Diss. (sammanfattning). Umeå : Sveriges lantbruksuniv., 2003. / Härtill 6 uppsatser.

Diss. (sammanfattning) Umeå : Umeå universitet, 2005. / Härtill 4 uppsatser.

Lic.-avh. Umeå : Sveriges lantbruksUniversity. / Härtill 2 uppsatser.

Lic.-avh. (sammanfattning) Umeå : Sveriges lantbruksuniv., 2006. / Härtill 2 uppsatser.

Diss. (sammanfattning) Umeå : Sveriges lantbruksuniv., 2006. / Härtill 4 uppsatser.

Lic.-avh. (sammanfattning) Uppsala : Sveriges lantbruksuniv., 2008. / Härtill 2 uppsatser.

Diss. (sammanfattning) Uppsala : Sveriges lantbruksuniversitet,2008. / Härtill 4 uppsatser.

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.

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.

In boreal catchments, stream water chemistry is influenced and controlled by several landscape factors. The influence of spatially distributed variables is in turn dependent on the hydrological scale. Headwater streams have larger variability of water chemistry, and thus together represent a large biodiversity, and therefore need to be monitored in official environmental assessments. One objective of this study was, using Geographical Information Systems (GIS), to analyse co-variation between landscape variables and water chemistry and to determine which of the landscape variables have a major influence on the concentration of dissolved organic carbon (DOC) in headwater streams. Another objective was to find a simple method for predicting sources of DOC, using official map data and publically available GIS applications. Totally 85 headwater catchments (0.1-4 km2) in the county of Värmland, western south Sweden, were used in the study. Water chemistry was analysed for water sampled at low, medium and high flows, and landscape variables were extracted from official map data sources: topographic maps, a digital elevation model (DEM, 50 m grid), and vegetation data. Statistical analyses showed that topography (mean slope and mean topographic wetness index (TWI)) and wetland cover often correlated well with DOC in headwater catchments. Official map data could satisfactorily extract landscape variables (mean slope, mean TWI) that were useful in predicting stream water chemistry (DOC). A high-resolution elevation model, which was generated by interpolation of photogrammetric data, was used to calculate and evaluate two different wetness indices and their ability to predict the occurrence of wetlands in six catchments of different sizes and topography. The SAGA (System for Automated Geoscientific Analyses) wetness index (SWI) gave substantially better results than the TWI. The effects of resolution of DEMs on calculations of the SWI were investigated using 5, 10, 25 and 50 m grids. The results showed that SWI values increased with increasing cell size. The near linear increment of mean values for resolutions 10-50 m suggests a independence of terrain type and catchment size, which supported previous findings that indicated that mean slope and mean wetness index calculated from coarse elevation models may be used for prediction of DOC in headwater streams.