Guo, Xulin2019-11-132020-11-132019-112019-11-13November 2http://hdl.handle.net/10388/12448Understanding carrying capacity of plains bison (B. bison bison) is critical for protecting this wild species and grassland ecosystem in mixed-grass prairie. The overall goal of this study is to examine plains bison carrying capacity in the mixed-grass prairie. There are four specific objectives: 1) investigate annual space use of plains bison and their seasonal core ranges, 2) assess seasonal Resources Selection Functions (RSFs) of plains bison, 3) estimate vegetation biomass and productivity of mixed-grass prairie, and 4) estimate carrying capacity taking into account RSFs. I used Kernel Density Estimator to address the first objective. Generalized Linear Mixed Effects models were used for the second objective. The last two objectives were completed using Sentinel-2 Multispectral Image (MSI). This study highlights the power of remote sensing and Geographic Information Systems (GIS) techniques in estimating key driver of bison carrying capacity (available forage) and adjusting factor (RSFs). Results show that bison family groups in Grasslands National Park frequent specific areas. They mainly use the northeast corner of the West Block and expand the core range when it comes to dormant season. Vegetation type information and other landscape factors (slope, distance to water, roads, fences, and prairie dog town) are influencing seasonal RSFs of bison family groups. Vegetation productivity is 734 kg ha-1 supporting 671 - 959 Bison Unit as the carrying capacity. Our study not only contributes to a better bison management plan for Grasslands National Park, one of seven conservation areas of wild plains bison in Canada, but also assists in understanding the interaction of this wild species with the mixed-grass prairie ecosystem.application/pdfcarrying capacity, plains bison, mixed-grass prairie, Sentinel-2, Resources Selection FunctionApplication of remote sensing and GIS in modelling bison carrying capacity in mixed-grass prairieThesis2019-11-13