McDermid, GregorySmith, Brent2013-05-272013-11-122013-05-272013http://hdl.handle.net/11023/735Canadian Forces Base (CFB) Suffield, located in southeastern Alberta, faces pressure from a variety of competing land uses and requires geospatial tools to quantify and manage the effect of human activities (particularly military training-related fire) on ecosystem functions. I used multi-temporal remote-sensing techniques to model plant functional types (PFT; C3 vs. C4 grasses), as an indicator of ecosystem state. The best-performing model (overall accuracy = 74 %, weighted kappa = 0.53) was compared against a spatial fire-history database digitized from the Landsat archive (1972 to 2007). Probit regression results revealed statistically significant relationships between PFT-derived ecosystem states and fire history (P < .001), but succession processes were different between ecological units. In general, this ecosystem is sensitive to repeated fire, with recovery taking decades. This research provides novel contributions to ecological knowledge in northern mixedgrass prairie, and outlines specific management actions required to maintain ecologically sustainable fire frequency.engUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.Range ManagementEcologyRemote Sensingfire ecologyplant functional type classificationnorthern dry mixedgrass prairiemaster thesis10.11575/PRISM/27041