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Rock glacier inventory and predictive modeling in the Mackenzie Mountains: predicting rock glacier likelihood with a generalized additive model

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ARCTIC SCIENCE 2024年第4期10卷 653-672页

作者： Thiessen, Rabecca Bonnaventure, Philip P. Lapalme, Caitlin M. Univ Lethbridge Dept Geog & Environm Lethbridge AB T1K 3M4 Canada Queens Univ Dept Geog & Planning Kingston ON K7L 3N6 Canada

Rock glaciers have been the subject of extensive research in recent years due to their potential to serve as indicators of past and present climate conditions and their potential impacts on water resources. Location and descriptive rock glacier data within the Mackenzie Mountains were used to build a rock glacier inventory that will serve as a valuable resource for future research and monitoring efforts. Additionally, this study maps the likelihood of rock glacier presence using extracted variables in a generalized additive model (GAM). The model incorporates attribute data, including potential incoming solar radiation (PISR), topographic position index (TPI), slope, elevation, and lithology as controls for rock glacier development. Topographic data were compiled for three study regions of the Mackenzie Mountains from a 30 m digital elevation model (DEM). The analysis of the GAM showed that the most significant explanatory variables were PISR, elevation, slope, and TPI. The GAM model had an accuracy of 0.87 with a sensitivity of 0.92. This study provides important insights into the controls, distribution, and dynamics of rock glaciers in the Mackenzie Mountains, as well as both the limitations and the potential of statistical models in predicting their occurrence.

关键词： rock glacier permafrost Mackenzie Mountains generalized additive model

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Wildfire Impacts on O3 in the Continental United States Using PM2.5 and a generalized additive model (2018-2023)

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ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024年第33期58卷 14764-14774页

作者： Lee, Haebum Jaffe, Daniel A. Univ Washington Sch Sci Technol Engn & Math Bothell WA 98011 USA Univ Washington Dept Atmospher Sci Seattle WA 98195 USA

We examined PM2.5 and Hazard Mapping System smoke plume satellite data at similar to 600 United States (US) air monitoring stations to identify surface smoke on 14.0% of all May-September days for 2018-2023, with large influences in 2020 and 2021, due to California fires, and 2023, due to Canadian fires. Days with smoke have an average of 11 mu g m(-3) more PM2.5 and 8 ppb higher maximum daily 8 h average (MDA8) O-3 concentrations than nonsmoke days, and they also account for 94% of all days that exceed the daily PM2.5 health standard (35 mu g m(-3)) and 36% of all days that exceed the O-3 health standard (70 ppb). To estimate the smoke contributions to the O-3 MDA8, generalized additive models (GAMs) were built for each site using the nonsmoke day data and up to 8 predictors. The mean and standard deviation of the residuals from the GAMs were 0 +/- 6.1 ppb for the nonsmoke day data and 4.3 +/- 7.9 ppb for the smoke day data, indicating a significant enhancement in the MDA8 O-3 on smoke days. We found positive residuals on 72% of the smoke days and for these days, we calculate an average smoke contribution to the O-3 MDA8 of 7.8 +/- 6.0 ppb. Over the 6 year period, the percentage of exceedance days due to smoke in the continental US was 25% of all exceedance days, and the highest was in 2023 (38%). In 2023, the Central US experienced an unusually high number of exceedance days, 1522, with 52% of these impacted by smoke, while the Eastern US had fewer exceedance days, 288, with 78% of these impacted by smoke. Our results demonstrate the importance of wildland fires as contributors to exceedances of the health-based national air quality standards for PM2.5 and O-3.

关键词： generalized additive model ozone concentrations PM2.5 concentrations wildfire smoke

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Phytoplankton-environment dynamics in a tropical estuary of the northeastern Arabian Sea: a generalized additive model (GAM) approach

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ENVIRONMENTAL MONITORING AND ASSESSMENT 2025年第2期197卷 1-22页

作者： Akter, Sahina Wodeyar, K. Abhilash Nama, Suman Borah, Simanku Angmo, Sonam Deshmukhe, Geetanjali Nayak, Binaya Bhusan Ramteke, Karankumar ICAR Cent Inst Fisheries Educ Mumbai 400061 India ICAR Cent Inland Fisheries Res Inst Reg Ctr Gauhati 781006 Assam India

Phytoplankton are diverse photosynthetic organisms in estuarine ecosystems and sensitive indicators of environmental changes. This study employed generalized additive model (GAM) to explore the impact of environmental variables on the abundance of six dominant phytoplankton species in the tropical Karanja estuary, India. Data were collected from five sampling stations between January 2022 and March 2023. The GAM model explained >= 55% of the variability in species distribution, predicting that the Karanja estuary provides a suitable habitat for these phytoplankton. Spatiotemporal predictions revealed higher abundances of Asterionellopsis glacialis, Coscinodiscus sp., Pseudo-nitzschia pungens, Skeletonema costatum and Thalassionema frauenfeldii during post-monsoon and lower in pre-monsoon. Conversely, Odontella sinensis thrived during pre-monsoon. Optimal growth conditions included a water temperature range of 24-32 degrees C for O. sinensis, P. pungens and S. costatum, while chlorophyll-b concentrations between 1 and 20 mg/m3 favored A. glacialis, O. sinensis, P. pungens, S. costatum and T. frauenfeldii. P. pungens, S. costatum and T. frauenfeldii exhibited broad salinity tolerance ranging from 10-40 parts per thousand. Additionally, Coscinodiscus sp., P. pungens and T. frauenfeldii were found in environments with nitrate content of 0.1-1 mg/L, while O. sinensis preferred silicate levels of 1-10 mg/L. Notably, these species serve as indicators of eutrophication, providing insights into ecosystem health. This study represents the first application of GAM for exploring phytoplankton-environment interactions in India, offering critical data for water quality management, pollution control and food web preservation. Policymakers can use these findings to develop evidence-based regulations that support proactive coastal management, enhance estuarine resilience to climate stressors and ensure sustainable resource conservation.

关键词： Tropical ecosystems Estuary Phytoplankton Environmental variables Species distribution generalized additive model

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Interactions Between Serotonin Transporter Gene and Adverse Childhood Experience in a generalized additive model: A Pilot Study

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JOURNAL OF THE AMERICAN PSYCHIATRIC NURSES ASSOCIATION 2025年第1期31卷 55-63页

作者： Niitsu, Kosuke Lee, Chiyoung Rice, Michael J. Univ Washington Bothell Bothell WA USA Univ Arizona Tucson AZ USA Univ Colorado Anschutz Med Campus Aurora CO USA Univ Washington Bothell Sch Nursing & Hlth Studies Box 35853218115 Campus Way NE Bothell WA 98011 USA

BACKGROUND: While most people experience potentially traumatic events (PTEs), including Adverse Childhood Experiences (ACEs), the stress reactions to PTEs on mental health outcomes are highly heterogeneous. Resilience is influenced by a complex biopsychosocial ecological system, including gene serotonin transporter-linked promoter region or 5-HTTLPR /rs25531 by ACEs interactions. AIMS: This pilot study investigated the gene-by-environment interactions on mental health outcomes in adults enrolled in a health care profession program using a generalized additive model (GAM). METHODS: Seventy health care college students (mean age = 27.4 years, 67.1% women) participated in this cross-sectional study. Saliva samples were collected from students to analyze 5-HTTLPR/rs25531. Participants completed the ACE Questionnaire and the Mental Health Inventory. GAMs with different interaction terms were built adjusting for age, gender, and race. The value of the effective degree of freedom (EDF) quantifies the curvature of the relationship. RESULTS: Among participants with the long allele of 5-HTTLPR/rs25531, a linear pattern was found between the total ACE score and mental health outcomes (EDF = 1). Conversely, among participants with the short allele, EDF was approximately 2, indicating a curved association suggesting that mental health worsens in individuals exposed to up to four types of ACEs. CONCLUSIONS: The impact of up to four ACEs on mental health was stronger among individuals with the short allele of 5-HTTLPR/rs25531 than those with the long allele. Although this study does not claim to provide a definite approach to analyzing gene-by-environment interactions, we offer a different perspective to explore the relationship.

关键词： psychological resilience serotonin-transporter-linked promoter region (5-httlpr/rs25531) gene by environmental interaction adverse childhood experiences generalized additive model

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Application of a delta-generalized additive model to assess the impact of environmental changes on the spatial distribution of bigeye tuna (Thunnus obesus) in the Indian Ocean

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FISHERIES RESEARCH 2025年 281卷

作者： Lurkpranee, Supatcha Kitakado, Toshihide Tokyo Univ Marine Sci & Technol Dept Marine Biosci 4-5-7 Konan Minato Tokyo 1080075 Japan

This study estimated the spatial distribution of bigeye tuna (Thunnus obesus) in the Indian Ocean under changing environmental conditions through habitat suitability modeling. Fisheries data from the Indian Ocean Tuna Commission and environmental satellite data from COPERNICUS were used in a delta-generalized additive model approach. This involved separately modeling the probability of presence or absence using binomial logistic regression and the positive catch using lognormal distribution. Results showed that sea surface temperature, mixed layer depth, and chlorophyll-a significantly influenced the presence of bigeye tuna in the Indian Ocean, whereas sea surface height, mixed layer depth, and chlorophyll-a exerted a substantial impact on their density. Adjusted simulated environmental data from 2020 to 2100 under three climate change scenarios (SSP126, SSP245, and SSP585) from Coupled model Intercomparison Project Phase 6 were utilized to predict the future spatial distribution pattern of bigeye tuna in the Indian Ocean. Bigeye tuna is expected to variedly shift its spatial distribution under the three different climate change scenarios, with SSP585 having the most pronounced changes. Generally, bigeye tuna is predicted to spread poleward from the equator as a result of tropicalization in the higher latitudes.

关键词： Climate change Delta model Future prediction generalized additive model Spatial distribution

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Mapping the spatial disparities of HIV prevalence in Ethiopian zones using the generalized additive model

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SCIENTIFIC REPORTS 2024年第1期14卷 1-10页

作者： Yilema, Seyifemickael Amare Shiferaw, Yegnanew A. Belay, Alebachew Taye Belay, Denekew Bitew Debre Tabor Univ Coll Nat & Computat Sci Dept Stat POB 272 Debre Tabor Ethiopia Univ Johannesburg Dept Stat Auckland Pk Kingsway CampusPOB 524 ZA-2006 Johannesburg South Africa Bahir Dar Univ Coll Sci Dept Stat Bahir Dar Ethiopia

HIV is a worldwide social and health pandemic that poses a significant problem. This study contributes to the 2030 global agenda of reducing HIV prevalence. The study analyzed HIV prevalence using the 2016 Ethiopian Demographic and Health Survey data. The study included men aged 15-54 years and women aged 15-49 years who responded to questions about HIV tests. A generalized geo-additive model (GAM) was fitted to HIV data using nonparametric smooth terms for geolocations. Two smoothing techniques were used in GAMs to evaluate spatial disparities and the probable effects of variables on HIV risk. There were certain areas in Ethiopia that were identified as hot spot zones for HIV, including Nuer and Agnuak in Gambella, West Wollega and Illubabor in Oromia, Benchi Maji and Shaka in SNNPR, Awsi, Fantana, Kilbet, and Gabi in the Afar region, Shinilie of the Somalia region, North and South Wollo, Oromia special zones of the Amhara region, Central Ethiopia, and Addis Ababa city. On the other hand, the eastern parts of Ethiopia, particularly most zones in the Somalia region, were identified as cold spot zones with the lowest HIV odds ratio. The odds of HIV+ were higher for those who reside in rural areas than in urban areas. Furthermore, people who have STIs, who used contraceptive methods, and who learned at the secondary level of education were more likely to be infected with HIV. After adjusting for confounding variables, the results indicated that there are substantially significant spatial variations in HIV prevalence across Ethiopian zones. These results provide essential information to strategically target geographic areas to allocate resources and policy interventions at zonal level administrations.

关键词： generalized additive model Spatial heterogeneity HIV Odds ratio Zones

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Assessment of factors affecting infant mortality in Sudan: application of generalized additive model

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BMC PEDIATRICS 2025年第1期25卷 1-10页

作者： Ayele, Dawit Getnet. Mohammed, Mohammed Omar Musa Abdallah, Ahmed Saied Rahama DC Hlth Ctr Policy Planning & Evaluat CPPE Washington DC USA Prince Sattam Bin Abdulaziz Univ Coll Business Adm Hawtat Bani Tamim Al Kharj Saudi Arabia

Background The evaluation of the factors influencing infant mortality entails examining the various factors contributing to the high rate of infant deaths in Sudan. These factors encompass access to healthcare services, nutritional status, sanitation, maternal health, vaccination, and socioeconomic circumstances. This study aims to assess the factors affecting infant mortality in the state of Gezira in Sudan. Methods The study conducted in Gezira state, Sudan, was a cross-sectional analytical household cluster survey carried out from July 2021 to December 2021. This survey used a questionnaire divided into two parts: the first section collected basic demographic information about each participant to identify the general characteristics of the population. In the second section, detailed demographic, socioeconomic, and geographic information was gathered regarding factors influencing infant mortality in Gezira. The generalized additive models was used to identify factors affecting infant mortality. Results The findings indicate a statistically significant correlation between the child's sex (AOR = 1.108, P-value = 0.0227), breastfeeding exclusively (AOR = 0.883, P-value = 0.0294), maternal follow-up (AOR = 0.883, P-value = 0.0294), a child suffering from malaria (AOR = 0.883, P-value = 0.0294), a child experiencing malnourishment (AOR = 1.44, P-value < 0.0001), a child suffering from septicemia (AOR = 0.883, P-value = 0.0294), and infant mortality. Conclusion These results support WHO recommendations and other studies showing that exclusive breastfeeding is a major preventive factor against infant morbidity and mortality from respiratory and gastrointestinal tract illnesses. This emphasizes how crucial it is to provide early childhood primary healthcare, especially in Sudan where infant death rates are high because of common illnesses including blood poisoning, malaria, and other ailments. Thus, the government needs to adopt measures and policies to minimize this mort

关键词： Assessment Infant Factors generalized additive model Mortality Sudan

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Study on the correlation between the number of mushroom poisoning cases and meteorological factors based on the generalized additive model in Guizhou Province, 2023

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BMC PUBLIC HEALTH 2024年第1期24卷 1页

作者： Xiong, Sufang Wu, Anzhong Weng, Ling Zhang, Li Wu, Muli Li, Haijiao Zuo, Peipei Zhu, Shu Li, Jun Guo, Hua Long, Tao Guizhou Ctr Dis Control & Prevent Inst Publ Hlth Surveillance & Evaluat Guiyang Guizhou Peoples R China Guizhou Med Univ Sch Publ Hlth Key Lab Environm Pollut Monitoring & Dis Control Minist Educ Guiyang Guizhou Peoples R China Guiyang Meteorol Bur Guiyang Guizhou Peoples R China Chinese Ctr Dis Control & Prevent Natl Inst Occupat Hlth & Poison Control Beijing Peoples R China Zunyi Ctr Dis Control & Prevent Zunyi Guizhou Peoples R China

Background Mushroom poisoning is a significant food safety issue in Guizhou Province, China. Studies on this topic are essential for its prevention and control. We aimed to analyze the epidemiological characteristics of mushroom poisoning and study the correlation between its cases and meteorological factors in Guizhou Province. Methods We collected data on mushroom poisoning and meteorological factors in Guizhou Province in 2023. A descriptive analysis was conducted on the epidemiological features of mushroom poisoning and meteorological factors. We used Spearman correlation analysis and the generalized additive model to examine the relationship between meteorological factors and the number of mushroom poisoning cases. Results In 2023, mushroom poisoning cases in Guizhou Province were concentrated among individuals aged 20-59. Clinical symptoms were primarily gastrointestinal symptoms and occurrences peaked from June to October, mainly in the northeastern region of the province. Most incidents occurred in households. In 72 mushroom poisoning incidents where species were identified, 33 poisonous mushrooms were found. The number of mushroom poisoning cases in Guizhou Province was positively correlated with each meteorological factor(P < 0.05). The generalized additive model showed a significant nonlinear relationship between DGT, PRE, RHU, SSD, and the number of mushroom poisoning cases (P < 0.05). Interaction analysis showed that the risk of mushroom poisoning in Guizhou Province increased with the rising values of any two of these four meteorological factors. Conclusion Mushroom poisoning incidents in Guizhou Province are characterized by high-risk groups, seasonality, and specific high-incidence regions and places. Public awareness for high-risk groups and early warnings for high-incidence regions and places should be strengthened every summer and fall. There is a correlation between meteorological factors and the number of mushroom poisoning cases, suggesting tha

关键词： Mushroom poisoning Meteorological factors generalized additive model Interaction

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Air pollution and coronary heart disease-related hospital visits in Beijing, China: time-series analysis using a generalized additive model

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ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 2023年第13期30卷 36938-36951页

作者： Gao, Yuan Sheng, Weixuan Yang, Yongtao Capital Med Univ Beijing Shijitan Hosp Dept Anesthesiol Beijing 100038 Peoples R China Tsinghua Univ Beijing Huaxin Hosp Affiliated Hosp 1 Dept Blood Transfus Beijing 100016 Peoples R China

To investigate correlations between environmental and meteorological factors and frequency of presentation for coronary heart disease (CHD) in Beijing. Daily measurements of levels of six atmospheric pollutants were made, data relating to meteorological conditions collected, and CHD-related outpatient visits recorded from January 2015 to December 2019 in Beijing. A time-series analysis was made, using a generalized additive model with Poisson distribution, and R 3.6.3 software was used to estimate relationships among levels of atmospheric pollutants, ambient temperature, and visits occasioned by CHD. Results were controlled for time-dependent trend, other weather variables, day of the week, and holiday effects. Lag-response curves were plotted for specific and incremental cumulative effects of relative risk (RR). The aim was to correlate meteorological-environmental factors and the daily number of CHD-related hospital visits and to quantify the degree of correlation to identify any pathological associations. Response diagrams and three-dimensional diagrams of predicted exposure lag effects were constructed in order to evaluate relationships among the parameters of air pollution, temperature, and daily CHD visits. The fitted model was employed to predict the lag RR and 95% confidence interval (95% CI) for specific and incremental cumulative effects of random air pollutants at random concentrations. This model may then be used to predict effects on the outcome variable at any concentration of any defined pollutant, giving flexibility for public health purposes. The overall lag-response RR curves for the specific cumulative effects of the pollutants, particulate matter (PM)2.5, PM10, SO2, CO, and NO2, were statistically significant and for PM2.5, PM10, CO, and NO2, the overall lag-response RR curves for the incremental cumulative effect were statistically significant. When PM2.5, PM10, SO2, CO, and NO2 concentrations were above threshold values and the temperature was

关键词： Coronary heart disease Environmental-meteorological factors generalized additive model Time-series analysis

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Variations in polycyclic aromatic hydrocarbons concentrations and their contribution to aerosol optical depth during the COVID-19 outbreak: A study in Yokohama using generalized additive model

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ATMOSPHERIC POLLUTION RESEARCH 2025年第8期16卷

作者： Jing, Weidong Nakano, Kohei Mitani, Ryosuke Shen, Zhenxing Okuda, Tomoaki Xian Univ Architecture & Technol Sch Environm & Municipal Engn Xian 710055 Peoples R China Keio Univ Fac Sci & Technol Dept Appl Chem Yokohama Kanagawa 2238522 Japan Xi An Jiao Tong Univ Dept Environm Sci & Engn Xian 710049 Peoples R China

The severe social restrictions aiming at reducing the novel coronavirus disease (COVID-19) transmission during its outbreak significantly affected regional air quality. This study analyzed changes in polycyclic aromatic hydrocarbons (PAHs) concentrations in cyclone-collected powder form particulate matter (PM) samples collected in Yokohama, Japan, from 2018 to 2023. The annual mean & sum;PAHs concentration decreased significantly from 20.7 ng/mg in 2019 to 13.2 ng/mg in 2020 after the outbreak. However, the main sources of PAHs remained stable and were dominated by incomplete fossil fuel combustion. A generalized additive model was utilized to analyze the statistical relationships of air pollutants, namely, aerosol particulate matter (PM2.5), & sum;PAHs, ozone (O3), metal, and meteorological factors such as solar radiation and their impact on aerosol optical depth (AOD). AOD remote sensing data collected by the Terra/MODIS satellite reflects the degree of air turbidity and atmospheric aerosol loading. Despite the small sample size, the model fitting demonstrated a good fit and showed smoothing non-linear interaction effects among the target factors influencing secondary aerosol generation. In conclusion, intense solar radiation, high concentrations of oxidative gases, elevated levels of organic contaminants in aerosols, and the catalytic degradation of PAHs by transition metals contribute to increased atmospheric aerosol loads. This finding enhances the present understanding of the photochemical reaction processes of aerosol particles. However, longer-term observational studies are needed to confirm our findings due to the limited sample size in this study.

关键词： Cyclone PM-Bound PAHs Aerosol optical depth generalized additive model Multifactor interaction

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