Spatial versus spatio-temporal approaches for studying metacommunities: a multi-taxon analysis in Mediterranean and tropical temporary ponds

Prior research on metacommunities has largely focused on snapshot surveys, often overlooking temporal dynamics. In this study, our aim was to compare the insights obtained from metacommunity analyses based on a spatial approach repeated over time, with a spatio-temporal approach that consolidates all data into a single model. We empirically assessed the influence of temporal variation in the environment and spatial connectivity on the structure of metacommunities in tropical and Mediterranean temporary ponds. Employing a standardized methodology across both regions, we surveyed multiple freshwater taxa in three time periods within the same hydrological year from multiple temporary ponds in each region. To evaluate how environmental, spatial and temporal influences vary between the two approaches, we used nonlinear variation partitioning analyses based on generalized additive models. Overall, this study underscores the importance of adopting spatio-temporal analytics to better understand the processes shaping metacommunities. While the spatial approach suggested that environmental factors had a greater influence, our spatio-temporal analysis revealed that spatial connectivity was the primary driver influencing metacommunity structure in both regions. Temporal effects were equally important as environmental effects, suggesting a significant role of ecological succession in metacommunity structure.

[Change and Prediction of Water Purification Function in the South Bank of Hangzhou Bay in the Past 20 Years]

The investigation of regional water purification functionality and its influencing factors holds significant pragmatic implications in understanding the potential of regional water purification, guiding context-specific regional comprehensive planning schemes, and environmental conservation measures. The study site, situated along the southern coast of Hangzhou Bay, represents a prototypical region characterized by intricate land-sea interactions that bear substantial economic and ecological functions. By assimilating a meticulously collected topographical and land-use dataset, in conjunction with site-specific meteorological records, the water purification model embedded within the integrated valuation of ecosystem services and trade-offs (InVEST) framework was employed to scrutinize the spatiotemporal dynamics of nitrogen (N) and phosphorus (P) loads, discharges, and removals within the southern coast of Hangzhou Bay. The prime objective of this study was to unravel the differentials in water purification functionality under diverse developmental scenarios. The investigation unearthed distinct temporal discrepancies in N and P discharges and removals over two temporal dimensions. Relative to the benchmark year 2000, the total N load experienced a reduction of 276.72 t, whereas the N discharge and removals decreased by 140.86 and 137.86 t, respectively, in the year 2020. In contrast, the total P load observed an increase of 93.65 t, accompanied by a surge in P discharge and removals by 28.91 and 64.74 t, respectively. Spatially, the distribution pattern of N and P discharges exhibited a general inclination of elevated values in the northern region and subdued values in the southern region, with certain pockets in the southern region exhibiting pronounced peaks, intimately associated with land-use typologies. Simulation analyses conducted under distinct scenarios unveiled that under the natural development priority scenario, the N and P discharges within the study area amounted to 1 682.36 and 115.50 t, respectively. Conversely, under the scenario emphasizing economic development, the regional N and P discharges showed an approximate escalation of 83.02% and 79.93%, correspondingly. In contrast, under the scenario emphasizing environmental conservation, the regional N and P discharges exhibited a notable decline of approximately 79.96% and 56.44%, respectively. Hence, the scenario prioritizing the amalgamation of environmental conservation and development effectively reduced the N and P discharges within the region, bolstering the water purification functionality. The results derived from this study furnish a solid theoretical foundation for effectuating region-specific planning schemes fostering coordinated economic and ecological advancement within the study area.

[Spatio-temporal Variation in Net Primary Productivity of Different Vegetation Types and Its Influencing Factors Exploration in Southwest China]

Studying the spatiotemporal variation in vegetation net primary productivity (NPP) and exploring its influencing factors are of considerable practical significance for understanding the spatiotemporal variation in vegetation and for guiding ecological restoration and management projects based on local conditions. Based on MODIS NPP data, combined with in situ meteorological data, land use data, and vegetation type data, this study explores the spatiotemporal variation in different types of vegetation NPP in southwest China via the Mann-Kendall significance test and Theil-Sen Median slope estimator. It reveals the influencing factors of spatial differentiation of different types of vegetation NPP and the interaction between influencing factors in combination with stability analysis and Geo Detectors. The results revealed that on the temporal scale, from 2000 to 2021, vegetation NPP, NPPPre (vegetation NPP exclusively under the influence of climate change), and NPPRes (vegetation NPP exclusively under the influence of human activities) in southwest China showed a fluctuating upward trend. Among different vegetation types, NPP, NPPPre, and NPPRes exhibited an upward trend, except for a minor decline in NPPRes of tree vegetation at a rate of -0.183 g·(m2·a)-1. Among them, NPP, NPPPre, and NPPRes of economic vegetation showed the most significant upward rates, 5.96, 3.09, and 2.94 g·(m2·a)-1, respectively. On the spatial scale, the tree vegetation NPP with the most significant downward trend was mainly distributed in Tibet and southern Yunnan, while the economic vegetation NPP with the highest upward trend was primarily distributed in eastern Sichuan Province. The stability of vegetation NPP in southwest China presented a spatial distribution pattern of "low in the south and high in the north," and the average value of the correlation coefficient increased in the ascending order of arbor vegetation (0.101), shrub vegetation (0.105), herb vegetation (0.110), and economic vegetation (0.114). The interaction between surface temperature and relative humidity was the main influencing factor for spatial differentiation of vegetation NPP, while the interaction between sunshine duration and warmth index had the most significant impact on vegetation in southwest China, with an increasing percentage of 30.91%. Different types of vegetation had different requirements for different climatic factors, but their requirements for surface temperature and warmth index were significantly consistent. When the surface temperature was 21.03-28.49℃, and the warmth index was 106.46-167.2, the NPP of different vegetation types peaked. Under natural succession, the impact of climate change on vegetation was inversely proportional to the stability of the vegetation community. The arbor vegetation community with high stability was less affected, while the herb vegetation community with low stability was highly affected by climate. In contrast, the stability of economic vegetation was directly proportional to the impact of climate due to the influence of human activities. This study establishes a theoretical foundation for evaluating the impact of regional climate on the growth of different vegetation types and can be crucial for formulating ecological restoration and management strategies in southwest China that are adapted to the local conditions.

[Spatio-temporal Variations in PM2.5and Its Influencing Factors in the Yangtze River Delta Urban Agglomeration]

To coordinate the contradiction between economic development and environmental pollution and achieve the sustainable development of the economy and society, the spatio-temporal variations in PM2.5 were analyzed based on PM2.5 concentration and meteorological data of the Yangtze River Delta (YRD) urban agglomeration. Wavelet transform coherence (WTC), partial wavelet coherence (PWC), and multiple wavelet coherence (MWC) were used to analyze the multi-scale coupling oscillation between PM2.5 and meteorological factors in the time-frequency domain. The results showed that:① the concentration of PM2.5 in the YRD decreased from northwest to southeast, and the spatial range with high PM2.5 concentration decreased annually. The spatial distribution characteristics of the seasonal average PM2.5 concentration were similar to those of the annual average PM2.5 concentration. PM2.5 concentration exhibited the seasonal variation characteristics of high in winter, low in summer, and transitioning between spring and autumn. ② PM2.5 concentration decreased from 2015 to 2021, and the compliance rate increased. The difference in annual average PM2.5 concentration was decreased with dynamic convergence characteristics. The convergence of PM2.5 concentration in summer was greater than that in winter. During the whole study period, the daily average PM2.5 concentration showed a "U" distribution, and the proportion of days with excellent and good PM2.5 levels were 49.72% and 41.45%, respectively. ③ The wavelet coherence between PM2.5 and meteorological factors was different in different time-frequency domains. The main factors affecting PM2.5 were different in different time-frequency scales. At all time-frequency scales, WTC and PWC showed that wind speed and temperature were the best explanatory variables of PM2.5 variation, respectively. ④ The larger the time-frequency scale, the stronger the interaction of multi-factor combinations to explain PM2.5 variations. The synergistic effect of temperature and wind speed could better explain the variation in PM2.5. These results can provide reference for air pollution control in the YRD.

Characterizing the Spatio-Temporal Variations of Urban Growth with Multifractal Spectra

Urban morphology exhibits fractal characteristics, which can be described by multifractal scaling. Multifractal parameters under positive moment orders primarily capture information about central areas characterized by relatively stable growth, while those under negative moment orders mainly reflect information about marginal areas that experience more active growth. However, effectively utilizing multifractal spectra to uncover the spatio-temporal variations of urban growth remains a challenge. To addresses this issue, this paper proposes a multifractal measurement by combining theoretical principles and empirical analysis. To capture the difference between growth stability in central areas and growth activity in marginal areas, an index based on generalized correlation dimension Dq is defined. This index takes the growth rate of Dq at extreme negative moment order as the numerator and that at extreme positive moment order as the denominator. During the stable stage of urban growth, the index demonstrates a consistent pattern over time, while during the active stage, the index may exhibit abnormal fluctuations or even jumps. This indicates that the index can reveal spatio-temporal information about urban evolution that cannot be directly observed through multifractal spectra alone. By integrating this index with multifractal spectra, we can more comprehensively characterize the evolutionary characteristics of urban spatial structure.

[Spatio-temporal Variation in PM2.5 Concentration and Its Relationship with Vegetation Landscape Patterns in Typical Economic Zones in China from 2000 to 2020]

This study explored the temporal and spatial variation in PM_2.5 concentration and its relationship with the vegetation landscape pattern in three typical economic zones in China, which is of great significance for regional PM_2.5pollution control and atmospheric environmental protection. In this study, the pixel binary model, Getis-Ord G_i^* analysis, Theil-Sen Median analysis, Mann-Kendall significance test, Pearson correlation analysis, and multiple correlation analysis were used to explore the spatial cluster and spatio-temporal variation in PM_2.5 and its correlation with the vegetation landscape index in the three economic zones of China on the basis of PM_2.5 concentration data and MODIS NDVI data set. The results showed that PM_2.5 in the Bohai Economic Rim was mainly dominated by the expansion of hot spots and the reduction in cold spots from 2000 to 2020. The proportion of cold spots and hot spots in the Yangtze River Delta showed insignificant changes. Both cold and hot spots in the Pearl River Delta had expanded. PM_2.5 showed a downward trend in the three major economic zones from 2000 to 2020, and the magnitudes of increasing rates were higher in the Pearl River Delta, followed by those in the Yangtze River Delta and Bohai Economic Rim. From 2000 to 2020, PM_2.5 exhibited a downward trend in the context of all vegetation coverage grades, and PM_2.5 had most significantly improved within extremely low vegetation coverage in the three economic zones. On the landscape scale, PM_2.5 values were mostly correlated with aggregation index in the Bohai Economic Rim, with the largest patch index in the Yangtze River Delta and Shannon's diversity in the Pearl River Delta, respectively. Under the context of different vegetation coverage levels, PM_2.5showed the highest correlation with aggregation index in the Bohai Economic Rim, landscape shape index in the Yangtze River Delta, and percent of landscape in the Pearl River Delta, respectively. PM_2.5 showed significant differences with vegetation landscape indices in the three economic zones. The combined effect of multiple vegetation landscape pattern indices on PM_2.5 was stronger than that of the single vegetation landscape pattern index. The above results indicated that the spatial cluster of PM_2.5 in the three major economic zones had changed, and PM_2.5 showed a decreasing trend in the three economic zones during the study period. The relationship between PM_2.5 and vegetation landscape indices exhibited obvious spatial heterogeneity in the three economic zones.

Spatiotemporal dynamics of net primary productivity and its influencing factors in the middle reaches of the Yellow River from 2000 to 2020

Introduction

Net primary productivity (NPP) is an important indicator used to characterize the productivity of terrestrial ecosystems. The spatial distribution and dynamic change in NPP are closely related to regional climate, vegetation growth and human activities. Studying the spatiotemporal dynamics of NPP and its influencing factors plays a vital role in understanding ecosystem carbon sink capacity.

Methods

Based on MODIS-NPP data, meteorological data, and land use data from 2000 to 2020, we analyzed the spatiotemporal variation characteristics and influencing factors of NPP in the middle reaches of the Yellow River (MRYR) by using unary linear regression analysis, third-order partial correlation analysis, and Sen+Mann-Kendall trend analysis.

Results

The results showed that the annual average NPP of the MRYR was 319.24 gCm-2a-1 with a spatially decreasing trend from the southern part to the northern part. From 2000 to 2020, the annual average NPP experienced a fluctuating upward trend at a rate of 2.83 gCm-2a-1, and the area with a significant upward trend accounted for 87.68%. The NPP of different land use types differed greatly, in which forest had the greatest increase in NPP. Temperature had a negative correlation with NPP in most parts of the MRYR. Water vapor pressure promoted the accumulation of NPP in the northwestern MRYR. The areas with a positive correlation between NPP and water vapor pressure accounted for 87.6%, and 20.43% of the MRYR area passed the significance test of P< 0.05.

Conclusion

The results of the study highlight the impact of climate factors and land-use changes on NPP and provide theoretical guidance for high-quality sustainable development in the MRYR.

Net Primary Productivity Variations Associated with Climate Change and Human Activities in Nanjing Metropolitan Area of China

Rapid economic development has changed land use and population density, which in turn affects the stability and carbon sequestration capacity of regional ecosystems. Net primary productivity (NPP) can reflect the carbon sequestration capacity of ecosystems and is affected by both climate change and human activities. Therefore, quantifying the relative contributions of climate change and human activities on NPP can help us understand the impact of climate change and human activities on the carbon sequestration capacity of ecosystems. At present, researchers have paid more attention to the impact of climate change and land use change on NPP. However, few studies have analyzed the response of the NPP to gross domestic product (GDP) and population density variations on a pixel scale. Therefore, this paper analyzes the impact of climate change and human activities to NPP on a pixel scale in the Nanjing metropolitan area. During the period 2000-2019, the annual mean NPP was 494.89 g C·m^-2·year^-1, and the NPP in the south of the Nanjing metropolitan area was higher than that in the north. The NPP was higher in the forest, followed by unused land, grassland, and cropland. In the past 20 years, the annual mean NPP showed a significant upward trend, with a growth rate of 3.78 g C·m^-2·year^-1. The increase in temperature and precipitation has led to an increasing trend of regional NPP, and the impact of precipitation on NPP was more significant than that of temperature. The transformation of land use from low-NPP type to high-NPP type also led to an increase in NPP. Land use change from high-NPP type to low-NPP type was the main cause of regional NPP decline. Residual analysis was used to analyze the impact of human activities on NPP. Over the last 20 years, the NPP affected by human activities (NPP_hum) showed a high spatial pattern in the south and a low spatial pattern in the north, and the annual mean NPP_hum also showed a fluctuating upward trend, with a growth rate of 2.00 g C·m^-2·year^-1. The NPP_hum was influenced by both GDP and population density, and the impact of population density on NPP was greater than that of GDP.

[Water Quality Assessment and Spatial-temporal Variation Analysis in Yellow River Basin]

During the implementation of ecological protection in the Yellow River basin, understanding the water pollution status and spatio-temporal variation of water quality has become the most important thing for water safety in the basin. To analyze the water quality in recent years, the water quality data in the Yellow River basin from 2004 to 2018 were firstly collected from eight typical monitoring stations. Using a combination of multivariate data analysis methods including the Mann-Kendall (M-K) trend test, hierarchical clustering analysis (HCA), principal component analysis (PCA), and modified comprehensive water quality identification index (WQI), the spatio-temporal variation characteristics of the water quality were then explored in the Yellow River basin. The results indicated that in terms of time variation, the HCA from the water quality time series showed that the water quality of the Yellow River basin could be divided into the wet season, normal season, and dry season, being basically consistent with the hydrological period. Combined with the M-K trend test and WQI-based water quality assessment, the water quality of the Yellow River basin was improving gradually, with 2010 as the critical year. The water quality in the wet season was superior to that in the dry season. The pollution indicator NH₄⁺-N and permanganate index were dominant in both the wet season and dry season. According to the spatial variation analysis, the water quality for all the studied stations improved significantly. Spatial clustering showed that the S6 (Shanxi Yuncheng Hejin Bridge) was obviously different from others, and further comparative study demonstrated that S6 was constantly seriously polluted. The S7 (Henan Jiyuan Xiaolangdi) exhibited different characteristics in the wet and dry season. In all stations, NH₄⁺-N was considered to be the most common pollution indicator, whereas the permanganate index and DO were also relatively serious for S6. In different hydrological seasons, NH₄⁺-N and the permanganate index showed different characteristics, and their variety was related to the fact that the former mainly came from domestic and industrial sources, whereas the latter was mainly derived from agricultural sources. The modified WQI showed obvious advantages over single-factor water quality assessment, and the findings from this study can provide scientific evidence for water pollution control and comprehensive water quality management in the Yellow River basin.

Spatio-Temporal Variation of Synechococcus Assemblages at DNA and cDNA Levels in the Tropical Estuarine and Coastal Waters

Synechococcus is a major contributor to global marine primary production. Here, its spatio-temporal variations in abundance and phylogenetic structure were studied at three stations of the South China Sea at both DNA and cDNA levels. Synechococcus cell abundance was lowest in March, but highest in October at two coastal stations. Its abundance was higher at the estuarine station, which reached a peak value of 1.36 × 105 cells/ml in April, owing to the nitrogen nutrients discharged from the Sanya River. Gene and gene transcript abundances of four Synechococcus lineages, clades II, III, VIII, and S5.3, were studied by quantitative PCR, which showed that clade II was the most abundant lineage at both DNA and cDNA levels. High-throughput sequencing revealed that, at the DNA level, Synechococcus assemblage was dominated by clade SY4 (a novel clade defined in this study), S5.2, and clade II in the coastal waters and was dominated by freshwater/S5.2 Synechococcus, reaching a value up to 88.61% in June, in estuarine waters. Changes in salinity and nutrient concentration caused by seasonal monsoonal forcing and river discharge were the key determinants of the spatio-temporal variation in Synechococcus assemblages at the DNA level. In comparison, high dissimilation among samples at the same stations and in the same seasons leads to the imperceptible spatio-temporal variation pattern of Synechococcus assemblages at the cDNA level. Furthermore, co-occurrence networks disclosed that Synechococcus community had closer and more complex internal interactions at the cDNA level. These discrepancies highlighted the necessity to study Synechococcus assemblages at both DNA and cDNA levels.

Intraspecific diversity alters the relationship between climate change and parasitism in a polymorphic ectotherm

Climate-modulated parasitism is driven by a range of factors, yet the spatial and temporal variability of this relationship has received scant attention in wild vertebrate hosts. Moreover, most prior studies overlooked the intraspecific differences across host morphotypes, which impedes a full understanding of the climate-parasitism relationship. In the common lizard (Zootoca vivipara), females exhibit three colour morphs: yellow (Y-females), orange (O-females) and mixed (mixture of yellow and orange, M-females). Zootoca vivipara is also infested with an ectoparasite (Ophionyssus mites). We therefore used this model system to examine the intraspecific response of hosts to parasitism under climate change. We found infestation probability to differ across colour morphs at both spatial (10 sites) and temporal (20 years) scales: M-females had lower parasite infestations than Y- and O-females at lower temperatures, but became more susceptible to parasites as temperature increased. The advantage of M-females at low temperatures was counterbalanced by their higher mortality rates thereafter, which suggests a morph-dependent trade-off between resistance to parasites and host survival. Furthermore, significant interactions between colour morphs and temperature indicate that the relationship between parasite infestations and climate warming was contingent on host morphotypes. Parasite infestations increased with temperature for most morphs, but displayed morph-specific rates. Finally, infested M-females had higher reductions in survival rates than infested Y- or O-females, which implies a potential loss of intraspecific diversity within populations as parasitism and temperatures rise. Overall, we found parasitism increases with warming temperatures, but this relationship is modulated by host morphotypes and an interaction with temperature. We suggest that epidemiological models incorporate intraspecific diversity within species for better understanding the dynamics of wildlife diseases under climate warming.

[Spatio-temporal variation of reference crop evapotranspiration and its climatic mechanism in Nenjiang River Basin, China]

To understand the temporal and spatial variations of reference crop evapotranspiration (ET₀) in Nenjiang River Basin, and clarify the effects of climatic factors on ET₀, we calculated the daily ET₀ of each station in Nenjiang River Basin from 1970 to 2019 by Penman-Monteith formula, analyzed the temporal variation trend and spatial distribution pattern of ET₀. We further quantitatively examined the sensitivity of ET₀ to meteorological factors by sensitivity analysis, and explored the contribution of meteorological factors to ET₀ changes. The results showed that ET₀ generally showed an insignificant decreasing trend during the study period in the Nenjiang River Basin. ET₀ decreased in spring, summer, and autumn, but increased in winter, and decreased from southeast to northwest. ET₀ had the highest sensitivity to relative humidity at both temporal and spatial scales. The sensitivity coefficients of mean temperature, relative humidity and wind speed increased gradually, while that of sunshine hours decreased gradually. ET₀ was sensitive to mean temperature in northern Greater Khingan Mountains and Lesser Khingan Mountains, while to wind speed in southern Greater Khingan Mountains and Songnen Plain. Wind speed was the main factor affecting the change of ET₀ in the whole year, spring, autumn, and winter. Sunshine hours was the main affecting factor in summer. The mean temperature and relative humidity had the greatest contribution to ET₀ in the north of Greater Khingan Mountains and Lesser Khingan Mountains, and it was the wind speed in Songnen Plain.

Spatio-Temporal Variation in the Prevalence of Major Mastitis Pathogens Isolated From Bovine Milk Samples Between 2008 and 2017 in Ontario, Canada

An understanding of the spatio-temporal distribution of several groups of mastitis pathogens can help to inform programs for the successful control and management of mastitis. However, in the absence of an active surveillance program such information is not readily available. In this retrospective study we analyzed passive surveillance data from a diagnostic laboratory with an aim to describe the spatio-temporal trend of major mastitis pathogens between 2008 and 2017 in Ontario dairy cattle. Data for all milk culture samples submitted to the Animal Health Laboratory (AHL) at the University of Guelph between 2008 and 2017 was accessed. Descriptive analyses were conducted to identify the major pathogens and Chi-square goodness-of-fit tests were used to compare between multiple proportions. Likewise, univariable logistic regression analysis was performed to determine if there was a change in the probability of isolating the major mastitis pathogens depending on geography or time. Seasonality was assessed by calculating the seasonal relative risk (RR). Of a total of 85,979 milk samples examined, more than half of the samples (61.07%) showed no growth and the proportion of samples that showed no growth almost halved during the study period. Of the samples (36.21%, n = 31,133) that showed any growth, the major bacterial pathogens were Staphylococcus aureus (15.60%), Non-aureus Staphylococci (NAS) (5.04%), Corynebacterium spp. (2.96%), and Escherichia coli (2.00%). Of the NAS, the major species reported were Staphylococcus chromogenes (69.02%), Staphylococcus simulans (14.45%), Staphylococcus epidermidis (12.99%), and Staphylococcus hyicus (2.13%). A temporal change in the prevalence of contagious pathogens like S. aureus and Corynebacterium spp. was observed with an increasing odds of 1.06 and 1.62, respectively. Likewise, except for Trueperella pyogenes, the prevalence of all the major environmental mastitis pathogens increased during the study period. The isolation of most of the pathogens peaked in summer, except for S. aureus, T. pyogenes, and Streptococcus dysgalactiae which peaked in spring months. Interestingly, a regional pattern of isolation of some bacterial pathogens within Ontario was also observed. This study showed a marked spatio-temporal change in the prevalence of major mastitis pathogens and suggests that a regional and seasonal approach to mastitis control could be of value.

Characteristics of aerosol optical depth dynamics and their causes over typical cities along the 21st Century Maritime Silk Road

Atmospheric aerosols, i.e., suspension of liquid and/or solid particles in air, have serious impacts on human health. Exploring the variation and patterns of regional atmospheric aerosols is of great significance to monitor and evaluate atmosphere quality, especially in urban areas with large population. Here, with nine typical pivotal cities along the 21st Century Maritime Silk Road through Southeast Asia, South Asia to West Asia as case studies, based on MCD19A2 550 nm AOD products, combined meteorological factors, land use data, and nighttime light data, we analyzed the spatio-temporal distribution, variation features, influencing and/or driving factors of aerosols in developed urban areas over Asia. The results showed that the descending sequence of the annual aerosol optical depth (AOD) of the nine cities was Karachi, Doha, Chittagong, Bangkok, Colombo, Ho Chi Minh, Singapore, Gwadar, and Yangon during 2013-2018. Due to the influence of regional climate system and atmospheric aerosol types, the time series of annual, seasonal, and monthly AODs were significantly different. The high values of AODs in most cities were mainly located in the urban center or rapid socio-economic (e.g., industrial and agricultural) development regions. The effects of different meteorological factors on the AODs varied in different cities. The rainfall, relative humidity, and wind speed had great impacts on AODs in Ho Chi Minh, Bangkok, Singapore, and Yangon. Temperature, relative humidity, and wind speed had close correlations with AODs in Chittagong, Colombo, Karachi, and Gwadar of South Asia and Doha in West Asia. The urban area's AOD was influenced by the combined and synergistic effects of socio-economy, urbanization, and meteorological factors, with that in Karachi being the most significant.

Urban road congestion patterns under the COVID-19 pandemic: A case study in Shanghai

The novel coronavirus (COVID-19) pandemic has had a significant impact on human mobility around the world. Many cities issued “stay-at-home” orders during the outbreak of COVID-19, and many commuters have also changed their travel modes in the post pandemic period; e.g., transit/bus passengers have switched to driving or car-sharing. Urban road traffic congestion patterns are significantly different than they were pre-pandemic, and understanding such changes can be an opportunity to improve future emergency traffic management and control. Previous studies on this topic have focused on natural disasters or major accidents/incidents. However, very few studies have analyzed the empirical traffic congestion patterns that have occurred during a pandemic. This study takes Shanghai as an example, and conducts a retrospective analysis of empirical spatio-temporal road traffic congestion during the COVID-19 pandemic. The three-month road traffic speed data in the 446 Traffic Analysis Zones (TAZs) collected from Baidu Maps was used in this study. The algorithm of Singular Value Decomposition (SVD) was employed to investigate the inherent composition of the spatio-temporal variation simultaneously influenced by several factors. Three principal components were identified from the spatio-temporal variation, including the stable, main part of variation; the part of the variation that is affected by commuting; and the part of the variation that is affected by migrant populations and the pandemic. The results may suggest ways to improve the emergency management and control of urban roadways in other metropolitan areas worldwide during and after the COVID-19 pandemic period.

Progress and Prospects of Mycorrhizal Fungal Diversity in Orchids

Orchids form mycorrhizal symbioses with fungi in natural habitats that affect their seed germination, protocorm growth, and adult nutrition. An increasing number of studies indicates how orchids gain mineral nutrients and sometime even organic compounds from interactions with orchid mycorrhizal fungi (OMF). Thus, OMF exhibit a high diversity and play a key role in the life cycle of orchids. In recent years, the high-throughput molecular identification of fungi has broadly extended our understanding of OMF diversity, revealing it to be a dynamic outcome co-regulated by environmental filtering, dispersal restrictions, spatiotemporal scales, biogeographic history, as well as the distribution, selection, and phylogenetic spectrum width of host orchids. Most of the results show congruent emerging patterns. Although it is still difficult to extend them to all orchid species or geographical areas, to a certain extent they follow the "everything is everywhere, but the environment selects" rule. This review provides an extensive understanding of the diversity and ecological dynamics of orchid-fungal association. Moreover, it promotes the conservation of resources and the regeneration of rare or endangered orchids. We provide a comprehensive overview, systematically describing six fields of research on orchid-fungal diversity: the research methods of orchid-fungal interactions, the primer selection in high-throughput sequencing, the fungal diversity and specificity in orchids, the difference and adaptability of OMF in different habitats, the comparison of OMF in orchid roots and soil, and the spatiotemporal variation patterns of OMF. Further, we highlight certain shortcomings of current research methodologies and propose perspectives for future studies. This review emphasizes the need for more information on the four main ecological processes: dispersal, selection, ecological drift, and diversification, as well as their interactions, in the study of orchid-fungal interactions and OMF community structure.

[Spatio-temporal variation of atmospheric CH4 concentration and its driving factors in monsoon Asia]

Based on the ground-based observations from seven atmospheric background stations during 2009 to 2018 in monsoon Asia (including BKT station in Indonesia, LLN and WLG stations in China, RYO and YON stations in Japan, TAP station in Republic of Korea, and UUM station in Mongolia), we analyzed the temporal and spatial variation of atmospheric CH₄ concentration and its driving factors using harmonic model and maximal information-based nonparametric exploration. The results showed that the CH₄ concentration in monsoon Asia varied from 1853.04 to 1935.61 nmol·mol^-1, higher than that in Mauna Loa (MLO) station (1838.33 nmol·mol^-1) in Hawaii, USA. The CH₄ concentration decreased from north to south, with the highest value in TAP station (1935.61 nmol·mol^-1) in Republic of Korea and RYO station (1907.19 nmol·mol^-1) in Japan. The average seasonal amplitude at YON station in Japan was the largest (108.20 nmol·mol^-1); while that at WLG station in China was the smallest (29.48 nmol·mol^-1). The seasonal amplitude of TAP station in Republic of Korea changed faster at the rate of 4.49 nmol·mol^-1·a^-1. Except for WLG and TAP stations, CH₄ concentrations were low in summer and high in winter. From the long-term perspective, the CH₄ concentration at LLN (7.68 nmol·mol^-1·a^-1) and WLG (7.56 nmol·mol^-1·a^-1) stations in China exhibited the most obvious growth trend. Compared with wind speed, temperature and precipitation had greater impact on CH₄ concentration, which were negatively associated with CH₄ concentration. Local CH₄ emission at some stations had a significant positive effect on CH₄ concentration.

[Spatio-temporal Variation of PM2.5 Related Relationships in China from the Perspective of Air Pollution Regional Linkage Control and Prevention]

Identification of spatio-temporal variation of PM_2.5 related relationships under joint management zones is of great significance for scientifically conducting joint control of air pollution in China. Based on the PM_2.5 concentration data of 334 prefecture-level cities in China from 2000 to 2016, from the perspective of air pollution regional linkage control and prevention, this paper systematically analyzes the spatio-temporal variation of PM_2.5 related relationships in China using a spatial unit aggregation strategy and geographically and temporally weighted regression. The results show that:① With PM_2.5 as the primary pollutant, ten air pollution joint management areas are obtained by considering the degree of pollution, geographical location, meteorology, topography, and economy. ② Geographically and temporally weighted regression can effectively reveal the spatio-temporal non-stationarity of the relationships between PM_2.5 concentration and related factors. Meanwhile, population size, secondary industry gross domestic product, SO₂ emissions, annual average temperature, annual precipitation, and annual relative humidity are identified as having a significant effect on changes in PM_2.5 concentration. ③ The population impacts on PM_2.5 concentration in the Beijing-Tianjin-Yunmeng region are the largest of all regions during the period. The influence of the secondary industry's gross domestic product on the PM_2.5 concentration in the Sichuan-Yunnan District is the most variable. Apart from these values in the northeast of China, the regression coefficient values of SO₂ emissions first decrease with time, then increase, and then decrease again. The time variability of the average annual temperature of each treatment area to PM_2.5 is small. The influences of annual precipitation and annual average relative humidity on PM_2.5 present different variability characteristics in each region.

[Spatio-temporal Variations in the Characteristics of Water Eutrophication and Sediment Pollution in Baiyangdian Lake]

Since the establishment of Xiong'an New District, a series of comprehensive pollution control measures have been implemented in Baiyangdian Lake. To evaluate the pollution status and identify the main sources of pollution of Baiyangdian Lake, 30 water samples and 29 sediment samples were collected in the lake. Five water quality indexes (i.e., concentrations of chemical oxygen demand, total phosphorus (TP), total nitrogen (TN), NH₄⁺-N, and chlorophyll-a) and three sediment quality indexes (i.e., concentrations of TN, TP, and heavy metals) were measured. Along with historical monitoring data, the spatio-temporal pollution characteristics and their influencing factors in Baiyangdian Lake were analyzed. The results show that the Baiyangdian Lake water is eutrophicated. Of the 30 sampling sites, 8 are "mildly eutrophicated" (accounting for 26.7%), 16 are "moderately eutrophicated" (accounting for 53.3%), and 6 are "severely eutrophicated" (accounting for 20%). Compared with the periods between 1991 and 2017, the water quality of most sampling sites, especially in the northern parts, has improved a lot. This shows that the pollution control measures have basically curbed the gradually increasing trend of pollution in the waterbody. The nutritive pollution in sediment is severe. The concentrations of TN are between 1483.7 and 14234.1 mg·kg^-1, with a mean value of 5054.9 mg·kg^-1, and the concentration coefficient variation in different sites is as high as 46.5%. The concentrations of TP are between 360.3 and 1964.4 mg·kg^-1, with a mean value of 925.4 mg·kg^-1, and the concentration coefficient variation in different sites is 25.7%. Geoaccumulation index calculation shows that the mean I_geo value of heavy metals in sediments is less than 1, which indicates cleanness or slight pollution. The main contributions to heavy metal pollution are Cd, Zn, and Cu. Regarding ecological risk of heavy metals, only some sites (i.e., L3, L21, L28, and L29) are at high and very high risk level, while the remaining sites are at moderate risk level. Overall, the pollution of Baiyangdian Lake changes from the northern part to the southern part, and the main influencing factors also change from external pollution to endogenous pollution caused by the discharge of villages in the lake and the sediments.

Effect of the wetland environment on particulate matter and dry deposition

In Beijing, particulate matter (PM) in the atmosphere, especially PM_2.5 and PM₁₀, have attracted public attention because of its adverse effects. A series of studies have investigated the sources and spatial-temporal variation of PM. Wetland has been reported to own the capacity of resolving air problem. To examine the characteristics of the particulate matter in wetlands, the diurnal variation of PM_2.5 and PM₁₀ concentrations with respect to two heights (i.e. 1.5 and 10 m, respectively) and three meteorological factors (i.e. wind speed, temperature, and relative humidity, respectively) was monitored in the Cuihu National Wetland Park in Beijing, and the dry deposition velocity and flux were analysed using the above-mentioned data. Results indicated that (1) As for diurnal variation, the PM concentration constantly decreased at 07:00-16:00 and gradually increased at 16:00-18:00. The maximum instantaneous concentration was observed at 07:00-10:00, while the minimum instantaneous concentration was observed at 13:00-16:00. (2) The annual concentration variation of PM followed the order of dry period > wet period > normal period. (3) The particulate concentrations at 10 m were always greater than those at 1.5 m. (4) The PM concentration was positively correlated to the relative humidity and negatively correlated to the temperature. Wind speed exhibited a complex effect on PM concentration. (5) The regulation of dry deposition efficiency followed the order of spring > winter > summer. (6) Wind speed strongly and positively affected the dry deposition velocity of PM10. The effects of temperature and relative humidity on dry deposition were uncertain.

Temporal and Spatial Features of the Correlation between PM2.5 and O3 Concentrations in China

In recent years, particulate matter of 2.5 µm or less (PM2.5) pollution in China has decreased but, at the same time, ozone (O3) pollution has become increasingly serious. Due to the different research areas and research periods, the existing analyses of the correlation between PM2.5 and O3 have reached different conclusions. In order to clarify the relationship between PM2.5 and O3, this study selected mainland China as the research area, based on the PM2.5 and O3 concentration data of 1458 air quality monitoring stations, and analyzed the correlation between PM2.5 and O3 for different time scales and geographic divisions. Moreover, by combining the characteristics of the pollutants, topography, and climatic features of the study area, we attempted to discuss the causes of the spatial and temporal differences of R-PO (the correlation between PM2.5 and O3). The study found that: (1) R-PO tends to show a positive correlation in summer and a negative correlation in winter, (2) the correlation coefficient of PM2.5 and O3 is lower in the morning and higher in the afternoon, and (3) R-PO also shows significant spatial differences, including north-south differences and coastland-inland differences.

Spatio-Temporal Variation of Gender-Specific Hypertension Risk: Evidence from China

Previous studies which have shown the existence of gender disparities in hypertension risks often failed to take into account the participants' spatial and temporal information. In this study, we explored the spatio-temporal variation for gender-specific hypertension risks in not only single-disease settings but also multiple-disease settings. From the longitudinal data of the China Health and Nutrition Survey (CHNS), 70,374 records of 21,006 individuals aged 12 years and over were selected for this study. Bayesian B-spline techniques along with the Besag, York, and Mollie (BYM) model and the Shared Component Model (SCM) model were then used to construct the spatio-temporal models. Our study found that the prevalence of hypertension in China increased from 11.7% to 34.5% during 1991 and 2015, with a higher rate in males than that in females. Moreover, hypertension was found mainly clustered in spatially adjacent regions, with a significant high-risk pattern in Eastern and Central China while a low-risk pattern in Western China, especially for males. The spatio-temporal variation of hypertension risks was associated with regional covariates, such as age, overweight, alcohol consumption, and smoking, with similar effects of age shared by both genders whereas gender-specific effects for other covariates. Thus, gender-specific hypertension prevention and control should be emphasized in the future in China, especially for the elderly population, overweight population, and females with a history of alcohol consumption and smoking who live in Eastern China and Central China.

Spatio-Temporal Variation Characteristics of PM2.5 in the Beijing-Tianjin-Hebei Region, China, from 2013 to 2018

Air pollution, including particulate matter (PM_2.5) pollution, is extremely harmful to the environment as well as human health. The Beijing–Tianjin–Hebei (BTH) Region has experienced heavy PM_2.5 pollution within China. In this study, a six-year time series (January 2013–December 2018) of PM_2.5 mass concentration data from 102 air quality monitoring stations were studied to understand the spatio-temporal variation characteristics of the BTH region. The average annual PM_2.5 mass concentration in the BTH region decreased from 98.9 μg/m³ in 2013 to 64.9 μg/m³ in 2017. Therefore, China has achieved its Air Pollution Prevention and Control Plan goal of reducing the concentration of fine particulate matter in the BTH region by 25% by 2017. The PM_2.5 pollution in BTH plain areas showed a more significant change than mountains areas, with the highest PM_2.5 mass concentration in winter and the lowest in summer. The results of spatial autocorrelation and cluster analyses showed that the PM_2.5 mass concentration in the BTH region from 2013–2018 showed a significant spatial agglomeration, and that spatial distribution characteristics were high in the south and low in the north. Changes in PM_2.5 mass concentration in the BTH region were affected by both socio-economic factors and meteorological factors. Our results can provide a point of reference for making PM_2.5 pollution control decisions.

[Spatio-temporal variations of functional diversity of fish communities in Haizhou Bay.]

As the link among species, ecological environment, and ecosystem function, functional diversity can help us to better understand the relationship between biodiversity and ecosystem function. We analyzed functional diversity with thirteen functional traits reflecting the characteristics of food acquisition, locomotion, ecological adaptation, reproduction and population dynamics of fish species. The seasonal, interannual and spatial variations of functional diversity of fish communities were examined using functional richness index (FRic), functional evenness index (FEve), functional divergence index (FDiv) and community weighted mean index (CWM) based on the data from the bottom trawl surveys in spring and autumn from 2011 to 2017 (except 2012) in Haizhou Bay. The results showed that functional diversity indices were significantly different in spring and autumn, with FRic was significantly higher in autumn than that in spring and FDiv was significantly higher in spring than that in autumn. Migration might be the main reason for the seasonal change of functional diversity indices. CWM analysis showed that dominant fish species were cold-temperate or warm-temperate species, with higher trophic level, strong motion ability, and relatively high growth coefficient, resilience and vulnerability in spring. In autumn, the dominant species showed the opposite traits. In both spring and autumn, fish species with pelagic eggs dominated the fish communities. Inter-annual variations in functional diversity indices were observed in spring and autumn. The functional diversity indices showed an annual fluctuation during the study period in both spring and autumn, indicating the low stability of fish community in Haizhou Bay. Significant spatial changes in functional diversity of fish assemblages were observed, with FDiv being higher in the offshore coastal waters (>20 m) than that in the shallow waters (<20 m). The functional diversity showed obvious spatio-temporal variation. The ecological niches and resource utilization of fish species varied with season, year and space in Haizhou Bay.

Water Productivity Evaluation under Multi-GCM Projections of Climate Change in Oases of the Heihe River Basin, Northwest China

As the second largest inland river basin situated in the middle of the Hexi Corridor, Northwest China, the Heihe River basin (HRB) has been facing a severe water shortage problem, which seriously restricts its green and sustainable development. The evaluation of climate change impact on water productivity inferred by crop yield and actual evapotranspiration is of significant importance for water-saving in agricultural regions. In this study, the multi-model projections of climate change under the three Representative Concentration Pathways emission scenarios (RCP2.6, RCP4.5, RCP8.5) were used to drive an agro-hydrological model to evaluate the crop water productivity in the middle irrigated oases of the HRB from 2021–2050. Compared with the water productivity simulation based on field experiments during 2012–2015, the projected water productivity in the two typical agricultural areas (Gaotai and Ganzhou) both exhibited an increasing trend in the future 30 years, which was mainly attributed to the significant decrease of the crop water consumption. The water productivity in the Gaotai area under the three RCP scenarios during 2021–2050 increased by 9.2%, 14.3%, and 11.8%, while the water productivity increased by 15.4%, 21.6%, and 19.9% in the Ganzhou area, respectively. The findings can provide useful information on the Hexi Corridor and the Belt and Road to policy-makers and stakeholders for sustainable development of the water-ecosystem-economy system.

Spatio-Temporal Variation of Longevity Clusters and the Influence of Social Development Level on Lifespan in a Chinese Longevous Area (1982-2010)

The study aims to determine the spatial and temporal variation of a longevous region and explore the correlation between longevity and socioeconomic development. Population data at the township level were obtained from the last four population censuses (1982-2010). Five main lifespan indicators and the Human Development Index (HDI) were calculated. Getis-Ord G*, Gravity modeling, and Pearson's r between lifespan indicators and HDI were applied. In this study, a stable longevous gathering area was discovered in Hechi during different periods. Under the influence of social and economic development, more longevous areas appeared. However, the effects of genetic and natural environmental factors on longevity were always dominant in this remote and mountainous city. Furthermore, longevity indicators lacked any significant correlation with life expectancy. No significant positive correlation was detected between lifespan indicators and HDI. Thus, we conclude that lifespan indicators can determine the spatial distribution and variation pattern of longevity from multiple dimensions. The geographical scope of longevity in Hechi City is gradually expanding, and significant spatial clustering was detected in southwestern, southern, and eastern parts of Hechi. This study also found that social economic development is likely to have a certain impact on new longevous areas, but their role on extreme longevity is not significant.

Spatio-Temporal Variation of Core and Satellite Arbuscular Mycorrhizal Fungus Communities in Miscanthus giganteus

Arbuscular mycorrhizal fungi (AMF) are a group of obligate plant symbionts which can promote plant nutrition. AMF communities are diverse, but the factors which control their assembly in space and time remain unclear. In this study, the contributions of geographical distance, environmental heterogeneity and time in shaping AMF communities associated with Miscanthus giganteus (a perennial grass originating from south-east Asia) were determined over a 13 months period. In particular, the community was partitioned into core (abundant and persistent taxa) and satellite (taxa with low abundance and persistence) constituents and the drivers of community assembly for each determined. β-diversity was exceptionally low across the 140 m line transects, and there was limited evidence of geographical scaling effects on the composition of the core, satellite or combined communities. However, AMF richness and community composition changed over time associated with fluctuation within both the core and satellite communities. The degree to which AMF community variation was explained by soil properties was consistently higher in the core community than the combined and satellite communities, suggesting that the satellite community had considerable stochasticity associated with it. We suggest that the partitioning of communities into their core and satellite constituents could be employed to enhance the variation explained within microbial community analyses.

Spatio-temporal variation of biotic factors underpins contemporary range dynamics of congeners

Species' ranges are complex often exhibiting multidirectional shifts over space and time. Despite the strong fingerprint of recent historical climate change on species' distributions, biotic factors such as loss of vegetative habitat and the presence of potential competitors constitute important yet often overlooked drivers of range dynamics. Furthermore, short-term changes in environmental conditions can influence the underlying processes of local extinction and local colonization that drive range shifts, yet are rarely considered at broad scales. We used dynamic state-space occupancy models to test multiple hypotheses of the relative importance of major drivers of range shifts of Golden-winged Warblers (Vermivora chrysoptera) and Blue-winged Warblers (V. cyanoptera) between 1983 and 2012 across North America: warming temperatures; habitat changes; and occurrence of congeneric species, used here as proxy for biotic interactions. Dynamic occupancies for both species were most influenced by spatial relative to temporal variation in temperature and habitat. However, temporal variation in temperature anomalies and biotic interactions remained important. The two biotic factors considered, habitat change and biotic interactions, had the largest relative effect on estimated extinction rates followed by abiotic temperature anomalies. For the Golden-winged Warbler, the predicted presence of the Blue-winged Warbler, a hypothesized competitor, most influenced extinction probabilities, contributing to evidence supporting its role in site-level species replacement. Given the overall importance of biotic factors on range-wide dynamic occupancies, their consideration alongside abiotic factors should not be overlooked. Our results suggest that warming compounds the negative effect of habitat loss emphasizing species' need for habitat to adapt to a changing climate. Notably, even closely related species exhibited individual responses to abiotic and biotic factors considered.