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Previous research has indicated that some aspects of Chinese culture became more individualistic. However, prior studies have suggested a decrease in individualism in other aspects of China. Thus, it was unclear whether China became more individualistic. Therefore, the current research investigated whether Chinese culture became more individualistic by examining historical changes in family structure. Specifically, I analyzed temporal shifts in the divorce rate and household size, which have been confirmed as valid representative indicators of individualism. Results showed that the divorce rate increased between 1978 and 2017 and household size decreased between 1953 and 2017, indicating a rise in individualism. Moreover, analyses suggested that the one-child policy was unlikely the sole and major factor in the decrease in household size. Additionally, the aggregated score of divorce rate and household size demonstrated a clear increase in individualism. Therefore, the present research provided further evidence of the rise in individualism in China.

Balancing economic growth with environmental protection is vital for the sustainable development of cities and regions. However, urban greening has rarely been considered in extensive studies. This study incorporates urban greening into a coupling coordination degree (CCD) model, in order to evaluate its coordination with economic performance. A total of 286 cities in China between 2005 and 2019 were selected as specific study subjects. Meanwhile, clustering method was used to classify different clusters based on CCD values, the Gini coefficient analysis was applied to discover the CCD values inequality characteristics and the exploratory spatial data analysis (ESDA) method was employed to study the CCD values spatial aggregation features. The results indicate that the CCD values presented significant spatial heterogeneity. Spatially, the CCD values were divided into eight clusters, with those in the eastern region generally being higher than in the central and western regions. Temporally, the CCD in all cities showed an increasing trend, but more than 60% of cities were still in the uncoordinated or low-level coordination stage. In addition, inequality and spatial aggregation characteristics were observed in CCD values, both of which presented decreasing trends. Greening has a stronger influence on the linked and coordinated growth of the two systems; therefore, we propose policy recommendations for pursuing the development of environmentally friendly cities from different aspects. In summary, this research allows for a better understanding of economic and environmental relationships, thus contributing to the objective of creating sustainable cities and communities.

Culling large herbivores can reduce browsing damage. Our objective was to verify the effect of culling by considering spatial changes in browsing damage to test the hypothesis that the benefits of spatially biased culling extend to the spatial scale of culling. Culling sika deer (Cervus nippon) in Kumamoto Prefecture, Japan, increased from 2009–2017, but browsing damage remained stable across the prefecture; regional damage trends differed among grid meshes (i.e., 5 km × 5 km). Meshes with browsing damage reduction received higher culling pressure and a decline in the deer population. Browsing damage reduction from culling was not uniform across regions and was biased by spatial bias in culling. This study highlights the importance of spatial scale in large herbivore management and evaluation of its effect.

The provision of webGIS-based water quality data services has become a priority area for both the public and administrative sectors in the context of the pandemic emergency associated with the global spread of COVID-19. Current geographic, monitoring and decision supporting systems, typically based on web-based geospatial information, greatly facilitate the sharing of spatial and temporal data from environmental databases and real-time analyses. In the present study, different water quality indices are determined, compared and geovisualized, during which the changes in the quality of the shallow groundwater resources of a settlement are examined in the period (2011–2019) in an eastern Hungarian settlement. Another objective of the research is to determine three water quality indices (Water Quality Index, CCME Water Quality Index, Contamination degree) and categorize water samples based on the same input spatial and temporal data using self-developed freely available geovisualization tools. Groundwater quality was assessed by using different water quality indices. Significant pollution of the groundwater in the time period before the installation of a sewage network was shown. Regarding water quality, significant positive changes were shown based on all three water quality indices in the years after installing a sewage network (2015–2019). The presence of pollution apart from the positive changes suggests that the purification processes will last for a long time.

Analysis of temporal dynamics of climatic parameters is indispensable for advancing the “Sustainable Development Goals (SDGs)-11 and 13”. This study aims to assess the trend of temperature and rainfall in Kolkata District using CRU (Climate Research Unit) data from 1901 to 2019. Statistical methods such as anomaly index, CV (“coefficient of variation”), and PCI (“Precipitation Concentration Index”) were employed along with ITA (Innovative trend analysis) techniques, Mann-Kendall test, and Spearman’s Rho tools. These measures are widely used in climate and environmental research to recognize the trend of climate change. The Mann-Kendall and Spearman’s Rho tools both reveal that the seasonal (summer and winter) and yearly temperatures are rising significantly (P

Background: Despite numerous reports about temporal changes in semen quality from all over the world, the debates continue. The latest systemic review has shown an overtime decrease in semen quality worldwide. Objective: To assess the temporal changes in the semen quality among Iranian population referred to an infertility center. Materials and Methods: In this retrospective cross-sectional study, semen parameters including concentration, motility, and morphology were compared between Iranian men reffered to Research and Clinical Center for Infertility, Yazd between 1990 to 1992 (group 1, n = 707) and 2010 to 2012 (group 2, n = 1108). Demographic characteristics and semen analysis were collected from the records. The effect of age on semen parameters was also investigated. Results: Despite the increase in sperm concentration l in group 2, sperm with normal morphology decreased significantly (p < 0.001). Grade-A motility decreased (p < 0.001), grade B motility increased (p < 0.001), and grade C and D motile sperm remained constant (p = 0.303 and p = 0.315, respectively). Also, no significant correlation between the age and semen parameters were observed. Conclusion: This study showed inconsistent temporal changes in the participant semen quality. Significant temporal decline were obtained between various semen parameters, sperm morphology and grade A motility. These results should be further evaluated by larger studies in the future. Key words: Infertility, Semen quality, Temporal changes.

Aim: Changes in climate and land use practices have been found to affect animal populations in different parts of the world. These studies have typically been conducted during the breeding season, whereas the non-breeding season (hereafter 'winter') has received much less attention. Changes in regional winter abundances could be caused by changes in overall population sizes and/or redistribution of populations. We tested these mechanisms for terrestrial winter bird population changes in Northern Europe and explored the role of climate change and species habitat preference. Location: The Netherlands, Denmark, Sweden, Finland. Methods: We used winter bird counts from four countries conducted annually between 15 December and 20 January in 1980/1981–2013/2014. We report national population trends for 50 species for which a trend could be calculated in at least three of the countries. We analysed country-specific population growth rates in relation to species' climatic summer and winter niches, habitat preference and migratory behaviour. Results: Species breeding in colder (typically northern) areas showed more negative winter population trends than species breeding in warmer areas. Regional winter population trends were negatively correlated with characteristics of their winter climatic niche: populations in the colder part of their winter distribution increased in abundance, whereas populations in the warmer part of their winter distribution decreased. Woodland species tended to do better than farmland species. Migratory behaviour did not explain variation in population trends. Main conclusions: The generally decreasing winter population trends of colddwelling breeding species probably reflect the general decline in population sizes of these species. In contrast, increasing winter population trends for populations in the colder parts of the winter distribution indicate a redistribution of wintering individuals towards the north-east. Both these patterns are likely caused by climate change.

Regional land-use change is the leading cause of ecosystem carbon stock change; it is essential to investigate the response of LUCC to carbon stock to achieve the strategic goal of “double carbon” in a region. This paper proposes a residual network algorithm, the Residual Multi-module Fusion Network (R-MFNet), to address the problems of blurred feature boundary information, low classification accuracy, and high noise, which are often encountered in traditional classification methods. The network algorithm uses an R-ASPP module to expand the receptive field of the feature map to extract sufficient and multi-scale target features; it uses the attention mechanism to assign weights to the multi-scale information of each channel and space. It can fully preserve the remote sensing image features extracted by the convolutional layer through the residual connection. Using this classification network method, the classification of three Landsat-TM/OLI images of Zhengzhou City (the capital of Henan Province) from 2001 to 2020 was realized (the years that the three images were taken are 2001, 2009, and 2020). Compared with SVM, 2D-CNN, and deep residual networks (ResNet), the overall accuracy of the test dataset is increased by 10.07%, 3.96%, and 1.33%, respectively. The classification achieved using this method is closer to the real land surface, and its accuracy is higher than that of the finished product data obtained using the traditional classification method, providing high-precision land-use classification data for the subsequent carbon storage estimation research. Based on the land-use classification data and the carbon density data corrected by meteorological data (temperature and precipitation data), the InVEST model is used to analyze the land-use change and its impact on carbon storage in the region. The results showed that, from 2001 to 2020, the carbon stock in the study area showed a downward trend, with a total decrease of 1.48 × 107 t. Over the course of this 19-year period, the farmland area in Zhengzhou decreased by 1101.72 km2, and the built land area increased sharply by 936.16 km2. The area of land transfer accounted for 29.26% of the total area of Zhengzhou City from 2001 to 2009, and 31.20% from 2009 to 2020. The conversion of farmland to built land is the primary type of land transfer and the most important reason for decreasing carbon stock. The research results can provide support, in the form of scientific data, for land-use management decisions and carbon storage function protections in Zhengzhou and other cities around the world undergoing rapid urbanization.

For the first time an international acoustic survey dataset covering three decades was used to investigate the factors shaping the spatial and temporal patterns in the condition of sprat and herring in the Baltic Proper. Generalized additive models showed that the spatial and temporal fluctuations in sprat density have been the main drivers of the spatio-temporal changes of both sprat and herring condition, evidencing intra- and inter-specific density dependence mediated by the size and distribution of the sprat population. Salinity was also an important predictor of herring condition, whereas temperature explained only a minor part of sprat model deviance. Herring density was an additional albeit weak significant predictor for herring condition, evidencing also intra-specific density dependence within the herring population. For both species, condition was high and similar in all areas of the Baltic Proper until the early 1990s, coincident with low sprat densities. Afterwards, a drop in condition occurred and a clear south–north pattern emerged. The drop in condition after the early 1990s was stronger in the northern areas, where sprat population increased the most. We suggest that the increase in sprat density in the northern areas, and the consequent spatial differentiation in clupeid condition, have been triggered by the almost total disappearance of the predator cod from the northern Baltic Proper. This study provides a step forward in understanding clupeid condition in the Baltic Sea, presenting evidence that density-dependent mechanisms also operate at the spatial scale within stock units. This stresses the importance of spatio-temporal considerations in the management of exploited fish.

Land-use classification is fundamental for environmental and water resource evaluation in coastal plain areas. However, comprehensive remote sensing image-based land-use analysis is challenged by the lack of massive remote sensing images and the massive computing power of large-scale server systems. In this paper, the spatial-temporal land-use change characteristics of the Hangzhou Bay area coastal plain are investigated on the Google Earth Engine platform. The proposed model uses a random forest algorithm to assist the land-use classification. The dataset is selected from the year 2009 to 2020 and classified with an average classification accuracy of 89% and Kappa coefficient of 88%. The results show that the land use in the selected region is affected by urbanization, the balance of cultivated land occupation and compensation, construction of economic development zone, and other activities. The investigation also shows that in the past 12 years, land use has changed rapidly, and each land-use type maintains the dynamic balance of occupation and compensation. Although the overall land-use distribution is stable, the information entropy fluctuates at a high level, with an average value of 1.15, and the multi-year average value of equilibrium is as high as 0.83. The driving force of land-use change is analyzed and accounted as demographics and human population dynamics, social-economic development, urbanization, and coupling effects of the above-mentioned factors.