Local Geographical Characteristics Research Articles

Biometeorological feedbacks on peatlands: Raising the water table to reduce meteorologically-related stress on cattle

Peatland restoration is an important mitigation action in the fight against climate change. Researchers encourage farmers to rewet deep-drained lands on organic soil to a shallow water table depth (WTD) to reduce carbon emissions. Raising WTD under grasslands will likely affect local air temperature (TA) and increase relative humidity (RH), with uncertain consequences during heat waves on cattle welfare. We used WTD, TA and RH data (both measured between 1.25 and 2 m above ground) from 22 peatland sites globally to evaluate peatlands’ overall Temperature Humidity Index (THI), an indicator correlated to cattle welfare used in dairy farms (THI>68 increases heart rate, breathing rate and reduces milk yield). We compared them with THI at state weather stations located on neighbouring lands with short grass on non-organic soil, and assessed the impact of WTD.At most sites, peatlands with shallow WTD had lower TA, higher RH, and an overall lower THI than surrounding lands, compared to those with deep WTD. In most cases, THI decreased with increasing WTD, especially at night in the temperate region, except for coastal peatlands. Shallow and submerged sites had 20 % less hours with stressful meteorologic conditions (high THI) than surrounding areas. In contrast, the number of hours with high THI did not change significantly on peatlands with WTD under 20 cm below ground level compared to control sites. Our results confirm the influence of WTD on local temperature and THI, and suggest that raising WTD on drained peatlands will slightly improve cattle welfare with reduced THI during heat waves, but also acknowledge that local geographic characteristics add complexity to this relationship. Our research indicates that raising WTD to ground level in sections of grasslands could provide “heat wave shelters” and increase cattle resilience to climate change while contributing to the global reduction of carbon emissions.

Study on the Geographical Spatial Characteristics of Forest Health Resorts in Fujian Province, China

Forest health tourism is an increasingly popular new form of tourism. Fujian Province, with its abundant forest resources, ranks among the top provinces in China in terms of forest coverage and holds significant development potential. The study focuses on 80 provincial-level forest health resorts in Fujian Province, China. Software such as the ArcGIS geographic information system is used to analyze the resorts’ nearest neighbor index, geographic concentration index, kernel density, etc., thus indicating their spatial distribution characteristics. Overlay analysis, correlation analysis, and fitting analysis are employed to explore the spatial distribution specificity and its influencing factors. The research results indicate that forest health resorts in the area exhibit an aggregated distribution with a higher overall concentration. They are influenced by factors such as the distribution of river systems, the accessibility of transportation, distance to central cities, and socio-economic conditions. The geographic concentration index (G) is 50.28 and the unevenness index (S) is 0.640, both indicating that the forest health resorts in Fujian Province demonstrate a distribution pattern of “overall dispersion with multiple core aggregations”. Based on the research findings, the article puts forward some policy insights. Taking into account the local geographical characteristics, it advocates for the rational development of forest health resort industry models suitable for the region. It suggests incorporating innovative ideas into the forest health resort industry in order to broaden development channels. Additionally, it emphasizes the importance of close collaboration between the government and the market for mutual development.

Landscape Design in the Perspective of Rural Revitalization

Rural revitalization is a strategic plan proposed in the report of the 19th National Congress of the Communist Party of China, aimed at solving the three rural issues in China. Therefore, it is also one of the strategic plans that China should focus on implementing in the future stage. In the perspective of implementing rural revitalization, it is a common strategy to help local areas develop the tourism industry, thereby driving the improvement of local economic benefits through tourism. In fact, the vast majority of rural areas have a certain potential for tourism development. Landscape design is a key approach to tapping into its potential and helping rural areas establish sustainable economic profit models. However, whether landscape design can play its advantageous role depends on the compatibility between landscape design and local geographical characteristics and culture, as well as whether the landscape can match the existing development models in the local area. That is to say, it is necessary to create new development opportunities and effectively link new development with local production and life, so as to achieve the fundamental goal of helping local economy generate income without affecting the quality of life of local residents.

Assessment of Urban Forest Ecological Benefit Based on the i-Tree Eco Model—A Case Study of Changchun Central City

Urban forests are one of the most ecologically significant systems in urban ecosystems. To make the layout and input–output ratio of urban forests more economically rational for sustainable strategic planning, it is necessary to assess the ecological benefits and ecosystem services of urban forests according to the local geographical characteristics of different cities and analyse their cost–benefit relationships. In this study, the i-Tree Eco model was used to assess the ecological benefits of urban forests in terms of four aspects: carbon sequestration and oxygen release, energy saving, rainwater retention, and air quality improvement. To translate them into economic benefits, using mathematical and statistical analysis, the cost–benefit relationship of urban forests with different tree and shrub proportions was analysed, and the impact range of urban forests with different layout types was compared. The research found that: (1) tree species are the main influencing factor of urban forest ecological benefits, (2) linear urban forests have a wider impact range, (3) if the proportion of trees in urban forests in the research area is adjusted to 0.36, the ecological benefits can increase by RMB 0.061 billion per year. We provide efficient and convenient research paths and tools for studying the cost–benefit relationship. By using an i-Tree Eco model, we realized the economic characteristics of urban forests. This research provides quantitative support for the balanced construction of urban ecological civilization and economic benefits. It can provide quantitative support for a balance between urban ecological development, economic development, and spatial optimization.

Site Selection via Learning Graph Convolutional Neural Networks: A Case Study of Singapore

Selection of store sites is a common but challenging task in business practices. Picking the most desirable location for a future store is crucial for attracting customers and becoming profitable. The classic multi-criteria decision-making framework for store site selection oversimplifies the local characteristics that are both high dimensional and unstructured. Recent advances in deep learning enable more powerful data-driven approaches for site selection, many of which, however, overlook the interaction between different locations on the map. To better incorporate the spatial interaction patterns in understanding neighborhood characteristics and their impact on store placement, we propose to learn a graph convolutional network (GCN) for highly effective site selection tasks. Furthermore, we present a novel dataset that encompasses land use information as well as public transport networks in Singapore as a case study to benchmark site selection algorithms. It allows us to construct a geospatial GCN based on the public transport system to predict the attractiveness of different store sites within neighborhoods. We show that the proposed GCN model outperforms the competing methods that are learning from local geographical characteristics only. The proposed case study corroborates the geospatial interactions and offers new insights for solving various geographic and transport problems using graph neural networks.

Availability of Medications for the Treatment of Alcohol Use Disorder in U.S. Counties, 2016–2019

Although numerous studies have examined the geographic availability of medications for opioid use disorder, none have measured the availability of medications for alcohol use disorder (MAUD) in the United States. We examined county-level trends in MAUD offerings in the specialty substance use disorder treatment system and compared MAUD availability with local geographic characteristics and alcohol use disorder treatment need. We constructed annual county-level measures of MAUD availability for 2016-2019 using the National Directory of Drug and Alcohol Abuse Treatment Facilities, determining the number of outpatient facilities offering MAUD in each county (n = 12,568). Two-part, multivariable regression models estimated the association between MAUD availability and temporal trends, census region, urbanicity, and prevalence of excessive drinking. Availability of MAUD increased significantly over the study period. By 2019, 38% of U.S. facilities offered at least one MAUD, 40% of counties had at least one specialty treatment facility offering MAUD, and counties with at least one facility had an average of 3.36 MAUD facilities. Availability was significantly higher in urban counties and in the Northeast (both p < .01), but not in counties with higher prevalence of excessive drinking. We observed large increases in the availability of MAUD in the U.S. specialty treatment system from 2016 to 2019. Although these results are encouraging, a majority (60%) of U.S. counties did not have a specialty outpatient treatment facility that offered MAUD in 2019. Additional efforts are needed to improve availability of MAUD, especially in rural counties and in the southern and midwestern United States.

Significance of specially protected nature areas in protection of resource potential of urbanized regions (the case of Volgograd region)

Strengthening of the functional role of cities in the development of regions is always associated with a change in local geographical characteristics connected with the joining of the areas beyond the fixed boundaries of urbanized territories. As a result of this process, the areas occupied by natural ecosystems are reduced, new resources are involved into the technogenic use, and the natural potential of the neighboring territories is exhausted and depleted. That is why such a method of resources’ protection as conservation of nature areas is of a particular importance for the regions with a high level of urbanization, for example, Volgograd region. The main idea of the article determined the logic and methods of research. The cartographic analysis made it possible to distinguish specially protected nature areas of the region according to their location in respect of urbanized administrative entities. On the basis of the statistical processing of the data found in the reports of the authorized regional authority, the current state and dynamics of development of specially protected nature areas are found according to categories, level of subordination, number, areas, types of resources’ diversity. Particular attention is paid to the degree of vulnerability and to the threats of the impact of human activity on nature and resource potential of specially protected nature areas when the cities are spatially planned. Attention is also paid to the ways of protection from negative effects. The study showed that the limitation of anthropogenic processes within the boundaries of specially protected nature areas makes it possible to preserve thousands of biological resources from destruction, protect hundreds of water sources from pollution, and provide a compliance of “friendly” human habitat to industrial and technological requirements. As a result, the article proves high importance of specially protected nature areas as a way of conservation of the natural potential of Volgograd region. It also determines the relevant tasks of security activities and methods for its effectiveness growth.

Predictive modelling of mesophotic habitats in the north‐western Gulf of Mexico

Abstract Effective management of marine resources requires an understanding of the spatial distribution of biologically important communities. The north‐western Gulf of Mexico contains diverse marine ecosystems at a large range of depths and geographic settings. To better understand the distribution of these marine habitats across large geographic areas under consideration for marine sanctuary status, presence‐only predictive modelling was used. Results confirmed that local geographic characteristics can accurately predict the probability of occurrence for marine habitat types, and include a novel technique for assigning a single, most likely habitat in areas where multiple habitats are predicted. The highest resolution bathymetric data (10 m) available for the region was used to develop raster layers that represent characteristics that have been shown to influence species occurrence in other settings. A georeferenced historical photo record collected via remotely operated vehicle was classified according to six commonly found mesophotic habitats across the 18 reefs and banks under consideration for Flower Garden Banks National Marine Sanctuary boundary expansion. Using maximum entropy modelling, the influence of local geographic characteristics on the presence of these habitats was measured and a spatial probability distribution was developed for each habitat type across the study area.

Comparative Analysis of Rainfall Prediction Models Using Machine Learning in Islands with Complex Orography: Tenerife Island

We present a comparative study between predictive monthly rainfall models for islands of complex orography using machine learning techniques. The models have been developed for the island of Tenerife (Canary Islands). Weather forecasting is influenced both by the local geographic characteristics as well as by the time horizon comprised. Accuracy of mid-term rainfall prediction on islands with complex orography is generally low when carried out with atmospheric models. Predictive models based on algorithms such as Random Forest or Extreme Gradient Boosting among others were analyzed. The predictors used in the models include weather predictors measured in two main meteorological stations, reanalysis predictors from the National Oceanic and Atmospheric Administration, and the global predictor North Atlantic Oscillation, all of them obtained over a period of time of more than four decades. When comparing the proposed models, we evaluated accuracy, kappa and interpretability of the model obtained, as well as the relevance of the predictors used. The results show that global predictors such as the North Atlantic Oscillation Index (NAO) have a very low influence, while the local Geopotential Height (GPH) predictor is relatively more important. Machine learning prediction models are a relevant proposition for predicting medium-term precipitation in similar geographical regions.

Carbon Sequestration Anticipation Response to land use change in a mountainous karst basin in China

The present article reports an assessment of afforestation potential and anticipation of carbon sequestration in the Houzhai River Basin in Guizhou Province in southwestern China. Total of 2755 soil profiles consisting of 22,057 soil samples were collected according to a grid-sampling method at a 150 m scale in the Houzhai River basin, and the SOC contents in soil samples were analyzed using a titration method. General information regarding the geographic characteristics of each sampling grid was recorded in the field. The results indicate that land use in the Houzhai River Basin is very complex. Land use status and land use change in the study area were closely associated with local geographic characteristics and variations in economic structures. There were approximately 15.26 km2 of land that could or should be rearranged as afforestation land in the Houzhai River Basin. The increased SOC storage (0.00–1.00 m soil horizon) would be up to 5.48 × 104 Mg, 6.42 × 104 Mg, 4.77 × 104 Mg and 3.18 × 104 Mg when all of the calculated lands became shrub-grass lands, shrub lands, arbor-shrub forest lands and arbor forest lands, respectively. The increased SOC percentages would be 52.16%, 61.13%, 45.39% and 30.32%, respectively, in comparison with the present SOC storage in these lands.

Stability of the HTLV-1 glycoprotein 46 (gp46) gene in an endemic region of the Brazilian Amazon and the presence of a significant mutation (N93D) in symptomatic patients

BackgroundThe human T-lymphotropic virus type 1 (HTLV-1) affects 2–5 million people worldwide, and is associated with a number of degenerative and infectious diseases. The Envelope glycoproteins (gp) are highly conserved among the different HTLV-1 isolates, although nucleotide substitutions in the region that codifies these proteins may influence both the infectivity and the replication of the virus. The gp46 gene has functional domains which have been associated with the inhibition of the formation of the syncytium, cell-cell transmission, and the production of antibodies. The present study investigated the genetic stability of the gp46 gene of HTLV-1 in an endemic region of Brazilian Amazonia.MethodsIndex case (IC - a sample of a given family group) carriers of HTLV-1 were investigated in the metropolitan region of Belém (Pará, Brazil) between January 2010 (registered retrospectively) and December 2015. The sequences that codify the gp46 were amplified by PCR, purified and sequenced (MF084788–MF084825). The gene was characterized using bioinformatics and Bayesian Inference.ResultsThe 40 patients analyzed had a mean age of 45.2 years and 70% presented some type of symptom, with a predominance of pain and sensitivity, dysautonomia, and motor disorders. All patients presented the aA (Transcontinental Cosmopolitan) genotype, with an extremely low mutation rate, which is characteristic of the codifying region (aA – 1.83 × 10–4 mutations per site per year). The gp46 gene had a nucleotide diversity of between 0.00% and 2.0%. Amino acid mutations were present in 66.6% of the samples of individuals with signs/symptoms or diseases associated with HTLV-1 (p = 0.0091). Of the three most frequent mutations, the previously undescribed N93D mutant was invariably associated with symptomatic cases.ConclusionsThe aA HTLV-1 subtype is predominant in the metropolitan region of Belém and presented a high degree of genetic stability in the codifying region. The rare N93D amino acid mutation may be associated with the clinical manifestations of this viral infection.ImportanceLittle is known of the phylogeny of HTLV-1 in the endemic region of Brazilian Amazonia, and few complete gene sequences are available for the gp46 glycoprotein from the local population. The nucleotide sequences of the viral gp46 gene recorded in the present study confirmed the genetic stability of the region, and pointed to a homogeneous viral group, with local geographic characteristics. Further research will be necessary to more fully understand the molecular diversity of this protein, given the potential of this codifying region as a model for an effective HTLV-1 vaccine. The identification of a rare mutation (N93D), present only in symptomatic patients, should also be investigated further as a potential clinical marker.Trial registrationISRCTN 12345678, registered 28 September 2014.

Constraints to achieve infrastructure sustainability for mountainous townships in China

This paper investigates the constraints to achieving optimal infrastructure sustainability for mountainous townships in Southwest China. Although such townships are relatively less developed, it is well recognized that investment in infrastructure projects in less developed townships plays a vital role in China's sustainable development mission. While the benefits of infrastructure investments are usually measured by means of economic performance, their long-term sustainability performance is largely overlooked. It is therefore imperative to understand the constraints that impede infrastructure sustainability and what corrective actions can be taken. The constraints are identified in this study via exploratory factor analysis and structural equation modeling. Twenty-one townships in the mountainous regions of Southwest China were investigated by means of a questionnaire survey. The study reveals that the major constraints include four dimensions: “Economic Capacity”, “Governance and Management”, “Policy Instrument and Public Participation”, and “Local Geographic Characteristics”. Identification of these constraints provides a valuable reference for local governments to take adequate measures to ensure that their infrastructure sustainability can be improved.

Simple scaling of extreme precipitation in North America

Abstract. Extreme precipitation is highly variable in space and time. It is therefore important to characterize precipitation intensity distributions on several temporal and spatial scales. This is a key issue in infrastructure design and risk analysis, for which intensity–duration–frequency (IDF) curves are the standard tools used for describing the relationships among extreme rainfall intensities, their frequencies, and their durations. Simple scaling (SS) models, characterizing the relationships among extreme probability distributions at several durations, represent a powerful means for improving IDF estimates. This study tested SS models for approximately 2700 stations in North America. Annual maximum series (AMS) over various duration intervals from 15 min to 7 days were considered. The range of validity, magnitude, and spatial variability of the estimated scaling exponents were investigated. Results provide additional guidance for the influence of both local geographical characteristics, such as topography, and regional climatic features on precipitation scaling. Generalized extreme-value (GEV) distributions based on SS models were also examined. Results demonstrate an improvement of GEV parameter estimates, especially for the shape parameter, when data from different durations were pooled under the SS hypothesis.

Agglomeration effects, institutions, and natural resources in the changing economic geography of Russia

The paper discusses a number of hypotheses as potential explanations of the spatial income distribution in Russia. The hypotheses include the increasing return hypothesis, the institutions hypothesis and the simple and sophisticated versions of the geography hypothesis. According to the existing evidence, the sophisticated geography hypothesis fits best Russian data. This suggests that the changes in spatial income distribution follow the changes in local geographical characteristics and in their economic value.

Investigation of disputes’ resolving over ecclesiastical and monastic land property in Greece using cadastral and land use data

Land disputes are among the primary issues that Land Administration Systems attempt to accommodate. They derive from a variety of purposes including law, history, culture, traditions, administration and local geographical characteristics. There is no uniform approach in addressing land disputes and each country implements different resolution techniques. Ecclesiastical and monastic institutions throughout the world are owners of immense real estate property to such an extent that can indeed affect land administration policies. Greece is in the limelight of international attention due to its economical crisis and actually under pressure to modernise its dysfunctional land policy framework and create a stable investment environment. Within this framework, this paper investigates issues hindering proper land administration in Greece through the examination of a the resolving process regarding a case study in the island of Crete; a complex legal land dispute between the Greek State, two ecclesiastical institutions, a monastery and a church, and squatters took place, lasting for nearly 40 years. In order to evaluate this procedure and its impact on the development of the disputed area, a variety of data sources were accumulated and processed through time-based analysis. In this direction, cadastral survey’s contribution was examined along with land use change analysis, indicating how uncertainties in securing property rights on land, result in illegalities and trespassing posing significant barriers in land administration and management in the course of time. Although old and ambiguous in describing land boundaries the monasterial documentation might be, it proved sufficient to prevail over other litigants claims; the monastery was even adjudicated more than twice the size of the area that was claiming. By this investigation process, the distinct role of ecclesiastical institutions in Greece regarding land acquisition and the defects and malfunctions within Greek Land Administration System are presented. The paper concludes with the authors’ suggestions for addressing similar real estate property situations concerning land disputes.

Maximizing net benefits for conventional and flexible bus services

Transit ridership is usually sensitive to fares, travel times, waiting times, and access times, among other factors. Therefore, the elasticities of demand with respect to such factors should be considered in modeling bus transit services and must be considered when maximizing net benefits (i.e. “system welfare”=consumer surplus+producer surplus) rather just minimizing costs. In this paper welfare is maximized with elastic demand relations for both conventional (fixed route) and flexible-route services in systems with multiple dissimilar regions and periods. As maximum welfare formulations are usually too complex for exact solutions, they have only been used in a few studies focused on conventional transit services. This limitation is overcome here for both conventional and flexible transit services by using a Real Coded Genetic Algorithm to solve such mixed integer nonlinear welfare maximization problems with constraints on capacities and subsidies. The optimized variables include service type, zone sizes, headways and fares. We also determine the maximum welfare threshold between optimized conventional and flexible services) and explore the effects of subsidies. The proposed planning models should be useful in selecting the service type and optimizing other service characteristics based on local geographic characteristics and financial constraints.

B2-1: Estimation of Standardized Hospital Costs from Claims Data that Reflect Resource Requirements for Care

Background/Aims Payments to hospital providers are not solely driven by the resource requirements of individual patients, but also reflect payment policies specific to the health care payer and hospital provider. For example, Medicare adjusts payments to hospitals according to facility and local geographic characteristics that may not be relevant to studies estimating the associations of individual patient characteristics with true costs of care. We developed a method to estimate hospital costs using the diagnosis related group (DRG) payment weights on which Medicare bases hospital payments that reflect patient medical and surgical acuity. Our purpose was to compare cost estimates for hospital stays calculated using DRG payments weights to actual Medicare hospital payments.

The Protestant Legacy: Missions and Literacy in India

As an important expression of culture, religion represents a possible fundamental source of economic and social outcomes. This paper investigates how the historical development of Protestantism may contribute to explain current literacy disparities in India. In order to enable everyone to read the Bible by themselves, Protestants have always stressed the importance of promoting universal literacy. Combining information about the spatial distribution of Protestant missions in India at the end of the nineteenth century with contemporary district-level data, this paper documents a strong long-term relationship between the historical exposure to Protestant missions and current literacy. This pattern does not depend on either local geographic characteristics or the level of historical development of the districts. By exploiting only the variation within groups of geographically contiguous districts and using historical Catholic missions as control group, I verify that this relationship is not driven by unobserved characteristics that may affect both current literacy outcomes as well as the missionaries’ location decisions.

Estimation of Standardized Hospital Costs from Medicare Claims That Reflect Resource Requirements for Care: Impact for Cohort Studies Linked to Medicare Claims

To compare cost estimates for hospital stays calculated using diagnosis-related group (DRG) weights to actual Medicare payments. Medicare MedPAR files and DRG tables linked to participant data from the Study of Osteoporotic Fractures (SOF) from 1992 through 2010. Participants were women age 65 and older recruited in three metropolitan and one rural area of the United States. Costs were estimated using DRG payment weights for 1,397 hospital stays for 795 SOF participants for 1year following a hip fracture. Medicare cost estimates included Medicare and secondary insurer payments, and copay and deductible amounts. The mean (SD) of inpatient DRG-based cost estimates per person-year were $16,268 ($10,058) compared with $19,937 ($15,531) for MedPAR payments. The correlation between DRG-based estimates and MedPAR payments was 0.71, and 51 percent of hospital stays were in different quintiles when costs were calculated based on DRG weights compared with MedPAR payments. DRG-based cost estimates of hospital stays differ significantly from Medicare payments, which are adjusted by Medicare for facility and local geographic characteristics. DRG-based cost estimates may be preferable for analyses when facility and local geographic variation could bias assessment of associations between patient characteristics and costs.

Study of Traditional Tibetan Architectural Material and Security

Yushu earthquake, Qinghai province seriously damaged the local Tibetan traditional buildings. With the local geographical characteristics and religious significance of the Tibetan traditional architecture, post-disaster reconstruction should inherit the local people's cultural tradition as well as create a positive, intimate space, so that the victims could re-feel the sense of their original homeland. Therefore, with the premise of respecting local customs and traditions, this paper argued that applying the advanced disaster-resistant construction techniques and materials performance into the design could improve the security, stability as well as highlighting the regional characteristics.