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Vegetative Community Response to Landscape-Scale Post-fire Herbicide (Imazapic) Application

Published online by Cambridge University Press:  26 October 2018

Cara Applestein
Affiliation:
Ecologist, U.S. Geological Survey, Forest and Rangeland Ecosystems Science Center, Boise, ID, USA
Matthew J. Germino*
Affiliation:
Supervisory Ecologist, U.S. Geological Survey, Forest and Rangeland Ecosystems Science Center, Boise, ID, USA
Matthew R. Fisk
Affiliation:
Ecologist, U.S. Geological Survey, Forest and Rangeland Ecosystems Science Center, Boise, ID, USA
*
Author for correspondence: Matthew J. Germino, U.S. Geological Survey, Forest and Rangeland Ecosystems Science Center, 970 Lusk Street, Boise ID 83706. (Email: mgermino@usgs.gov)
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Abstract

Disturbances such as wildfire create time-sensitive windows of opportunity for invasive plant treatment, and the timing of herbicide application relative to the time course of plant community development following fire can strongly influence herbicide effectiveness. We evaluated the effect of herbicide (imazapic) applied in the first winter or second fall after the 113,000 ha Soda wildfire on the target exotic annual grasses and also key non-target components of the plant community. We measured responses of exotic and native species cover, species diversity, and occurrence frequency of shrubs and forbs seeded before (1 to 2 or 9 to 10 mo) herbicide application. Additionally, we asked whether landscape factors, including topography, species richness, and/or soil characteristics, influenced the effectiveness of imazapic. Cover of exotic annual grass cover, but not of deep-rooted perennial bunchgrass, was less where imazapic had been applied, whereas more variability was evident in the response of Sandberg bluegrass (Poa secunda J. Presl) and seeded shrubs and forbs. Regression-tree analysis of the subset of plots measured both before and after the second fall application revealed greater reductions of exotic annual grass cover in places where their cover was <42% before spraying. Otherwise, imazapic effects did not vary with the landscape factors we analyzed.

Information

Type
Research and Education
Copyright
© Weed Science Society of America, 2018 
Figure 0

Table 1 Previous publications on the effects of imazapic on different functional groups and the current findings of our study.a

Figure 1

Figure 1 Location of herbicide spraying post-fire (sprayed first winter or sprayed second fall). (A) The location of the boundaries of post hoc analysis blocks (measured blocks) and plots within blocks (plots monitored) used to assess the effects of spraying herbicide on plant community and functional group cover between control (no herbicide) areas and areas sprayed either in the first winter or areas sprayed in the second fall post-fire. Regions in which the blocks occur are circled, but the plots monitored points show exact locations of data collection. (B) The location of all plots monitored in the second fall post-fire herbicide treatment that were used for the pre/posttreatment analysis of landscape factors on herbicide variability.

Figure 2

Figure 2 Estimated mean percent cover and 95% confidence intervals of different functional groups measured in 2017 from a mixed beta regression model in control plots and plots sprayed in the first winter or second fall post-fire. Exotic annual grass treatment effects are conditional on a constant heat-load index (not included in other functional group models). Asterisks denote treatments that are significantly different from untreated controls.

Figure 3

Figure 3 Estimated frequency of 2016 species occupancy in January 2016 between unsprayed control plots and plots sprayed in the first winter post-fire from a mixed-effects logistic regression with 95% confidence intervals (left). Estimated frequency of 2017 seeded species occupancy between unsprayed control plots and plots sprayed in the second fall post-fire is displayed on the right. ACMI, Achillea millefolium; ARTEM, Artemisia spp.; MESA, Medicago sativa; SAMI, Sanguisorba minor. Asterisks denote treatments that are significantly different from untreated controls.

Figure 4

Figure 4 Random forest variable importance plot showing the importance of each landscape variable on predicting postherbicide exotic annual grass (EAG) cover in 2017. EAG species’ dominance is a metric calculated by subtracting the 2016 (preherbicide) cover of Taeniatherum caput-medusae from the 2016 cover of Bromus tectorum. Pre-fire EAG cover (NLCD model) is derived from 2011 National Land Cover Database (Homer et al. 2015). Preherbicide EAG cover and preherbicide perennial bunchgrass cover (PBG) are also given from 2016 field monitoring. The x-axis quantifies the percent mean increase in mean squared error (MSE) as a result of a given variable being permuted. The higher the percent increase in MSE as a result of a variable being permuted, the more important that variable is to explaining variability in postherbicide EAG cover.

Supplementary material: File

Applestein et al. supplementary material

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