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Selection of a Barley Yield Model Using Information–Theoretic Criteria
- Marie Jasieniuk, Mark L. Taper, Nicole C. Wagner, Robert N. Stougaard, Monica Brelsford, Bruce D. Maxwell
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- Journal:
- Weed Science / Volume 56 / Issue 4 / August 2008
- Published online by Cambridge University Press:
- 20 January 2017, pp. 628-636
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Empirical models of crop–weed competition are integral components of bioeconomic models, which depend on predictions of the impact of weeds on crop yields to make cost-effective weed management recommendations. Selection of the best empirical model for a specific crop–weed system is not straightforward, however. We used information–theoretic criteria to identify the model that best describes barley yield based on data from barley–wild oat competition experiments conducted at three locations in Montana over 2 yr. Each experiment consisted of a complete addition series arranged as a randomized complete block design with three replications. Barley was planted at 0, 0.5, 1, and 2 times the locally recommended seeding rate. Wild oat was planted at target infestation densities of 0, 10, 40, 160, and 400 plants m−2. Twenty-five candidate yield models were used to describe the data from each location and year using maximum likelihood estimation. Based on Akaike's Information Criterion (AIC), a second-order small-sample version of AIC (AICc), and the Bayesian Information Criterion (BIC), most data sets supported yield models with crop density (Dc), weed density (Dw), and the relative time of emergence of the two species (T) as variables, indicating that all variables affected barley yield in most locations. AIC, AICc, and BIC selected identical best models for all but one data set. In contrast, the Information Complexity criterion, ICOMP, generally selected simpler best models with fewer parameters. For data pooled over years and locations, AIC, AICc, and BIC strongly supported a single best model with variables Dc, Dw, T, and a functional form specifying both intraspecific and interspecific competition. ICOMP selected a simpler model with Dc and Dw only, and a functional form specifying interspecific, but no intraspecific, competition. The information–theoretic approach offers a rigorous, objective method for choosing crop yield and yield loss equations for bioeconomic models.
Quantifying Invasiveness of Plants: A Test Case with Yellow Toadflax (Linaria vulgaris)
- Erik A. Lehnhoff, Lisa J. Rew, Bruce D. Maxwell, Mark L. Taper
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- Journal:
- Invasive Plant Science and Management / Volume 1 / Issue 3 / July 2008
- Published online by Cambridge University Press:
- 20 January 2017, pp. 319-325
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Land managers commonly assume that nonindigenous plant species (NIS) are rapidly increasing in population size in all environments in which they occur. In fact, these plant species have differing levels of invasiveness depending on environment. A method was developed that quantifies invasiveness of a plant population based on annual changes in plant density and area occupied, within a series of permanently placed 1 m2 (10.76 ft2) monitoring plots. An invasiveness index (I) was calculated from the change in proportion of cells occupied and the proportions of cells that had growth rates > 1 and < 1; the possible value is restricted from −4 to +4. The method was tested on populations of yellow toadflax over 6 yr on a total of six populations within three distinct environments (Ridge, Valley, and Forest). Invasiveness values were different between environments. The Ridge populations had the highest mean level of invasiveness (I = 0.31), followed by the Valley (I = 0.26), and then the Forest (I = −0.90). Invasiveness also varied by year. The highest annual value of invasiveness was at the Ridge (I = 1.77) and the lowest was at the Forest (I = −1.90), both in 2005. Values of invasiveness were correlated (Pearson's correlation coefficient = 0.82) with the traditional calculations of population growth rate, but our method provides an enhanced measure of invasiveness because it includes information on both change in population area and density. This research shows that populations of yellow toadflax are not equally invasive in different environments or through time, although consistent patterns can be observed. The method presented and tested was implemented in approximately three person-days per year at less than $500 per year, and can be used to quantify the invasiveness of plant populations and thus allow land managers to prioritize the most invasive populations for management.