Land cover classification and assessment of carrying capacities and stocking rates of crown lands in Manitoba
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Date
2022-12-14
Authors
Encabo, Jan Bryan
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Abstract
Understanding the carrying capacity and the stocking rates of crown lands is critical for the beef industry in the Prairies that relies heavily on these lands for grazing. The overall goal of this study was to examine the current carrying capacities and stocking rates of the crown lands in Manitoba. The main objectives of this study were to i) classify each crown land parcel in the province by land cover type or vegetation type and ii) estimate the carrying capacities and stocking rates of each parcel and compare these to the current stocking rates allowed by the provincial crown land leases. This study used remote sensing and geographic information system (GIS) technologies for land cover monitoring and estimation of carrying capacities and stocking rates. Based on the assessment of remotely sensed land cover inventories, forest and shrubland were found to be the dominant land cover types in the crown lands compared to native and tame grasslands, which are more desirable for grazing due to higher forage quality and palatability. Then, the carrying capacities were estimated from past field surveys that measured forage productivity in different ecoregions of Manitoba. The carrying capacities were used to calculate the stocking rates based on the delineated land cover types within each crown land parcel. Results show that the current stocking rates of the majority of the crown lands were lower than the estimated stocking rates. This suggests that these parcels were being undergrazed compared to the current grazing intensities permitted by the lease contracts. Overall, the forage resources of the crown lands in Manitoba were being undergrazed by -44.64%. This study can contribute to the existing management of crown lands and it also demonstrated the potential of remote sensing technology to improve and expedite land cover monitoring and stocking rate estimation for crown land managers in the future.
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remote sensing, geographic information system, grasslands, rangelands, carrying capacity, stocking rate, vegetation classification, land cover classification, parcel delineation, forage productivity, grazing, animal unit months, ecoregions, climate variables, generalized additive models