Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Ariola Visha"'
Autor:
George B. Arhonditsis, Satyendra P. Bhavsar, Carlos Arnillas Alberto, Felicity J. Ni, Ariola Visha
Publikováno v:
Journal of Great Lakes Research. 47:1097-1116
In this study, we conducted a retrospective analysis of the spatio-temporal trends of fish contamination in the Canadian Great Lakes. We subsequently formulated consumption advisories that explicitly account for all sources of uncertainty, such as mo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c7ebdd36936c8299d1cf222adfbe506e
https://doi.org/10.1016/j.jglr.2021.03.016
https://doi.org/10.1016/j.jglr.2021.03.016
Autor:
Mark E. McMaster, Paul C. Baumann, E. Agnes Blukacz-Richards, Ariola Visha, Carlos Alberto Arnillas, George B. Arhonditsis
Publikováno v:
Journal of Great Lakes Research. 47:916-933
Liver and skin tumours in brown bullhead (Ameiurus nebulosus) and white sucker (Catostomus commersoni) have been associated with contamination of the aquatic environment. In this study, we present a Bayesian hierarchical logistic-Bernoulli framework
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::13172ccd981300425f05c6c59ac2e6e5
https://doi.org/10.1016/j.jglr.2021.02.004
https://doi.org/10.1016/j.jglr.2021.02.004
Autor:
George B. Arhonditsis, Maryam Ramin, Aisha Javed, Dong-Kyun Kim, Shan Mugalingam, Demetrios Kobiliris, Tianna Peller, Ariola Visha, Yuko Shimoda, Cindy Yang, Felicity J. Ni, Gurbir Perhar, Noreen E. Kelly, Vincent Cheng, Samarth Kaluskar, Christopher Wellen, Alex Neumann
Publikováno v:
Ecological Informatics. 48:147-157
In water quality management, delisting decisions for impaired waterbodies bear resemblance to the statistical null hypothesis testing in which the prevailing conditions in the system at hand are compared against a reference (or non-impaired) state. T
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b43e486b417643b107382202cc8c6b5f
https://doi.org/10.1016/j.ecoinf.2018.08.005
https://doi.org/10.1016/j.ecoinf.2018.08.005
Publikováno v:
Chemosphere. 210:1193-1206
Polychlorinated biphenyl (PCB) contamination has historically posed constraints on the recreational and commercial fishing industry in the Great Lakes. Empirical evidence suggests that PCB contamination represents a greater health risk from fish cons
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ba1271b90a02e1d8490e6d26f39cb490
https://doi.org/10.1016/j.chemosphere.2018.07.070
https://doi.org/10.1016/j.chemosphere.2018.07.070
Autor:
George B. Arhonditsis, Shane R. de Solla, Daryl L. McGoldrick, Ariola Visha, Matthew L. Graham, David J. Moore, E. Agnes Blukacz-Richards
Publikováno v:
Chemosphere. 172:476-487
Total mercury levels in aquatic birds and fish communities have been monitored across the Canadian Great Lakes by Environment and Climate Change Canada (ECCC) for the past 42 years (1974-2015). These data (22 sites) were used to examine spatio-tempor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8ed2cca4f784527a26dcd06d9f6990a6
https://doi.org/10.1016/j.chemosphere.2016.12.148
https://doi.org/10.1016/j.chemosphere.2016.12.148
Autor:
Ariola Visha, David C. Depew, Felicity J. Ni, Laud Matos, Cindy Yang, George B. Arhonditsis, Alexander Lau, Satyendra P. Bhavsar
Publikováno v:
Ecological Informatics. 62:101271
Environmental policy analysis aims to identify the important drivers of degradation, elucidate sources of controversy, and put the necessary risk assessment tools in place to prepare for the unexpected. It is thus critical to develop risk assessment
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1ef89c17c7b320c414376a9d3be2f2b0
https://doi.org/10.1016/j.ecoinf.2021.101271
https://doi.org/10.1016/j.ecoinf.2021.101271
Publikováno v:
Journal of Great Lakes Research. 42:70-82
We evaluate the temporal trends of total mercury (THg) and polychlorinated biphenyls (PCBs) in walleye ( Sander vitreus ) and lake trout ( Salvelinus namaycush ) based on approximately 40 years of contaminant data from different locations in Lake Ont
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d32ce026b98c61f0fa35be2610f99084
https://doi.org/10.1016/j.jglr.2015.11.005
https://doi.org/10.1016/j.jglr.2015.11.005
Publikováno v:
Environmental pollution (Barking, Essex : 1987). 243
We examine the spatio-temporal trends of mercury, a well-known global legacy contaminant, in eleven fish species across all of the Canadian Great Lakes. These particular fish species are selected based on their ecological, commercial, and recreationa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::570a751d535f74274cca5d5de3cb5e26
https://pubmed.ncbi.nlm.nih.gov/30224205
https://pubmed.ncbi.nlm.nih.gov/30224205
Publikováno v:
Ecotoxicology and Environmental Safety. 117:174-186
Polychlorinated biphenyls (PCBs) and total mercury (THg) are two of the most prevalent contaminants, resulting in restrictive advisories on consuming fish from the Laurentian Great Lakes. The goal of this study is to examine the temporal trends of th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ce2c40d7b7284ad83bbc1c750d92a255
https://doi.org/10.1016/j.ecoenv.2015.03.022
https://doi.org/10.1016/j.ecoenv.2015.03.022
Autor:
Aisha Javed, Alex Neumann, Ariola Visha, Meghan Brady, Cindy Yang, George B. Arhonditsis, Dong-Kyun Kim, Yuko Shimoda, Feifei Dong, Gabriela Onandia, Felicity J. Ni, Vincent Cheng
Publikováno v:
Ecological Informatics. 53:100969
In Lake Erie, a wide variety of statistical and process-based models have significantly advanced our understanding of the major causal linkages/ecosystem processes underlying the local water quality problems. In this study, our aim is to identify kno
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::210c8f14997f581c07e2e1e234a09c1e
https://doi.org/10.1016/j.ecoinf.2019.05.015
https://doi.org/10.1016/j.ecoinf.2019.05.015