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ARS Home » Plains Area » El Reno, Oklahoma » Grazinglands Research Laboratory » Forage and Livestock Production Research » Research » Publications at this Location » Publication #367462

Research Project: Integrated Agroecosystem Research to Enhance Forage and Food Production in the Southern Great Plains

Location: Forage and Livestock Production Research

Title: Comparing the impacts of continuous and rotational grazing on tallgrass prairie landscape using the National Agricultural Imagery Program imagery

Author
item MA, SHENGFANG - Oklahoma State University
item ZHOU, YUTING - Oklahoma State University
item Gowda, Prasanna
item Starks, Patrick - Pat
item STEINER, JEAN - Retired ARS Employee
item Neel, James - Jim

Submitted to: American Geophysical Union
Publication Type: Abstract Only
Publication Acceptance Date: 10/2/2019
Publication Date: 12/11/2019
Citation: Ma, S., Zhou, Y., Gowda, P.H., Starks, P.J., Steiner, J.L., Neel, J.P. 2019. Comparing the impacts of continuous and rotational grazing on tallgrass prairie landscape using the National Agricultural Imagery Program imagery [abstract]. American Geophysical Union. Available at: https://agu.confex.com/agu/fm19/meetingapp.cgi/Paper/518124.

Interpretive Summary: Abstract only

Technical Abstract: Cattle grazing is an important disturbance on tallgrass prairie landscape in the Great Plains of the United States. However, evaluating the impacts of different grazing management practices (e.g., continuous stocking and rotational stocking, CS and RS) on landscape is challenging due to the mismatch between pasture size and spatial resolutions of commonly available satellite datasets. Using the National Agriculture Imagery Program (NAIP), which acquires high spatial resolution aerial imagery (1-m at RGB and NIR bands) during the agricultural growing season of selected years in the continental U.S, we studied the impacts of CS and RS on tallgrass prairie landscape within two replicates (A and B) of each grazing system in 2010, 2013, 2015, and 2017. Land cover maps were generated by combining visual interpretation, support vector machine, and decision tree classifiers. Landscape metrics (e.g. class area, patch number, and fragmentation index) were calculated using FRAGSTATS. Both the metrics and land cover results were used to analyze landscape dynamics in the experimental pastures. Results showed that grass and shrub in different pastures differed largely in the same year and had significant annual dynamics controlled by climate. High stocking intensity in the RS replicates typically delayed grass growth relative to the CS replicates. A large proportion of bare soil occurred in sub-paddocks of some RS paddocks. Continuous stocking replicate A experienced rapid shrub encroachment with large proportion of shrub at the beginning of the experiment. Linear regression revealed that shrub may occupy 41% of CS and 15% of RS replicate a by 2030. In contrast, shrub encroachment was not significant in RS replicate B, which only had a small number of shrub patches at the beginning of the experiment. The results indicate that shrub encroachment is mainly controlled by the initial status of shrubs in the pastures and that stocking method had little effect shrub encroachment.