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ARS Home » Pacific West Area » Reno, Nevada » Great Basin Rangelands Research » Research » Research Project #428220

Research Project: Effects of Post-Fire Grazing on Sagebrush Steppe Ecosystem Recovery

Location: Great Basin Rangelands Research

Project Number: 2060-13610-002-02-S
Project Type: Non-Assistance Cooperative Agreement

Start Date: Jan 15, 2015
End Date: Jul 31, 2018

Our research will investigate perennial grass responses to alternative post-fire grazing management approaches, which addresses the ‘appropriate timeframe of grazing’ and ‘grazing techniques for promoting resiliency’ research needs stated in the SSP call for proposals. We will focus on grass tiller responses and plant reproduction because they are the most important factors dictating perennial grass survival and vigor (Briske and Richards 1995). Our objectives include: 1. Determine how season of defoliation affects perennial grass tiller demography and inflorescence production for plants that have survived a fire. 2. Determine how number of years of post-fire rest from grazing affects perennial grass tiller demography and inflorescence production for plants that have survived a fire. 3. Examine the effects of grazing on new seedlings established in post-fire rehabilitation treatments.

Site selection: In year one, we will visit sites that have burned two to three years prior and where post-fire livestock grazing has not yet resumed. We have identified candidate sites on USFWS, BLM and on private land. We will target two ecological sites: mountain sagebrush (cooler, moister environments) and Wyoming big sagebrush (warmer, drier environments). As feasible, we will control for existing factors, such as slope, soil characteristics, land treatment history, and degree of degradation. Study Design: Surviving Perennial Grasses: We will select three mountain sagebrush and three Wyoming big sagebrush sites with high post-fire survival of perennial grasses to provide a range of resistance and resilience among sites (soil moisture and temperature). Target perennial grasses include Elymus elymoides and the most dominant deep-rooted bunchgrass. At each project site, we will build 0.4 ha exclosures to exclude livestock. At each site, we will identify 40 individuals of Elymus elymoides and 40 individuals of the most dominant deep-rooted bunchgrass that survived the most recent fire. These individuals will be randomly assigned to one of 8 treatments in a complete factorial design: utilization level (two levels: 0% vs. 50%)* timing of defoliation* time since fire. Each treatment combination will be applied at each of the 6 sites, on 2 species, and on 5 individuals. Defoliation treatments will be applied to entire plants, but for each grass individual we will select and mark 3-5 tillers with electrical wires. Fates of these tillers will be followed for two years. Post-defoliation measurements of these individual tillers include per tiller counts of the number of newly initiated tillers in 1) the post-defoliation grazing season, and 2) the following growing season. We also will assess numbers of inflorescences per tiller, basal width, height of each plant. Study Design: Seedling Survival: We will select 1-2 mountain big sagebrush and 1-2 Wyoming big sagebrush post-fire rehabilitation seeding sites where perennial grasses have successfully established. Forty 1-m2 areas will be randomly located across each rehabilitation area to include 2-3 perennial grass seedings each. Within each 1-m2 area, we will use wire hoops to mark 2-3 perennial grass seedlings before livestock grazing returns to the area for the first time since fire. Twenty of the 1-m2 areas will be protected by grazing exclusion cages and the other half will remain exposed to grazing. We will census individual seedlings to determine grazing status (grazed or not) and intensity of defoliation for grazed plants. We will measure tiller number, inflorescence production, and survival of each individual seedling. Statistical Analyses: For each surviving perennial grass species, we will analyze the data using a mixed model ANOVA. Prior to analysis we will transform any data to improve residual distributions and to meet parametric statistical assumptions. For seedlings, we will analyze these data using survival analysis techniques.