Seeding native species increases resistance to fire-induced annual grass invasion in semiarid woodlands

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Authors:
Alexandra K. Urza, Jeanne C. Chambers, Peter J. Weisberg

Publication Date:
2021

Abstract/Summary:
In the cold deserts of the western United States, the invasion of fire-adapted annual grasses such as cheatgrass (Bromus tectorum) can initiate a grass-fire cycle that results in the progressive loss of native plant communities. Invasion is often facilitated by fire, and given observed increases in the size and frequency of wildfires, there is a pressing need to understand the ecosystem attributes associated with susceptibility to invasion and to identify appropriate management responses. In this talk, we share lessons from a long-term experiment examining plant community responses to fire and post-fire seeding treatments in a shrubland-woodland mosaic. We found that resistance to post-fire cheatgrass invasion varied across the landscape, with the highest levels of invasion occurring at lower elevation (warm/dry) sites and in plots with high pre-fire tree cover. Where resistance to invasion was low, seeding perennial species after burning reduced invasibility. Importantly, seeding a functionally diverse mix of native species was more effective at increasing perennial cover and inhibiting cheatgrass invasion than seeding a mix of non-native perennial grasses commonly used in rehabilitation efforts. Our results are consistent with other experimental research, yet differ from observational studies that have shown limited success from post-fire seeding of native species. We integrate our findings with what is known from the available literature to discuss key factors determining post-fire seeding treatment outcomes: landscape heterogeneity in plant community recovery, year-to-year fluctuations in weather conditions, post-fire grazing, and bet hedging strategies such as functional diversity in seed mixes.

Resource Type:
Conference Presentation, SER2021

Pre-approved for CECs under SER's CERP program

Source:
SER2021