scholarly journals Long-Term Spatio-Temporal Trends of Organotin Contaminations in the Marine Environment of Hong Kong

PLoS ONE ◽  
2016 ◽  
Vol 11 (5) ◽  
pp. e0155632 ◽  
Author(s):  
Kevin K. Y. Ho ◽  
Guang-Jie Zhou ◽  
Elvis G. B. Xu ◽  
Xinhong Wang ◽  
Kenneth M. Y. Leung
Keyword(s):  
Hong Kong ◽  
Marine Environment ◽  
Temporal Trends ◽  
Spatio Temporal

scholarly journals An Analysis of Long-Term Rainfall Trends and Variability in the Uttarakhand Himalaya Using Google Earth Engine

2020 ◽  
Vol 12 (4) ◽  
pp. 709 ◽  
Author(s):  
Abhishek Banerjee ◽  
Ruishan Chen ◽  
Michael E. Meadows ◽  
R.B. Singh ◽  
Suraj Mal ◽  
...  
Keyword(s):  
River Basin ◽  
Temporal Trends ◽  
Google Earth ◽  
Monthly Rainfall ◽  
Annual Rainfall ◽  
Google Earth Engine ◽  
Spatio Temporal ◽  
Uttarakhand Himalaya ◽  
Rainy Days

This paper analyses the spatio-temporal trends and variability in annual, seasonal, and monthly rainfall with corresponding rainy days in Bhilangana river basin, Uttarakhand Himalaya, based on stations and two gridded products. Station-based monthly rainfall and rainy days data were obtained from the India Meteorological Department (IMD) for the period from 1983 to 2008 and applied, along with two daily rainfall gridded products to establish temporal changes and spatial associations in the study area. Due to the lack of more recent ground station rainfall measurements for the basin, gridded data were then used to establish monthly rainfall spatio-temporal trends for the period 2009 to 2018. The study shows all surface observatories in the catchment experienced an annual decreasing trend in rainfall over the 1983 to 2008 period, averaging 15.75 mm per decade. Analysis of at the monthly and seasonal trend showed reduced rainfall for August and during monsoon season as a whole (10.13 and 11.38 mm per decade, respectively); maximum changes were observed in both monsoon and winter months. Gridded rainfall data were obtained from the Climate Hazard Infrared Group Precipitation Station (CHIRPS) and Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR). By combining the big data analytical potential of Google Earth Engine (GEE), we compare spatial patterns and temporal trends in observational and modelled precipitation and demonstrate that remote sensing products can reliably be used in inaccessible areas where observational data are scarce and/or temporally incomplete. CHIRPS reanalysis data indicate that there are in fact three significantly distinct annual rainfall periods in the basin, viz. phase 1: 1983 to 1997 (relatively high annual rainfall); phase 2: 1998 to 2008 (drought); phase 3: 2009 to 2018 (return to relatively high annual rainfall again). By comparison, PERSIANN-CDR data show reduced annual and winter precipitation, but no significant changes during the monsoon and pre-monsoon seasons from 1983 to 2008. The major conclusions of this study are that rainfall modelled using CHIRPS corresponds well with the observational record in confirming the decreased annual and seasonal rainfall, averaging 10.9 and 7.9 mm per decade respectively between 1983 and 2008, although there is a trend (albeit not statistically significant) to higher rainfall after the marked dry period between 1998 and 2008. Long-term variability in rainfall in the Bhilangana river basin has had critical impacts on the environment arising from water scarcity in this mountainous region.

scholarly journals 1249Trends and disparities in adult body mass index across 47 prefectures in Japan, 1975–2018

2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
Nayu Ikeda ◽  
Tomoki Nakaya ◽  
James Bennett ◽  
Majid Ezzati ◽  
Nobuo Nishi
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Temporal Trends ◽  
Poor Performance ◽  
Bayesian Hierarchical ◽  
Adult Body Mass ◽  
Adult Body ◽  
Adult Body Mass Index ◽  
Spatio Temporal

Abstract Background Consistent and comparable health information across prefectures is necessary for monitoring progress in improving population health and reducing geographic health disparities in Japan. We aimed to examine long-term trends and variations in adult body mass index (BMI) by prefecture. Methods We obtained a total sample of 233,988 males and 261,086 females aged 20–79 years with anthropometric measurements from National Health and Nutrition Surveys conducted annually during 1975–2018. We applied a spatio-temporal Bayesian hierarchical model to estimate the annual time series of prefectural mean BMI by 20-year age group and sex. Results Prefectural mean BMI consistently increased in males regardless of age but decreased in younger females. It increased in older females until starting to decrease in the early 2000s. Mean BMI was noticeably higher in Okinawa, the southernmost prefecture, than in other prefectures from 1975 in males and from the 1990s in females. The interquartile range of mean BMI across prefectures was consistently higher in females than in males. It decreased over time to plateau during the 2000s in both sexes. Conclusions Mean BMI increased in males across prefectures and there is a need for stimulating a further reduction in geographic disparities particularly for females. Okinawa once ranked first in longevity but has shown relatively poor performance in recent years, which may be partly attributable to the distinctive trends in adult BMI. Key messages Bayesian hierarchical modelling is useful for reconstructing long-term spatio-temporal trends of mean BMI by integrating small-size survey samples.

Two monitoring methods that assess species composition and spatio-temporal trends in bycatch from an important temperate rock lobster (Jasus edwardsii) fishery

2007 ◽  
Vol 58 (3) ◽  
pp. 273 ◽  
Author(s):  
Daniel J. Brock ◽  
Peter J. Hawthorne ◽  
Timothy M. Ward ◽  
Adrian J. Linnane
Keyword(s):  
Temporal Trends ◽  
Cost Effective ◽  
Accurate Information ◽  
Monitoring Methods ◽  
Rock Lobster ◽  
Scientific Analysis ◽  
Jasus Edwardsii ◽  
Fisheries Bycatch ◽  
Spatio Temporal

The effectiveness of two monitoring programs, designed to describe and quantify the bycatch from commercial pots, was examined in the South Australian rock lobster (Jasus edwardsii) fishery (SARLF). The first, logbook sampling, relied on information collected and recorded by fishers in logbooks. The second, bycatch sampling, required fishers to collect bycatch specimens on a nominated day for later scientific analysis. A total of 40 bycatch species were recorded during the study. Finfish, mainly blue-throat wrasse (Notolabrus tetricus) and leather jacket species (Meuschenia hippocrepis and Meushenia australis), were the major component (>90% by number). Data from the logbook program were appropriate for monitoring spatio-temporal trends in bycatch, whereas the bycatch sampling provided more accurate information on bycatch species. Each program was subject to bias when estimating total bycatch numbers and, as a result, a combination of both methods indicated a cost-effective and appropriate way with which to monitor bycatch from the fishery. In comparison with other fisheries, bycatch from the SARLF was relatively low; however, because bycatch was dominated by relatively few species, ongoing monitoring and risk assessment of these populations is needed to ensure long-term sustainability of bycatch levels.

scholarly journals Spatio-temporal change in rainfall over five different climatic regions of India

2021 ◽  
Author(s):  
Litan Kumar Ray ◽  
Narendra Kumar Goel
Keyword(s):  
Serial Correlation ◽  
Temporal Trends ◽  
Tropical Regions ◽  
Climatic Regions ◽  
Seasonal Basis ◽  
Spatio Temporal ◽  
Almost All ◽  
Stationary Behaviour ◽  
Semi Arid

Abstract The present study deals with the estimation of dependences, spatio-temporal trends, change points, and stationarity in rainfall and rainy day series (1901–2013) for five (out of six) different climatic regions of India. Only one-fourth of the station rainfall and rainy day datasets exhibits long-term dependence on an annual and seasonal basis. The presence of lag-one serial correlation is prominent for almost all the climatic regions of India. The significant decreasing trend is found mainly for the stations of semi-arid and humid sub-tropical regions. The magnitude of rainfall is decreasing for most parts of the study area by 10% for annual and monsoon seasons. The change point is presented in a smaller number of stations. Non-stationary behaviour is observed for the rainy day series of semi-arid and humid sub-tropical regions, which may increase the temporal variability of rainfall over the same regions. The findings of this study could be very useful for the planning and management of water resources of different climatic regions of India.

scholarly journals Documentary data and the study of past droughts: a global state of the art

2018 ◽  
Vol 14 (12) ◽  
pp. 1915-1960 ◽  
Author(s):  
Rudolf Brázdil ◽  
Andrea Kiss ◽  
Jürg Luterbacher ◽  
David J. Nash ◽  
Ladislava Řezníčková
Keyword(s):  
Large Scale ◽  
State Of The Art ◽  
Drought Indices ◽  
Documentary Evidence ◽  
Climatic Trends ◽  
Instrumental Observations ◽  
Spatio Temporal ◽  
Epigraphic Evidence ◽  
Administrative Evidence

Abstract. The use of documentary evidence to investigate past climatic trends and events has become a recognised approach in recent decades. This contribution presents the state of the art in its application to droughts. The range of documentary evidence is very wide, including general annals, chronicles, memoirs and diaries kept by missionaries, travellers and those specifically interested in the weather; records kept by administrators tasked with keeping accounts and other financial and economic records; legal-administrative evidence; religious sources; letters; songs; newspapers and journals; pictographic evidence; chronograms; epigraphic evidence; early instrumental observations; society commentaries; and compilations and books. These are available from many parts of the world. This variety of documentary information is evaluated with respect to the reconstruction of hydroclimatic conditions (precipitation, drought frequency and drought indices). Documentary-based drought reconstructions are then addressed in terms of long-term spatio-temporal fluctuations, major drought events, relationships with external forcing and large-scale climate drivers, socio-economic impacts and human responses. Documentary-based drought series are also considered from the viewpoint of spatio-temporal variability for certain continents, and their employment together with hydroclimate reconstructions from other proxies (in particular tree rings) is discussed. Finally, conclusions are drawn, and challenges for the future use of documentary evidence in the study of droughts are presented.

scholarly journals Climate drivers of plague epidemiology in British India, 1898–1949

2020 ◽  
Vol 287 (1928) ◽  
pp. 20200538
Author(s):  
Warren S. D. Tennant ◽  
Mike J. Tildesley ◽  
Simon E. F. Spencer ◽  
Matt J. Keeling
Keyword(s):  
Predictive Models ◽  
Control Measures ◽  
Climate Data ◽  
British India ◽  
Middle Income ◽  
Middle Income Countries ◽  
Complex Interactions ◽  
The World ◽  
Spatio Temporal

Plague, caused by Yersinia pestis infection, continues to threaten low- and middle-income countries throughout the world. The complex interactions between rodents and fleas with their respective environments challenge our understanding of human plague epidemiology. Historical long-term datasets of reported plague cases offer a unique opportunity to elucidate the effects of climate on plague outbreaks in detail. Here, we analyse monthly plague deaths and climate data from 25 provinces in British India from 1898 to 1949 to generate insights into the influence of temperature, rainfall and humidity on the occurrence, severity and timing of plague outbreaks. We find that moderate relative humidity levels of between 60% and 80% were strongly associated with outbreaks. Using wavelet analysis, we determine that the nationwide spread of plague was driven by changes in humidity, where, on average, a one-month delay in the onset of rising humidity translated into a one-month delay in the timing of plague outbreaks. This work can inform modern spatio-temporal predictive models for the disease and aid in the development of early-warning strategies for the deployment of prophylactic treatments and other control measures.

Sign in / Sign up

Export Citation Format

Share Document