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ARS Home » Pacific West Area » Albany, California » Western Regional Research Center » Invasive Species and Pollinator Health » Research » Publications at this Location » Publication #154005
Title: EXPERIMENTAL CONTROL OF ANNUAL BROME AND KNAPWEED ON MILITARY TRAINING LANDS.

Author
item PASCHKE, MARK - COLORADO STATE UNIVERSITY
item REDENTE, EDWARD - COLORADO STATE UNIVERSITY
item WARREN, STEVEN - COLORADO STATE UNIVERSITY
item KLEIN, DONALD - COLORADO STATE UNIVERSITY
item Smith, Lincoln

Submitted to: Society for Range Management Meeting Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 9/2/2003
Publication Date: 1/25/2004
Citation: PASCHKE, M.W., REDENTE, E.F., WARREN, S.D., KLEIN, D.A., SMITH, L. Experimental control of annual brome and knapweed on military training lands.. SOCIETY FOR RANGE MANAGEMENT MEETING ABSTRACTS. 2004.

Interpretive Summary:

Technical Abstract: We are attempting to control non-indigenous invasive plant species by using a combination of four manipulations that accelerate natural secondary succession. These are: 1) reduction of the pest plant population using biological control or burning, 2) reducing soil N availability, 3) reseeding with desirable plant species, and 4) reintroduction of a native late-seral soil microbial community. These treatments were initiated at two military bases. We are monitoring our research plots using remote sensing techniques in order to develop methods for assessing the status of weed populations and monitoring large-scale effectiveness of control methodologies. We will extrapolate our results to larger spatial and temporal scales using an ecosystem dynamics model (EDYS) in order to gain insight into ecological mechanisms of control methods so that we can project the likely effectiveness of single and combined control methodologies. Biological control agents have increased and knapweed populations have decreased. Adding sugar reduced soil nitrogen availability. Aircraft collection of high-spatial resolution multispectral data has indicated that vegetation species differentiation is possible. The EDYS model has been implemented for the test sites using existing information and plot-specific baseline and post-treatment data collected annually.