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We have found 62 datasets for the keyword " pesticides". You can continue exploring the search results in the list below.
Datasets: 106,578
Contributors: 42
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62 Datasets, Page 1 of 7
Monitoring of pesticides in surface water
This thematic layer shows the location of pesticide stations in surface water monitored as part of various studies. The data comes from an extraction from the BQMA and, when a report is available on the Department's website, the reader can access it from a link in the information window. The dataset on the monitoring of pesticides in surface water also includes a layer of sampling stations, a layer of polygons presenting the drainage areas of some of the stations and finally, a data table including the compilation of land use by year for each of these drainage areas. The drainage areas and the land use table are linked to the sampling stations based on the BQMA station number.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**
Agri-Environmental Indicator – Risk of Water Contamination by Pesticides
The Agri-Environmental Indicator Risk of Water Contamination by Pesticides dataset reports the annual and semi-decadal status of pesticide transport to surface water, the concentration of pesticide in ground water, and the risk of water contamination by pesticide. Products in this data series present results for predefined areas as defined by the Soil Landscapes of Canada (SLC v.3.2) data series, uniquely identified by SOIL_LANDSCAPE_ID values.
Monitoring of pesticides in groundwater
This thematic layer shows the location of the wells sampled for pesticides in the context of various studies carried out near certain target crop environments between 1999 and 2024. The data comes from an extraction from the BQMA and, when a report is available on the Department's website, the reader can access it from a link in the information window. Private well sampling stations are grouped by watershed in order to comply with sections 53 and 54 of the Act on access to documents held by public bodies and on the protection of personal information.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**
Contaminants in fish database
The contaminants in fish database is a compilation of contaminant data analysed from fish tissue at the Fresh Water Institute from 1970 to 2005. Data include lab number, region, analysis, organs, species, lake, form (whole fish, headon dressed, headless dressed), weight, and length and contaminant concentrations. Total mercury was the predominant contaminant measured. Results were expressed as ppm or ppb based on the parameter analyzed. Concentrations are expressed based on wet weight.
Chemical Expense Index 2001
The data represents the relative expense of farm chemicals (herbicides, insecticides and fungicides) in the agricultural area of Alberta. It is an estimate of the degree to which crop production agriculture may contribute to surface or groundwater contamination.Agriculture production that makes greater use of herbicides, insecticides and pesticides in generally considered more intensive. Presenting the relative farm chemical expenses by SLC polygons reveals where the most intensive agricultural production in the province occurs. Chemical use is part of an equation to determine a measure of surface water quality risk. If an area is known to have certain risk factors that would affect not only surface, but groundwater quality as well, a higher chemical expense index ranking in that same area may be of concern. Where risks of surface or groundwater contamination exist, environmental farm planning can help to minimize them.
Maritime region grain size data
Fisheries and Oceans Canada (DFO) Maritime Science Branch has collected grain size data from sediment and water column samples using bottle samples, sediment cores, and sediment grabs as part of numerous research projects not only in the Atlantic provinces, but also worldwide. The data collected by DFO focuses on the fine grained (<1mm) particles as these are both a source of food and means of contaminant transport. Grain size data are used to study the fate and distribution of complimentary chemistries like heavy metals, pesticides, hydrocarbons, aquaculture waste as well as a variety of physical processes such as the resuspension and transport of sediment.
Gilpinia hercyniae
Historical finds of Gilpinia hercyniae
Coleophora laricella
Historical finds of Coleophora laricella
Characterization of the Batture-aux-Alouettes kelp bed in 2018-2019
The purpose of this study was to characterize the kelp bed at Batture-aux-Alouettes, a preferred food source for the green sea urchin (Strongylocentrotus droebachiensis). The green urchin is fished commercially in Quebec and the fishing effort is concentrated on the Batture-aux-Alouettes near Tadoussac, at the mouth of the Saguenay Fjord. The study was conducted in two separate phases in 2018 and 2019. The main objective of this study was to determine the abundance and biomass of the kelp bed at Batture-aux-Alouettes. The first phase, using a stratified random sampling design, was conducted from August 21th to August 24th, 2018. Sampling of two 50 x 50 cm quadrats, separated by a distance of approximately 30 m, was conducted at eleven sites during twelve dives in the eastern section of the Batture-aux-Alouettes to collect kelp for biomass estimation and macroalgal species richness assessment. In the second phase, a total of 429 stations were first sampled between July 15 and 18, 2019 with a camera system dropped in two 50 x 50 cm quadrats. The presence or absence of kelp, percent macroalgal cover, and substrate type were assessed for each photo. As a result of this underwater photographic analysis, 129 of these stations were identified as having a presence of kelp and 88 of these stations had a presence of other algal species. To ensure equal representation of the different depth strata, the stations with kelp were divided into three depth categories: shallow (-1.7 m to 0 m), medium (0 m to 2 m) and deep (2 m to 5 m). Dives were conducted from August 13 to 15, 2019, at ten of these stations using a stratified random sampling design, taking care to ensure a balanced spatial distribution as well as an equal distribution of the different depth strata (four in the shallow, three in the medium, and two in the deep). Sampling of the 50 x 50 cm dive quadrat took place at three different distances spaced 5 m apart from a transect, i.e. at the 3 m (_3m), 8 m (_8m) and 13 m (_13m) mark. If there was little or no kelp in the quadrat, the quadrat sampling could be repeated for up to four quadrats per distance for a total area of 1 m². Two additional quadrats were conducted (_x) at two stations. Biomass assessment was also done via "cookie cutter" sampling (_CC). Divers took the same 50 x 50 cm quadrat and placed it on a selected (i.e., non-random) plot with 100% kelp cover.The three files provided (DarwinCore format) are complementary and are linked by the "eventID" key. The "event_information" file includes generic information about the event, such as date and location. The "additional_information_event_and_occurrence" file includes sample size, protocol and sampling effort. The "taxon_occurrence" file includes the taxonomy of the species observed, identified to the species or lowest possible taxonomic level. To obtain the abundance and biomass assessment of the kelp bed at Batture-aux-Alouettes, contact Rénald Belley (renald.belley@dfo-mpo.gc.ca).For quality control, the organisms were identified in the field fallowing the guide: Chabot, Robert et Anne Rossignol. 2003. Algues et faune du littoral du Saint-Laurent maritime : Guide d'identification. Institut des Sciences de la mer de Rimouski, Rimouski; Pêches et Océans Canada (Institut Maurice-Lamontagne), Mont-Joli. 113 pages. The taxonomy was checked against the World Register of Marine Species (WoRMS) to match recognized standards and using the R obistools and worrms libraries. The WoRMS match was placed in the "scientificNameID" field of the occurrence file. All sample locations were spatially validated. This project was funded by DFO Coastal Environmental Baseline Program under Canada’s Oceans Protection Plan. This initiative aims to acquire environmental baseline data contributing to the characterization of important coastal areas and to support evidence-based assessments and management decisions for preserving marine ecosystems.
Lymantria dispar
Historical finds of Lymantria dispar
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