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    Predicting plant community response to picloram

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    Author
    Kedzie-Webb, S. A.
    Sheley, R. L.
    Borkowski, J. J.
    Issue Date
    2002-11-01
    Keywords
    Festuca idahoensis
    endemic species
    ground cover
    mathematical models
    regression analysis
    species diversity
    weed control
    equations
    forbs
    plant communities
    plant density
    picloram
    Centaurea maculosa
    biomass
    range management
    introduced species
    Montana
    invasive species
    grasses
    spotted knapweed
    predicting plant response
    integrated weed management
    optimizing herbicide use
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    Citation
    Kedzie-Webb, S. A., Sheley, R. L., & Borkowski, J. J. (2002). Predicting plant community response to picloram. Journal of Range Management, 55(6), 576-583.
    Publisher
    Society for Range Management
    Journal
    Journal of Range Management
    URI
    http://hdl.handle.net/10150/643702
    DOI
    10.2307/4004001
    10.2458/azu_jrm_v55i6_kedzie-webb
    Additional Links
    https://rangelands.org/
    Abstract
    Effective rangeland weed programs require the ability to predict plant community responses to management. Our objective was to develop regression equations to predict the plant community after control with picloram using the pre-treatment plant community. Five transects were established from dense spotted knapweed (Centaurea maculosa Lam.) in the center of each patch to an area of low or no spotted knapweed occurrence on the outside of the patch. Transects ended in areas dominated by Idaho fescue (Festuca idahoensis Elmer). Twenty permanent plots (20 x 50 cm, spacing along the transect ranged from 1/2 to 2 m) were placed along this gradient. Pre-treatment density and cover of all species were sampled in each plot. Biomass of all species was harvested in plots adjacent to the transect. Picloram (4-amino-3,5,6-trichloropicolinic acid) was applied along each transect at a rate of 0.28 kg a.iha-1 in October 1996 to each plot. Density, cover, and biomass of all species were re-sampled in August 1998. Regression models were fit using perennial grasses, Idaho fescue, forbs, species richness, and species diversity after treatment as predicted variables. All predicted variables were indigenous species. Regressor variables used were site, transect, and spotted knapweed, a spotted knapweed quadratic component, indigenous perennial grasses, Idaho fescue, indigenous forbs, species richness, and species diversity sampled in the first year (1996) prior to treatment. The best predictive models for assessing post-management indigenous perennial grass, Idaho fescue, and species richness were based on density. The best models predicting post-management forbs and species diversity were based on cover and biomass, respectively. In 4 out of the 5 models, for a given post-management parameter, an important predictor in the model was its pre-management regressor variable. Additionally, pre-management spotted knapweed was a relatively unimportant preditar in most models. The model predicting species diversity based on density (pre-treatment) predicted an increase in species diveristy 2 years after management. This study indicated that it may be feasible to use pre-management spotted knapweed was a relatively unimportant predictor in most models. The model predicting species diversity based on density (pre-treatment) predicted an increase in species diversity 2 years after management. This study indicated that it may be feasible to use pre-management plant community data to predict post-management plant community response for spotted knapweed-infested rangeland using picloram.
    Type
    text
    Article
    Language
    en
    ISSN
    0022-409X
    ae974a485f413a2113503eed53cd6c53
    10.2307/4004001
    Scopus Count
    Collections
    Journal of Range Management, Volume 55, Number 6 (November 2002)

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