Ontario boreal fire regimes in the context of lightning-caused ignition point spatial patterns

Lightning-caused forest fires are one of the major natural disturbances in Ontario managed boreal forests. Survival of these forests with fires for centuries shows that such disturbances are integral to the boreal ecosystem and its ecological functioning. Characterizing the fire regimes defined by f...

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Main Author: Ashiq, Muhammad Waseem
Language:en
Published: 2011
Subjects:
Online Access:http://hdl.handle.net/10012/6257
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spelling ndltd-WATERLOO-oai-uwspace.uwaterloo.ca-10012-62572013-03-19T04:21:07ZAshiq, Muhammad Waseem2011-09-20T18:36:42Z2011-09-20T18:36:42Z2011-09-20T18:36:42Z2011http://hdl.handle.net/10012/6257Lightning-caused forest fires are one of the major natural disturbances in Ontario managed boreal forests. Survival of these forests with fires for centuries shows that such disturbances are integral to the boreal ecosystem and its ecological functioning. Characterizing the fire regimes defined by fire ignition frequency, fire sizes and their spatial distribution patterns etc. thus can help to improve our understanding of the boreal forest dynamics and provide guidance for management practices attempting to maintain biodiversity and achieve sustainability. In this thesis the lightning-caused fire ignitions data for four ecoregions in Ontario managed boreal forests (3E, 3W, 3S and 4S) for 1960–2009 were analyzed using pattern analysis and density estimation to determine the spatial nature of fire ignitions. These fire ignition spatial patterns were further used (as weighted ignition scenario) to simulate forest fire regimes in the study area. Fire regimes were also simulated using spatially unweighted ignitions (unweighted ignition scenario). Non-spatial (total number of fires, total burn area, number of fires by size classes, annual burn fraction) and spatial (spatial burn probability) indicators of the simulated fire regimes under both ignition scenarios were compared to test the null hypothesis that modeled forest fire regime is not affected by the spatial patterns of input fire ignitions. All data analysis were performed for individual ecoregions. Spatial pattern of ignitions were analyzed using the nearest neighbour index and Ripley’s K-function. Ignition densities were estimated using the adaptive kernel density estimation method and the fire regimes were simulated using BFOLDS (Boreal Forests Landscape Dynamics Simulator). Results showed that lightning-caused fire ignitions are clustered in all ecoregions. Fire ignition density also varied spatially within ecoregions. Overall fire ignition density was highest in the northwestern ecoregion (4S) and lowest in the eastern ecoregion (3E), which corresponds to the combined gradient of effective humidity and temperature in Ontario. For each ecoregion, comparison of non-spatial simulated fire regime indicators showed statistically non-significant differences between unweighted and weighted ignitions. The spatial burn probability however captured clear spatial differences between unweighted and weighted ignitions. Spatial differences in spatial burn probability between both ignition scenarios were more prominent in ecoregions of high fire occurrence. Results of the weighted ignition scenario closely followed the spatial patterns of the estimated fire ignition density in the study area. Based on these results this thesis rejects the null hypothesis and emphasizes that ignition patterns must be considered in simulating fire regime in Ontario boreal forests.enOntario boreal forestsFire regimes simulationsPoint pattern analysisDensity estimationBFOLDSSpatial burn probabilityOntario EcoregionsLightning-caused firesOntario boreal fire regimes in the context of lightning-caused ignition point spatial patternsThesis or DissertationGeographyMaster of ScienceGeography
collection NDLTD
language en
sources NDLTD
topic Ontario boreal forests
Fire regimes simulations
Point pattern analysis
Density estimation
BFOLDS
Spatial burn probability
Ontario Ecoregions
Lightning-caused fires
Geography
spellingShingle Ontario boreal forests
Fire regimes simulations
Point pattern analysis
Density estimation
BFOLDS
Spatial burn probability
Ontario Ecoregions
Lightning-caused fires
Geography
Ashiq, Muhammad Waseem
Ontario boreal fire regimes in the context of lightning-caused ignition point spatial patterns
description Lightning-caused forest fires are one of the major natural disturbances in Ontario managed boreal forests. Survival of these forests with fires for centuries shows that such disturbances are integral to the boreal ecosystem and its ecological functioning. Characterizing the fire regimes defined by fire ignition frequency, fire sizes and their spatial distribution patterns etc. thus can help to improve our understanding of the boreal forest dynamics and provide guidance for management practices attempting to maintain biodiversity and achieve sustainability. In this thesis the lightning-caused fire ignitions data for four ecoregions in Ontario managed boreal forests (3E, 3W, 3S and 4S) for 1960–2009 were analyzed using pattern analysis and density estimation to determine the spatial nature of fire ignitions. These fire ignition spatial patterns were further used (as weighted ignition scenario) to simulate forest fire regimes in the study area. Fire regimes were also simulated using spatially unweighted ignitions (unweighted ignition scenario). Non-spatial (total number of fires, total burn area, number of fires by size classes, annual burn fraction) and spatial (spatial burn probability) indicators of the simulated fire regimes under both ignition scenarios were compared to test the null hypothesis that modeled forest fire regime is not affected by the spatial patterns of input fire ignitions. All data analysis were performed for individual ecoregions. Spatial pattern of ignitions were analyzed using the nearest neighbour index and Ripley’s K-function. Ignition densities were estimated using the adaptive kernel density estimation method and the fire regimes were simulated using BFOLDS (Boreal Forests Landscape Dynamics Simulator). Results showed that lightning-caused fire ignitions are clustered in all ecoregions. Fire ignition density also varied spatially within ecoregions. Overall fire ignition density was highest in the northwestern ecoregion (4S) and lowest in the eastern ecoregion (3E), which corresponds to the combined gradient of effective humidity and temperature in Ontario. For each ecoregion, comparison of non-spatial simulated fire regime indicators showed statistically non-significant differences between unweighted and weighted ignitions. The spatial burn probability however captured clear spatial differences between unweighted and weighted ignitions. Spatial differences in spatial burn probability between both ignition scenarios were more prominent in ecoregions of high fire occurrence. Results of the weighted ignition scenario closely followed the spatial patterns of the estimated fire ignition density in the study area. Based on these results this thesis rejects the null hypothesis and emphasizes that ignition patterns must be considered in simulating fire regime in Ontario boreal forests.
author Ashiq, Muhammad Waseem
author_facet Ashiq, Muhammad Waseem
author_sort Ashiq, Muhammad Waseem
title Ontario boreal fire regimes in the context of lightning-caused ignition point spatial patterns
title_short Ontario boreal fire regimes in the context of lightning-caused ignition point spatial patterns
title_full Ontario boreal fire regimes in the context of lightning-caused ignition point spatial patterns
title_fullStr Ontario boreal fire regimes in the context of lightning-caused ignition point spatial patterns
title_full_unstemmed Ontario boreal fire regimes in the context of lightning-caused ignition point spatial patterns
title_sort ontario boreal fire regimes in the context of lightning-caused ignition point spatial patterns
publishDate 2011
url http://hdl.handle.net/10012/6257
work_keys_str_mv AT ashiqmuhammadwaseem ontarioborealfireregimesinthecontextoflightningcausedignitionpointspatialpatterns
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