Municipal Scale Research Articles

Correlations and dominant climatic factors among diversity patterns of plant families, genera, and species

At present, the relationship between the diversity distribution patterns of different taxonomic levels of plants and climatic factors is still unclear. This paper explored the diversity pattern of vascular plant families, genera, and species in China at the municipal scale. It also studied the effects of accumulated temperature ≥ 10°C, annual precipitation, and hydrothermal base which reflect the effect of hydrothermal resources on the plant diversity pattern. The results showed that: There were extremely significant correlations among the diversities of plant families, genera, and species, and the interpretation degree of diversity between adjacent the taxonomic levels was more than 90%. The diversity pattern of plant families was mainly affected by dominant climatic state indicators such as the maximum value of accumulated temperature, annual precipitation, and hydrothermal base, and the gradient range of the hydrothermal base, which showed a clear latitudinal gradient law. The diversity pattern of plant species was found to be mainly dependent on the climatic heterogeneity indicators, being closely related to the heterogeneity indicators and sum indicators of the hydrothermal base. It was also affected by the range of precipitation gradient range. Plant genus and its diversity pattern are not only significantly affected by heterogeneity and sum indicators but also closely related to climate state indicators. In comparison with the humidity index in vegetation ecological studies, the related indicators of the hydrothermal base proposed in this paper excelled at revealing the relationship between climate and diversity patterns of plant families, genera, and species, and could effectively solve the species-area relationship issue in arid and low-temperature areas. The results of this paper have presented important theoretical and practical values for comprehensively understanding the correlation between climate and diversity of plant families, genera, and species, clarifying the impact of climate difference and climate change on plant diversity.

Ecosystem Services Supply from Peri-Urban Landscapes and Their Contribution to the Sustainable Development Goals: A Global Perspective

Peri-urban landscapes (PULs) play an important role in the supply of ecosystem services (ES), which support development and well-being in urban and rural areas. Understanding the impacts of policy actions on the supply of ES and how they might contribute to the achievement of a range of sustainable development goals (SDG) is a key challenge, especially for spatial planning. The aim of this article is to explore the links between the ES supply from PULs and how they support different SDGs from a global perspective. For this, we implemented a review of the literature oriented to identify (1) the most relevant ES provided by PULs at a global level, (2) how they support the achievement of different SDG, and (3) the type of policy interventions and actors related to PULs. We identified the supply of 17 different ES by PULs and a relationship to 12 SDGs. In 58% of the cases, the SDGs were related to two ES sections, where regulation and maintenance was dominant. Pure research was the main type of intervention, mainly at the municipal scale. Increasing the cooperation between science and policy and expanding the scale of analysis beyond municipal boundaries are critical aspects.

Incorporating uncertainty from downscaled rainfall projections into climate resilience planning in U.S. cities

The planning, design, and maintenance of stormwater infrastructure must be informed by changing rainfall patterns due to climate change. However, there is little consensus on how future climate information should be used, or how uncertainties introduced by use of different methods and datasets should be characterized or managed. These uncertainties exacerbate existing challenges to using climate information on local or municipal scales. Here we analyze major cities in the U.S., 48 of which developed climate adaptation and resilience plans. Given the prevalence of depth duration frequency (DDF) curves for planning infrastructure for rainfall, we then assessed the underlying climate information used in these 48 plans to show how DDF curves used for resilience planning and the resulting outcomes can be affected by stakeholders’ methodological choices and datasets. For rainfall extremes, many resilience plans varied by trend detection method, data preprocessing steps, and size of study area, and all used only one of the available downscaled climate projection datasets. We evaluate the implications of uncertainties across five available climate datasets and show the level of climate resilience to extreme rainfall depends on the dataset selected for each city. We produce risk matrices for a broader set of 77 U.S. cities to highlight how local resilience strategies and decisions are sensitive to the climate projection dataset used in local adaptation plans. To help overcome barriers to using climate information, we provide an open dataset of future daily rainfall values for 2-, 5-, 10-, 25-, 50-, and 100 years annual recurrence intervals for 77 cities and compare resilience outcomes across available climate datasets that each city can use for comparison and for robust resilience planning. Because of uncertainty in climate projections, our results highlight the importance of no-regret and flexible resilience strategies that can be adjusted with new climate information.

A ten-year (2009–2018) database of cancer mortality rates in Italy

In Italy, approximately 400.000 new cases of malignant tumors are recorded every year. The average of annual deaths caused by tumors, according to the Italian Cancer Registers, is about 3.5 deaths and about 2.5 per 1,000 men and women respectively, for a total of about 3 deaths every 1,000 people. Long-term (at least a decade) and spatially detailed data (up to the municipality scale) are neither easily accessible nor fully available for public consultation by the citizens, scientists, research groups, and associations. Therefore, here we present a ten-year (2009–2018) database on cancer mortality rates (in the form of Standardized Mortality Ratios, SMR) for 23 cancer macro-types in Italy on municipal, provincial, and regional scales. We aim to make easily accessible a comprehensive, ready-to-use, and openly accessible source of data on the most updated status of cancer mortality in Italy for local and national stakeholders, researchers, and policymakers and to provide researchers with ready-to-use data to perform specific studies.

Spatial disparity and structural inequality in disability patterns across Tianjin municipality: A multiple deprivation perspective

Reducing the spatial disparities and structural inequalities faced by disabled people is a global challenge in both developed and developing countries that requires an understanding of disability-driven deprivation. This study aims to develop and validate a conceptual framework for analysing the structural inequality and spatial disparity of disability-related deprivation. To achieve this goal, an Index of Disability-Related Multiple Deprivation (IDMD) based on six specific domains, including employment, education, marital status, health, services and barrier-free environments, is proposed. The IDMD was calculated at the sub-district level within the Tianjin municipality using aggregated registration information from the Tianjin Disability Database in 2020. Principal component analysis (PCA) was used to assign the weight of each indicator of IDMD. Moran I and LISA analysis were used to quantify the spatial disparity of IDMD across the municipality. Multi-Scale Geographically Weighted Regression (MGWR) was used to model the structural factors shaping the spatial disparity of disability-related deprivation in terms of gender, age, and disability types. Three key findings have been generated as follows. The spatial variability of IDMD revealed significant urban-rural disparity across the municipality, highlighting the difficulties faced by vulnerable and disadvantaged disabled people in rural areas. Men, working age groups and those with intellectual disability contributed most to the structural inequalities of IDMD. Thirdly, the location of greatest deprivation varied for different groups; working age groups faced the highest levels of deprivation in the urban centre, males faced the most deprivation in the urban fringe and those with intellectual, limb, visual, speech or mental disabilities were most deprived in rural areas. These findings reflect the complexity of structural factors affecting disability-related deprivation at the municipality scale. This study points to the need for informed, targeted welfare facilities planning and management strategies to improve spatial equity and social justice for disabled people.

Comprehensive evaluation on water resources carrying capacity based on water-economy-ecology concept framework and EFAST-cloud model: A case study of Henan Province, China

Water is the basic need for human survival and the development of economy and ecology. Water resources carrying capacity (WRCC) modelling is a fundamental task to explore the interaction mechanism between economy-ecology development and water resources carrying system. To reasonably quantify the regional WRCC, an evaluation method based on Water-economy-ecology (WEE) concept framework and EFAST-Cloud model is proposed in this study, and Henan Province of China is selected as a typical study area. It can both identify the inter-feeding relationships between sub-systems and evaluate the proportion of each grade in detail by reflecting the randomness and fuzziness of the evaluation. A total of 15 indicators including water system, economy system, and ecology system are constructed. The study analyzes the sensitivity of indicators by using Simlab software and then calculates the weight of indicators by using EFAST method. Compared with other traditional methods, EFAST algorithm is a special method for model sensitivity analysis, which can fully consider the coupling effect between indicators. According to the statistical data of 2010, 2015, and 2020, the WRCC at the watershed scale and municipal scale in Henan Province are evaluated through the EFAST-Cloud model. At the watershed scale, the ecology system criterion layer performs best over the multiple years, the Huaihe and Yangtze River basin have better WRCC at the target layer. At the municipal scale, Xuchang, Luohe, and Zhumadian have better WRCC, Puyang, Zhoukou, and Jiaozuo are slightly worse. The results show that WRCC of the study area has shown an overall improvement, but there is still much space for its development. Therefore, targeted recommendations are made for the water, economy, and ecology system respectively. The conclusion of this paper can provide a reference for the government in making water resources management policies.

Capitalism, Protectionism, and Beer Wars in Rock Island, 1880–1900

Capitalism, Protectionism, and Beer Wars in Rock Island, 1880–1900

Review of open space rules and regulations and identification of specificities for plot-level open spaces to facilitate sustainable development: An Indian case

Rapid urbanization and an increase in the alteration of natural resources have led to climate crises, driving the need to promote sustainable development. Urban open space management plays a vital role in such scenarios. Research on urban open spaces has been mainly conducted at regional, municipal, and neighborhood scales. Rarely has the focus been on the plot-level potentials and management of open spaces. Therefore, the study looks into the Indian development control rules and regulations and identifies that although these stipulate the percentage of open space for development on each plot, specificities for open spaces are unclear. Further, the study analyses quantitative and qualitative aspects of open spaces for selected group housing schemes in Pune city. The inquiry shows that per capita open space in Pune is comparatively lower than national standards. The quantitative aspects include FSI, building ground coverage, built-up area, number of floors, and number of dwelling units, and each relates to open spaces in one way or another. The qualitative interpretations disclose that a plot-level open space can significantly impact the regional-level open space network. Hence, the research advocates a bottom-up approach wherein plot-level open space can become the focus in formulating new norms and policies for sustainable development.

Annual 30 m soybean yield mapping in Brazil using long-term satellite observations, climate data and machine learning

Long-term spatially explicit information on crop yield is essential for understanding food security in a changing climate. Here we present a study that combines twenty-years of Landsat and MODIS data, climate and weather records, municipality-level crop yield statistics, random forests and linear regression models for mapping crop yield in a multi-temporal, multi-scale modeling framework. The study was conducted for soybean in Brazil. Using a recently developed 30 m resolution, annual (2001–2019) soybean classification map product, we aggregated multi-temporal phenological metrics derived from Landsat and MODIS data over soybean pixels to the municipality scale. We combined phenological metrics with topographic features, long-term climate data, in-season weather data and soil variables as inputs to machine learning models. We trained a multi-year random forests model using yield statistics as reference and subsequently applied linear regression to adjust the biases in the direct output of the random forests model. This model combination achieved the best performance with a root-mean-square-error (RMSE) of 344 kg/ha (12% relative to long-term mean yield) and an r2 of 0.69, on the basis of 20% withheld test data. The RMSE of the leave-one-year-out model assessment ranged from 259 kg/ha to 816 kg/ha. To eliminate the artifacts caused by the coarse-resolution climate and weather data, we developed multiple models with different categories of input variables. Employing the per-pixel uncertainty estimates of different models, the final soybean yield maps were produced through per-pixel model composition. We applied the models trained on 2001–2019 data to 2020 data and produced a soybean yield map for 2020, demonstrating the predictive capability of trained machine learning models for operational yield mapping in future years. Our research showed that combining satellite, climate and weather data and machine learning could effectively map crop yield at high resolution, providing critical information to understand yield growth, anomaly and food security.

Spatio-Temporal Dynamics and Driving Forces of Multi-Scale CO2 Emissions by Integrating DMSP-OLS and NPP-VIIRS Data: A Case Study in Beijing-Tianjin-Hebei, China

The emission of greenhouse gases, especially CO2, is the main factor causing global warming. Due to incomplete statistical data on energy consumption at and below the urban scale of Beijing-Tianjin-Hebei (BTH), in this study, Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS) and Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) data were combined, and a neural network model and weighted average method based on DN (Digital Number) value were used to obtain CO2 emissions at the municipal and county scales with a resolution of 1 km × 1 km from 2000–2019. Next, a spatial-temporal analysis model and spatial econometric model were used to study the CO2 emissions at different scales of BTH. This study also solved the problem that STIRPAT analysis cannot be carried out due to insufficient urban statistical CO2 emissions data. The results show that the energy CO2 emissions in BTH present a distribution pattern of “East greater than West”, with a trend of first rising and then slowing down. Moreover, the rapid growth areas are mainly located in Chengde and Tianjin. The degree of regional spatial aggregation decreased year by year from 2000–2019. Population, affluence and technology factors were positively correlated with CO2 emissions in Tianjin and Hebei. For Beijing, in addition to foreign investment, factors such as urbanization rate, energy intensity, construction and transportation factors all contributed to the increase in CO2 emissions. Among them, the growth of population is the main reason for the increase of CO2 at the urban scale in BTH. Finally, based on the research results and the specific situation of the cities, corresponding policies and measures are proposed for the future low-carbon development of the cities.

Contested geographies of localization(s): towards open-locales

ABSTRACT In this paper, we identify localization(s) as an expanding set of spatial processes by which key economic and social mobilities are shifting towards regional, municipal and neighbourhood scales in response to interconnected crises of globalization, ecology, economy, politics, and public health. Localizations are already underway, and are likely to proliferate as these various crises intensify. They are diverse in their politics and have implications for all scales of social organization. Localizations raise important questions around inequalities and injustices, new topologies of (dis)connected communities, ethical dilemmas of obdurate globalizations, contesting turns to nativism, and ensuring the just and democratic construction of open-locales. Observing this trend of localizations from within the UK lockdowns of the global coronavirus pandemic, we argue that more geographically embedded but socially and politically interconnected futures are both an implication of this paper and should constitute the format of an important emerging research agenda around localizations.

PERAN PEMASARAN DIGITAL: SEBUAH PERSPEKTIF DARI MANAJER HOTEL DI SUMBAWA

The role of the Internet in the buying behavior of tourists has led to a change in increasingly digital marketing plans. This study aims to find out how hotel industry managers use digital marketing as a marketing tool. In this study, using qualitative methodologies was adopted. Then semi-structured interviews were conducted with managers and marketers from 39 hotels that participated in the study. Digital marketing tools provide many benefits to the hospitality industry. However, managers still haven't used their potential in the realm of digital marketing. Although the data was collected at the end of 2020, we believe that the findings and recommendations are still valid and relevant. This study offers several recommendations to improve the effectiveness of hotel digital marketing in Sumbawa. Although it uses a thematic approach, this article provides an extensive assessment of the range of digital marketing communications in the luxury segment of the hospitality industry. In addition, these estimates are made for all units on a municipal scale.

Long-term exposure to PM2.5 and avoidable mortality in Colombia 2014-2019

Objective: To compare estimates of surface PM2.5 concentrations in Colombia from 2014-2019 at municipality level derived from two global air quality models, as well as to quantify the avoidable deaths attributable to the long-term exposure to concentrations above the current PM2.5 annual mean national standard of 25 µg/m3 and projected standard of 15 µg/m3. Methods: We retrieved PM2.5 concentrations at the surface level from the ACAG and CAMSRA global air quality models for all 1,122 municipalities, and compare 28 of them with available concentrations from monitor stations. Annual mortality data 2014-2019 by municipality of residence and pooled effect measures for total, natural and specific causes of mortality were used to calculate the number of annual avoidable deaths and years of potential life lost. Results: Compared to surface data from 28 municipalities with monitoring stations in 2019, ACAG and CAMSRA models under or overestimated annual mean PM2.5 concentrations. Estimations from ACAG model had a mean bias 1,7 μg/m3 compared to a mean bias of 4,7 μg/m3 from CAMSRA model. Using ACAG model, estimations of total nationally attributable deaths to PM2.5 exposure over 25 and 15 μg/m3 were 142 and 34,341, respectively. Cardiopulmonary diseases accounted for most of the attributable deaths due to PM2.5 excess of exposure (38%). Estimates of YPLL due to all-cause mortality for exceeding the national standard of 25 μg/m3 were 2,381 years. Conclusions: Comparison of two global air quality models for estimating surface PM2.5 concentrations during 2014-2019 at municipality scale in Colombia showed important differences. Avoidable deaths estimations represent the total number of deaths that could be avoided if the current and projected national standard for PM2.5 annual mean have been met, and show the health-benefit of the implementation of more restrictive air quality standards. Key words: Air quality standards, Particulate Matter, Satellite data, Mortality

The impacts of cropland balance policy on habitat quality in China: A multiscale administrative perspective

Cropland protection policies are implemented to guarantee food security, especially the cropland balance policy in China. Although these policies alleviate the quantitative loss of cropland, they cause a serious decline in habitat quality and reduce biodiversity. With the reform trial of China's cropland balance policy from the within-province scale to the cross-provincial scale, the evaluation of habitat quality for obtaining cropland balance at different administrative scales is necessary to help seek sustainable strategies of cropland protection. Thus, taking Chinese mainland as the study area, this research assessed the different impacts of the cropland balance policy on habitat quality during 2000–2015 and 2015–2030 at national, provincial, municipal and county scales on the basis of the LAND System Cellular Automata model for Potential Effects (LANDSCAPE) and the Integrated Valuation of Ecosystem Services and Tradeoffs model (InVEST). The results revealed that (1) the loss of habitat quality by compensated cropland was 4.02 times that of the loss by occupied cropland in 2000–2015. Compared with occupied cropland, compensated cropland dominated the impacts of cropland change on habitat quality. (2) For both cropland quantity balance and cropland quality balance, habitat quality was slightly lost the most on the national scale in 2030. In detail, the greatest loss of habitat quality mostly occurred in areas where the ecological environment is already vulnerable at the national scale, whereas habitat quality was relatively less in these areas at the provincial, municipal and county scales. (3) Under the same administrative scales, habitat quality was lost more in cropland quality balance scenarios than in cropland quantity balance scenarios. The loss of habitat quality caused by cropland quality balance at national, provincial, municipal and county scales was 1.25, 1.05, 0.90 and 1.37 times higher than that by cropland quantity balance, respectively. The research highlights that considering the differentiated loss of habitat quality caused by cropland protection is quite important when implementing the cropland balance policy and land use planning.

Improved delivery of social benefits through the maintenance planning of public assets

The prioritisation of public facilities’ maintenance is a necessary but complex task due to the need of considering both physical and socio-economic criteria. This study addresses this problem by quantifying the improvement in the delivery of social benefits that the corrective maintenance of an urban area’s public facilities could yield. Based on this, a decision framework is proposed to design and schedule corrective maintenance plans at a municipal scale. The methodology integrates multi-criteria assessment with an analytical method for evaluating the contribution of an area’s public facilities to its sustainable urban development based on their type of social infrastructure and their maintenance condition. The decision framework is implemented as a software to facilitate its application to a case study, consisting in building urban regeneration strategies aligned with governmental guidelines. The results revealed that decision-making is more efficient when considering the facilities’ type of social infrastructure. In addition, a cost-efficient prioritisation of corrective measures yields better results than neglecting the economy.

Variation in smoking attributable all-cause mortality across municipalities in Belgium, 2018: application of a Bayesian approach for small area estimations

BackgroundSmoking is one of the leading causes of preventable mortality and morbidity worldwide, with the European Region having the highest prevalence of tobacco smoking among adults compared to other WHO regions. The Belgian Health Interview Survey (BHIS) provides a reliable source of national and regional estimates of smoking prevalence; however, currently there are no estimates at a smaller geographical resolution such as the municipality scale in Belgium. This hinders the estimation of the spatial distribution of smoking attributable mortality at small geographical scale (i.e., number of deaths that can be attributed to tobacco). The objective of this study was to obtain estimates of smoking prevalence in each Belgian municipality using BHIS and calculate smoking attributable mortality at municipality level.MethodsData of participants aged 15 + on smoking behavior, age, gender, educational level and municipality of residence were obtained from the BHIS 2018. A Bayesian hierarchical Besag-York-Mollie (BYM) model was used to model the logit transformation of the design-based Horvitz-Thompson direct prevalence estimates. Municipality-level variables obtained from Statbel, the Belgian statistical office, were used as auxiliary variables in the model. Model parameters were estimated using Integrated Nested Laplace Approximation (INLA). Deviance Information Criterion (DIC) and Conditional Predictive Ordinate (CPO) were computed to assess model fit.Population attributable fractions (PAF) were computed using the estimated prevalence of smoking in each of the 589 Belgian municipalities and relative risks obtained from published meta-analyses. Smoking attributable mortality was calculated by multiplying PAF with age-gender standardized and stratified number of deaths in each municipality.ResultsBHIS 2018 data included 7,829 respondents from 154 municipalities. Smoothed estimates for current smoking ranged between 11% [Credible Interval 3;23] and 27% [21;34] per municipality, and for former smoking between 4% [0;14] and 34% [21;47]. Estimates of smoking attributable mortality constituted between 10% [7;15] and 47% [34;59] of total number of deaths per municipality.ConclusionsWithin-country variation in smoking and smoking attributable mortality was observed. Computed estimates should inform local public health prevention campaigns as well as contribute to explaining the regional differences in mortality.

A New Framework for Reconstructing Time Series DMSP-OLS Nighttime Light Data Using the Improved Stepwise Calibration (ISC) Method

Calibration and reconstruction of time series DMSP-OLS nighttime light images are critical for understanding urbanization processes and the evolution of urban spatial patterns from a unique perspective. In this study, we developed an improved stepwise calibration (ISC) method based on numerical constancy to correct and reconstruct the time series of China’s regional nighttime light data, thus eliminating the drawbacks of the invariant target region method. We evaluated the different calibration methods and quantitatively validated the calibrated nighttime light data using gross domestic product (GDP) and electricity consumption (EC) at municipal, provincial, and national scales. The results indicated that the ISC method demonstrated its advantage in screening stable lit pixels and maintaining the temporal variability of multi-year nighttime light variation. The variation curve of reconstructed multi-year nighttime light obtained by the ISC method based on numerical constancy was more consistent with the actual urban development. The ISC method retained the original data’s most abundant and complete information than other calibration methods. Moreover, the significant advantages of this method in the low-light high-variation regions and high-light low-variation regions offered new possibilities for understanding the development of small- and medium-sized nighttime light centers such as towns and villages from a nighttime light perspective. This is an advantage that other calibration methods do not offer. The correlation between the multi-year nighttime light dataset obtained by the ISC method and the socio-economic data was significantly improved. The correlation coefficients with GDP and EC are 0.9695 and 0.9923, respectively. Last but not least, the ISC method is more straightforward to implement. The new framework developed in this study produces a more accurate and reliable long time series nighttime light dataset and provides quality assurance for subsequent research in socio-economic development, urban development, natural disasters, and other fields.

The risk assessment of surface recession damage for architectural buildings in Italy

Limestone monuments are generally subjected to natural and anthropogenic environmental threats. This paper describes a methodology to assess the risk of surface recession damage, due to air pollution and meteorological factors, to architectural buildings in Italy. Through the elaboration of environmental data and information on conservation conditions of cultural heritage, three different risk models were identified: i) the territorial risk, obtained combining territorial hazard information with the density of historic buildings defined at municipal scale; ii) the individual risk, attained by overlapping territorial hazard data at municipal scale, with surface vulnerability and exposure information of a single monument; iii) the local risk, defined starting from the combination of territorial hazard at sub-municipal scale, with vulnerability and exposure information of a single monument. The first model refers to the risk of an aggregate of cultural assets located in a municipality, while the other two indicators identify the damage risk of a single monument at municipal and sub-municipal spatial scales. The proposed method was applied, using GIS (Geographical Information System) application, to identify the three risk models for Italian architectural buildings using environmental and monument conservation data updated to 2018. The territorial hazard was defined by assessing the material loss damage expressed as surface recession and quantified starting from air pollutant concentrations and meteorological data measured by the monitoring station network of Italy in 2018. The vulnerability and exposure information were extracted from the Italian Risk Map of Cultural Heritage system. The obtained results allowed to identify the potentially most aggressive areas from climatic and environmental point of view and the architectural buildings most exposed to surface recession risk. The methodology described in this paper can be therefore considered as a tool that can be used, by policy makers, to plan priority maintenance and conservation activities in order to reduce the progress and the intensity of decay on outdoor cultural properties.

Disclosure and Competition for Capital

Ownership segmentation in the municipal bond market gives rise to competition among local issuers for a limited supply of capital. We consider the disclosure implications of this competition for capital, using Moody’s 2010 recalibration of the municipal rating scale. The recalibration placed lowly upgraded issuers at a disadvantage relative to their highly upgraded peers within the same market segment. We develop a model in which two municipal bond issuers compete for investors’ capital by choosing bond yields. The model predicts the issuer that is disadvantaged by the recalibration is more likely to improve its disclosure to better compete with its advantaged peer if (i) the rating upgrade that its peer receives is higher and (ii) competition for capital is fiercer. Empirically, we find that the disadvantaged issuers provide more and timelier financial disclosures after the recalibration. This improvement in disclosure quality increases in the extent of the issuer’s disadvantage, arises only if we consider peers with whom the issuer directly competes for capital, and is pronounced when the local capital supply is constrained. Our analytical and empirical analyses support the idea that a competitive disadvantage in raising capital in segmented markets can motivate issuers to improve disclosure quality. This paper was accepted by Brian Bushee, accounting. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2022.4525 .

A study on hypothermia and associated countermeasures in tsunami disasters: A case study of Miyagi Prefecture during the 2011 great East Japan earthquake

In this study, the impact of hypothermia during tsunami disasters based on casualty data from Miyagi Prefecture during the Great East Japan Earthquake was analyzed. The spatial distribution of the locations in which the corpses of hypothermia victims were found and the effects of age group, location, environmental temperature, and tsunami exposure were examined at the municipal and postal code scales. Hypothermia victims were identified only in coastal areas, indicating an increased risk of hypothermia due to wetting of the body caused by exposure to tsunami water and a cold environment at the evacuation centers. The proportion of older (>70 years) individuals among the hypothermia victims was significantly higher (p > 0.05) compared to the victims of drowning. Based on the findings of this study, a response checklist in evacuation centers and a modified government response flowchart are proposed, assuming response by nonmedical personnel to reduce the risk of hypothermia after a disaster.