Geographically Weighted Regression (GWR) is one of the local statistical models that can capture the effects of spatial heterogeneity. This model can be used for both univariate and multivariate responses. However, it should be noted that GWR models require the assumption of error normality. To overcome this problem, we propose a GWR model for generalized gamma distributed responses that can capture the phenomenon of some special continuous distributions. The proposed model is known as Geographically Weighted Multivariate Generalized Gamma Regression (GWMGGR). Parameter estimation is performed using the Maximum Likelihood Estimation (MLE) method optimized with the Bernt-Hall-Hall-Haussman (BHHH) algorithm. To determine the significance of the spatial heterogeneity effect, a hypothesis test was conducted using the Maximum Likelihood Ratio Test (MLRT) approach. We made a spatial cluster based on the estimated model parameters for each response using the k-means clustering method to interpret the obtained results. Some highlights of the proposed method are:•A new model for GWR with multivariate generalized gamma distributed responses to overcome the assumption of normally distributed errors.•Goodness of fit test to test the spatial effects in GWMGGR model.•Spatial clustering of districts/cities in Central Java based on three dimensions of educational indicators.

Trees are exposed to significant spatio-temporal thermal variations, which can induce intracrown discrepancies in the onset and dynamics of primary and secondary growth. In recent decades, an increase in late winter and early spring temperatures has been observed, potentially accelerating bud break, cambial activation and their potential coordination. Intracrown temperature heterogeneities could lead to asymmetric tree shapes unless there is a compensatory mechanism at the crown level. An original warming experiment was conducted on young Juglans regia trees in a greenhouse. From February to August, the average temperature difference during the day between warmed and control parts was 4°C. The warming treatment advanced the date of budbreak significantly, by up to 14 days. Warming did not alter secondary growth resumption but increased growth rates, leading to higher xylem cell production (twice as many) and to an increase in radial increment (+80% compared to control). Meristems resumptions were asynchronous without coordination in response to temperature. Buds on warmed branches began to swell two weeks prior to cambial division, which was one week earlier than on control branches. A difference in carbon and water remobilisation at the end of bud ecodormancy was noted under warming. Overall, our results argue for a lack of compensatory mechanisms at the crown scale, which may lead to significant changes in tree architecture in response to intra-crown temperature heterogeneities.

The source diversity and health risk of trace elements (TEs) in soil make it necessary to reveal the relationship between pollution, source, and risk. However, neglect of spatial heterogeneity restricts the reliability of existing identification methods. In this study, spatial heterogeneity is proposed as a necessary and feasible factor for accurately dissecting the pollution-source-risk link of soil TEs. A comprehensive framework is developed by integrating positive matrix factorization, Geodetector, and risk evaluation tools, and successfully applied in a mining-intensive city in northern China. Overall, the TEs are derived from natural background (28.5 %), atmospheric deposition (25.6 %), coal mining (21.8 %), and metal industry (24.1 %). The formation mechanism of heterogeneity for high-variance TEs (Se, Hg, Cd) is first systematically deciphered by revealing the heterogeneous source-sink relationship. Specifically, Se is dominated (76.5 %) by heterogeneous coal mining (q=0.187), Hg is determined (92.6 %) by the heterogeneity of metal mining (q=0.183) and smelting (q=0.363), and Cd is caused (50.9 %) by heterogeneous atmospheric deposition (q>0.254) co-influenced by the terrains and soil properties. Highly heterogeneous sources are also noteworthy for their potential to pose extreme risks (THI=1.122) in local areas. This study highlights the necessity of integrating spatial heterogeneity in pollution and risk assessment of soil TEs.

The fluorescence intensities of the cellular respiratory cofactors NADH (reduced nicotinamide adenine dinucleotide) and FAD++ (oxidized flavin adenine dinucleotide) reflect energy metabolism in skin and other tissues and can be quantified in vivo by fluorescence spectroscopy (FS). However, the variability of physiological parameters largely determines the reproducibility of measurement results and the reliability of the diagnostic test. In this prospective study, we evaluated the interday reproducibility of NADH and FAD++ fluorescence intensity measurements in the skin of 51 healthy volunteers assessed by the FS at baseline, after local cooling (10°C) and heating of the skin (35°C). Results showed that the fluorescence amplitude of NADH (AFNADH) in forearm skin was the most reproducible of the FS parameters studied. Assessment of AFNADH in the dorsal forearm in combination with a thermal functional test is the most promising method for clinical use for assessing energy metabolism in the skin.

Social determinants of health are the conditions in the environments where people are born, live, learn, work, play, worship, and age that affect a wide range of health, functioning and quality of life outcomes and risks - these social determinants of health often aid in explaining the racial and ethnic health inequities present in the United States (US). The root cause of these social determinants of health has been tied to structural racism, and residential segregation is one such domain of structural racism that allows for the operationalization of the geography of structural racism. This review focuses on three residential segregation measures that are often utilized to capture segregation as a function of race/ethnicity, income, and simultaneously race/ethnicity and income. Empirical findings related to the spatial and spatio-temporal heterogeneity of these residential segregation measures are presented. We also discuss some of the implications of utilizing these three residential segregation measures.

There is abundant research showing the disproportionate impacts of violence on health in disadvantaged neighborhoods, making an understanding of recent violent crime trends essential for promoting health equity. Carjackings have been of particular interest in the media, although little research has been undertaken on this violent crime. We use interrupted time series models to examine the impact of the police killing of George Floyd on the spatiotemporal patterns of carjacking in Minneapolis in relation to neighborhood disadvantage. To provide grounding, we compare our results to the well-studied patterns of homicides. Results indicate that carjackings both increased and dispersed spatially after the murder of George Floyd and subsequent social unrest, more so than homicides. Socially disadvantaged neighborhoods experienced the greatest absolute increase while more advantaged neighborhoods saw a greater relative increase. The challenge ahead is to identify policy responses that will effectively curb such violence without resorting to harsh and inequitable policing and sentencing practices.

Understanding the drivers of assemblages of arbuscular mycorrhizal fungi (AMF) is essential to leverage the benefits of AMF for plant growth and health. Arbuscular mycorrhizal fungi are heterogeneously distributed in space even at small scale. We review the role of plant distribution in driving AMF assemblages (the passenger hypothesis), using a transposition of the conceptual framework of landscape ecology. Because rooting systems correspond to habitat patches with limited carrying capacity that differ in quality due to host-preference effects, we suggest considering plant communities as mosaics of AMF microhabitats. We review how predictions from landscape ecology apply to plant community effects on AMF, and the existing evidence that tests these predictions. Although many studies have been conducted on the effect of plant compositional heterogeneity on AMF assemblages, they mostly focused on the effect of plant richness, while only a few investigated the effect of configurational heterogeneity, plant connectivity or plant community temporal dynamics. We propose key predictions and future prospects to fill these gaps. Considering plant communities as landscapes extends the passenger hypothesis by including a spatially explicit dimension and its associated ecological processes and may help understand and manipulate AMF assemblages at small spatial scales.

BACKGROUND: In developing countries, the death probability of a child and mother is more significant than in developed countries; these inequalities in health outcomes are unfair. The present study encompasses a spatial analysis of maternal and child mortalities in Pakistan. The study aims to estimate the District Mortality Index (DMI), measure the inequality ratio and slope, and ascertain the spatial impact of numerous factors on DMI scores across Pakistani districts.
METHODS: This study used micro-level household datasets from multiple indicator cluster surveys (MICS) to estimate the DMI. To find out how different the DMI scores were, the inequality ratio and slope were used. This study further utilized spatial autocorrelation tests to determine the magnitude and location of the spatial dependence of the clusters with high and low mortality rates. The Geographically Weighted Regression (GWR) model was also applied to examine the spatial impact of socioeconomic, environmental, health, and housing attributes on DMI.
RESULTS: The inequality ratio for DMI showed that the upper decile districts are 16 times more prone to mortalities than districts in the lower decile, and the districts of Baluchistan depicted extreme spatial heterogeneity in terms of DMI. The findings of the Local Indicator of Spatial Association (LISA) and Moran\'s test confirmed spatial homogeneity in all mortalities among the districts in Pakistan. The H-H clusters of maternal mortality and DMI were in Baluchistan, and the H-H clusters of child mortality were seen in Punjab. The results of GWR showed that the wealth index quintile has a significant spatial impact on DMI; however, improved sanitation, handwashing practices, and antenatal care adversely influenced DMI scores.
CONCLUSIONS: The findings reveal a significant disparity in DMI and spatial relationships among all mortalities in Pakistan\'s districts. Additionally, socioeconomic, environmental, health, and housing variables have an impact on DMI. Notably, spatial proximity among individuals who are at risk of death occurs in areas with elevated mortality rates. Policymakers may mitigate these mortalities by focusing on vulnerable zones and implementing measures such as raising public awareness, enhancing healthcare services, and improving access to clean drinking water and sanitation facilities.

Per- and polyfluoroalkyl substances (PFASs) in high-latitude polar regions and the Tibetan Plateau have received widespread international attention. Here, we measured 18 PFASs and 11 major isomers in the lake water, sediment, and surrounding runoff of Lake Nam Co in 2020. The concentrations of ultrashort-chain trifluoroacetic acid (TFA) and perfluoropropanoic acid (PFPrA) and major isomers of perfluoooctanoic acid (PFOA) and perfluoooctane sulfonate acid (PFOS) in water bodies in high-latitude polar regions and the Tibetan Plateau are reported for the first time. The results showed that the concentration of ∑PFASs in glacial runoff was approximately 139 % greater than that in nonglacial runoff. The concentrations of ∑PFASs in the lake water and sediment in the southern lake with multiple glacial runoff events were approximately 113 % and 108 % higher, respectively, than those in the northern lake. The concentrations of short-chain perfluorobutanoic acid (PFBA) and ultrashort-chain TFA and PFPrA, which may be indicators of ice and snow melt, exhibited significant spatial heterogeneity. Overall, the spatial heterogeneity of PFAS concentrations in the water, sediment and surrounding runoff of Lake Nam Co may be caused mainly by glacial melting.

Evaluating the impact of large-scale human activities on carbon storage through land use changes is of growing interest in terrestrial ecosystem assessments. The Huaihe River Basin, a vital Chinese grain production area, has undergone marked land use changes amid socio-economic acceleration. Evaluating the impacts of land use change on carbon storage and future carbon sequestration is imperative for regional ecosystem sustainability and Chinese food security, simultaneously, furnishing data support to regional land use planning and decision-making processes. Nonetheless, the mechanisms linking land use changes to carbon storage and the future carbon reservoir responses remain unclear. We utilized a multi-source dataset and representative scenarios, integrating PLUS, InVEST models, and Geodetector to assess land use change impacts on carbon storage in the Huaihe River Basin (2000-2030). The data indicates the following: (1) from 2000 to 2020, cultivated land decreased by 28,344.69 km2, construction land increased by 26,914.56 km2, and other land types changed little. (2) Land use change resulted a carbon loss of 1.17 × 108 t, primarily due to the expansion of construction land. (3) All four simulation scenarios exhibited diminished carbon storage relative to 2020, with the economic development scenario recording the lowest at 4.98 × 109 t and the ecological protection scenario the highest at 5.06 × 109 t. (4) Elevation predominantly drives carbon storage changes, with its interaction with NPP having the greatest impact. The factors synergistically enhance their explanatory power. The research provides a scientific basis for strategies aimed at augmenting regional carbon sequestration and refining low-carbon land management, safeguarding ecosystem stability.