Mixed grasslands in south Canada serve a variety of economic, environmental and ecological purposes. Numerical modeling has become a major method used to identify potential grassland ecosystem responses to environment changes and human activities. In recent years, the focus has been on process models because of their high accuracy and ability to describe the interactions among different environmental components and the ecological processes. At present, two commonly-used process models (CENTURY and BIOME-BGC) have significantly improved our understanding of the possible consequences and responses of terrestrial ecosystems under different environmental conditions. However, problems with these models include only using site-based parameters and adopting different assumptions on interactions between plant, environmental conditions and human activities in simulating such complex phenomenon. In light of this shortfall, the overall objective of this research is to integrate remote sensing products into ecosystem process model in order to simulate productivity for the mixed grassland ecosystem in the landscape level. Data used includes 4-years of field measurements and diverse satellite data (System Pour lObservation de la Terre (SPOT) 4 and 5, Landsat TM and ETM, Advanced Very High Resolution Radiometer (AVHRR) imagery). <p>Using wavelet analyses, the study first detects that the dominant spatial scale is controlled by topography and thus determines that 20-30 m is the optimum resolution to capture the vegetation spatial variation for the study area. Second, the performance of the RDVI (Renormalized Difference Vegetation Index), ATSAVI (Adjusted Transformed Soil-Adjusted Vegetation Index), and MCARI2 (Modified Chlorophyll Absorption Ratio Index 2) are slightly better than the other VIs in the groups of ratio-based, soil-line-related, and chlorophyll-corrected VIs, respectively. By incorporating CAI (Cellulose Absorption Index) as a litter factor in ATSAVI, a new VI is developed (L-ATSAVI) and it improves LAI estimation capability by about 10%. Third, vegetation maps are derived from a SPOT 4 image based on the significant relationship between LAI and ATSAVI to aid spatial modeling. Fourth, object-oriented classifier is determined as the best approach, providing ecosystem models with an accurate land cover map. Fifth, the phenology parameters are identified for the study area using 22-year AVHRR data, providing the input variables for spatial modeling. Finally, the performance of popular ecosystem models in simulating grassland vegetation productivity is evaluated using site-based field data, AVHRR NDVI data, and climate data. A new model frame, which integrates remote sensing data with site-based BIOME-BGC model, is developed for the mixed grassland prairie. The developed remote sensing-based process model is able to simulate ecosystem processes at the landscape level and can simulate productivity distribution with 71% accuracy for 2005.

Decision support systems (DSS) that integrate long-term duck population and land use data are currently being used to develop conservation programs on the Canadian prairies. However, understanding inter-relationships between ducks and other grassland bird species would greatly enhance program planning and delivery among various bird conservation initiatives. Therefore, to achieve these goals, grassland bird species richness and relative abundance were compared between areas of low, moderate and high predicted waterfowl breeding densities (strata) in the southern Missouri Coteau, Saskatchewan. Roadside point counts were conducted during spring 2001 and 2002, and habitats were delineated within 400 m radius of each point. More birds of more species were encountered in the high density waterfowl stratum when compared with low but species that tended to co-occur with ducks were primarily wetland-associated. Overall, duck and other grassland bird species richness and abundance were moderately correlated (0.69 > r > 0.37, all Ps < 0.05); strong positive correlations between priority species of conservation concern and northern pintails were not found. No difference in mean number of priority grassland species occurred among strata, but differences were found for both number of species and total birds detected among routes within strata. High duck density stratum was more heterogeneous, consisting of greater areas of forage, shrub, wetlands, and open water bodies whereas low stratum contained larger, more uniformly-shaped habitat patches and greater proportion of cropland. Ordination analyses revealed that most priority species occurred in grassland-dominated sites with lower shrub area and wetland density whereas most wetland-associated species, including ducks and 2 priority species (Wilsons phalarope and marbled godwit) inhabited cultivated areas with higher wetland density. Ducks and priority species generally did not co-occur at the stop-level in highly heterogeneous landscapes but suitable habitats for both groups may exist in near proximity. In homogeneous landscapes, ducks and other wetland-associated common species were less abundant because of limited number of suitable wetlands. To achieve these dual goals, conservation efforts should be focused in areas containing wetlands adjacent to contiguous tracts of native pasture.

With the increase in atmospheric CO2 concentrations, and the resulting potential for climate change, there has been increasing research devoted to understanding the factors that determine the magnitude of CO2 fluxes and the feedback of ecosystem fluxes on climate. This thesis is an effort to investigate the feasibility of using alternate methods to measure and estimate the CO2 exchange rates in the northern mixed grass prairie. Specifically, the objectives are to evaluate the capability of using ground-level hyperspectral, and satellite-level multispectral data in the estimation of mid-season leaf CO2 exchange rates as measured with a chamber, in and around Grasslands National Park (GNP), Saskatchewan. Data for the first manuscript was collected during June of 2004 (the approximate period for peak greenness for the study area). Spectral reflectance and CO2 exchange measurements were collected from 13 sites in and around GNP. Linear regression showed that the Photochemical Reflectance Index (PRI) calculated from hyperspectral ground-level data explained 46% of the variance seen in the CO2 exchange rates. This indicates that the PRI, which has traditionally been used only in laboratory conditions to predict CO2 exchange, can also be applied at the canopy level in grassland field conditions. <p>The focus of the second manuscript is to establish if the relationship found between ground-level hyperspectral data and leaf CO2 exchange is applicable to satellite-level derived vegetation indices. During June of 2005, biophysical and CO2 exchange measurements were collected from 24 sites in and around GNP. A SPOT satellite image was obtained from June 22, midway through the field data collection. Cubic regression showed that Normalized Difference Vegetation Index (NDVI) explained 46% of the variance observed in the CO2 exchange rates. To our knowledge, this is the first time that a direct correlation between satellite images and leaf CO2 fluxes has been shown within the grassland biome.

Global climate change has been linked to the increase in greenhouse gas (GHG) emissions. Mixedgrass Prairie of hummocky terrain in Saskatchewan is an understudied landscape contributing an unknown quantity of greenhouse gases (GHGs) to global climate change. The objectives of this study were to determine the effects of topography and mowing on carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) flux and to correlate them with environmental and plant community characteristics. The study site was located in the Northern Mixedgrass Prairie of the Missouri Coteau near Macrorie, SK. April mowing and an unmowed control were imposed on six different landform elements. Carbon dioxide, CH4 and N2O were measured every 7-10 days from spring until fall for two years with closed, vented chambers. Soil physical characteristics, weather and plant community characteristics were measured. Landform element and mowing influenced the flux of all three gases in both sampling seasons. Soil CO2 flux ranged from 3.1 to 23.3 kg CO2-C ha-1 d-1 among the unmowed control plots and 3.6 to 26.4 kg CO2-C ha-1 d-1 after mowing. Soils were a net sink for CH4, consuming 1.4 to 4.4 g CH4-C ha-1 d-1 among the unmowed control plots and 1.8 to 4.1 g CH4-C ha-1 d-1 among the mowed plots. Nitrous oxide flux ranged from -0.25 to 1.17 g N2O-N ha-1 d-1 among the unmowed control plots and -0.20 to 1.51 g N2O-N ha-1 d-1 among the mowed plots. Greenhouse gas flux changed from year-to-year and within years. The greatest GHG flux rate occurred in the depression landform element. Mowing increased the positive flux of CO2 and N2O while increasing the negative flux of CH4. Species composition was correlated with soil water, topography, percentage litter cover and GHG flux rate. Overall, the Mixedgrass Prairie of Saskatchewan likely contributes very little to GHGs. Properly managed, the Mixedgrass Prairie has a well-balanced nutrient cycle that includes various GHGs. The grassland ecosystem plays a role in mitigating climate change by retaining carbon that would be released to the atmosphere with poor grazing management or the conversion to arable agriculture. Government agencies and the ranching industries could best mitigate GHG emissions of Mixedgrass Prairie in Saskatchewan by promoting the retention of above-ground plant material, increasing below-ground carbon sequestration and the avoidance of conversion to cropland.

Decision support systems (DSS) that integrate long-term duck population and land use data are currently being used to develop conservation programs on the Canadian prairies. However, understanding inter-relationships between ducks and other grassland bird species would greatly enhance program planning and delivery among various bird conservation initiatives. Therefore, to achieve these goals, grassland bird species richness and relative abundance were compared between areas of low, moderate and high predicted waterfowl breeding densities (strata) in the southern Missouri Coteau, Saskatchewan. Roadside point counts were conducted during spring 2001 and 2002, and habitats were delineated within 400 m radius of each point. More birds of more species were encountered in the high density waterfowl stratum when compared with low but species that tended to co-occur with ducks were primarily wetland-associated. Overall, duck and other grassland bird species richness and abundance were moderately correlated (0.69 > r > 0.37, all Ps < 0.05); strong positive correlations between priority species of conservation concern and northern pintails were not found. No difference in mean number of priority grassland species occurred among strata, but differences were found for both number of species and total birds detected among routes within strata. High duck density stratum was more heterogeneous, consisting of greater areas of forage, shrub, wetlands, and open water bodies whereas low stratum contained larger, more uniformly-shaped habitat patches and greater proportion of cropland. Ordination analyses revealed that most priority species occurred in grassland-dominated sites with lower shrub area and wetland density whereas most wetland-associated species, including ducks and 2 priority species (Wilsons phalarope and marbled godwit) inhabited cultivated areas with higher wetland density. Ducks and priority species generally did not co-occur at the stop-level in highly heterogeneous landscapes but suitable habitats for both groups may exist in near proximity. In homogeneous landscapes, ducks and other wetland-associated common species were less abundant because of limited number of suitable wetlands. To achieve these dual goals, conservation efforts should be focused in areas containing wetlands adjacent to contiguous tracts of native pasture.

Exotic plant invasions represent a significant threat to the integrity of native grasslands. Across the Northern Great Plains, grasslands invaded by smooth brome (Bromus inermis Leyss) support lower plant diversity, potentially resulting in important consequences for ecosystem function. Previous research on smooth brome has primarily focused on aboveground changes in plant communities, but there is growing evidence that the soil ecosystem can be significantly altered with invasion. The two objectives of this thesis were to examine whether smooth brome invasion alters soil nitrogen cycling, and to determine if changes in plant community diversity or productivity influence soil bacterial communities. Relationships between smooth brome and the soil ecosystem were assessed using data collected from a Festuca hallii Vasey (Piper) (plains rough fescue) grassland located near Macrorie, SK. Gross rates of nitrogen cycling and community productivity from smooth brome invaded and native grassland sites were compared to determine the potential influence of smooth brome invasion on the soil nitrogen cycle. The relationship between increasing smooth brome abundance and soil bacterial structure and composition was also studied. Gross mineralization rates and total soil nitrogen were significantly higher in smooth brome-invaded areas relative to native grassland. Bacterial and archaeal amoA, used as indicators of ammonia-oxidizer population sizes, were altered by smooth brome cover. Higher gross mineralization rates were likely due to stimulated microbial activity caused by increased litter and root production in areas invaded by smooth brome. Smooth brome decreased plant species richness through increased litter production, but had the opposite effect on bacterial communities. Bacterial communities had higher species richness and evenness in soils invaded by smooth brome, and smooth brome invasion was also associated with bacteria important for soil nitrogen cycling. As bacteria dominate microbial biomass and are important for decomposition processes, a more even bacterial community may have supported increased mineralization rates in smooth brome-invaded soils. Specifically, a more even bacterial community may have increased mineralization rates through greater resource utilization and niche partitioning. The responses observed in these studies suggest that belowground changes with smooth brome invasion have the potential to have important consequences for ecosystem processes.

Global climate change has been linked to the increase in greenhouse gas (GHG) emissions. Mixedgrass Prairie of hummocky terrain in Saskatchewan is an understudied landscape contributing an unknown quantity of greenhouse gases (GHGs) to global climate change. The objectives of this study were to determine the effects of topography and mowing on carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) flux and to correlate them with environmental and plant community characteristics. The study site was located in the Northern Mixedgrass Prairie of the Missouri Coteau near Macrorie, SK. April mowing and an unmowed control were imposed on six different landform elements. Carbon dioxide, CH4 and N2O were measured every 7-10 days from spring until fall for two years with closed, vented chambers. Soil physical characteristics, weather and plant community characteristics were measured. Landform element and mowing influenced the flux of all three gases in both sampling seasons. Soil CO2 flux ranged from 3.1 to 23.3 kg CO2-C ha-1 d-1 among the unmowed control plots and 3.6 to 26.4 kg CO2-C ha-1 d-1 after mowing. Soils were a net sink for CH4, consuming 1.4 to 4.4 g CH4-C ha-1 d-1 among the unmowed control plots and 1.8 to 4.1 g CH4-C ha-1 d-1 among the mowed plots. Nitrous oxide flux ranged from -0.25 to 1.17 g N2O-N ha-1 d-1 among the unmowed control plots and -0.20 to 1.51 g N2O-N ha-1 d-1 among the mowed plots. Greenhouse gas flux changed from year-to-year and within years. The greatest GHG flux rate occurred in the depression landform element. Mowing increased the positive flux of CO2 and N2O while increasing the negative flux of CH4. Species composition was correlated with soil water, topography, percentage litter cover and GHG flux rate. Overall, the Mixedgrass Prairie of Saskatchewan likely contributes very little to GHGs. Properly managed, the Mixedgrass Prairie has a well-balanced nutrient cycle that includes various GHGs. The grassland ecosystem plays a role in mitigating climate change by retaining carbon that would be released to the atmosphere with poor grazing management or the conversion to arable agriculture. Government agencies and the ranching industries could best mitigate GHG emissions of Mixedgrass Prairie in Saskatchewan by promoting the retention of above-ground plant material, increasing below-ground carbon sequestration and the avoidance of conversion to cropland.

With the increase in atmospheric CO2 concentrations, and the resulting potential for climate change, there has been increasing research devoted to understanding the factors that determine the magnitude of CO2 fluxes and the feedback of ecosystem fluxes on climate. This thesis is an effort to investigate the feasibility of using alternate methods to measure and estimate the CO2 exchange rates in the northern mixed grass prairie. Specifically, the objectives are to evaluate the capability of using ground-level hyperspectral, and satellite-level multispectral data in the estimation of mid-season leaf CO2 exchange rates as measured with a chamber, in and around Grasslands National Park (GNP), Saskatchewan. Data for the first manuscript was collected during June of 2004 (the approximate period for peak greenness for the study area). Spectral reflectance and CO2 exchange measurements were collected from 13 sites in and around GNP. Linear regression showed that the Photochemical Reflectance Index (PRI) calculated from hyperspectral ground-level data explained 46% of the variance seen in the CO2 exchange rates. This indicates that the PRI, which has traditionally been used only in laboratory conditions to predict CO2 exchange, can also be applied at the canopy level in grassland field conditions. <p>The focus of the second manuscript is to establish if the relationship found between ground-level hyperspectral data and leaf CO2 exchange is applicable to satellite-level derived vegetation indices. During June of 2005, biophysical and CO2 exchange measurements were collected from 24 sites in and around GNP. A SPOT satellite image was obtained from June 22, midway through the field data collection. Cubic regression showed that Normalized Difference Vegetation Index (NDVI) explained 46% of the variance observed in the CO2 exchange rates. To our knowledge, this is the first time that a direct correlation between satellite images and leaf CO2 fluxes has been shown within the grassland biome.

Mixed grasslands in south Canada serve a variety of economic, environmental and ecological purposes. Numerical modeling has become a major method used to identify potential grassland ecosystem responses to environment changes and human activities. In recent years, the focus has been on process models because of their high accuracy and ability to describe the interactions among different environmental components and the ecological processes. At present, two commonly-used process models (CENTURY and BIOME-BGC) have significantly improved our understanding of the possible consequences and responses of terrestrial ecosystems under different environmental conditions. However, problems with these models include only using site-based parameters and adopting different assumptions on interactions between plant, environmental conditions and human activities in simulating such complex phenomenon. In light of this shortfall, the overall objective of this research is to integrate remote sensing products into ecosystem process model in order to simulate productivity for the mixed grassland ecosystem in the landscape level. Data used includes 4-years of field measurements and diverse satellite data (System Pour lObservation de la Terre (SPOT) 4 and 5, Landsat TM and ETM, Advanced Very High Resolution Radiometer (AVHRR) imagery). <p>Using wavelet analyses, the study first detects that the dominant spatial scale is controlled by topography and thus determines that 20-30 m is the optimum resolution to capture the vegetation spatial variation for the study area. Second, the performance of the RDVI (Renormalized Difference Vegetation Index), ATSAVI (Adjusted Transformed Soil-Adjusted Vegetation Index), and MCARI2 (Modified Chlorophyll Absorption Ratio Index 2) are slightly better than the other VIs in the groups of ratio-based, soil-line-related, and chlorophyll-corrected VIs, respectively. By incorporating CAI (Cellulose Absorption Index) as a litter factor in ATSAVI, a new VI is developed (L-ATSAVI) and it improves LAI estimation capability by about 10%. Third, vegetation maps are derived from a SPOT 4 image based on the significant relationship between LAI and ATSAVI to aid spatial modeling. Fourth, object-oriented classifier is determined as the best approach, providing ecosystem models with an accurate land cover map. Fifth, the phenology parameters are identified for the study area using 22-year AVHRR data, providing the input variables for spatial modeling. Finally, the performance of popular ecosystem models in simulating grassland vegetation productivity is evaluated using site-based field data, AVHRR NDVI data, and climate data. A new model frame, which integrates remote sensing data with site-based BIOME-BGC model, is developed for the mixed grassland prairie. The developed remote sensing-based process model is able to simulate ecosystem processes at the landscape level and can simulate productivity distribution with 71% accuracy for 2005.

Padre Island National Seashore provides important habitat for wintering grassland birds, which are declining throughout their breeding range, yet oil and gas development is widespread in the park. My objective was to evaluate the effects of resource extraction on the park's grassland birds and make management recommendations based on my findings. In January-March 2007 and 2008, I surveyed 5 active, 4 abandoned, and 4 road sites to investigate the relationship between distance from disturbance (well pads, access roads) and bird abundance. I also compared abundance among the 3 site types. At each site I recorded bird numbers and species in 10-m distance bands along all transects (4 transects/well, 2 transects/road), each extending 300 m from the road or pad. At road sites bird abundance was positively correlated with increased distance from road edge, but I found no linear relationship at active or abandoned well sites. However, mean bird abundance in the first (0-30-m) distance interval of active well transects was less than half that at the second interval, and was the lowest value for all active intervals except the ninth. First-interval abundance at active wells was lower than abundance at any abandoned well interval. Road transects likewise showed low abundance in the initial interval, although unlike at active wells abundance increased steadily with distance from the center of disturbance. This trend of lower overall numbers at the first interval of active well transects was driven largely by 1 species, the meadowlark. A combination of high noise levels near active well pads (up to 80 dB) and lack of tall vegetation (on average 30% lower than the 60-90-m interval) from which to sing may have contributed to low numbers of meadowlarks, which were the only birds to sing regularly during my study period. While most birds appear to be minimally affected by resource extraction at Padre Island, to ensure minimal impacts on sensitive species I recommend: 1) reducing noise at active sites, 2) limiting disturbance to vegetation near pads and roads, 3) maintaining existing perch sites, 4) restoring all vegetation to its pre-extraction condition, 5) limiting road construction.