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Increasing dominance of non-native fishes in the yield of central European streams and rivers

FISHERIES RESEARCH 2022年 254卷

作者： Lyach, Roman Inst Evaluat & Social Anal INESAN Sokolovska 25 Prague 18600 Czech Republic

Introductions of non-native fishes are among the biggest threats to freshwater ecosystems globally. However, the effects of such introductions on fisheries management and fish yields are understudied. This study is trying to fill this knowledge gap by analyzing relationships between yields of native and non-native fishes with regards to important fisheries management factors, such as fish stocking, fishing effort, and the type or size of the fishery. I analyzed the changes in fish yields in the regions of Prague and central Bohemia from 1986 to 2017. Based on the 32 years of reported data that included 60 million harvested fish weighing 80 tons that were harvested by 250,000 anglers, I conclude that while predominately native fish species were harvested by anglers in the 1980, non-native fish species started dominating in the 21st century. This was true on both small trout streams (1-m wide) and medium-sized cyprinid rivers (5-250 m wide). This dominance is partially explained by the decreasing percentage of native salmonids and cyprinids and by the decreasing or stagnating percentage of native piscivores in the overall fish yield. Conversely, the percentage of non-native salmonids in the overall fish yield was increasing on both streams and rivers. Most importantly though, the percentage of non-native cyprinids - which made 60-80 % of all harvested fish - increased by 16 % over 32 years. Fish yield had a strong positive relationship with fish stocking intensity, a strong negative relationship with angling effort, and strong but mixed relationships with size of the fishery. In conclusion, native fishes are being slowly replaced by non-native fishes in the yield of recreational anglers in central Europe.

关键词： Angling diary Fishery management Game fishing generalized additive model Recreational fishing

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modelling seasonal dynamics of secondary growth in R

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ECOGRAPHY 2022年第9期2022卷 e06030-e06030页

作者： Jevsenak, Jernej Gricar, Jozica Rossi, Sergio Prislan, Peter Slovenian Forestry Inst Dept Forest & Landscape Planning & Monitoring Ljubljana Slovenia Slovenian Forestry Inst Dept Forest Physiol & Genet Ljubljana Slovenia Univ Quebec Chicoutimi Dept Sci Fondamentales Chicoutimi PQ Canada Chinese Acad Sci South China Bot Garden Guangdong Prov Key Lab Appl Bot Key Lab Vegetat Restorat & Management Degraded Ec Guangzhou Peoples R China Slovenian Forestry Inst Dept Forest Tech & Econ Ljubljana Slovenia

The monitoring of seasonal radial growth of woody plants addresses the ultimate question of when, how and why trees grow. Assessing the growth dynamics is important to quantify the effect of environmental drivers and understand how woody species will deal with the ongoing climatic changes. One of the crucial steps in the analyses of seasonal radial growth is to model the dynamics of xylem and phloem formation based on increment measurements on samples taken at relatively short intervals during the growing season. The most common approach is the use of the Gompertz equation, while other approaches, such as general additive models (GAMs) and generalised linear models (GLMs), have also been tested in recent years. For the first time, we explored artificial neural networks with Bayesian regularisation algorithm (BRNNs) and show that this method is easy to use, resistant to overfitting, tends to yield s-shaped curves and is therefore suitable for deriving temporal dynamics of secondary tree growth. We propose two data processing algorithms that allow more flexible fits. The main result of our work is the XPSgrowth() function implemented in the radial Tree Growth (rTG) R package, that can be used to evaluate and compare three modelling approaches: BRNN, GAM and the Gompertz function. The newly developed function, tested on intra-seasonal xylem and phloem formation data, has potential applications in many ecological and environmental disciplines where growth is expressed as a function of time. Different approaches were evaluated in terms of prediction error, while fitted curves were visually compared to derive their main characteristics. Our results suggest that there is no single best fitting method, therefore we recommend testing different fitting methods and selection of the optimal one.

关键词： artificial neural networks cambium generalized additive model Gompertz function growing season intra-annual time series

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Crash frequency analysis of different types of urban roadway segments using generalized additive model

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JOURNAL OF SAFETY RESEARCH 2012年第2期43卷 107-114页

作者： Zhang, Yunlong Xie, Yuanchang Li, Linhua Texas A&M Univ Zachry Dept Civil Engn College Stn TX 77843 USA Univ Massachusetts Dept Civil & Environm Engn Lowell MA 01854 USA TEDSI Infrastruct Grp Houston TX 77042 USA

Introduction: This paper utilizes generalized additive model to explore the potential non-linear relationship between crash frequency and exposure on different types of urban roadway segments. Methods: generalized additive models are used to analyze crash frequency data and compared with the commonly used crash rate method and generalized linear models using a five-year crash data set from Houston, Texas. Results: The study shows that the relationship between crash frequency and exposure varies by segment type and the linearity may only approximately exist in certain segment types. In addition, the generalized additive modeling results suggest that such relationship curves may not be monotonic. Finally, this study demonstrates that generalized additive models in general provide better flexibility and modeling performance than generalized linear models. Impact on Industry: The generalized additive model provides a very promising alternative for crash frequency modeling and other safety studies. (C) 2012 National Safety Council and Elsevier Ltd. All rights reserved.

关键词： Crash analysis Crash rate generalized linear model generalized additive model Roadway type

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Association between meteorological factors and the epidemics of influenza (sub)types in a subtropical basin of Southwest China

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EPIDEMICS 2022年 41卷 100650-100650页

作者： Zhou, Linlin Yang, Huiping Pan, Wen Xu, Jianan Feng, Yuliang Zhang, Weihua Shao, Zerui Li, Tianshu Li, Shuang Huang, Ting Wang, Chuang Li, Wanyi Li, Mingyuan He, Shusen Zhan, Yu Pan, Ming Sichuan Univ West China Sch Basic Med Sci & Forens Med Dept Pathogen Biol Chengdu 610041 Peoples R China Sichuan Ctr Dis Control & Prevent Chengdu 610041 Peoples R China Sichuan Univ Dept Environm Sci & Engn Chengdu 610065 Sichuan Peoples R China Sichuan Univ Coll Comp Sci Chengdu 610065 Peoples R China Sichuan Univ West China Sch Publ Hlth Dept Med Technol Chengdu 610041 Peoples R China Sichuan Ctr Dis Control & Prevent 6 Zhongxue Rd Chengdu 610041 Sichuan Peoples R China

Background: The effects of climatic conditions on the prevalence of individual influenza (sub)types are not well understood in the subtropics. This study aims to evaluate the associations between meteorological factors and seasonal epidemics of A(H3N2), A(H1N1)pdm09, and type B influenza viruses, as well as to estimate the in-teractions between climatic variables in a subtropical basin ***: The seasonality of influenza (sub)types during 2010-2019 were characterized in Chengdu Plain Eco-nomic Zone, a densely populated and highly humid plain area in Sichuan Basin in subtropical Southwest China. generalized additive models were adopted to assess the independent exposure-response relationship between meteorological variables and influenza prevalence. The interactions of meteorological variables were further estimated using bivariate response surface models and strata ***: Our analyses indicated that the temperature, relative humidity, and absolute humidity have exhibited a major influence on influenza infection in Chengdu Plain Economic Zone. Low temperature was shown to promote the prevalence of A(H1N1)pdm09 and type B in winter-spring days at all levels of relative humidity. High risk of A(H3N2) infections was observed at low temperature or high temperature, and at higher relative humidity. Moreover, absolute humidity decreased or increased influenza (sub)type infections within different ***: This study found different nonlinear relationships between meteorological factors and the season-ality of influenza (sub)types, as well as significant interactive effects between climatic variables, contributing to the research on the climate drivers of influenza prevalence in warm-humid basin regions in the subtropics.

关键词： Influenza subtype Meteorological factors generalized additive model Subtropical basin region Southwest China

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Ozone pollution in London and Edinburgh: spatiotemporal characteristics, trends, transport and the impact of COVID-19 control measures

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HELIYON 2022年第11期8卷 e11384页

作者： Tudor, Cristiana Bucharest Univ Econ Studies Int Business & Econ Dept Bucharest 010374 Romania

Air pollution remains the most serious environmental health issue in the United Kingdom while also carrying nontrivial economic costs. The COVID-19 lockdown periods reduced anthropogenic emissions and offered unique conditions for air pollution research. This study sources fine-granularity geo-spatial air quality and meteorological data for the capital cities of two UK countries (i.e. England's capital London and Scotland's capital Edinburgh) from the UK Automatic Urban and Rural Network (AURN) spanning 2016-2022 to assess long-term trends in several criteria pollutants (PM10, PM2.5, SO2, NO2, O3, and CO) and the changes in ozone pollution during the pandemic period. Unlike other studies conducted thus far, this research integrates several tools in trend estimation, including the Mann-Kendall test, the Theil-Sen estimator with bootstrap resampling, and the generalized additive model (GAM). Moreover, several investigations, including cluster trajectory analysis, pollution rose plots, and potential source contribution function (PSCF), are also employed to identify potential origin sources for air masses carrying precursors and estimate their contributions to ozone concentrations at receptor sites and downwind areas. The main findings reveal that most of the criteria pollutants show a decreasing trend in both geographies over the seven-year period, except for O3, which presents a significant ascending trend in London and a milder ascending trend in Edinburgh. However, O3 concentrations have significantly decreased during the year 2020 in both urban areas, despite registering sharp increases during the first lockdown period. In turn, these findings indicate on one hand that the O3 generation process is in the VOC-limited regime in both UK urban areas and, on the other hand, confirm previous findings that, when stretching the analysis period, diminishing ozone levels can lead to NOx reduction even in VOC-controlled geographies. Trajectory analysis reveals that northern E

关键词： Air pollutants Trend estimation Theil-Sen estimator Mann -Kendall test generalized additive model Trajectory analysis COVID-19 lockdown impact Ozone pollution London Edinburgh

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Early dengue outbreak detection modeling based on dengue incidences in Singapore during 2012 to 2017

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STATISTICS IN MEDICINE 2020年第15期39卷 2101-2114页

作者： Chen, Piao Fu, Xiuju Ma, Stefan Xu, Hai-Yan Zhang, Wanbing Xiao, Gaoxi Goh, Rick Siow Mong Xu, George Ng, Lee Ching Delft Univ Technol Delft Inst Appl Math Delft Netherlands Inst High Performance Comp Singapore Singapore Minist Hlth Epidemiol & Dis Control Div Singapore Singapore Nanyang Technol Univ Sch Elect & Elect Engn Singapore Singapore Natl Environm Agcy Environm Hlth Inst Singapore Singapore

Dengue has been as an endemic with year-round presence in Singapore. In the recent years 2013, 2014, and 2016, there were several severe dengue outbreaks, posing serious threat to the public health. To proactively control and mitigate the disease spread, early warnings of dengue outbreaks, at which there are rapid and large-scale spread of dengue incidences, are extremely helpful. In this study, a two-step framework is proposed to predict dengue outbreaks and it is evaluated based on the dengue incidences in Singapore during 2012 to 2017. First, a generalized additive model (GAM) is trained based on the weekly dengue incidence data during 2006 to 2011. The proposed GAM is a one-week-ahead forecasting model, and it inherently accounts for the possible correlation among the historical incidence data, making the residuals approximately normally distributed. Then, an exponentially weighted moving average (EWMA) control chart is proposed to sequentially monitor the weekly residuals during 2012 to 2017. Our investigation shows that the proposed two-step framework is able to give persistent signals at the early stage of the outbreaks in 2013, 2014, and 2016, which provides early alerts of outbreaks and wins time for the early interventions and the preparation of necessary public health resources. In addition, extensive simulations show that the proposed method is comparable to other potential outbreak detection methods and it is robust to the underlying data-generating mechanisms.

关键词： generalized additive model statistical process control public health surveillance EWMA control chart

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modeling the Influence of Groundwater Exploitation on Land Subsidence Susceptibility Using Machine Learning Algorithms

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NATURAL RESOURCES RESEARCH 2020年第2期29卷 1127-1141页

作者： Zamanirad, Mahtab Sarraf, Amirpouya Sedghi, Hossein Saremi, Ali Rezaee, Payman Islamic Azad Univ Dept Water Engn Sci & Res Branch Tehran Iran Islamic Azad Univ Roudehen Branch Dept Civil Engn Roudehen Iran Univ Hormozgan Fac Sci Dept Geol Bandar Abbas Hormuzgan Iran

Groundwater over-exploitation in arid and semiarid environments has led to many land subsidence cases. Immense economic losses incurred from land subsidence occurrences prompted many scientists to model this phenomenon. To this end, we used three machine learning models, boosted regression trees (BRTs), generalized additive model (GAM), and random forest (RF), together with four anthropological and geo-environmental predictors, to produce a spatial prediction map across land subsidence-prone area in the south of Iran. The inventory map and preparatory thematic layers were generated through extensive field surveys, using Google Earth images, local information, and organizational archives. The results revealed that the GAM significantly out-performs the BRT in terms of high goodness of fit (84.3% vs. 80.2%) and predictive power (81.6% vs. 70.1%). The RF model, as a benchmark model, showed slightly higher goodness of fit (85.45%) compared to the GAM;however, its prediction power was evidently lower than the GAM. Hence, the GAM was found as the best susceptibility model in the study area. According to the relative contribution test, the drawdown of groundwater level with 77.5% contribution was found to be the main causative predictor of land subsidence occurrence, followed by lithology (19.2%), distance from streams (2.5%), and altitude (0.8%). The results of the GAM suggest that almost 31.6% of the study area is highly susceptible zone to land subsidence occurrence, which can be of interest for further pragmatic actions.

关键词： Land subsidence Boosted regression trees generalized additive model GIS Kerdi Shirazi Plain

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Socioeconomic drivers of urban heat island effect: Empirical evidence from major Chinese cities

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SUSTAINABLE CITIES AND SOCIETY 2020年 63卷 102425-102425页

作者： Li, Ying Sun, Yanwei Li, Jialin Gao, Chao Heilongjiang Univ Sci & Technol Sch Min Engn Harbin 150022 Peoples R China Ningbo Univ Dept Geog & Spatial Informat Tech Ningbo 315211 Peoples R China Ningbo Univ Inst East China Sea Ningbo 315211 Peoples R China

Does socioeconomic development result in exacerbation of urban thermal environment? The answer to this question is extremely critical for mitigating and adapting urban heat island effect (UHI). However, such question has not yet been fully understood the details. The aim of this study was to measure the magnitudes and marginal effect of socioeconomic drivers on UHI dynamics in major Chinese cities. We utilized generalized additive model (GAM) for modelling non-linear/linear relations between economic output, population, industrial structure, geographical features and UHI at seasonal and climate-zones level. The results demonstrate socioeconomic factors explain 12 % 20 % of UHI intensity variations. Urban economic scale generally has a higher contribution rate than variables of population and industrial structure. Urban economic growth raised the heat stress in hot summer. Moreover, a negative linear nexus was observed between the UHI intensity and per capita GDP, indicating that the empirical results supported a post-environmental Kuznets curve (EKC) relationship during the sample period. We suggest both controlling population size and increasing per capita GDP may contribute to mitigate the summer UHI in the tropical cities. Our study highlights macro socioeconomic policy design and urban planning should be combined to counteract or mitigate the UHI.

关键词： Urban heat island effects Urban socioeconomic development generalized additive model

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Too hot to handle: summer space use shift in a cold-adapted ungulate at the edge of its range

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LANDSCAPE ECOLOGY 2020年第6期35卷 1341-1351页

作者： Borowik, Tomasz Ratkiewicz, Miroslaw Maslanko, Weronika Duda, Norbert Kowalczyk, Rafal Polish Acad Sci Mammal Res Inst Stoczek 1 Bialowieza 17230 Poland Univ Bialystok Inst Biol Ciolkowskiego 1 J Bialystok 15245 Poland Univ Life Sci Lublin Dept Anim Ethol & Wildlife Management Akad 13 Lublin 20950 Poland Zespol Szkol Ogolnoksztalcacych 2 Bialymstoku Narewska 11 Bialystok 15840 Poland

Context Global warming has been exerting an increasing stress on mammal populations occurring at the bioclimatic edges of their ranges. Moose, as heat-sensitive ungulates, are expected to be increasingly susceptible to thermal stress;however, the behavioral responses of animals could mitigate unfavorable weather conditions. Objectives We aimed to evaluate the temperature-mediated behavioral changes in moose occurring at the southwestern edge of the species' range in Europe. We predicted that increasing temperature in summer would modify the daily activity pattern of animal and fine-scale utilization of thermal cover. Methods We analysed data from 36 moose, who were fitted with GPS collars from two study sites located in Eastern Poland. The distance between moose locations served for assessing moose activity. We applied additive modelling to test the effect of the daily temperature on daily activity patterns and landscape use of moose. Results Moose, when exposed to temperatures exceeding thermal comfort, increased their activity during cooler twilight hours. On the hottest days, moose were more likely to use tree canopy cover, especially during midday hours. Finally, with increased temperatures and the risk of thermal stress, at that part of the day, moose utilized denser forest stands which could have provided extra protection against solar radiation. Conclusions Our observations suggested that under a scenario of further climate warming, moose at the southwestern periphery of their range will be forced to make further behavioral alterations. However, it is not clear whether they will be able to compensate for the negative effects of on-going climate change.

关键词： Climate change Northern ungulate generalized additive model Daily activity Canopy cover Thermal stress

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Viral zoonotic risk is homogenous among taxonomic orders of mammalian and avian reservoir hosts

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PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 2020年第17期117卷 9423-9430页

作者： Mollentze, Nardus Streicker, Daniel G. Univ Glasgow Ctr Virus Res Med Res Council Glasgow G61 1QH Lanark Scotland Univ Glasgow Inst Biodivers Anim Hlth & Comparat Med Coll Med Vet & Life Sci Glasgow G12 8QQ Lanark Scotland

The notion that certain animal groups disproportionately maintain and transmit viruses to humans due to broad-scale differences in ecology, life history, and physiology currently influences global health surveillance and research in disease ecology, virology, and immunology. To directly test whether such "special reservoirs" of zoonoses exist, we used literature searches to construct the largest existing dataset of virus-reservoir relationships, consisting of the avian and mammalian reservoir hosts of 415 RNA and DNA viruses along with their histories of human infection. Reservoir host effects on the propensity of viruses to have been reported as infecting humans were rare and when present were restricted to one or two viral families. The data instead support a largely host-neutral explanation for the distribution of human-infecting viruses across the animal orders studied. After controlling for higher baseline viral richness in mammals versus birds, the observed number of zoonoses per animal order increased as a function of their species richness. Animal orders of established importance as zoonotic reservoirs including bats and rodents were unexceptional, maintaining numbers of zoonoses that closely matched expectations for mammalian groups of their size. Our findings show that variation in the frequency of zoonoses among animal orders can be explained without invoking special ecological or immunological relationships between hosts and viruses, pointing to a need to reconsider current approaches aimed at finding and predicting novel zoonoses.

关键词： infectious disease reservoir surveillance generalized additive model

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