The range of the pervious coefficient should ideally fall within the range of 4~8 mm/s. In addition, the pavement's large contact area with the air and internal water evaporation contributes to its self-regulating capability, reducing the occurrence of extreme temperatures. Related experiments have shown that from 8 am to 12 pm, pervious concrete pavement can reduce the temperature by approximately 1 °C compared to conventional concrete. From 12 pm to 8 pm, this temperature difference increases to approximately 3 °C. To meet the needs of environmental protection and resource utilization, permeable concrete pavement can serve as an ideal tool to achieve green and low-carbon development.

Multiple events determine the distribution of fishes’ early life stages in the Abrolhos Bank, Southwestern Atlantic

Fluctuations in reef fish settlement and recruitment significantly impact local population dynamics and adult population size. We use light traps to evaluate reef fish settlement in inshore and offshore reefs in the Abrolhos Bank, in addition to the spatio-temporal distribution patterns, and environmental variables' influence. Data were collected from inshore and offshore reefs, and statistical analyses, including GLMs, PERMANOVA and nMDS, aimed to understand spatial-temporal species distribution patterns and the relationship between environmental variables. Results indicate greater species abundance and diversity offshore, influenced by winds, tides, and distance from shore, explaining 50% of larval patterns and highlighting the importance of spatial-temporal variations in early-life reef fish assemblages. However, several factors, including habitat type, quality, complexity, seascape configuration, and MPA location, may influence these patterns. Additionally, we provide evidence that commercially important species like Lutjanids use Abrolhos reef areas as nursery grounds.

Spatial-temporal analysis of hepatitis B in Fujian Province, China in 2012–2021

BackgroundFujian Province has one of the highest reported incidences of hepatitis B virus infection in China. This study aimed to provide a theoretical framework for preventing and controlling hepatitis B in Fujian Province, and to assess the trends and the spatial-temporal distribution patterns of hepatitis B in this region. MethodsData on hepatitis B cases were extracted from the National Notifiable Infectious Disease Surveillance System. Spatial autocorrelation analysis, trend surface analysis, and spatial-temporal scanning statistics were used to identify the spatial and aggregation patterns at the county level. The Joinpoint was used to assess the reported incidence trends. ResultsThe average reported incidence of hepatitis B in Fujian from 2012 to 2021 was 14.46/10,000 population, with 583,262 notified cases. The age-adjusted reported incidence of hepatitis B decreased from 17.44/10,000 population in 2012 to 11.88/10,000 population in 2021, with an average reduction in the annual percentage change of 4.5%. There were obvious spatial-temporal aggregation characteristics in hepatitis B cases, and a high-incidence area was located in eastern Fujian. Spatio-temporal scanning statistics revealed four levels of aggregation of hepatitis B reporting rates. The first level of aggregation area included Minhou, Gulou, Jin'an, Taijiang, and nine other districts and counties. ConclusionsThe incidence of hepatitis B is declining in Fujian Province. Spatial clusters of hepatitis B cases in Fujian Province were identified, and high-risk areas in eastern Fujian still exist. Closely monitoring the general patterns in the occurrence of hepatitis B and implementing focused control and preventative strategies are important.

Temporal-spatial characteristics and sources of heavy metals in bulk deposition across China

With the rapid development of industries, agriculture, and urbanization (including transportation and population growth), there has been a significant alteration in the emission and atmospheric deposition of heavy metal pollutants. This has consequently given rise to a range of ecological and environmental health issues. In this study, we conducted a comprehensive two-year investigation on the temporal and spatial distribution characteristics of heavy metals in atmospheric deposition across China based on the Nationwide Nitrogen Deposition Monitoring Network (NNDMN). The atmospheric bulk deposition of Lead (Pb), Arsenic (As), Nickel (Ni), Selenium (Se), Chromium (Cr) and Cadmium (Cd) were 6.32 ± 1.59, 4.49 ± 0.57, 1.31 ± 0.21, 1.05 ± 0.16, 0.60 ± 0.06 and 0.21 ± 0.03 mg m−2 yr−1, respectively, with a large variation among the different regions of China. The order for atmospheric deposition flux was Southwest China > Southeast China > North China > Northeast China > Qinghai-Tibet Plateau and rural area > urban area > background area. The concentrations of heavy metals in bulk deposition exhibit seasonal variation with higher levels observed during winter compared to summer and spring, which are closely associated with anthropogenic activities. The Positive Matrix Factorization (PMF) results indicated that combustion, industrial emissions and traffic are the primary contributors to atmospheric deposition of heavy metals. The single factor pollution index (Pi) of heavy metals is consistently below 1, and the composite pollution index (Ni) is 0.16 across China, indicating that atmospheric heavy metal deposition is at a pollution-free level. The comprehensive potential ecological risk index of heavy metals is 11.8, with Cd exhibiting the highest single factor potential ecological risk index at 7.09, suggesting that more attention should be paid to Cd deposition in China. The present study reveals the spatial-temporal distribution pattern of atmospheric heavy metals deposition in China, identifying regional source characteristics and providing a theoretical foundation and strategies for reducing emissions of atmospheric pollutants.

Spatial–temporal distribution patterns and influencing factors analysis of comorbidity prevalence of chronic diseases among middle-aged and elderly people in China: focusing on exposure to ambient fine particulate matter (PM2.5)

ObjectiveThis study describes regional differences and dynamic changes in the prevalence of comorbidities among middle-aged and elderly people with chronic diseases (PCMC) in China from 2011–2018, and explores distribution patterns and the relationship between PM2.5 and PCMC, aiming to provide data support for regional prevention and control measures for chronic disease comorbidities in China.MethodsThis study utilized CHARLS follow-up data for ≥ 45-year-old individuals from 2011, 2013, 2015, and 2018 as research subjects. Missing values were filled using the random forest machine learning method. PCMC spatial clustering investigated using spatial autocorrelation methods. The relationship between macro factors and PCMC was examined using Geographically and Temporally Weighted Regression, Ordinary Linear Regression, and Geographically Weighted Regression.ResultsPCMC in China showing a decreasing trend. Hotspots of PCMC appeared mainly in western and northern provinces, while cold spots were in southeastern coastal provinces. PM2.5 content was a risk factor for PCMC, the range of influence expanded from the southeastern coastal areas to inland areas, and the magnitude of influence decreased from the southeastern coastal areas to inland areas.ConclusionPM2.5 content, as a risk factor, should be given special attention, taking into account regional factors. In the future, policy-makers should develop stricter air pollution control policies based on different regional economic, demographic, and geographic factors, while promoting public education, increasing public transportation, and urban green coverage.

Unraveling the spatial-temporal distribution patterns of soil abundant and rare bacterial communities in China's subtropical mountain forest.

The pivotal roles of both abundant and rare bacteria in ecosystem function are widely acknowledged. Despite this, the diversity elevational patterns of these two bacterial taxa in different seasons and influencing factors remains underexplored, especially in the case of rare bacteria. Here, a metabarcoding approach was employed to investigate elevational patterns of these two bacterial communities in different seasons and tested the roles of soil physico-chemical properties in structuring these abundant and rare bacterial community. Our findings revealed that variation in elevation and season exerted notably effects on the rare bacterial diversity. Despite the reactions of abundant and rare communities to the elevational gradient exhibited similarities during both summer and winter, distinct elevational patterns were observed in their respective diversity. Specifically, abundant bacterial diversity exhibited a roughly U-shaped pattern along the elevation gradient, while rare bacterial diversity increased with the elevational gradient. Soil moisture and N:P were the dominant factor leading to the pronounced divergence in elevational distributions in summer. Soil temperature and pH were the key factors in winter. The network analysis revealed the bacteria are better able to adapt to environmental fluctuations during the summer season. Additionally, compared to abundant bacteria, the taxonomy of rare bacteria displayed a higher degree of complexity. Our discovery contributes to advancing our comprehension of intricate dynamic diversity patterns in abundant and rare bacteria in the context of environmental gradients and seasonal fluctuations.

Spatial-temporal distribution pattern and driving factors of agricultural carbon sinks in Beijing-Tianjin-Hebei region from the perspective of carbon neutrality

AbstractDeveloping policies to reduce carbon emissions in agriculture is crucial for achieving the ‘dual carbon’ goal. Therefore, scientifically analysing the temporal and spatial distribution characteristics of agricultural carbon sinks and their driving factors holds paramount importance for the coordinated and integrated development of regional agriculture and the realization of sustainable development. Based on the perspective of carbon cycle in agricultural production, the measurement system of agricultural net carbon sink was established from the perspective of carbon sink/carbon source, this study conducted an analysis of the temporal and spatial variation characteristics as well as driving mechanisms of agricultural net carbon sinks. The findings are as follows: (1) The agricultural net carbon sink exhibited an increasing trend from 2009 to 2020, with favourable intensity and level. (2) Agricultural land use and livestock and poultry production constituted the primary sources of agricultural carbon emissions. Notably, agricultural carbon emissions demonstrated a decreasing trend during the study period. (3) The net agricultural carbon sink displayed local spatial aggregation, indicating significant regional differences. (4) Factors such as rural economic level, urbanization level and agricultural employment significantly promoted the net carbon sink. In contrast, the rural industrial structure, technical level and crop seeding had inhibitory effects. Therefore, it is imperative to promote the reduction of agricultural carbon emissions in the Beijing-Tianjin-Hebei region. This entails accelerating the construction of new agriculture and rural areas, facilitating industrial upgrading, promoting the development of low-carbon-sink regions into high-carbon-sink regions and actively fostering the coordinated and integrated development of regional agriculture.

Spatiotemporal Distribution and Fragmentation Driving Mechanism in Paddy Fields and Dryland of Urban Agglomeration in the Middle Reaches of the Yangtze River

The spatial-temporal distribution pattern of China’s cultivated land has changed dramatically from 1990 to 2020, and the problem of cultivated land fragmentation has become more prominent. However, the existing research lacks a focus on the two specific land use types, paddy fields and dryland. In this study, the spatiotemporal distribution pattern and the fragmentation driving mechanism of paddy field and dryland during the years 1990 to 2020 were identified by using the center of gravity center migration model, standard deviation ellipse, and land-use dynamic model for the urban agglomeration in the middle reaches of the Yangtze River as an example. The results show that there are significant differences in the spatiotemporal distribution characteristics of paddy field and dryland in the MRYRUA. Among the provinces and cities, Hubei province and its Xiangyang city showed the most obvious trend of change. The loss and gain of paddy fields and dryland is related to economic and policy contexts in each period. The main driving factor of paddy field and dryland fragmentation is natural condition, whereas a relatively important factor is the per capita disposable income of rural residents. The effects of each factor on paddy field and dryland fragmentation were not independent; any two factor interactions had a stronger effect on paddy field and dryland fragmentation than a single factor. In general, this study provides guidance and references for the main grain-producing areas undergoing rapid urbanization relating to cultivated land conservation, food security, and sustainable agricultural utilization.

Spatial and temporal urban air pollution patterns based on limited data of monitoring stations

Urban air pollution is one of the serious environmental problems in the development of high-density cities, especially for traffic-related pollution. Effective urban environmental monitoring technologies are helpful to predict and control the air pollution emitted by traffic sectors. However, the complex temporal and spatial characteristics of air pollution in urban areas pose a great challenge for its monitoring, prediction, and control. This work investigated on the spatiotemporal air pollution patterns and its correlation mechanism with urban elements (such as traffic) based on limited data of monitoring stations, which is significant for the accurate prediction and regulation of urban environment. Regional Cluster Monitoring (RCM) methods were proposed through integrating multi-source data, including data from U.S. Geological Survey (USGS) Landsat, OpenStreetMap (OSM) road network, and environmental monitoring stations to categorize different monitoring stations. According to different urban areas (defined as U: ‘urban’ or S: ‘suburban’) and traffic densities (T: ‘traffic’ or B: ‘background’), monitoring stations areas were categorized into U-B, U-T, S-B, and S-T. Then the spatiotemporal characteristics of traffic-related pollutants in different region categories were analyzed. The rapid prediction of air pollution distribution in different categories of urban regions was realized by RCM method-based Long Short-Term Memory (LSTM) neural network. Results showed that the proposed methods could accurately represent the spatiotemporal distribution characteristics of urban air pollution. The mean absolute percentage errors (MAPE) between the predicted results and actual observed values were 20.31% to 28.05% (absolute errors were 3.9-14.3 μg/m³). This work can significantly impact on low-cost & effective monitoring and control strategies for urban area, and further contribute to comprehend the spatial-temporal distribution patterns of urban traffic-related air pollution from limited data of monitoring stations.

Entropy Change of Historical and Cultural Heritage in Traditional Tibetan Area of China Based on Spatial-Temporal Distribution Pattern

The traditional Tibetan area of China is an ethnically and culturally significant region with a historical geographical connection. This study investigates the spatial-temporal distribution patterns and entropy changes of historical and cultural heritage by examining the association between cultural heritage and socio-historical factors. It utilizes analytical methods such as information entropy and incorporates temporal, spatial, and typological information from the data obtained in the Third National Cultural Relics Census. The findings are as follows: (1) The three major regions in the Tibetan area of China alternately serve as development cores for the traditional Tibetan area, exhibiting a fluctuating “dispersion-aggregation” trend of historical and cultural heritage, which also displays notable regional variations. (2) The quantity and entropy change of historical and cultural heritage exhibit correlations between different periods, but there are also some intergenerational differences. (3) The spatial-temporal distribution pattern of historical and cultural heritage demonstrates an inter-era correlation, indicating that socio-historical development is a nonlinear process characterized by both “transition” and “accumulation”. These findings are of significant importance for further understanding the social evolutionary process of human settlements in high-altitude areas and for the comprehensive protection of cultural heritage in ethnic regions.

Spatial-temporal distribution and potential risk of pesticides in ambient air in the North China Plain

The intensive use of pesticides in the North China Plain (NCP) has resulted in widespread contamination of pesticides in the local atmosphere, posing risks to air quality and human health. However, the occurrence and distribution of atmospheric pesticides in the NCP as well as their risk assessment have not been well investigated. In this study, 300 monthly samples were collected using passive air samplers with polyurethane foam at ten rural sites with different crop systems in Quzhou county, the NCP, from June 2021 to May 2022. The pesticides were quantified using mass-spectrometric techniques. Our results revealed that chlorpyrifos, carbendazim, and atrazine were the most frequently found pesticides in the air samples, with detection frequencies of ≥ 87 % across the samples. The average concentrations of atmospheric pesticides during spring (7.47 pg m−3) and summer (16.05 pg m−3) were significantly higher than those during autumn (2.04 pg m−3) and winter (1.71 pg m−3), attributable to the intensified application of pesticides during the warmer seasons. Additionally, cash crop sites exhibited higher concentrations (10.26 pg m−3) of atmospheric pesticides compared to grain crop (5.59 pg m−3) and greenhouse sites (3.81 pg m−3), primarily due to more frequent pesticides spraying events in cash crop fields. These findings indicate a distinct spatial–temporal distribution pattern of atmospheric pesticides influenced by both seasons and crop systems. Furthermore, the model-based inhalation risk assessment indicates that inhalation exposure to atmospheric pesticides is unlikely to pose a significant public concern.

Origin of the Dashuigou Independent Tellurium Deposit at the Southeastern Qinghai-Tibet Plateau: Based on the Abundances of Trace Elements in the Country Rocks

Through a detailed study of the abundances and spatial-temporal distribution patterns of Te, Bi, As, Se, Cu, Pb, Zn, Au, and Ag in the rock types of different geological epochs in the Dashuigou independent tellurium deposit, and in combination with other research findings of previous researchers in this area, the authors conclude as follows: Abundances of the main ore-forming elements Te, Bi, As, Se, Au, and Ag are not high in the regional geological background, generally lower or close to their respective crustal Clark values, but almost all altered country rocks contain high levels of ore-forming elements. This indicates that the deposit’s ore-forming elements do not come from the country rocks. This also indicates that the geological thermal events that cause alteration and mineralization originate from depths and may be related to mantle plumes. Considering the distribution pattern of these ore-forming elements in the ore bodies’ hanging wall and footwall, the metallogenic mechanism may be as follows: Mineralization is not achieved through lateral secretion in the horizontal or near horizontal direction, but rather through the upward movement and emplacement of deep ore-forming elements driven by geological processes such as mantle plumes. In addition, the migration of deep ore-forming elements is not achieved through dispersed infiltration between overlying rock particles, but through non widespread concentrated penetrating channels. This type of channel is likely to be the expansion structures where faults from different directions intersect, or where linear faults intersect with circular structures.

Exploring temperature dynamics in Madhya Pradesh: a spatial-temporal analysis.

Understanding the dynamics of temperature trends is vital for assessing the impacts of climate change on a regional scale. In this context, the present study focuses on Madhya Pradesh state in Central Indian region to explore the spatial-temporal distribution patterns of temperature changes from 1951 to 2021. Gridded temperature data obtained from the Indian Meteorological Department (IMD) in 1° × 1° across the state are utilised to analyse long-term trends and variations in temperature. The Mann-Kendall (MK) test and Sen's slope (SS) estimator were used to detect the trends, and Pettitt's test was utilised for change point detection. The analysis reveals significant warming trends in Madhya Pradesh during the study period during specific time frames. The temperature variables, such as the annual mean temperature (Tmean), maximum temperature (Tmax), and minimum temperature (Tmin), consistently increase, with the most pronounced warming observed during winter. The trend analysis reveals that the rate of warming has increased in the past few years, particularly since the 1990s. However, Pettitt's test points out significant changes in the temperature, with Tmean rising from 25.46 °C in 1951-2004 to 25.78 °C in 2005-2021 (+0.33 °C), Tmax shifting from 45.77 °C in 1951-2010 to 46.24 °C in 2011-2021 (+0.47°C), and Tmin increasing from 2.65 °C in 1951-1999 to 3.19 °C in 2000-2021 (+0.46 °C). These results, along with spatial-temporal distribution maps, shed important light on the alterations and variations in monthly Tmean, Tmax, and Tmin across the area, underlining the dynamic character of climate change and highlighting the demand for methods for adaptation and mitigation.

Bayesian phylodynamic analysis reveals the evolutionary history and the dispersal patterns of citrus tristeza virus in China based on the p25 gene

BackgroundCitrus tristeza virus (CTV) is one of the most serious threats to the citrus industry, and is present in both wild and cultivated citrus. The origin and dispersal patterns of CTV is still poorly understood in China.MethodsIn this study, 524 CTV suspected citrus samples from China were collected, including 354 cultivated citrus samples and 174 wild citrus samples. Finally, 126 CTV coat protein sequences were obtained with time-stamped from 10 citrus origins in China. Bayesian phylodynamic inference were performed for CTV origin and dispersal patterns study in China.ResultWe found that CTV was mainly distributed in southern and coastal areas of China. The substitution rate of CTV was 4.70 × 10− 4 subs/site/year (95% credibility interval: 1.10 × 10− 4 subs/site/year ~ 9.10 × 10− 4 subs/site/year), with a slight increasing trend in CTV populations between 1990 and 2006. The CTV isolates in China shared a most common recent ancestor around 1875 (95% credibility interval: 1676.57 ~ 1961.02). The CTV in China was originated from wild citrus in Hunan and Jiangxi, and then spread from the wild citrus to cultivated citrus in the growing regions of Sichuan, Chongqing, Hubei, Fujian, Zhejiang, Guangxi and Guangdong provinces.ConclusionsThis study has proved that CTV in China was originated from wild citrus in Hunan and Jiangxi. The spatial-temporal distribution and dispersal patterns has uncovered the population and pandemic history of CTV, providing hints toward a better understanding of the spread and origin of CTV in China.

Blue button (Cnidaria: Hydrozoa) distribution and trends in the Mexican Atlantic, based on field surveys and open-access data

Access to digital technology and software allows the production of a significant amount of biodiversity data, including citizens' species records, combined with field monitoring and standardized surveys, which are valuable to biological sciences; these data can help to know the distribution of organisms like medusozoans. We compiled records of the presence of Porpita porpita from open-access databases, scientific articles, and field observations to know their current distribution on the Mexican Atlantic for the first time. The yearly records of P. porpita increased over time, adding up to 22 records, of which 18 were assigned to citizen science. Most records correspond to 2011-2022, from April to May, and the Veracruz and Quintana Roo states. The records of the species in warm months and states with long shores can be related to an increase in touristic activities and observations by citizens. On the Mexican Atlantic, it is suggested that the use of digital technological devices under citizen science practices for recording P. porpita and its compilation in open-access databases acts as the principal method for tracking the distribution of this species. This work evidenced the need for a solid research framework of knowledge for P. porpita in the Mexican Atlantic, and future research could combine citizen science records and fieldwork records and improve the relationship between biological and oceanographic data to understand their spatial-temporal distribution patterns.

Mesoscale habitat use by St. Lawrence estuary beluga over the annual cycle from an acoustic recording network.

The spatial-temporal distribution pattern of St. Lawrence Estuary (SLE) beluga is examined with a passive acoustic monitoring network of 13 stations from June 2018 to October 2021. A beluga calling index, correlated with beluga density, is used as a proxy for habitat use by the population at weekly, monthly, and yearly scales. The seasonal pattern along SLE upstream-downstream axis was repeated annually. In summer, beluga habitat was confined to a 150 km segment of the SLE, with higher occurrences in its ∼20 km central portion, including the head of the Laurentian Channel and Saguenay Fjord mouth. During fall, the distribution gradually shifted to the downstream portion of the SLE and into the Northwestern Gulf, leaving low to no occurrences upstream in winter, until the spring return, characterized by the highest upstream occurrences. Occurrences off Ste. Marguerite Bay, 25 km upstream in Saguenay Fjord, were essentially from June to October. This multi-year continuous habitat use pattern provides a baseline for year-round SLE beluga distribution dynamics for assessing and mitigating anthropogenic threats to this endangered population, such as shipping noise. It also provides insights for optimizing the assessments of population size from aerial line transect surveys.