Regional Variability Research Articles

A glacial chronology for sub-Antarctic Marion Island from MIS 2 and MIS 3

It is increasingly apparent that local and regional factors, including geographic location, topography and climatic variability, strongly influence the timing and extent of glaciations across the Southern Hemisphere. Glacial chronologies of sub-Antarctic islands can provide valuable insights into the nature of regional climatic variability and the localised response(s) of glacial systems during periods of climatic change. With new cosmogenic 36Cl exposure ages from Marion Island in the southern Indian Ocean, we provide the oldest dated terrestrial moraine sequences for the sub-Antarctic islands. Results confirm that a local Last Glacial Maximum was reached prior to ∼56 ka when ice retreated with localised stand still events at ∼43 ka and between ∼38 and 33 ka. Evidence of ice re-advances throughout MIS 2 are limited and particularly absent for the cooling periods at ∼32 and ∼21 ka, and retreat continued until ∼17 ka ago. Any MIS 1 readvances on the island would be confined to altitudes above 900 m a.s.l. but the Holocene exposure ages remains to be documented. We compare Marion Island's glacial chronology with other sub-Antarctic islands (e.g., the Kerguelen archipelago, Auckland and Campbell islands and South Georgia) and review the evidence for a Southern Hemisphere glacial maximum in late MIS 3 (∼41 ka). At a regional scale we recognize sea surface temperatures, sea ice extent and the latitudinal position of the Southern Westerly Wind belt as key controls on equilibrium-line altitudes and ice accumulation due to their influence on air temperature and precipitation regimes. At an island scale, geomorphological mapping shows that deglaciation of individual glacier lobes was a-synchronous due to local physiographical and topographical factors controlling the island's micro-climate. We suggest that variability in deglaciation chronologies at smaller scales (particularly at the sub-Antarctic Islands) are important to consider when untangling climatic drivers across the Southern Ocean.

Association between aortic pathology, surgeon experience, and regional variability on use of intravascular ultrasonography during thoracic endovascular aortic repair

ObjectiveIntravascular ultrasound (IVUS) is a useful adjunct to obtain precise intraluminal measurements during thoracic endovascular aortic repair (TEVAR), but IVUS examination is not routinely used by all surgeons or centers during TEVAR. We sought to identify patient- and system-related factors that influence the decision to use IVUS examination during TEVAR. MethodsA retrospective review of the Vascular Quality Initiative (VQI) database was performed to identify all patients undergoing TEVAR from 2015 to 2019. Multivariable logistic regression modeling with three-fold repeated cross-validation was performed to identify predictors of IVUS use during TEVAR. Association of IVUS use with contrast volume and radiation exposure was also assessed. ResultsA total of 12,414 patients undergoing TEVAR met the inclusion criteria. Of these, IVUS examination was used in 41.3% of cases (n = 5121). IVUS use was more common in younger patients with fewer comorbidities; however, IVUS examination was also more commonly deployed in symptomatic patients and those with a higher preoperative American Society of Anesthesiology classification. IVUS examination was use in 80% (n = 3385/4213) TEVAR procedures performed for type B aortic dissection, which accounted for 50% of total IVUS use and only 11% of cases during which IVUS examination was not used (n = 822/7293) (P < .01). In multivariable analysis, the strongest independent predictor of IVUS use was aortic dissection (odds ratio, 13.7; 95% confidence interval, 11.7-16.3; P < .001, with aortic aneurysm as the reference). Surgeon years of independent practice experience was not associated with IVUS use, but when accounting for clustering on physicians and geographic regions, these variables explained 15% of the variance observed in the final risk-adjusted model. After adjustment for confounding factors, IVUS use was associated with a significant decrease in fluoroscopy time and contrast volume (both P < .001). ConclusionsThe decision to use IVUS examination during TEVAR is most heavily influenced by aortic pathology. Although surgeon experience was not associated with the decision to use IVUS examination, there was substantial variation in IVUS examination use among individual surgeons and VQI regions. IVUS use was associated with decreased contrast administration and fluoroscopy use but did not appear to have an impact on survival or re-intervention. Although aortic dissection was strongly associated with IVUS use, a significant number of TEVAR for dissection were performed without IVUS examination. Further research is warranted to identify the barriers to IVUS use as well as the risks and benefits of IVUS use during TEVAR so that quality benchmarks can be established and resource use is improved.

NEOLITHIC LITHIC INDUSTRIES OF THE EASTERN WING OF THE FERTILE CRESCENT: PAYING HOMAGE TO PROFESSOR STEFAN K. KOZŁOWSKI

A systematic study by Stefan K. Kozłowski during the 1990s and the 2000s revealed marked techno-typological differences between the Neolithic lithic industries of the “Eastern and Western Wings” of the Fertile Crescent of Southwest Asia. The present article addresses regional variability in Pottery Neolithic flaked stone industries within the Eastern Wing. It suggests the potential existence of lithic variability between the plains and the mountains of central Mesopotamia. Given the known lithic variability also in the Eastern Wing of northern Mesopotamia, the present study suggests the need to define the variability of lithic industries in other parts of each wing; such research would help better explain the historical, ecological, and cultural backgrounds of regional differences.

Investigation of the spatial effects on PM2.5 in relation to land use and ecological restoration in urban agglomerations

Heavy pollution of particulate matter with an aerodynamic diameter of <2.5 μm (PM2.5) poses increasing threats to the living environment worldwide. Urban agglomerations often lead to regional rather than local air pollution problems. This study explored the underlying global and local spatial driving mechanisms of PM2.5 variations of the 195 county-level administrative units in the urban agglomeration in the middle reaches of the Yangtze River, China, in 2020, using the global spatial regression and geographically weighted regression methods. Results showed that (1) at the county level, there were spatial variations of PM2.5, fluctuating from 20.1263 μg/m3 to 44.8416 μg/m3. (2) The concentrations of PM2.5 presented a positive spatial autocorrelation with a remarkable direct spatial spillover effect. (3) Forestland, grassland, elevation and ecological restoration were negatively correlated with PM2.5 concentrations, the indirect spatial spillover effect of elevation was noticeable. (4) The indirect reduction effects of ecological restoration on PM2.5 concentrations were substantial in the Wuhan urban agglomeration. (5) The reduction effect of forestland, grassland, ecological restoration and elevation on PM2.5 showed a noticeable spatial heterogeneity. In the future, it is suggested regional variability and the spatial spillover effect of air pollution be taken into account in environmental governance. Simultaneously, utilization of the mitigation effect of ecological restoration on PM2.5 is anticipated for the concerted effort in air pollution governance.

Orphan drugs in Italy: availability and time-to-access at regional level

Introduction: There are an estimated 26 million rare disease patients in Europe, about 2 million in Italy. Access to orphan drugs has been evaluated nationally and internationally, and delays have been observed due to evaluation of price and therapeutic value. The objectives of this study are: to assess the availability of EMA-authorized orphan drugs at national and regional level; to study time trends and regional variability in consumption and spending, and to estimate the time to access in Italian regions. Methods: We evaluate the availability of EMA authorized orphan drugs in Italy. Based on data from the Traceability of medicines dataflow for period 2016-2021 we evaluate the expenditure, consumption and availability of orphan drugs in each region. To estimate the time to access we consider the days between the end of negotiation procedure and the first purchase by regions. Results: In 2021 in Italy are available 94% of EMA authorized orphan drugs. The expenditure and consumption have grown during the last decade. The availability is higher in bigger regions, that also take care of patients from smaller regions. The pro capite expenditure and consumption in DDD/1,000 ab die is similar in all the geographic area. Time to regional access is on average 123 days, that grows to 224 excluding the orphan drugs dispensed before the end of reimbursement procedure.

Genetic Diversity of Grapevine Virus A in Three Australian Vineyards Using Amplicon High Throughput Sequencing (Amplicon-HTS).

Shiraz disease (SD) is one of the most destructive viral diseases of grapevines in Australia and is known to cause significant economic loss to local growers. Grapevine virus A (GVA) was reported to be the key pathogen associated with this disease. This study aimed to better understand the diversity of GVA variants both within and between individual SD and grapevine leafroll disease (LRD) affected grapevines located at vineyards in South Australia. Amplicon high throughput sequencing (Amplicon-HTS) combined with median-joining networks (MJNs) was used to analyze the variability in specific gene regions of GVA variants. Several GVAII variant groups contain samples from both vineyards studied, suggesting that these GVAII variants were from a common origin. Variant groups analyzed by MJNs using the overall data set denote that there may be a possible relationship between variant groups of GVA and the geographical location of the grapevines.

Innovative Research on Industrial Upgrading and Transformation Path of Regional Economy in the Perspective of Digital Economy

Abstract This paper utilizes the digital economy, regional spatial distribution digital mining technology, establishes the indicator system, assigns values to the indicators, and applies the indicator system to evaluate the development of industrial structure upgrading and transformation of the regional economy. According to the research results of the basic structure and algorithm of the self-organized neural network model, combined with the classification layer smoothing algorithm, the regional spatial clustering model is constructed. Using the constructed model, the regional economic spatial dynamic data is mined, and the path of industrial transformation and upgrading in the regional spatial area is dynamically studied. Furthermore, using the CA algorithm, the evolution law of land use structure in the region is predicted, and the development of the regional economy is inferred. At the same time, through the spatial autocorrelation regional prediction model, the relevant regional spatial expansion prediction method is proposed, the three research hypotheses of this paper are made, and the constructed model is utilized to innovate the exploration of industrial transformation and upgrading paths from the spatial dimension. Using empirical research methods, descriptive statistics, and mediating effect heterogeneity analysis are carried out to analyze the factors that influence regional economic variables in place A. The empirical analysis shows that the fluctuation range interval of industrial structure is between [0.811,10.2805], which brings a large positive impact on the regional economy.2017 national digital economic growth rate changed from -0.17446 to 0.17143 to realize a positive growth rate, and at the same time, there is a heterogeneity in the development of the east-west and central regions of A. The hypotheses presented in this paper are all valid.

Complete Chloroplast Genomes and the Phylogenetic Analysis of Three Native Species of Paeoniaceae from the Sino-Himalayan Flora Subkingdom.

Paeonia delavayi var. lutea, Paeonia delavayi var. angustiloba, and Paeonia ludlowii are Chinese endemics that belong to the Paeoniaceae family and have vital medicinal and ornamental value. It is often difficult to classify Paeoniaceae plants based on their morphological characteristics, and the limited genomic information has strongly hindered molecular evolution and phylogenetic studies of Paeoniaceae. In this study, we sequenced, assembled, and annotated the chloroplast genomes of P. delavayi var. lutea, P. delavayi var. angustiloba, and P. ludlowii. The chloroplast genomes of these strains were comparatively analyzed, and their phylogenetic relationships and divergence times were inferred. These three chloroplast genomes exhibited a typical quadripartite structure and were 152,687-152,759 bp in length. Each genome contains 126-132 genes, including 81-87 protein-coding genes, 37 transfer RNAs, and 8 ribosomal RNAs. In addition, the genomes had 61-64 SSRs, with mononucleotide repeats being the most abundant. The codon bias patterns of the three species tend to use codons ending in A/U. Six regions of high variability were identified (psbK-psbL, trnG-UCC, petN-psbM, psbC, rps8-rpl14, and ycf1) that can be used as DNA molecular markers for phylogenetic and taxonomic analysis. The Ka/Ks ratio indicates positive selection for the rps18 gene associated with self-replication. The phylogenetic analysis of 99 chloroplast genomes from Saxifragales clarified the phylogenetic relationships of Paeoniaceae and revealed that P. delavayi var. lutea, P. delavayi var. angustiloba, and P. ludlowii are monophyletic groups and sisters to P. delavayi. Divergence time estimation revealed two evolutionary divergences of Paeoniaceae species in the early Oligocene and Miocene. Afterward, they underwent rapid adaptive radiation from the Pliocene to the early Pleistocene when P. delavayi var. lutea, P. delavayi var. angustiloba, and P. ludlowii formed. The results of this study enrich the chloroplast genomic information of Paeoniaceae and reveal new insights into the phylogeny of Paeoniaceae.

Spatial Assessment and Variation of Soil Physicochemical Properties and Water Quality in the Tungi Watershed of Maharashtra, India

Aims: To thoroughly evaluate the spatial variability of soil physicochemical properties and groundwater quality of the study area by systematic collection and analysis of geo-referenced soil and groundwater samples to quantify the physical, chemical and biological attributes of the soil. The objective is to gain a comprehensive understanding of soil and water quality in the Tungi watershed, providing valuable insights to guide sustainable land and water management practices in the region.&#x0D; Place and Duration of Study: Department of Soil Science and Agricultural Chemistry, College of Agriculture, Latur between 2020 and 2021.&#x0D; Methodology: A total of one hundred geo-referenced surface soil samples (0-30 cm) and ten groundwater samples were methodically collected from the surrounding area of soil profiles in the Tungi watershed, situated in Latur, Maharashtra. Physical, chemical and biological properties of soil evaluated using recommended standard methods.&#x0D; Results: Bulk density varied from 1.13 to 1.93 Mg m-3, particle density from 2.48 to 2.94 Mg m-3 and porosity from 22 to 58 percent. Soil pH ranged from 7.05 to 8.96 and electrical conductivity was within the permissible range. Organic carbon content of soils ranged from 0.15 to 1.05 percent, with some soils having a calcareous character (0.6 to 22.2 percent). The analysis of nutrient content revealed variable quantities with available nitrogen ranging from 53.31 to 250.88 kg ha-1, available phosphorus from 12.51 to 27.49 kg ha-1, available potassium from 106.9 to 851.5 kg ha-1 and available sulphur from 4.37 to 66.65 mg kg-1. Exchangeable calcium and magnesium quantities revealed ranges of 14.60 to 42.40 cmol(p+) kg-1 and 5.40 to 21.60 cmol(p+) kg-1, respectively. Furthermore, DTPA extractable iron varied from 4.24 to 16.38 mg kg-1, manganese from 4.76 to 25.84 mg kg-1, zinc and copper from 0.5 to 6.56 mg kg-1 and 0.72 to 15.56 mg kg-1, respectively and boron from 0.1 to 3.56 mg kg-1. Microbial population estimates revealed the dominance of bacteria over fungi and actinomycetes in the studied area. Groundwater carbonate and bicarbonate ranged from 0.01 to 0.62 m mol-1 and 6.35 to 10.24 mmol-1 respectively. The dug well, bore well and tube well water RSC ranged from 0.70 to 1.25 mmol-1.&#x0D; Conclusion: This extensive study provides helpful insights into the regional variability of physical and chemical properties in both soil and water with help of soil fertility maps, providing better understanding of soil fertilizer input and environmental conditions in the Tungi watershed.

Modelling Maize Yield Vulnerability to Climate Variability

The effect of climate variability on maize yield has been the subject of numerous studies globally, but very few of these studies have focused on the local scale in Africa. As a result, the focus of this work is on creating a vulnerability index that combines sensitivity, exposure, and adaptive capacity to assess the degree of vulnerability of Maize yield to climate variability in the south-south region of Nigeria in West Africa. The ratio between the actual maize yield and the projected yield was used to calculate yield sensitivity. Adaptive capacity examines some of the socioeconomic and demographic factors in the study area. A fuzzy function was employed to derive the aggregation of the determinants of Adaptive Capacity (adult literacy, poverty prevalence, accessibility to the settlements of people, and dependency ratio). Exposure was expressed as the average of the long-term and short-term climatic factors (Rainfall and Temperature). Yield sensitivity ranges between 0.471 to 0.698 with moderate to high sensitivity observed in almost the entire growing region. Exposure values indicate a very high level of climate variability with the North of Edo to the Southeastern and Southwestern parts of the State being more exposed. Adaptive capacity is highly variable ranging from 0.174 to 1. The vulnerability index ranges from 0.393 to 0.698. The result indicates a very high to extremely high vulnerability on maize yield across the majority of growing regions in the south-south, which is an indication of a probable yield drop due to changing climate. This model provides a structure for decision-making and planning on climate variability mitigation needs assessment.

Modelling Maize Yield Vulnerability to Climate Variability

The effect of climate variability on maize yield has been the subject of numerous studies globally, but very few of these studies have focused on the local scale in Africa. As a result, the focus of this work is on creating a vulnerability index that combines sensitivity, exposure, and adaptive capacity to assess the degree of vulnerability of Maize yield to climate variability in the south-south region of Nigeria in West Africa. The ratio between the actual maize yield and the projected yield was used to calculate yield sensitivity. Adaptive capacity examines some of the socioeconomic and demographic factors in the study area. A fuzzy function was employed to derive the aggregation of the determinants of Adaptive Capacity (adult literacy, poverty prevalence, accessibility to the settlements of people, and dependency ratio). Exposure was expressed as the average of the long-term and short-term climatic factors (Rainfall and Temperature). Yield sensitivity ranges between 0.471 to 0.698 with moderate to high sensitivity observed in almost the entire growing region. Exposure values indicate a very high level of climate variability with the North of Edo to the Southeastern and Southwestern parts of the State being more exposed. Adaptive capacity is highly variable ranging from 0.174 to 1. The vulnerability index ranges from 0.393 to 0.698. The result indicates a very high to extremely high vulnerability on maize yield across the majority of growing regions in the south-south, which is an indication of a probable yield drop due to changing climate. This model provides a structure for decision-making and planning on climate variability mitigation needs assessment.

Spatio-temporal variability of climatic variables and its impacts on rice yield in Bangladesh

Bangladesh is a significant contributor to the global food basket but is also one of the most vulnerable countries to climate change. Understanding regional climatic variability helps reduce climate risks and ensure food security. This research examined monthly, seasonal, and yearly temperature, rainfall, and relative humidity in Bangladesh using data from 35 meteorological stations from 1970–2020. The study utilized the Mann–Kendall method to evaluate trends and employed Sen’s slope to quantify their magnitude. Additionally, quantile regression was applied to analyze the impact of climatic variables on rice yield. The findings revealed that maximum (Tmax) and minimum (Tmin) temperatures were steadily increasing, with the southwest experiencing a more rapid rise compared to other regions in Bangladesh. Seasonal Tmax and Tmin rose in most parts of Bangladesh, particularly during the monsoon. In most areas, there was a significant (p &amp;lt; 0.05) increase in Tmax from June to September and Tmin in December. The variability of minimum temperature was considerably affected by warming throughout the country. The eastern area had the most significant (p &amp;lt; 0.05) annual rainfall increase rate, while the northern region had the lowest. There was evidence of inter-seasonal rainfall shipment, with post-monsoon rainfall rising compared to monsoon season. The quantile regression showed that the rice yield of Aus (summer) and Aman (wet) seasons were influenced by maximum temperature and relative humidity, whereas the rice yield of the Boro (dry) season was affected by maximum temperature, rainfall, and relative humidity. Across geographical segmentation, the regression analysis indicated a high level of variability in the northern climate. Overall, the intensity of mean temperature increased throughout the country. So, there is a need to develop heat or drought-resistant rice varieties and modernized irrigation facilities to mitigate these climate risks. However, farmers should employ automated weather-based advisory services for sustaining rice productivity and food security.

Extending MESMER-X: a spatially resolved Earth system model emulator for fire weather and soil moisture

Abstract. Climate emulators are models calibrated on Earth system models (ESMs) to replicate their behavior. Thanks to their low computational cost, these tools are becoming increasingly important to accelerate the exploration of emission scenarios and the coupling of climate information to other models. However, the emulation of regional climate extremes and water cycle variables has remained challenging. The MESMER emulator was recently expanded to represent regional temperature extremes in the new “MESMER-X” version, which is targeted at impact-related variables, including extremes. This paper presents a further expansion of MESMER-X to represent indices related to fire weather and soil moisture. Given a trajectory of global mean temperature, the extended emulator generates spatially resolved realizations for the seasonal average of the Canadian Fire Weather Index (FWI), the number of days with extreme fire weather, the annual average of the soil moisture, and the annual minimum of the monthly average soil moisture. For each ESM, the emulations mimic the statistical distributions and the spatial patterns of these indicators. For each of the four variables considered, we evaluate the performances of the emulations by calculating how much their quantiles deviate from those of the ESMs. Given how it performs over a large range of annual indicators, we argue that this framework can be expanded to further variables. Overall, the now expanded MESMER-X emulator can emulate several climate variables, including climate extremes and soil moisture availability, and is a useful tool for the exploration of regional climate changes and their impacts.

Rural forested community shocks as perceived by in-migrants versus long-term residents

Rural communities face challenges and opportunities through changing relationships to natural resources that they depend on socially and culturally. Structural shifts in community-natural resource interactions may be expressed as “shocks”, or disruptions that create community change across multiple scales. These shocks may be isolated or connected events, and frequently have associated ripple effects. Our objectives were to (1) identify community shocks based on local resident perspectives, (2) evaluate regional variability of resident-perceived shock events, and (3) assess variation in perceptions of shocks between newer in-migrant and long-term residents. We used a mail survey to collect data from residents in rural New York, Ohio, Maine, and West Virginia (USA). Rather than starting with designated perspectives from past research, we used an inductive approach to identify shock events and their impacts. Categories of major shock events included, but were not limited to, employment loss, land transfers and designations, infrastructure development, loss of institutions, and natural disasters. Each community's history, shocks, and outcomes were uniquely place-dependent. Shocks identified and perception of them varied by residential tenure. Although identified similarly in a general sense by all respondents, details about individual shocks were more elaborately described by long-term residents, and in-migrants conveyed awareness of historical shocks. Conceptualizations of discrete, identifiable, and individual “shock” events are too simple and narrow for elucidating ongoing community perturbations that accumulate, counteract, and influence each other.

Remote impacts of low-latitude oceanic climate on coastal upwelling in a marginal sea of the Northwestern Pacific

Upwelling plays an important role in the physical processes and biological variability of coastal regions. Using 40-year-long hydrographic and climate data, the remote impacts of low-latitude oceanic climate on the upwelling along the east coast of Korea were investigated. During El Niño, the development of anomalously enhanced anti-cyclonic circulation over Northwestern Pacific resulted in relatively strong (∼1.1 m s−1) southerly winds, compared to La Niña. During El Niño, the mean upwelling index was 402 ± 106 kg m−1 s−1, and 10 °C isotherm was located at a depth of 32.7 m. During La Niña, they were 368 ± 95 kg m−1 s−1 and 39.9 m, respectively. During El Niño, in the approximation, the offshore Ekman transport by wind-induced upwelling and the vertical transport by isotherm were higher than those during La Niña. This finding can be explained by the increased sea surface height gradient, the subsequent enhanced geostrophic current, the decrease in onshore sea surface temperature, and the increase in chl-a concentration during El Niño. The intensity of upwelling tended to be stronger (weaker) during periods when El Niño (La Niña) and the PDO (Pacific Decadal Oscillation) were in phase than those when they were out of phase. These results suggest that low-latitude climate change could affect the coastal upwelling in the mid-latitude marginal sea through the teleconnection.

Empirical projection of global sea level in 2050 driven by Antarctic and Greenland ice mass variations

Global mean sea level rise, driven by ice mass loss in Antarctic and Greenland Ice Sheets (AIS and GrIS), is a significant consequence of global warming. Although various ice sheet models have attempted to predict the ice mass balance and subsequent sea level changes, non-trivial disagreements between models exist. In this study, we employ an empirical approach to estimate the future (2050) ice mass changes for both ice sheets, assuming their historical patterns of ice dynamics would persist in the coming decades. To achieve this, we estimate decadal-scale ice discharge variations by subtracting the surface mass balance (SMB) from the observed ice mass changes and extrapolate linear trend and acceleration components of ice discharges up to 2050. We also consider future SMB data from Coupled Model Intercomparison Project phase 6 models to estimate net ice mass balance. Our estimates suggest that from 2021 to 2050, the global sea level rise due to AIS and GrIS ranges between 6–19 mm and 15–31 mm, respectively. Additionally, we investigate regional sea level variability resulting from geoid changes induced by ice mass changes in both regions, highlighting that heterogeneous sea level changes may cause more pronounced sea level rises in lower latitude regions, where major cities are located.

Identification and quantification of nutrients sources in the Aspio watershed (Italy). Insight from geogenic mineralization and anthropogenic pressure

An accurate evaluation of river water quality could be challenging due to the complex hydrological and anthropogenic processes which affect its nature. Reliable water quality data are mandatory to identify long-term trends and regional variability at the watershed scale. In this study, a combined approach using time series, regression, and multivariate statistical analysis along with SWAT modelling was applied to identify the relevant hydrogeochemical processes and the nutrients sources within the Aspio watershed (Ancona, Italy). The analysis detected different processes: i) the geogenic origin of Cl- and SO42-, ii) the heavy metals (Cu and Ni) and hydrocarbons pollution due to runoff from urban and industrial areas, and iii) the agricultural contribution of pesticides, nitrogen, and phosphorous. A SWAT model was implemented to quantify the nutrients load in the Aspio river. A calibration for streamflow, river sediment yield, and for nutrients load was obtained considering agricultural, urban, and wastewater treatment plant contributions. Agriculture and treated wastewater contributed to the overall nitrogen load only for 4% and 12% respectively, while the majority was due to leakage from urban sewage (84%). A scenario with only fertilizers’ load (excluding other sources) highlighted that nitrogen and phosphorous export from agricultural lands did not significatively impact the Aspio river. The spatial representation of runoff susceptibility also showed how the highest susceptibility for nitrogen and phosphorous loads is due to areas located close to urban settlements.

Correlation of lifestyle behaviors during pregnancy with postpartum depression status of puerpera in the rural areas of South China.

Postpartum depression (PPD) is among the most common postpartum complications. Its prevalence is associated with strong regional variability. Women in rural areas of China have a high risk of PPD. The aim of this study was to investigate the PPD status of women in rural South China and explore the effects of modifiable lifestyle behaviors during pregnancy on their PPD status, thereby providing a scientific basis for the prevention and intervention of PPD in rural China. A cohort study was conducted on 261 women from four maternal health institutions situated in rural areas of Guangdong Province and the Guangxi Zhuang Autonomous Region from October 2021 to December 2022. The questionnaires were administered to these women to obtain data about sociodemographic characteristics, health literacy, physical activity during pregnancy, and sleep and dietary status during pregnancy, as well as depression status on the 42nd day after delivery. The lifestyle behaviors during pregnancy and the PPD status of the study population were analyzed. Multiple linear regression models were used to determine the correlation between lifestyle behaviors and PPD status. Path analysis was performed to explore the interaction between various lifestyle behaviors. A total of 14.6% of women had a PPD status. Women who continued to work during pregnancy had an Edinburgh Postpartum Depression Scale (EPDS) score of 1.386 points higher than that of women who did not (В = 1.386, β = 0.141, p = 0.029). For every 1-point increase in the infant feeding-related knowledge score and pregnancy diet diversity score, the EPDS score decreased by 0.188 and 0.484 points, respectively, and for every 1-point increase in the Pittsburgh sleep quality index score, the EPDS score increased by 0.288 points. Age was related to infant feeding-related knowledge (indirect path coefficient = 0.023). During pregnancy, sedentary time was correlated with sleep quality (indirect path coefficient = 0.031) and employment status (indirect path coefficient = 0.043). Employment status, infant feeding-related knowledge, sleep quality, and diet diversity during pregnancy directly influenced the PPD status, while age and sedentary time during pregnancy indirectly influenced the PPD status. Promoting healthy lifestyle behaviors, including reducing sedentary time, improving sleep quality, and increasing dietary diversity, may be effective in reducing PPD occurrence.

A new view of hillforts in the Andes: expanding coverage with systematic imagery survey

In the Andean highlands, hilltop fortifications known as pukaras are common. Dating predominantly to the Late Intermediate Period (AD 1000–1450), pukaras are important to archaeological characterisations of a political landscape shaped by conflict but the distribution of these key sites is not well understood. Here, the authors employ systematic satellite imagery survey to provide a contiguous picture of pukara distribution on an inter-regional scale covering 151 103km2 in the south-central highlands of Peru. They highlight the effectiveness of such survey at identifying pukaras and capturing regional variability in size and residential occupation, and the results demonstrate that satellite surveys of high-visibility sites can tackle research questions at larger scales of analysis than have previously been possible.

Indicators of primary disability in children with mental disorders and autism in St. Petersburg and the Voronezh region

BACKGROUND: Mental disorders (including autism) in the Russian Federation rank first among all classes of diseases that form the primary disability in children. Analysis of the state and dynamics of the indicators of primary childhood disability due to this pathology, considering age-specific features, is the basis for further development of medical and social expertise, rehabilitation, and disability prevention.&#x0D; AIMS: To analyze the state and dynamics of indicators of primary childhood disability caused by mental disorders and autism in St. Petersburg and the Voronezh Oblast.&#x0D; MATERIALS AND METHODS: The study enrolled children who were recognized to have a disability for the first time caused by mental disorders and autism in St. Petersburg and Voronezh Oblast for 2016–2021. Data sources included statistical collections of the Federal State Statistics Service and forms of state statistical reporting 7-D (sobes). The study is longitudinal and continuous. Analytical, documentary, data copying, statistical, and graphic research methods were employed.&#x0D; RESULTS: Indicators of primary childhood disability caused by mental disorders and autism are important criteria for the effectiveness of rehabilitation (habilitation) measures. The regional variability and growth of the number and level of IDD among the residents of the Russian Federation was revealed, reaching a maximum in St. Petersburg in 2021 (8.5 per 10 thousand pediatric population) and in the Voronezh region in 2019 (8.2 per 10 thousand pediatric population), which exceeded the all-Russian indicators. The level of autism-related primary childhood disability in 2016–2021 varied in the following ranges: from 0.5 to 0.7 in St. Petersburg (1.4-fold increase), from 2.4 to 1.2 in Voronezh Oblast (2-fold decrease), and from 1.4 to 2.0 per 10,000 children population (1.4-fold increase) in the Russian Federation. The results revealed the dependence of fluctuations in the rates of primary childhood disability caused by mental disorders and autism on changes in the normative legal framework for establishing disability.&#x0D; CONCLUSION: The data obtained on the regional peculiarities of the dynamics and state of primary childhood disability caused by mental disorders and autism in St. Petersburg and Voronezh Oblast should be used to develop priority directions of medical and social assistance for the prevention of primary childhood disability at the level of regional healthcare organizations.