Estimating biophysical parameters of native grassland enables management changes that affect ecological processes and economic benefits. Although multiple hyperspectral studies were focused on native grasslands, just a few compare data at different scales and among ecoregions. In this study, we compared data collected at different spectral and spatial scales and among Canadian Prairie ecoregions. Field observations indicate that the Fescue Ecoregion grasslands has specific dominant species, while the Moist-Mixed and Mixed Ecoregions share similar dominant species, which is important in determining parameters such as leaf area index (LAI) and canopy height. Hyperspectral measurements showed a specific signature for the Fescue Ecoregion, due to denser canopies, while the Moist-Mixed and Mixed Ecoregions showed similar spectral characteristics to each other. The correlation between biophysical parameters and spectral indices reveals the importance of LAI, since it was significantly correlated with all spectral indices analyzed. The Normalized Difference Vegetation Index (NDVI), Normalized Difference Moisture Index (NDMI), and the Plant Senescence Reflectance Index (PSRI) showed significant correlations with biophysical parameters. The comparison results indicated the PSRI being overestimated at all sites (satellite data) and NDVI underestimated at all sites. Finally, the satellite-derived LAI showed a significant positive relationship with the field-measured LAI.

Differentiation of grassland/forage types and accurate estimates of their location and extent are important for understanding their ecological processes and for applying appropriate management practices. We are aiming to reveal the different spectral characteristics of six grassland/forage land covers in three ecoregions located in the Canadian Prairies, based on field data and satellite images. Three spectral indices representing productivity (Normalized Difference Vegetation Index (NDVI)), moisture content (Normalized Difference Moisture Index (NDMI)), and plant photosynthetic activity (Plant Senescence Reflectance Index (PSRI)) were used for comparison of means, comparison of coefficient of variation (CV), and analysis of variance (ANOVA). The results indicated that different grassland types show distinguishable spectral characteristics in the Moist-Mixed and Mixed Ecoregions, while it was not possible to differentiate the classes in the Fescue Ecoregion. To further investigate the within-sites and between-sites heterogeneity, we calculated the CV in a 3 × 3 window and placed them in comparative triangles to demonstrate their potential separability. Results indicated that the triangles based on the CV offered greater class separability in the Fescue Ecoregion and in the Mixed Ecoregion.

Understanding nutrient cycling under different land uses can improve agricultural management practices. In southwestern Saskatchewan, long-term land use as annual cropland, native grassland pasture, tame (planted) crested wheatgrass grasslands, or roadsides altered soil physical and chemical properties based on the intensity and frequency of disturbance, with cropland > roadsides > tame grassland > native grassland. The majority of significant differences were detected at the soil surface (0-7.5 cm); few significant differences below 15 cm suggested that the soils were not significantly different prior to changes in land use. Bulk density was increased in cropland soils compared with native grassland, probably from compaction from farm equipment, and in tame pastures due to their past use as croplands. Croplands also had decreased carbon and organic phosphorus (P) and increased Olsen P compared with grasslands, from crop removal and fertilizer inputs. Roadsides, an important but poorly studied land use in Saskatchewan, had increased clay and Olsen P concentrations compared with native grassland. Roadsides were disturbed during road building and remained disturbed because of runoff from adjacent fields and dust from roads. These results on soil chemical and physical properties, combined with soil microbiology information, will help to improve land management and nutrient use efficiency in soils of this region.