Time-since-fire data are used to describe wildfire disturbances, the major disturbance type in the Boreal forest, over a landscape. These data can be used to calculate various parameters about wildfire disturbances, such as size, shape and severity. Collecting time-since-fire data is expensive and time consuming; the ability to derive it from existing forest inventory data would result in availability of fire data over larger areas. The objective of this thesis was to explore the use of forest inventory information for the prediction of time-since-fire data in the mixedwood boreal forests of Saskatchewan. Regression models were used to predict time-since-fire from forest inventory variables for each inventory polygon with a stand age. Non-water polygons with no stand age value were assigned values from neighbouring polygons, after splitting long polygons that potentially crossed many historic fire boundaries. This procedure filled gaps that prevented polygons from being grouped together in latter analysis. The predicted time-since-fire ages were used to generate wildfire parameters such as age-class distributions and fire cycle. Three methods were examined to group forest inventory polygons together to predict fire event polygons: simple partitions, hierarchical clustering, and spatially constrained clustering. The predicted fire event polygons were used to generate polygon size distribution wildfire metrics. I found that there was a relationship between time-since-fire and forest inventory variables at this study site, although the relationship was not strong. As expected, the strongest relationship was between the age of trees in a stand as indicated by the inventory and the time-since-fire. This relationship was moderately improved by including tree species composition, harvest modification value, and the ages of the surrounding polygons. Assigning no-age polygons neighbouring values and grouping the forest inventory polygons improved the predicted time-since-fire results when compared spatially to the observed time-since-fire data. However, a satisfactory method of comparing polygon shapes was not found, and the map outputs were highly dependent on the grouping method and parameters used. Overall it was found that forest inventory data did not have sufficient detail and accuracy to be used to derive high quality time-since-fire information.

Time-since-fire data are used to describe wildfire disturbances, the major disturbance type in the Boreal forest, over a landscape. These data can be used to calculate various parameters about wildfire disturbances, such as size, shape and severity. Collecting time-since-fire data is expensive and time consuming; the ability to derive it from existing forest inventory data would result in availability of fire data over larger areas. The objective of this thesis was to explore the use of forest inventory information for the prediction of time-since-fire data in the mixedwood boreal forests of Saskatchewan. Regression models were used to predict time-since-fire from forest inventory variables for each inventory polygon with a stand age. Non-water polygons with no stand age value were assigned values from neighbouring polygons, after splitting long polygons that potentially crossed many historic fire boundaries. This procedure filled gaps that prevented polygons from being grouped together in latter analysis. The predicted time-since-fire ages were used to generate wildfire parameters such as age-class distributions and fire cycle. Three methods were examined to group forest inventory polygons together to predict fire event polygons: simple partitions, hierarchical clustering, and spatially constrained clustering. The predicted fire event polygons were used to generate polygon size distribution wildfire metrics. I found that there was a relationship between time-since-fire and forest inventory variables at this study site, although the relationship was not strong. As expected, the strongest relationship was between the age of trees in a stand as indicated by the inventory and the time-since-fire. This relationship was moderately improved by including tree species composition, harvest modification value, and the ages of the surrounding polygons. Assigning no-age polygons neighbouring values and grouping the forest inventory polygons improved the predicted time-since-fire results when compared spatially to the observed time-since-fire data. However, a satisfactory method of comparing polygon shapes was not found, and the map outputs were highly dependent on the grouping method and parameters used. Overall it was found that forest inventory data did not have sufficient detail and accuracy to be used to derive high quality time-since-fire information.

Time-since-fire data are used to describe wildfire disturbances, the major disturbance type in the Boreal forest, over a landscape. These data can be used to calculate various parameters about wildfire disturbances, such as size, shape and severity. Collecting time-since-fire data is expensive and time consuming; the ability to derive it from existing forest inventory data would result in availability of fire data over larger areas. The objective of this thesis was to explore the use of forest inventory information for the prediction of time-since-fire data in the mixedwood boreal forests of Saskatchewan. Regression models were used to predict time-since-fire from forest inventory variables for each inventory polygon with a stand age. Non-water polygons with no stand age value were assigned values from neighbouring polygons, after splitting long polygons that potentially crossed many historic fire boundaries. This procedure filled gaps that prevented polygons from being grouped together in latter analysis. The predicted time-since-fire ages were used to generate wildfire parameters such as age-class distributions and fire cycle. Three methods were examined to group forest inventory polygons together to predict fire event polygons: simple partitions, hierarchical clustering, and spatially constrained clustering. The predicted fire event polygons were used to generate polygon size distribution wildfire metrics. I found that there was a relationship between time-since-fire and forest inventory variables at this study site, although the relationship was not strong. As expected, the strongest relationship was between the age of trees in a stand as indicated by the inventory and the time-since-fire. This relationship was moderately improved by including tree species composition, harvest modification value, and the ages of the surrounding polygons. Assigning no-age polygons neighbouring values and grouping the forest inventory polygons improved the predicted time-since-fire results when compared spatially to the observed time-since-fire data. However, a satisfactory method of comparing polygon shapes was not found, and the map outputs were highly dependent on the grouping method and parameters used. Overall it was found that forest inventory data did not have sufficient detail and accuracy to be used to derive high quality time-since-fire information. / Forestry, Faculty of / Graduate

Fire is the primary natural disturbance vital to the ecological integrity of Quetico Provincial Park, Ontario, Canada. A new provincial park planning process (i.e., Class Environmental Assessment) has required the review of Quetico’s Fire Management Plan. To support this review, large and severe (stand-replacing) Quetico fires were studied using 1966 Ontario Ministry of Natural Resources (OMNR) forest resource inventory (FRI) mapping. A Geographic Information Systems (GIS) database of the FRI was created and updated with the OMNR digital fire atlas. This database was used as a time-since-fire and fire interval dataset to estimate fire frequency. It also served to archive the 1966 FRI for the largest protected area in the transition between the Boreal and Great Lakes-St. Lawrence forest regions. Non-parametric (Kaplan-Meier) survival analysis was used to estimate survival functions and mean fire intervals (i.e., the expected time between two consecutive stand-replacing fires for any location within the Park). Previous studies that have used Kaplan-Meier survival analysis methods have based fire frequency estimates solely on time-since-fire data. However, time-since-fire data cannot be equated with fire interval data when using non-parametric methods. At least one fire interval is required to obtain reliable results. The mean fire interval for the entire 475,782 ha Park between the years 1668 and 2007 was 230 years. Performing the analysis on various geographic and temporal partitions revealed fire frequency spatial and temporal variability. A constant (independent of time-since-fire) probability of burning was not observed for Quetico which is contrary to accepted conjecture for northwestern Ontario boreal/mixed-wood forests. A current fire cycle was also estimated for the Park (342 years) using the digital fire atlas. The results suggested that use of historical static fire frequency estimates as fire management prescriptions may not be justified given considerable fire frequency temporal variability. The observed fire frequency spatial variability suggests that studies should be undertaken at coarser scales than is the norm to characterise the regions fire regime in support of landscape level fire management planning.

Fire is the primary natural disturbance vital to the ecological integrity of Quetico Provincial Park, Ontario, Canada. A new provincial park planning process (i.e., Class Environmental Assessment) has required the review of Quetico’s Fire Management Plan. To support this review, large and severe (stand-replacing) Quetico fires were studied using 1966 Ontario Ministry of Natural Resources (OMNR) forest resource inventory (FRI) mapping. A Geographic Information Systems (GIS) database of the FRI was created and updated with the OMNR digital fire atlas. This database was used as a time-since-fire and fire interval dataset to estimate fire frequency. It also served to archive the 1966 FRI for the largest protected area in the transition between the Boreal and Great Lakes-St. Lawrence forest regions. Non-parametric (Kaplan-Meier) survival analysis was used to estimate survival functions and mean fire intervals (i.e., the expected time between two consecutive stand-replacing fires for any location within the Park). Previous studies that have used Kaplan-Meier survival analysis methods have based fire frequency estimates solely on time-since-fire data. However, time-since-fire data cannot be equated with fire interval data when using non-parametric methods. At least one fire interval is required to obtain reliable results. The mean fire interval for the entire 475,782 ha Park between the years 1668 and 2007 was 230 years. Performing the analysis on various geographic and temporal partitions revealed fire frequency spatial and temporal variability. A constant (independent of time-since-fire) probability of burning was not observed for Quetico which is contrary to accepted conjecture for northwestern Ontario boreal/mixed-wood forests. A current fire cycle was also estimated for the Park (342 years) using the digital fire atlas. The results suggested that use of historical static fire frequency estimates as fire management prescriptions may not be justified given considerable fire frequency temporal variability. The observed fire frequency spatial variability suggests that studies should be undertaken at coarser scales than is the norm to characterise the regions fire regime in support of landscape level fire management planning.