Abstract

Invasion of cheatgrass (Bromus tectorum L.) into sagebrush steppe communities threatens the survival of these at-risk ecosystems. One tool available to combat cheatgrass invasion is dormant season grazing. This study investigates the effectiveness of dormant season cattle grazing to reduce cheatgrass abundance in two high-elevation sagebrush steppe communities in southeastern Idaho, as well as the impact of dormant season grazing on plant species biodiversity. Our experiment utilized a randomized complete block design with four grazing treatments – ungrazed, fall-grazed, spring-grazed, and a combination of spring- and fall-grazed. We used an ANOVA standard least squares procedure to determine differences in biodiversity (H^'), evenness (E1/D), percent cover, and biomass between grazing treatments. We used a random forest regression model to determine the relative importance of precipitation and grazing treatments on vegetation responses and biodiversity over the four-year course of the study. There was no difference in the mean change of annual grass biomass during the first two years of grazing treatments (P = 0.05). However, during the third year of grazing treatments, the mean change in annual grass biomass in the spring- and fall-grazed treatment (− 35 Kg•ha−1 ± 43) was different from the fall-grazed (+ 133 Kg•ha−1 ± 42) and ungrazed (+ 181 Kg•ha−1 ± 43) treatments (P < 0.01), and not separate from the spring-grazed treatment (+ 59 Kg•ha−1 ± 43) (P = 0.36). There was no difference in biodiversity or evenness between grazing treatments in any year during the study (P = 0.66, 0.42, respectively). One species – tarragon (Artemisia dracunculus L.) – benefited from a dormant season grazing treatment compared to the ungrazed treatment (P < 0.01). Precipitation features were more predictive of biodiversity, perennial grass cover, and cheatgrass frequency than grazing treatments. These results suggest that dormant season grazing can be used to reduce cheatgrass abundance without impacting biodiversity.

Degree

MS

College and Department

Life Sciences; Plant and Wildlife Sciences

Rights

https://lib.byu.edu/about/copyright/

Date Submitted

2024-04-12

Document Type

Thesis

Handle

http://hdl.lib.byu.edu/1877/etd13547

Keywords

targeted grazing, machine learning, cheatgrass, livestock, random forest

Language

english

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