Seasonal Characteristics Research Articles

CAR TRANSPORTATION IN UKRAINE: DOCUMENTATION AND FEATURES OF ACCOUNTING

The article examines approaches to documentation and accounting of road passenger transportation. The main problematic aspects regarding the regulatory and legal regulation of this direction of entrepreneurial activity are considered. One of the issues covered in this article is the lack of generalized regulations on the documentation of primary documents. Systematized seasonal features of providing transport services and maintenance of means of production in proper technical condition. The article examines the difficulty of keeping primary records of the provision of services to trucking companies, in the context of the provision of goods transportation services. The lack of a unified regulatory and legal approach to the requirements for filling out primary documents causes disputes in the accounting processes of the supplier and consumer of ATP services. The next aspect to which attention is drawn is the dispute between the technical necessity of updating the rolling stock and the lack of ways to accelerate the formation of sources of funding for renewal reserves.

Research on water environmental indicators prediction method based on EEMD decomposition with CNN-BiLSTM.

Water resources protection is related to the development of the social economy, and the monitoring and prediction of water environmental indicators have important practical significance. In view of the seasonality, periodicity, uncertainty, and nonlinear characteristics of water quality indicators data, traditional prediction models have poor performance. To address this issue, this paper introduces a hybrid water quality index prediction model based on Ensemble Empirical Mode Decomposition (EEMD), combined with Convolutional Neural Network (CNN) and Bidirectional Long Short-Term Memory Network (BiLSTM). We have conducted out experiments to predict dissolved oxygen based on the water quality monitoring indicators of the Liaohe National Control Sanhongcun Village station in Yichun City. The results show that the model proposed in this paper improves the [Formula: see text] index by 5%, 7% and 5% compared to the suboptimal model in the 4-h, 1-day and 2-day index predictions, respectively.

Improving long-term multivariate time series forecasting with a seasonal-trend decomposition-based 2-dimensional temporal convolution dense network

Improving the accuracy of long-term multivariate time series forecasting is important for practical applications. Various Transformer-based solutions emerging for time series forecasting. Recently, some studies have verified that the most Transformer-based methods are outperformed by simple linear models in long-term multivariate time series forecasting. However, these methods have some limitations in exploring complex interdependencies among various subseries in multivariate time series. They also fall short in leveraging the temporal features of the data sequences effectively, such as seasonality and trends. In this study, we propose a novel seasonal-trend decomposition-based 2-dimensional temporal convolution dense network (STL-2DTCDN) to deal with these issues. We incorporate the seasonal-trend decomposition based on loess (STL) to explore the trend and seasonal features of the original data. Particularly, a 2-dimensional temporal convolution dense network (2DTCDN) is designed to capture complex interdependencies among various time series in multivariate time series. To evaluate our approach, we conduct experiments on six datasets. The results demonstrate that STL-2DTCDN outperforms existing methods in long-term multivariate time series forecasting.

Temporal and Spatial Distribution of Phytoplankton and Role of Environment Factors in the Shending River Backwater in the Danjiangkou Reservoir Area

The Danjiangkou Reservoir supplies drinking water to most residents in northern China. However, signs of eutrophication have been observed in the inlet tributaries of the reservoir, including the Shending River backwater. This research used data from the Sentinel-2 Multispectral instrument and findings from a 2021 aquatic ecological survey to analyze the spatial and temporal characteristics of phytoplankton distribution in the Shending River backwater region. The average chlorophyll a (Chl-a) concentrations by season, ranked from largest to smallest, are as follows: summer (63.96 μg/L) > autumn (41.26 μg/L) > spring (27.47 μg/L) > winter (16.21 μg/L); the upstream of the backwater area and the near-shore tributary bay had relatively higher Chl-a concentration. Bacillariophyceae (Cyclotella meneghiniana and Synedra sp.) and Cryptophyceae species (Chroomonas acuta) were dominant in spring, whereas Chlorophyceae (Scenedesmus sp. and Chlorella vulgaris) and Cyanophyceae (Dactylococcopsis acicularis, Microcystis aeruginosa and Oscillatoria tenuis) species were dominant in summer. The seasonal succession characteristics of the phytoplankton community were consistent with those of the Plankton Ecology Group model. The average phytoplankton cell density was 4.80 × 107 cells/L, and the Shannon–Wiener average diversity index was 1.95, indicating that the Shending River backwater area was moderately eutrophic. According to Pearson correlation analysis and Mantel test, the main factors causing temporal and spatial differences in phytoplankton production in the Shending River’s backwater were water level (WL), water temperature (WT), ammonia nitrogen (NH3-N) and total nitrogen (TN). In particular, WL was significantly positively correlated with Bacillariophyceae, Chlorophyceae and Cyanophyceae, whereas WT was significantly correlated with Cryptophyceae and Chlorophyceae. NH3-N and TN were significantly correlated with Cyanophyceae. Therefore, intensive nitrogen removal from the tailwater of sewage treatment plants may be considered a feasible measure to prevent cyanobacterial bloom in the Shending River backwater of the Danjiangkou Reservoir.

Effects of Season, Habitat, and Host Characteristics on Ectoparasites of Wild Rodents in a Mosaic Rural Landscape.

Despite the large number of studies on rodent ectoparasites-most of them vectors of epidemiologically important pathogens-infestation patterns remain poorly understood in various ecological contexts, such as the highly patchy agricultural landscapes. We aimed to relate the infestation of rodents to temporal, habitat, and host variables. We assessed the difference in parasite prevalence and mean abundance depending on host sex, age, and body weight, season, and land use intensity. Furthermore, we analysed the effect of host species abundance and the differential responses of parasites in main and minor host species. The field survey was conducted in a rural landscape in southern Transylvania (Romania) between June and September 2010-2011. We live-trapped small mammals, collected the ticks and fleas, and recorded the presence of lice and mites. Overall, we found the same infestation patterns largely reported in the literature: higher prevalence and mean abundance in heavier adult males, significant seasonality and differences among host species, and evidence of the dilution effect. The uniqueness of our study system was the negative effect of the land use intensity on the prevalence and mean abundance of parasites, explained by the highly patchy mosaic landscape.

Seasonal characteristics of groundwater discharge controlled by precipitation and its environmental effects in a coal mining subsidence lake, eastern China

Many regions have formed subsidence lakes due to underground mining in the world. However, seasonal variations of lacustrine groundwater discharge (LGD) rate and solute fluxes in the coal mining subsidence were rarely reported. In this study, we conducted four seasonal samplings in a coal mining subsidence, during which samples for stable water (δ18O) and radioactive (222Rn) isotopes were collected to quantify the seasonal dynamics of LGD rates. The LGD rates estimated from the 222Rn mass balance model were 10.2 ± 8.7, 5.5 ± 3.2, 11.5 ± 7.8, and 7.8 ± 4.5 mm d−1 in summer, autumn, winter and spring, respectively. According to the 18O mass balance model, the corresponding LGD rates were 15.1, 7.3, 15.6, and 11.3 mm d−1 in summer, autumn, winter and spring, respectively. We found a significant correlation between precipitation and LGD rates, suggesting precipitation was recognized as the main control factor for seasonal variations of LGD rates. Based on this correlation, the extrapolated LGD rates over a year ranged from 3.1 to 12.7 mm d−1 with an average of 8.8 mm d−1. Moreover, the fluxes of dissolved silicon (DSi), iron (Fe), and manganese (Mn) from LGD in autumn were (1.6 ± 0.9) × 105, (1.9 ± 1.1) × 104, and (1.1 ± 0.6) × 104 mol a−1, respectively. Correspondingly, in winter they were (3.5 ± 2.4) × 105, (4.1 ± 2.8) × 103, and (2.8 ± 1.9) × 103 mol a−1, respectively. This study demonstrated significantly seasonal variations of LGD, with precipitation being the main control factor of LGD in the coal mining subsidence lake. The fluxes of dissolved substance (DSi, Fe, Mn) from LGD need to be emphasized because they may have important impacts on the ecological stability in coal mining subsidence lakes.

Nitrate leaching characteristics of red soils from different parent materials in subtropical China

Globally, nitrate (NO3−) leaching from agroecosystems has been of major concern. There is evidence that NO3− leaching exhibits intense seasonal variation in subtropical regions. However, influencing factors to the seasonal dynamics remain unclear. In this study, a two-year field lysimeters experiment was conducted with three red soils derived from different parent materials (Quaternary red clay (QR), red sandstone (RS), and basalt (BA)). An N fertilizer (15N-enriched urea, 10 atom% excess) of 200 kg N ha−1 yr−1 was applied for maize. The effect of parent material on NO3− leaching characteristics was examined in surface (0–20 cm) and subsoil (20–100 cm) layers. The results showed due to the weakening of abundant drainage, there was no significant effect of parent materials on NO3− leaching characteristics in surface layers. Environmental factors (precipitation and temperature) and fertilization together led to obvious seasonal characteristics, i.e. abundant NO3− leaching during both crop growth and fallow periods. In subsoil layers, NO3− leaching characteristics were completely different among three soils. The concentrations and δ15N of NO3− in QR and RS soils showed a continuous increase after first year's fertilization, while those in BA soil remained relatively stable after reaching peak levels around harvest in first year. Meanwhile, the NO3− leaching amount in BA soil was significantly lower than in the other two soils. These might be explained by different NO3− adsorption capacities caused by the differences in mineral composition and free iron and aluminium contents. These elucidated in subsoil layers, NO3− leaching characteristics highly depended on parent materials. Meanwhile, adsorption capacity was limited and cannot slow NO3− leaching in the long run. Our results suggest that seasonal variation of NO3− leaching in surface layers and temporary retardant effect from NO3− adsorption capacity in subsoil layers should receive much attention when calculating and predicting NO3− leaching in subtropical regions.

Water vapour exchange between the atmospheric boundary layer and free troposphere over eastern China: seasonal characteristics and the El Niño–Southern Oscillation anomaly

Abstract. This study develops a quantitative climatology of water vapour exchange between the atmospheric boundary layer (ABL) and free troposphere (FT) over eastern China. The exchange flux is estimated for January, April, July and October over 7 years based on a water vapour budget equation using simulated meteorological data. The spatiotemporal characteristics and occurrence mechanism of ABL–FT water vapour exchange and its relationship with the El Niño–Southern Oscillation (ENSO) are revealed: (1) the vertical exchange flux varies regionally and seasonally, with downward transport to maintain ABL moisture during winter and autumn in the northern region and persistent output to humidify the FT in the southern region, particularly in summer. Additionally, the vertical exchange flux is also topographic dependent. (2) The vertical motion at the ABL top, which is produced by the dynamic forcing of the terrain on synoptic winds, is the dominant mechanism for the water vapour vertical exchange over the long-term average. The evolution of the vertical exchange flux within 1 d scale is driven by the ABL diurnal cycle. (3) The interannual variation of water vapour vertical exchange is correlated with ENSO. A triple antiphase distribution with negative–positive–negative anomalies from north to south exists in La Niña years (and vice versa in El Niño years), which corresponds to the spatial pattern of anomalous precipitation. This phenomenon is mainly due to the alteration of vertical velocity and water vapour content at the ABL top varying with ENSO phases. These results provide new insight into understanding the atmospheric water cycle.

Responses of microbial communities subjected to hydrodynamically induced disturbances in an organic contaminated site

Organic contaminated sites have gained significant attention as a prominent contributor to shallow groundwater contamination. However, limited knowledge exists regarding the impact of hydrodynamic effects on microbially mediated contaminant degradation at such sites. In this study, we investigated the distribution characteristics and community structure of prokaryotic microorganisms at the selected site during both wet and dry seasons, with a particular focus on their environmental adaptations. The results revealed significant seasonal variations (P < 0.05) in the α-diversity of prokaryotes within groundwater. The dry season showed more exclusive OTUs than the wet season. The response of prokaryotic metabolism to organic pollution pressure in different seasons was explored by PICRUSt2, and enzymes associated with the degradation of organic pollutants were identified based on the predicted functions. The results showed that hormesis was considered as an adaptive response of microbial communities under pollution stress. In addition, structural equation models demonstrated that groundwater level fluctuations can, directly and indirectly, affect the abundance and diversity of prokaryotes through other factors such as oxidation reduction potential (ORP), dissolved oxygen (DO), and naphthalene (Nap). Overall, our findings imply that the taxonomic composition and functional properties of prokaryotes in groundwater in organic contaminated sites is influenced by the interaction between seasonal variations and characteristics of organic pollution. The results provide new insights into microbiological processes in groundwater systems in organic contaminated sites.

Factors Influencing the Variation in Phytoplankton Functional Groups in Fuchunjiang Reservoir

To explore the distribution characteristics, blooming risk mechanism and driving factors of phytoplankton community structure in Fuchunjiang Reservoir. The variation characteristics of phytoplankton, zooplankton and physicochemical indicators in Fuchunjiang Reservoir and its upper and lower reaches were investigated in 2020 and 2021. Based on the phytoplankton functional groups, non-metric multidimensional scale analysis, redundancy analysis and other statistical methods, the seasonal succession characteristics and driving factors of phytoplankton functional groups were analyzed. A total of 18 phytoplankton functional groups were identified, in of which 10 were predominant. The composition of phytoplankton functional groups in the Fuchunjiang Reservoir was significant different. Spatially, the upstream were dominated by group C and P while the represent species were Cyclotella and Aulacoseira,reflecting the mixed meso-eutrophic environments. However, group P was the main group in Fuchunjiang reservoir, and the dominance decreased gradually along the stream direction. Meanwhile, in the downstream, MP has an absolute advantage at Qiantang River estuary. It reflected the environmental characteristics of frequent disturbance and high turbidity of tide-sensing rivers. In addition, the predominant functional groups demonstrated strong seasonal variations. The dominant functional groups were diverse in summer and consisted of P+L0+J+M+S1+H1+MP. In addition to group P (Aulacoseira), which was dominant throughout the year, it also included several groups represented by cyanobacteria and chlorophyta, reflecting the environmental characteristics of changeable habitats and vigorous productivity. In autumn, the succession was dominated by H1 group represented by Dolichospermum and the representative function groups were P and H1, reflecting the hydrological background of reduced flow and static flow. In winter, the increase of Cyclotella led to the predominance of group C, which was dominated by P+C, reflecting the changing conditions of weakened water exchange and intensified eutrophication problems. In spring, the dominant functional groups were gradually enriched and were composed of C, D, P, and MP, which also reflected the changing environmental habitat characteristics which caused by increasing rainfall and air temperature. According to the results of the C-R-S growth strategy, the Fuchunjiang Reservoir has been in the R strategy for a long time, which was consistent with the habitat characteristics of Fuchunjiang Reservoir and its upper and lower reaches with high disturbance and low stress. In addition, C strategy and S strategy appeared in some reaches, reflecting the variability of water quality and hydrology. RDA analysis showed that water temperature, discharge, zooplankton biomass, permanganate index, total nitrogen and total phosphorus were significantly correlated with the seasonal succession of phytoplankton functional groups (P &lt; 0.05), and temperature and flow pattern were probably the most critical factors for the succession. Studies have shown that the impact of hydrometeorological processes on phytoplankton in the Fuchunjiang Reservoir is crucial:high temperature and changing discharge during the summer may lead to cyanobacterial blooms in the Fuchunjiang reservoir; To reduce the risk of algal blooms, it is still necessary to increase the control of nitrogen and phosphorus load in rivers, and fully consider the coordination of water conservancy dispatch methods.

Crop classification in South Korea for multitemporal PlanetScope imagery using SFC-DenseNet-AM

In this manuscript, a new methodology based on a deep learning model using a Siamese network and attention module was proposed to classify crop cultivation areas, such as onion and garlic, from multitemporal PlanetScope images in South Korea. To consider the seasonal characteristics of crops in the model, training data were constructed from multitemporal satellite images. It was generated using PlanetScope satellite imagery from January and April, corresponding to the seasonal growth period of onion and garlic, in South Korea. Image patches were generated by considering the ratio of crops to minimize the influence of imbalanced data in the training process. Siamese FC-DenseNet with an attention module model (SFC-DenseNet-AM) is proposed, and the attention module is used to classify cultivated crop areas. Based on the proposed network, we extract cultivated crop areas using preliminary cultivation information. The results of the experiment using PlanetScope images indicate that image classification for cultivated areas was effectively performed using the proposed deep learning model. The model's performance, with F1-scores of 0.823 (garlic) and 0.774 (onion), was verified through an ablation study.

On the use of routine airborne observations for evaluation and monitoring of satellite observations of thermodynamic profiles

Abstract. Satellite-based observations require independent sources of data to monitor and evaluate their precision and accuracy. For the temperature and water vapor profiles produced by satellite-based sounders, this typically results in comparisons to operational radiosonde observations. However, polar-orbiting satellite overpasses are frequently misaligned with the global synoptic launch times. The routine airborne in situ observations of temperature and water vapor from the Airborne Meteorological Data Relay (AMDAR) program and the Water Vapor Sensing System-II (WVSS-II) instrument greatly enhance opportunities to make precise matchups due to the far greater temporal frequency and spatial density of aircraft flights. The potential for the use of aircraft-based observations as a source of evaluation of tropospheric satellite sounder profiles is explored through a year-long intercomparison with the Infrared Atmospheric Sounding Interferometer (IASI) level-2 profiles produced from both the Metop-A and Metop-B satellites. Results using 1 h and 50 km match criteria indicating good agreement between the satellites and the aircraft-based observations with temperature, specific humidity, and relative humidity biases generally less than 0.5 K, 0.8 g kg−1, and 5 %, respectively; both IASI instruments perform nearly identically. While the intercomparisons are generally limited to the troposphere as aircraft typically reach their maximum height at the tropopause, the substantially larger number of intercomparison points enable characterization as a function of season, scan angle, and other characteristics heretofore unexplored due to a lack of sufficient validation data.

Urban-rural differences in seasonal malaria chemoprevention coverage and characteristics of target populations in nine states of Nigeria: a comparative cross-sectional study.

Differences between urban and rural contexts in terms of sociodemographic characteristics, geographical features and risk perceptions may lead to disparities in coverage and related outcomes of community-based preventive interventions, such as seasonal malaria chemoprevention (SMC). This study investigated urban-rural differences in SMC coverage and other programme outcomes, as well as child and caregiver characteristics of target populations in nine implementing states in Nigeria during the 2022 SMC round. This is a comparative cross-sectional study based on comprehensive end-of-round household surveys conducted in nine states where SMC was delivered in Nigeria in 2022. Data of 11,880 caregiver-child pairs were included in the analysis. Rural-urban differences in SMC outcomes and child and caregiver characteristics were assessed, first by using Pearsons' chi-square test for independence for categorical variables. Univariate multilevel mixed-effect logistic regression models, with random intercepts for cluster units, were used to quantify the strength of association between location and each SMC coverage and related outcomes. Significant urban-rural differences were observed in caregivers' sociodemographic characteristics, such as age, gender, level of education, occupation status and health-seeking behaviour for febrile childhood illnesses. Disparities were also seen in terms of SMC coverage and related outcomes, with lower odds of the receipt of Day 1 dose direct observation of the administration of Day 1 dose by community distributors, receipt of the full three-day course of SMC medicines and receipt of SMC in all cycles of the annual round among children residing in urban areas, compared with those residing in rural areas. Similarly, urban-dwelling caregivers had lower odds of being knowledgeable of SMC and believing in the protective effect of SMC than rural-dwelling caregivers. Findings highlight observable urban-rural disparities in SMC programme delivery and related outcomes, as well as target population characteristics, underscoring the need for context-specific strategies to ensure optimal delivery of SMC and improve programme implementation outcomes in urban settings.

Ultra-short-term forecasting model of power load based on fusion of power spectral density and Morlet wavelet.

An accurate ultra-short-term time series prediction of a power load is an important guarantee for power dispatching and the safe operation of power systems. Problems of the current ultra-short-term time series prediction algorithms include low prediction accuracy, difficulty capturing the local mutation features, poor stability, and others. From the perspective of series decomposition, a multi-scale sequence decomposition model (TFDNet) based on power spectral density and the Morlet wavelet transform is proposed that combines the multidimensional correlation feature fusion strategy in the time and frequency domains. By introducing the time-frequency energy selection module, the "prior knowledge" guidance module, and the sequence denoising decomposition module, the model not only effectively delineates the global trend and local seasonal features, completes the in-depth information mining of the smooth trend and fluctuating seasonal features, but more importantly, realizes the accurate capture of the local mutation seasonal features. Finally, on the premise of improving the forecasting accuracy, single-point load forecasting and quantile probabilistic load forecasting for ultra-short-term load forecasting are realized. Through the experiments conducted on three public datasets and one private dataset, the TFDNet model reduces the mean square error (MSE) and mean absolute error (MAE) by 19.80 and 11.20% on average, respectively, as compared with the benchmark method. These results indicate the potential applications of the TFDNet model.

Analysis of total nitrogen pollution load and identification of key pollution sources in Futuan River basin based on SWAT model

In order to identify the key source area of the Futuan River basin, the Futuan River basin is taken as the target area, establishes the Soil Water Assessment Tool (SWAT) model, simules the runoff and total nitrogen pollution process in the basin, and analyzes the spatiotemporal characteristics of total nitrogen pollution. The key source areas of total nitrogen pollution in the basin were identified by the cumulative load curve method. The results show that the total nitrogen pollution load in the Futuan River basin presents obvious seasonal distribution characteristics. The subbasins with high load intensity of total nitrogen into the river are mainly in the middle and upper reaches of the Futuan River.

Spatial and Temporal Variation of Satellite-Derived Chlorophyll-a in Bohai Sea over the Past 20 Years

The Chlorophyll-a (Chl-a) concentration in the surface layer of the Bohai Sea from 2003 to 2022 was obtained after processing the MODIS data with the improved shortwave infrared (SWIR) atmospheric correction algorithm and the Clack three-channel method. Its spatial and temporal variation were analyzed. The results show that it has obvious interannual spatial distribution characteristics, showing a trend of being high in nearshore waters and low in offshore waters, high in the estuarine bays and low in other sea areas. The interannual Chl-a variation shows an inverted U-shape. The year-by-year seasonal average spatial characteristics are basically consistent, with high in nearshore waters and low in other waters. The Chl-a in spring and summer was higher than that in autumn and winter. The temporal trend of the four seasons was similar to the interannual trend, showing an inverted U-shaped trend of first increasing, then stabilizing and then decreasing.

Seasonal and Genetic Characteristics of Human Metapneumovirus Circulating — Henan Province, China, 2017–2023

Seasonal and Genetic Characteristics of Human Metapneumovirus Circulating — Henan Province, China, 2017–2023

Epidemiological Characteristics and Trends of Scarlet Fever in Zhejiang Province of China: Population-Based Surveillance during 2004-2022.

Over the past two decades, scarlet fever has resurged in some countries or areas. Nationwide nonpharmaceutical interventions changed the patterns of other infectious diseases, but its effects on the spread of scarlet fever were rarely studied. This study aimed to evaluate the changes in scarlet fever incidence in Zhejiang Province, China, before and during the COVID-19 pandemic periods and to provide references for scarlet fever prevention and control. Scarlet fever surveillance data in Zhejiang, China (2004-2022), were analyzed in three stages. Two-sample z test, ANOVA, and Tukey's test were used to compare and analyze the characteristics of disease spread at different stages. The ARIMA model was used to predict the overall trend. The data were obtained from the National Infectious Disease Reporting Information System. A total of 28,652 cases of scarlet fever were reported across Zhejiang Province during the study period, with the lowest average monthly incidences in 2020 (0.111/100,000). The predominant areas affected were the northern and central regions of Zhejiang, and all regions of Zhejiang experienced a decrease in incidence in 2020. The steepest decline in incidence in 2020 was found in children aged 0-4 years (67.3% decrease from 23.8/100,000 to 7.8/100,000). The seasonal pattern changed, with peak occurrences in April to June and November to January during 2004-2019 and 2021 and a peak in January in 2020. The median duration from diagnosis to confirmation was highest before COVID-19 (4 days); however, it decreased to 1 day in 2020-2022, matching the other two medians. In 2020, Zhejiang experienced an unprecedented decrease in scarlet fever, with the lowest incidence in nearly 18 years, but it rebounded in 2021 and 2022. The seasonal epidemiologic characteristics of scarlet fever also changed with the COVID-19 outbreaks. This suggested that nationwide nonpharmaceutical interventions greatly depressed the spread of scarlet fever. With the relaxation of non-pharmaceutical intervention restrictions, scarlet fever may reappear. Government policymakers should prioritize the control of future scarlet fever outbreaks for public health.

Exploring the effects of methodological choices on the estimation and biological interpretation of life history parameters for harbour porpoises in Norway and beyond.

This study investigates effects of subtle methodological choices on the estimation and biological interpretation of age, growth and reproductive parameters for harbour porpoises. The core analyses are based on a focal Norwegian data set built on samples from 134 harbour porpoises caught incidentally in gillnet fisheries along the Norwegian coast during autumn 2016 and spring 2017. Two contrasting practices for interpretation of seasonal and ontogenetic characteristics of tooth growth layer formation resulted in significant age differences among spring samples of young porpoises and for older animals across seasons. In turn, these differences affected estimates of age at maturity and asymptotic lengths, respectively. We also found significant differences in male age at maturity between two well-documented maturity criteria and between mathematical estimators of age at maturity for both sexes. Two different criteria for corpus albicans classification furthermore resulted in different patterns of ovarian corpora accumulation, which may affect some estimates of fecundity rates and contaminant loads. Both corpora accumulation patterns were also found in reanalysed data from German and Greenlandic porpoises. Based on tabulated overviews of methodological choices made in previous harbour porpoise studies, we argue that several of the issues mentioned above have wider relevance and may affect the validity of meta-analyses as a tool for estimating harbour porpoise sensitivity to extrinsic pressures. Differences in cause of death (COD) composition between data sets can have a similar effect. We demonstrate this in a meta-analysis of published harbour porpoise pregnancy rates, showing significantly higher values for trauma-killed samples compared to samples comprising mixed COD categories. COD also affected the estimated impacts of three previously analysed extrinsic predictors as well as an added predictor for vessel noise levels. We discuss the potential contributions of methodological, biological and anthropogenic factors in shaping observed regional differences in estimates of harbour porpoise life history parameters.

Estimation of scrub typhus incidence and spatiotemporal multicomponent characteristics from 2016 to 2023 in Zhejiang Province, China.

China is one of the main epidemic areas of scrub typhus, and Zhejiang Province, which is located in the coastal area of southeastern China, is considered a key region of scrub typhus. However, there may be significant bias in the number of reported cases of scrub typhus, to the extent that its epidemiological patterns are not clearly understood. The purpose of this study was to estimate the possible incidence of scrub typhus and to identify the main driving components affecting the occurrence of scrub typhus at the county level. Data on patients with scrub typhus diagnosed at medical institutions between January 2016 and December 2023 were collected from the China Disease Control and Prevention Information System (CDCPIS). The kriging interpolation method was used to estimate the possible incidence of scrub typhus. Additionally, a multivariate time series model was applied to identify the main driving components affecting the occurrence of scrub typhus in different regions. From January 2016 to September 2023, 2,678 cases of scrub typhus were reported in Zhejiang Province, including 1 case of reported death, with an overall case fatality rate of 0.04%. The seasonal characteristics of scrub typhus in Zhejiang Province followed an annual single peak model, and the months of peak onset in different cities were different. The estimated area with case occurrence was relatively wider. There were 41 counties in Zhejiang Province with an annual reported case count of less than 1, while from the estimated annual incidence, the number of counties with less than 1 case decreased to 21. The average annual number of cases in most regions fluctuated between 0 and 15. The numbers of cases in the central urban area of Hangzhou city, Jiaxin city and Huzhou city did not exceed 5. The estimated random effect variance parameters , , and were 0.48, 1.03 and 3.48, respectively. The endemic component values of the top 10 counties were Shuichang, Cangnan, Chun'an, Xinchang, Pingyang, Xianju, Longquan, Dongyang, Yueqing and Qingyuan. The spatiotemporal component values of the top 10 counties were Pujiang, Anji, Pan'an, Dongyang, Jinyun, Ninghai, Yongjia, Xiaoshan, Yinwu and Shengzhou. The autoregressive component values of the top 10 counties were Lin'an, Cangnan, Chun'an, Yiwu, Pujiang, Longquan, Xinchang, Luqiao, Sanmen and Fuyang. The estimated incidence was higher than the current reported number of cases, and the possible impact area of the epidemic was also wider than the areas with reported cases. The main driving factors of the scrub typhus epidemic in Zhejiang included endemic components such as natural factors, but there was significant heterogeneity in the composition of driving factors in different regions. Some regions were driven by spatiotemporal spread across regions, and the time autoregressive effect in individual regions could not be ignored. These results that monitoring of cases, vectors, and pathogens of scrub typhus should be strengthened. Furthermore, each region should take targeted prevention and control measures based on the main driving factors of the local epidemic to improve the accuracy of prevention and control.