An abiotic damage event is a non-biological event -- such as wind or an ice storm -- that has damaged areas of forested land. Abiotic damage event information is mainly used to: * generate summary maps for these events at a general or provincial scale * monitor the extent of damage for forest fire prevention purposes * calculate gross timber volume loss estimates caused by these events This product requires the use of geographic information system (GIS) software.

Miscellaneous events are often the result of the cumulative impact of a combination of abiotic, insect and disease agents or events. For example, Aspen decline where repeated infestations of Forest Tent Caterpillar, are combined with several seasons of prolonged drought. The Government of Ontario tracks forest damage events to help proactively manage the detrimental effects to our forests.   We monitor the threat and spread of invasive forest pest insect species in Ontario. The data is also important to the Forest Management Planning process in calculating timber volume loss within affected areas. This product requires the use of geographic information system (GIS) software.

Most of these events involved community evacuations, significant structural loss and/or involvement of a Ministry of Natural Resources (MNR) Emergency Response Officer. Events include those assigned to MNR by an Order-In-Council under the Emergency Management and Civil Protection Act as well as events where MNR provided requested emergency response assistance. These events fall into one of ten type categories: * dam failure * drought /low water * erosion * flood * forest fire * soil and bedrock instability * Petroleum Resource Center event * EMO requested assistance * continuity of operations event * other requested assistance This product requires the use of geographic information system (GIS) software.

In 1949 a magnitude 8.1 earthquake occurred on the Queen Charlotte Fault, off the west coast of the Haida Gwaii archipelago. This magnitude 8.0 scenario along the Queen Charlotte Fault is slightly different and closer to population centres than the magnitude 7.8 earthquake that occurred in 2012.

The fire regime describes the patterns of fire seasonality, frequency, size, spatial continuity, intensity, type (e.g., crown or surface fire) and severity in a particular area or ecosystem.The number of large fires refers to the annual number of fires greater than 200 hectares (ha) that occur per units of 100,000 ha. It was calculated per Homogeneous Fire Regime (HFR) zones. These HFR zones represent areas where the fire regime is similar over a broad spatial scale (Boulanger et al. 2014). Such zonation is useful in identifying areas with unusual fire regimes that would have been overlooked if fires had been aggregated according to administrative and/or ecological classifications.Fire data comes from the Canadian National Fire Database covering 1959–1999 (for HFR zones building) and 1959-1995 (for model building). Multivariate Adaptive Regression Splines (MARS) modeling was used to relate monthly fire regime attributes with monthly climatic/fire-weather in each HFR zone. Future climatic data were simulated using the Canadian Earth System Model version 2 (CanESM2) and downscaled at a 10 Km resolution using ANUSPLIN for two different Representative Concentration Pathways (RCP). RCPs are different greenhouse gas concentration trajectories adopted by the Intergovernmental Panel on Climate Change (IPCC) for its fifth Assessment Report. RCP 2.6 (referred to as rapid emissions reductions) assumes that greenhouse gas concentrations peak between 2010-2020, with emissions declining thereafter. In the RCP 8.5 scenario (referred to as continued emissions increases) greenhouse gas concentrations continue to rise throughout the 21st century.Provided layer: projected number of large fires (>200 ha) across Canada for the short-term (2011-2040) under the RCP 8.5 (continued emissions increases).Reference: Boulanger, Y., Gauthier, S., et al. 2014. A refinement of models projecting future Canadian fire regimes using homogeneous fire regime zones. Canadian Journal of Forest Research 44, 365–376.

Data show where pathogens - fungal, bacillial or viral - have caused damage by reducing growth rates, tree vigor or have killed trees. Examples of forest diseases include White Pine Blister Rust, Armillaria Root Rot etc. The Government of Ontario tracks forest damage events to help proactively manage the detrimental effects to our forests. We monitor the threat and spread of invasive forest pest insect species in Ontario. The data is also important to the Forest Management Planning process in calculating timber volume loss within affected areas. This product requires the use of geographic information system (GIS) software.

A magnitude 5 earthquake scenario along an unnamed fault located about 15 km north-northeast of Burnaby City Hall and directly south of Mt Elsay. This fault is not known to be active, but this scenario represents a small but damaging event in the North Shore Mountains.

On July 6, a train of 72 cars, carrying 100 tons of crude oil each, exploded in Lac-Mégantic. A high-resolution aerial photograph was collected by Aéro-Photo after the train derailment. This aerial photograph was provided and georeferenced by Aéro-Photo (1961) inc. Purpose: This aerial photograph makes it possible to identify the impact radius of the accident. The image web service (WMS) is offered as an open service. However, to obtain the raw image, please contact Aéro-Photo (1961) inc.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

The fire regime describes the patterns of fire seasonality, frequency, size, spatial continuity, intensity, type (e.g., crown or surface fire) and severity in a particular area or ecosystem.The number of large fires refers to the annual number of fires greater than 200 hectares (ha) that occur per units of 100,000 ha. It was calculated per Homogeneous Fire Regime (HFR) zones. These HFR zones represent areas where the fire regime is similar over a broad spatial scale (Boulanger et al. 2014). Such zonation is useful in identifying areas with unusual fire regimes that would have been overlooked if fires had been aggregated according to administrative and/or ecological classifications.Fire data comes from the Canadian National Fire Database covering 1959–1999 (for HFR zones building) and 1959-1995 (for model building). Multivariate Adaptive Regression Splines (MARS) modeling was used to relate monthly fire regime attributes with monthly climatic/fire-weather in each HFR zone. Future climatic data were simulated using the Canadian Earth System Model version 2 (CanESM2) and downscaled at a 10 Km resolution using ANUSPLIN for two different Representative Concentration Pathways (RCP). RCPs are different greenhouse gas concentration trajectories adopted by the Intergovernmental Panel on Climate Change (IPCC) for its fifth Assessment Report. RCP 2.6 (referred to as rapid emissions reductions) assumes that greenhouse gas concentrations peak between 2010-2020, with emissions declining thereafter. In the RCP 8.5 scenario (referred to as continued emissions increases) greenhouse gas concentrations continue to rise throughout the 21st century.Provided layer: projected number of large fires (>200 ha) across Canada for the long-term (2071-2100) under the RCP 8.5 (continued emissions increases).Reference: Boulanger, Y., Gauthier, S., et al. 2014. A refinement of models projecting future Canadian fire regimes using homogeneous fire regime zones. Canadian Journal of Forest Research 44, 365–376.

The fire regime describes the patterns of fire seasonality, frequency, size, spatial continuity, intensity, type (e.g., crown or surface fire) and severity in a particular area or ecosystem.The number of large fires refers to the annual number of fires greater than 200 hectares (ha) that occur per units of 100,000 ha. It was calculated per Homogeneous Fire Regime (HFR) zones. These HFR zones represent areas where the fire regime is similar over a broad spatial scale (Boulanger et al. 2014). Such zonation is useful in identifying areas with unusual fire regimes that would have been overlooked if fires had been aggregated according to administrative and/or ecological classifications.Fire data comes from the Canadian National Fire Database covering 1959–1999 (for HFR zones building) and 1959-1995 (for model building). Multivariate Adaptive Regression Splines (MARS) modeling was used to relate monthly fire regime attributes with monthly climatic/fire-weather in each HFR zone. Future climatic data were simulated using the Canadian Earth System Model version 2 (CanESM2) and downscaled at a 10 Km resolution using ANUSPLIN for two different Representative Concentration Pathways (RCP). RCPs are different greenhouse gas concentration trajectories adopted by the Intergovernmental Panel on Climate Change (IPCC) for its fifth Assessment Report. RCP 2.6 (referred to as rapid emissions reductions) assumes that greenhouse gas concentrations peak between 2010-2020, with emissions declining thereafter. In the RCP 8.5 scenario (referred to as continued emissions increases) greenhouse gas concentrations continue to rise throughout the 21st century.Provided layer: projected number of large fires (>200 ha) across Canada for the long-term (2071-2100) under the RCP 2.6 (rapid emissions reductions).Reference: Boulanger, Y., Gauthier, S., et al. 2014. A refinement of models projecting future Canadian fire regimes using homogeneous fire regime zones. Canadian Journal of Forest Research 44, 365–376.