There are several species of moths whose caterpillars are significant pests on agricultural crops. While there are natural predators, some are unwilling hosts for parasites. Some parasitoid wasp species contribute to biological control of these caterpillar pests by laying eggs inside live caterpillars. Dataset Type: Occurrence Specimen Type: Preserved specimens

The white shark (Carcharodon carcharias), is a species found in Atlantic Canadian waters which is encountered in commercial and recreational fisheries. Pop-up Satellite Archival Tags (PSAT) from Wildlife Computers were applied to white sharks from 2016 to the present to collect data on depth (pressure), temperature and ambient light level (for position estimation). Deployments were conducted in Canada and the United States (Cape Cod and South Carolina) on scientific charters, typically in summer. Tag models deployed included: Mk10 (N=1), and MiniPAT (N=29) and 22 of 27 tags reported with 3 still at liberty. One individual shark returned to the location of tagging 1 year later and the physical tag was recovered. Another tag was recovered 5 years after deployment. White sharks tagged ranged in size from 259 cm to 459 cm Total Length (curved) estimated; 15 were female, 13 were male, and 2 were of unknown sex. Time at liberty ranged from 48 – 377 days and to date, only 3 tags remained on the shark for the programmed duration. Tagging of white sharks is an ongoing study and data will be updated here when it becomes available. Raw data transmitted from the PSAT’s after release was processed through Wildlife Computers software (GPE3) to get summary files, assuming a maximum swimming speed of 2m/s, NOAA OI SST V2 High Resolution data set for SST reference and ETOPO1-Bedrock dataset for bathymetry reference. The maximum likelihood position estimates are available in .csv and .kmz format and depth and temperature profiles are also in .csv format. Other tag outputs as well as metadata from the deployments can be obtained upon request from: warren.joyce@dfo-mpo.gc.ca or heather.bowlby@dfo-mpo.gc.ca.

The spatial record for all the province's geographic areas affected by provincial level, area-specific land use policy. This layer may contain geometry from the: * provincial parks-regulated layer * conservation reserves-regulated layer * natural heritage values area layer *  wilderness areas layer * crown land MNR acquisitions layer * crown land MNR unpatented layer * CLUPA geometry (enhanced management areas and general use areas) layer Not to be used as a source of protected areas (provincial park, conservation reserve, etc.), crown land or private land boundaries. Official GEO title: CLUPA Provincial

Two classes of beaches are distinguished, those with infrastructure and those without. Beaches with infrastructure: open sandy beaches along the shore of a great lake, within approximately 200 meters of a structure. Beaches without infrastructure: open sandy beaches along the shore of a great lake, not within 200 meters of a structure. The Southern Ontario Land Resource Information System didn't digitize beaches. Beaches were digitized by Austin Troy from Google Earth. This product requires the use of GIS software. *[GIS]: geographic information system

As the COVID-19 pandemic spreads, researchers and health professionals have noted large differences in the impact that the infection has on individuals. Whereas some remain asymptomatic and unaware of their infection or experience only mild symptoms, others require hospitalization, ventilation, and may even die. As research evidence accumulates, both nationally and internationally, it appears that certain health characteristics, such as obesity or the presence of chronic conditions, increase the risk of severe outcomes among those who are infected with the novel coronavirus. To better understand which segments of the Canadian population may be vulnerable to severe health outcomes related to COVID-19, Statistics Canada and the Public Health Agency of Canada have worked collaboratively to build an index of underlying health conditions in the adult household population. Using information from the 2017/2018 Canadian Community Health Survey, new data tables released today estimate the proportion of the adult household population who may be at greater risk of severe health outcomes related to COVID-19 due to the presence of underlying health conditions.

## Get data on boundaries of local climatic areas used for forest fire weather forecasting. This dataset shows the boundaries of administrative areas used for forest fire weather forecasting. North of the French River, boundaries correspond closely with Environment Canada’s areas for public weather forecasting. South of the French River, 25 Environment Canada areas are combined into six larger areas for provincial forecasting.

**NOTE: Not for operational use. This dataset is the result of an analysis (Aug 2018) of many input layers and as such the accuracy, currency, and completeness of the dataset cannot be relied upon for operational or management decision making.** Land designations that contribute to conservation are spatially-defined areas established through legislation or purchased for the protection of nature and cultural values, the conservation of biological diversity and ecosystem services and the management of natural resources. Over 40 land designations were divided into three broad categories: - **Protected Lands** includes all Parks & Protected Areas and Other Protected Lands with the primary purpose of the long-term conservation of nature and cultural values. - **Resource Exclusion Areas** includes all designations that fully exclude one or two resource activities for the purpose of conservation. - **Spatially Managed Areas** includes all spatial designations managing or limiting development or a resource activity for the purpose of conservation, or a spatial management regime in place to preserve specified elements of biodiversity but where activity is still allowed to occur. Land designations layers were combined into a single layer, with overlaps removed such that areas with overlapping designations were assigned to the highest conservation contribution category. **Data sources:** A list of the source datasets, including links to their sources, more information, and data processing steps is available [**here**](https://raw.githubusercontent.com/bcgov/designatedlands/v0.1.0/sources.csv). Details on methods are available [**here**](https://github.com/bcgov/designatedlands). Previous versions of the data are available [**here**](https://github.com/bcgov/designatedlands/releases).

“Waterton Lakes National Park - Total Ecosystem Forest Carbon Density” is the annual carbon density (tonnes carbon per hectare) within Waterton Lake’s forested over a 31-year period from 1990 to 2020. Total Ecosystem Forest Carbon Density includes aboveground and belowground biomass, soil carbon, and dead organic matter. Total Ecosystem Forest Carbon Density was estimated for 31 national parks using the Generic Carbon Budget Model (GCBM), a spatially explicit carbon budget model developed by Canadian Forest Service which uses forest inventory, disturbance, and mean annual temperature data along with yield data to estimate growth and merchantable volume for dominant tree species. Species- and Ecozone-specific equations are then used to convert merchantable volume to aboveground and belowground biomass carbon. Ecozones were classified according to Canada Ecological Land Classification Level 1. The GCBM simulates carbon dynamics to produce spatially explicit estimations of carbon stocks and fluxes. The model simulates and tracks carbon stocks, transfers between Intergovernmental Panel on Climate Change-defined pools, and other metrics including net ecosystem production, net biome production, and emissions of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) in annual time steps. The stocks and fluxes are also tracked by disturbance event (e.g., forest fires, insect outbreaks). Total Ecosystem Forest Carbon Density accounts for the effects of natural and anthropogenic disturbances, including wildfires, prescribed burns, and insect outbreaks. These products have a spatial resolution of 30m. This information is part of the Parks Canada Carbon Atlas Series. To obtain a copy of this report, please contact changementclimatique-climatechange@pc.gc.ca. When using this data, please cite as follows: Sharma, T., Kurz, W.A., Fellows, M., MacDonald, A.L., Richards, J., Chisholm, C., Seutin, G., Richardson, K., Keenleyside, K. (2023). Parks Canada Carbon Atlas Series: Carbon Dynamics in the Forests of Canada’s National Parks. Scientific Report. Parks Canada Agency, Gatineau, QC, Canada, 104 p.

Canada’s NFI survey was designed to provide an unbiased probability sample of Canada’s forests for long-term strategic monitoring purposes. The target population is Canada’s entire non-Arctic land area. A National Terrestrial Monitoring Framework (NTMF) was created by establishing a systematic 4 km by 4 km sampling grid over all of Canada from a random offshore point. Prior to T0, NFI partners determined that the NFI program would be able to affordably achieve its mission by establishing a 2 km by 2 km (400 ha) “photo plot” at every fifth sampling point on the NTMF (i.e. every 20 km), thereby providing a one percent sample of the target population. This sampling intensity was considered sufficient for national reporting and possible to sustain over the long term with anticipated funding. Photo plots were established across Canada during 2000-2006 (T0). There are 26,139 photo plot survey locations on the 20 km by 20 km grid, of which 18,570 lie inside the target population area. For each photo plot, information is collected on land cover, land use, ownership and protection status. NFI photo plot survey data are stratified by “NFI Unit” for standard estimation and reporting purposes. NFI Units were created by the geographic intersection of Canada’s 10 provinces, 3 territories and 12 non-Arctic terrestrial ecozones. Estimates produced for NFI Units are rolled up to produce standard reports for ecozones, jurisdictions (provinces and territories) and Canada. Some NFI Units are too small to produce robust estimates for with the current sampling intensity, so NFI Unit estimates are not publicly reported. Prince Edward Island (PEI) Atlantic Maritime, for example, is PEI’s only NFI Unit and it is small (1% sampling intensity achieved with only 19 photo plots), so the NFI avoids publishing provincial reports. Information consumers are encouraged to use official statistics produced by provincial and territorial governments for the forests in their jurisdictions. Most provinces are large, however, and the current NFI sampling intensity is sufficient for producing robust NFI reports for those jurisdictions. Special estimation reports can be produced using different ecological or administrative strata, such as the Boreal Zone, or the Managed Forest. NFI photo plots are surveyed on a ten-year cycle. During first re-measurement (T1; 2008-2017), survey intensity was reduced to one photo plot every 40 km across northern Canada (Figure 3) because of budget limitations. The T2 survey (2018-2027) is currently underway.

List of schools offering French programs.