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Projected seasonal flooding in Canada under climate change with statistical and machine learning

JOURNAL OF HYDROLOGY-REGIONAL STUDIES 2024年 53卷

作者： Grenier, Manuel Boudreault, Jeremie Raymond, Sebastien Boudreault, Mathieu Univ Quebec Montreal Dept Math 201 Ave President Kennedy Montreal PQ H2X 3Y7 Canada Cooperators Climat Hazards & Adv Risk Modelling 2875 Bd Laurier Quebec City PQ G1V 2M2 Canada Inst Natl Rech Sci Ctr Eau Terre Environm 490 Couronne Quebec City PQ G1K 9A9 Canada 490 Couronne Quebec City PQ G1K 9A9 Canada

Study region: Canada Study focus: Floods are among the costliest and deadliest natural hazards in the world. To date, little is known about future seasonal flooding across all Canada. In this paper, data-driven models for flood occurrence (i.e., happening of a flood) and impact (i.e., displaced population) were calibrated for spring and summer seasons in 14,000 watersheds across Canada. generalized additive models (GAM), Random Forests (RF) and Gradient Boosting Machines (GBM) were considered to model seasonal floods. The best -performing flood models were then used with regional climate models to assess the effect of climate change on flooding for three time horizons: historical, medium-term (similar to 2050) and long-term (similar to 2080). New hydrological insights for the region: GAM offered the best out-of-sample performance trade-off in both seasons for predicting flooding in Canada. Projections with GAM showed a general increase in summer flooding occurrence and impact in 2050 and 2080, mainly in the Yukon, western British Columbia, southern Prairies, Ontario and Quebec and some Atlantic provinces. Results for spring flooding were more mixed, but there seemed to be a slight decrease in the impact of spring flooding in the southern Prairies, particularly in 2080. The combination of statistical/machine learning and climate models have provided a more detailed and contrasted picture of the projected seasonal flooding situation over Canada that will help authorities better mitigate future flood risks.

关键词： Spring flooding Summer flooding generalized additive model Random forest Gradient boosting Regional climate models

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Prognostic implications of systemic immune-inflammation index in myocardial infarction patients with and without diabetes: insights from the NOAFCAMI-SH registry

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CARDIOVASCULAR DIABETOLOGY 2024年第1期23卷 1页

作者： Luo, Jiachen Qin, Xiaoming Zhang, Xingxu Zhang, Yiwei Yuan, Fang Shi, Wentao Liu, Baoxin Wei, Yidong Tongji Univ Sch Med Dept Cardiol Shanghai Peoples Hosp 10 301 Middle Yanchang Rd Shanghai 200072 Peoples R China

BackgroundIt is well-known that systemic inflammation plays a crucial role in the pathogenesis and prognosis of acute myocardial infarction (AMI). The systemic immune-inflammation index (SII, platelet x neutrophil/lymphocyte ratio) is a novel index that is used for the characterization of the severity of systemic inflammation. Recent studies have identified the high SII level as an independent predictor of poor outcomes in patients with AMI. We aimed to investigate the prognostic implications of SII in AMI patients with and without diabetes mellitus (DM).MethodsWe included 2111 patients with AMI from February 2014 to March 2018. Multivariable Cox regression analyses were performed to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) of all-cause death and cardiovascular (CV) death. Multiple imputation was used for missing *** 2111 patients (mean age: 65.2 +/- 12.2 years, 77.5% were males) analyzed, 789 (37.4%) had DM. generalized additive model analyses showed that as the SII increased, the C-reactive protein and peak TnT elevated while the LVEF declined, and these associations were similar in patients with and without DM. During a median of 2.5 years of follow-up, 210 all-cause deaths and 154 CV deaths occurred. When treating the SII as a continuous variable, a higher log-transformed SII was significantly associated with increased all-cause mortality (HR: 1.57, 95%CI: 1.02-2.43) and CV mortality (HR: 1.85, 95%CI 1.12-3.05), and such an association was also significant in the diabetics (HRs and 95%CIs for all-cause death and CV death were 2.90 [1.40-6.01] and 3.28 [1.43-7.57], respectively) while not significant in the nondiabetics (Pinteraction for all-cause death and CV death were 0.019 and 0.049, respectively). Additionally, compared to patients with the lowest tertiles of SII, those with the highest tertiles of SII possessed significantly higher all-cause mortality (HR: 1.82, 95%CI 1.19-2.79) and CV mortality (HR: 1.82, 95%CI 1

关键词： Myocardial infarction Diabetes Systemic immune-inflammation index generalized additive model Restricted cubic spline

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A dynamic separable network model with actor heterogeneity: An application to global weapons transfers*

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JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES A-STATISTICS IN SOCIETY 2021年第1期184卷 201-226页

作者： Lebacher, Michael Thurner, Paul W. Kauermann, Goeran Ludwig Maximilians Univ Munchen Dept Stat Munich Germany Ludwig Maximilians Univ Munchen Dept Polit Sci Munich Germany

In this paper, we analyse the network of international major conventional weapons (MCW) transfers from 1950 to 2016, based on data from the Stockholm International Peace Research Institute (SIPRI). The dataset consists of yearly bilateral arms transfers between pairs of countries, which allows us to conceive of the individual relationships as part of an overall trade network. For the analysis, we extend the separable temporal exponential random graph model (STERGM) to account for time-varying effects on both the network level (trade network) and the actor level (country effects). Our investigation enables the identification of potentially differing driving forces that influence the formation of new trade relationships versus the persistence of existing ones. In accordance with political economy models, we expect security- and network-related covariates to be most important for the formation of transfers, whereas repeated transfers should prevalently be determined by the importers' market size and military spending. Our proposed modelling approach corroborates the hypothesis and quantifies the corresponding effects. Additionally, we subject the time-varying heterogeneity effects to a functional principal component analysis. This analysis serves as an exploratory tool and allows us to identify countries with exceptional increases or decreases in their tendency to import and export weapons.

关键词： arms transfers functional principal component analysis generalized additive model security and defence network varying coefficient model

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Spectrally Sparse Nonparametric Regression via Elastic Net Regularized Smoothers

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JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS 2021年第1期30卷 182-191页

作者： Helwig, Nathaniel E. Univ Minnesota Dept Psychol Minneapolis MN 55455 USA Univ Minnesota Sch Stat Minneapolis MN 55455 USA

Nonparametric regression frameworks, such as generalized additive models (GAMs) and smoothing spline analysis of variance (SSANOVA) models, extend the generalized linear model (GLM) by allowing for unknown functional relationships between an exponential family response variable and a collection of predictor variables. The unknown functional relationships are typically estimated using penalized likelihood estimation, which adds a roughness penalty to the (negative) log-likelihood function. In this article, I propose a spectral parameterization of a smoothing spline, which allows for an efficient application of Elastic Net regression to smooth and select eigenvectors of a kernel matrix. The classic (ridge regression) solution for a smoothing spline is a special case of the proposed kernel eigenvector smoothing and selection operator. Extensions for tensor product smoothers are developed for both the GAM and SSANOVA frameworks. Using simulated and real data examples, I demonstrate that the proposed approach offers practical and computational gains over typical approaches for fitting GAMs, SSANOVA models, and Elastic Net penalized *** this article are available online.

关键词： Algorithms Functional data generalized additive model Regularization methods Smoothing spline ANOVA

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An Integrated Framework to Estimate Seabird Population Numbers and Trends

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JOURNAL OF WILDLIFE MANAGEMENT 2021年第4期85卷 751-771页

作者： Mercker, Moritz Markones, Nele Borkenhagen, Kai Schwemmer, Henriette Wahl, Johannes Garthe, Stefan Bionum GmbH Consultants Ecol Stat Finkenwerder Norderdeich 15 A D-21129 Hamburg Germany Univ Kiel Res & Technol Ctr FTZ Hafentorn 1 D-25761 Busum Germany Dachverband Deutsch Avifaunisten DDA eV Speichern 6 D-48157 Munster Germany

Generating trend and population estimates from bird count data is challenging and a variety of factors have to be taken into account. We present an integrative statistical approach for estimating population numbers and trends for seabirds at sea. The method allows for the integration of bird-count data from different sources and sampling schemes: offshore observer-based line transect and digital strip transect surveys and land-based point counts;the estimation of log-linear and highly nonlinear trends;the prediction of population numbers for predefined sub-areas, years, or seasons;and investigations of the effects of various environmental and detection-related covariates on bird count numbers. We applied the approach to count data for great black-backed gulls (Larus marinus) in the German part of the North Sea and Baltic Sea from 1990-2016. Count data were collected by observer-based offshore ship and aerial surveys, offshore digital aerial surveys, and point counts from the shore. The detectability of great black-backed gulls was affected by the sea state (the condition of the sea surface, characterized by wave height, wave form, foam, and spray) and survey method. Digital and observer-based aerial surveys detected only 59-77% of the abundance recorded by ship-based surveys. Great black-backed gulls are mainly present in German waters in winter, when they account for 3-4% of the European population. Their core distributional areas are mainly in deeper offshore waters where they are relatively dispersed, with several concentrations probably connected to fishing activity. Great black-backed gulls have undergone substantial declines, with the most pronounced decreases of >90% in the offshore waters of the German part of the North Sea. Breeding numbers at important European breeding sites do not show similar declines, suggesting that the trends observed in the sea areas might indicate a shift in the distribution or habitat use and a decreasing importance of marine area

关键词： abundance estimate digital survey generalized additive model great black‐ backed gull line transect survey population estimate seabirds trend analysis

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Validation of presence-only models for conservation planning and the application to whales in a multiple-use marine park

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ECOLOGICAL APPLICATIONS 2021年第1期31卷 1-14页

作者： Smith, Joshua N. Kelly, Natalie Renner, Ian W. Murdoch Univ Coll Sci Hlth Engn & Educ Environm & Conservat Sci 90 South St Perth WA 6150 Australia Australian Govt Dept Agr Water & Environm Australian Antarctic Div 203 Channel Highway Kingston Tas 7000 Australia Univ Newcastle Sch Math & Phys Sci Univ Dr Callaghan NSW 2308 Australia

Identification of species' Biologically Important Areas (BIAs) is fundamental to conservation planning and species distribution models (SDMs) are a powerful tool commonly used to do this. Presence-only data are increasingly being used to develop SDMs to aid the conservation decision-making process. The application of presence-only SDMs for marine species' is particularly attractive due to often logistical and economic costs of obtaining systematic species' distribution data. However, robust model validation is important for conservation management applications that require accurate and reliable species' occurrence data (e.g., spatially explicit risk assessments). This is commonly done using a random subset of the data and less commonly with fully independent test data. Here, we apply a spatial block cross-validation (CV) approach to validate a MaxEnt presence-only model using independent presence/absence survey data for a highly mobile, marine species (humpback whale,Megaptera novaengliae) in the Great Barrier Reef (GBR). A MaxEnt model was developed using opportunistic whale sightings (2003-2007) and then used to identify areas differing in habitat suitability (low, medium, high) to conduct a systematic, line-transect, aerial survey (2012) and derive a density surface model. A spatial block CV buffering strategy was used to validate the MaxEnt model, using the opportunistic sightings as training data and independent aerial survey sightings data as test data. Moderate performance measures indicate MaxEnt was reliable in identifying the distribution patterns of a mobile whale species on their breeding ground, indicated by areas of high density aligned to areas of high habitat suitability. Furthermore, we demonstrate that MaxEnt models can be useful and cost-effective for designing a sampling scheme to undertake systematic surveys that significantly reduces sampling effort. In this study, higher quality information on whale reproductive class (calf vs. non-calf groups

关键词： density surface model generalized additive model Great Barrier Reef habitat model humpback whale MaxEnt ship strike spatial cross-validation spatial risk assessment species distribution modeling

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Projecting climate-driven shifts in demersal fish thermal habitat in Iceland's waters

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ICES JOURNAL OF MARINE SCIENCE 2021年第10期78卷 3793-3804页

作者： Mason, Julia G. Woods, Pamela J. Thorlacius, Magnus Gudnason, Kristinn Saba, Vincent S. Sullivan, Patrick J. Kleisner, Kristin M. Environm Def Fund Boston MA 02108 USA Cornell Univ Atkinson Ctr Sustainabil Ithaca NY 14853 USA Marine & Freshwater Res Inst Hafnarfjorour Iceland Princeton Univ NOAA Natl Marine Fisheries Serv Northeast Fisheries Sci CtrGeophys Fluid Dynam L Princeton NJ 08544 USA Cornell Univ Dept Nat Resources & Environm Ithaca NY 14853 USA

As climate change shifts marine species distribution and abundance worldwide, projecting local changes over decadal scales may be an adaptive strategy for managers and industry. In Iceland, one of the top fish-producing nations globally, long-term monitoring enables model simulations of groundfish species habitat distribution. We used generalized additive models to characterize suitable thermal habitat for 51 fish species in Iceland's waters. We projected changes in suitable thermal habitat by midcentury with an ensemble of five general circulation models from the Coupled model Intercomparison Program 6 (CMIP6) and NOAA (CM2.6) and two scenarios (SSP 5-8.5 and SSP 2-4.5). We found a general northward shift in suitable thermal habitat distribution, with variable regional dynamics among species. Species thermal bias index was a weak predictor of projected thermal habitat change, with warmer-water species more likely to see increases in thermal habitat and southern warm-edge range expansions. While these results isolate the effects of future changes in temperature, providing an indication of suitable thermal habitat, low model explanatory power suggests that additional variables may improve distribution projections. Such projections might serve as guideposts to inform long-term management decisions about regional and species-specific suitability for Iceland's fisheries, infrastructure investment, and risk evaluation under climate change.

关键词： climate change generalized additive model global climate model species distribution modelling suitable thermal habitat

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Exploring biophysical links of catch rate from mid-water trawl fishery in the north-west coast of India, Eastern Arabian Sea: A remote sensing approach

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SCIENCE OF THE TOTAL ENVIRONMENT 2023年第1期886卷 163975页

作者： Azeez, Pokkathappada Abdul Rohit, Prathibha Raman, Mini Shenoy, Latha Jaiswar, Ashok Kumar Koya, Kunnamgalam Mohammed Mojjada, Suresh K. Damodaran, Divu Gopalakrishnan, Achamveetil ICAR Res Complex Cent Marine Fisheries Res Inst Veraval Reg Stn Veraval 362269 Gujarat India ICAR Res Complex Cent Marine Fisheries Res Inst Mangalore Reg Ctr Karnataka 575001 India Indian Space Res Org Space Applicat Ctr Ahmadabad 380015 Gujarat India ICAR Res Complex Cent Inst Fisheries Educ Fishery Resources Harvest & Postharvest Div Mumbai 400061 Maharashtra India ICAR Res Complex Cent Marine Fisheries Res Inst Cochin 682018 Kerala India

Fish frequently shift their distribution ranges as a result of changes in preferred environmental factors. Knowledge on distribution of fish in relation to their environmental optima is crucial for improving the understanding of fishing grounds and planning sustainable exploitation. This study investigated the monthly variability in environmental factors impacting the catch rate and the spatio-temporal distribution patterns of fish along northwest coast of India (NWCI) from 2017 to 2019. The time series images of sea surface temperature (SST), sea surface height anomaly (SSHa), chlorophyll-a concentration (CHL), and euphotic depth (Zeu) indicate close coupling between bio-physical variables in the region. generalized additive model (GAM) applied to the catch rate of mid-water trawlers found that CHL and Zeu were the most infiuential variables for ribbonfish distribution, while CHL and SST infiuence squid distribution and SST and SSHa infiuence cuttlefish distribution. The total deviation explained 37.70 %, 10.70 %, and 22.28 % in the final model for simulating the spatio-temporal distribution of ribbonfish, squid, and cuttlefish, respectively. Environmental factors were significant in the final GAM model (p < 0.05). Spatio-temporal distribution patterns of fishery resources from mid-water trawlers showed that they were related to biophysical changes in the northwest coast of India. The high catch rate was observed in the northern latitudes during the post-monsoon (October), the major fishing season in the region. However, it shrank and shifted to southern latitudes during the winter (January). This study could be adapted to nearby countries in the Arabian Sea region for an effective and useful tool to monitor and manage the fishery resources. Furthermore, it could aid in decision-making for policymakers and resource managers to formulate strategies for holistic marine fishery management and sustainable resource exploitation.

关键词： Trawl fishery Fishing grounds Chlorophyll Remote sensing generalized additive model Fish distribution

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Optimum environmental conditions controlling prevalence of vibrio parahaemolyticus in marine environment

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MARINE ENVIRONMENTAL RESEARCH 2023年 183卷 105828页

作者： Namadi, Peyman Deng, Zhiqiang Louisiana State Univ Dept Civil & Environm Engn Baton Rouge LA 70803 USA

This literature review presents major environmental indicators and their optimum variation ranges for the prevalence of Vibrio parahaemolyticus in the marine environment by critically reviewing and statistically analyzing more than one hundred studies from countries around the world. Results of this review indicated that the prevalence of Vibrio parahaemolyticus in the marine environment is primarily responsive to favorable environmental conditions that are described with environmental indicators. The importance of environmental indicators to the prevalence of Vibrio parahaemolyticus can be ranked from the highest to lowest as Sea Surface Temperature (SST), salinity, pH, chlorophyll a, and turbidity, respectively. It was also found in this study that each environmental indicator has an optimum variation range favoring the prevalence of Vibrio parahaemolyticus. Specifically, the SST range of 25.67 +/- 2 degrees C, salinity range of 27.87 +/- 3 ppt, and pH range of 7.96 +/- 0.1 were found to be the optimum conditions for the prevalence of Vibrio parahaemolyticus. High vibrio concentrations were also observed in water samples with the chlorophyll a range of 16-25 mu g/L. The findings provide new insights into the importance of environmental indicators and their optimum ranges, explaining not only the existence of both positive and negative associations reported in the literature but also the dynamic associations between the Vibrio presence and its environmental drivers.

关键词： Vibrio parahaemolyticus Prevalence Environmental indicators Optimum conditions generalized additive model Random forest

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Spatio-temporal variations of PM2.5 and O3 in China during 2013-2021: Impact factor analysis

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ENVIRONMENTAL POLLUTION 2023年第1期334卷

作者： Liu, Xian Yi, Guihua Zhou, Xiaobing Zhang, Tingbin Bie, Xiaojuan Li, Jingji Tan, Huizhi Chengdu Univ Technol Coll Earth Sci Chengdu 610059 Peoples R China Chengdu Univ Technol Coll Tourism & Urban Rural Planning Chengdu 610059 Peoples R China Montana Technol Univ Geol Engn Dept Butte MT 59701 USA Chengdu Univ Technol State Environm Protect Key Lab Synerget Control & Chengdu 610059 Peoples R China Chengdu Univ Technol Coll Ecol Environm Chengdu 610059 Peoples R China

Fine particulate matter (PM2.5) and ozone (O3) pollution are regarded as significant secondary air pollutants. The PM2.5 in most regions in China declined, and the decreasing rate in January was lower than the annual average. However, O3 concentration showed a steady increasing trend in most regions, and the increasing rate in July was slightly higher than the annual average. In particular, the annual average PM2.5 concentration and excess rate showed an increasing trend on the northern slope of the Tianshan Mountains. Conversely, O3 concentrations had shown a consistent increasing trend, exceeding the annual average limit of 100 & mu;g/m3. Surface pressure exhibited positive correlations with PM2.5 in winter and O3 in summer across urban agglomerations. Moreover, soil temperature at different depths explained over 30% of the variations in PM2.5 and O3 in the Chengdu-Chongqing, Beijing-Tianjin-Hebei, and Lanzhou-Xining urban agglomerations. In winter, relative humidity demonstrated a positive correlation with urban agglomerations in northeast and northwest China, regions characterized by dry climates. During the COVID-19 period, the impacts of meteorological factors and soil temperature on PM2.5 and O3 differed significantly compared to preceding and subsequent periods. Notably, during the winter of 2020, the Harbin-Changchuan urban agglomeration exhibited a notable transition, as O3 and PM2.5 concentrations shifted from a strong negative correlation to a robust positive correlation. This remarkable shift, with deviations explained up to 60%, represents a unique phenomenon worth emphasizing in the study's findings.

关键词： Spatiotemporal variations Spatiotemporal stability generalized additive model PM2 5 O-3

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