Abstract
AbstractRussian thistle, also known as tumbleweed (Salsola spp.), is a problematic invasive plant found on natural and working landscapes. On a California rangeland, we tested the singular and interactive treatments of grazing, herbicide, and seeding to determine how these approaches might influence Salsola cover across a 5-yr experiment. Total Salsola cover declined by 3% annually during the study. A single spring treatment of chlorsulfuron + 2,4-D followed by glyphosate applied in the fall just before seeding, and then 2,4-D the following spring, significantly reduced Salsola cover compared with the untreated control. Seeded forage species cover increased over time and was significantly higher than seeded native species cover at 5 yr after seeding. However, the seeding treatment had no effect on Salsola cover. Although grazing did not reduce Salsola cover, due to the beneficial effects of grazing on reducing other nonnative species, this study supports the use of an integrated approach of herbicide application, grazing, and seeding to achieve management goals on an arid working landscape.
Publisher
Cambridge University Press (CUP)
Reference52 articles.
1. Hrusa, GF (2012) Salsola. In Jepson eFlora, ed. Jepson Flora Project. http://ucjeps.berkeley.edu/eflora/eflora_display.php?tid=11507. Accessed: February 4, 2021
2. Barton, K (2020) MuMIn: Multi-Model Inference. R Package v. 1.43.17. https://CRAN.R-project.org/package=MuMIn. Accessed: October 29, 2016
3. Invasion, competitive dominance, and resource use by exotic and native California grassland species
4. Anonymous (n.d.) Telar® XP herbicide label. Cary, NC: Bayer Environmental Science. 17 p. https://www.environmentalscience.bayer.us/-/media/prfunitedstates/documents/resource-library/product-labels/telar-xp.ashx. Accessed: October 6, 2021
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Data-Augmented Few-Shot Object Detection for Efficient Identification of Invasive Weed Seedlings;2023 IEEE International Conference on Advances in Data-Driven Analytics And Intelligent Systems (ADACIS);2023-11-23