10.6084/m9.figshare.3562962.v1
Jayne L. Jonas
Jayne L.
Jonas
Deborah A. Buhl
Deborah A.
Buhl
Amy J. Symstad
Amy J.
Symstad
Supplement 4. Complete AICc results for three experiments at Konza Prairie LTER site (Manhattan, KS, USA).
Wiley
2016
fire frequency
temperature
seasonal burning
interannual variability
Shannon diversity
grazing
tallgrass prairie
mixed-grass prairie
shortgrass prairie
time series
precipitation
nitrogen fertilization
Environmental Science
Ecology
2016-08-10 10:20:42
Dataset
https://wiley.figshare.com/articles/dataset/Supplement_4_Complete_AICc_results_for_three_experiments_at_Konza_Prairie_LTER_site_Manhattan_KS_USA_/3562962
<h2>File List</h2><div>
<p><a href="Supplement4.csv">Supplement4.csv</a> (MD5: 9c2a02597ef066d593745194c0a92bb0)
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</div><h2>Description</h2><div>
<p>Model selection results from analysis of the relationship between a priori 1- and 2-variable weather models and total species (A) richness and (B) Shannon diversity in each fire frequency treatment (Experiment = FRI, 1984–2011, <i>N</i> = 28), grazing treatment (Experiment = Graze, 1994–2011, <i>N</i> = 18), and season of burn treatment (Experiment = SB, 1994–2011, <i>N</i> = 18) at Konza Prairie LTER. <i>R</i>² = least square means regression coefficient, K = # of model parameters including intercept and first order autoregressive parameter, LL = log likelihood, AICc = Akaike Information Criterion corrected for small samples size, DAICC = difference in AICc value between given model and model with lowest AICc, wi = Akaike weights (measure of relative importance of a given model compared to all other models in the model set). Treatments are as follows: 1 = annually burned, 4 = burned once every 4 years, 20 = burned once every 20 years, GR = bison grazed, UG = ungrazed, FAL = fall-burned, WIN = winter-burned, SPR = spring-burned, SUM = summer burned. CV = coefficient of variation, sum = summer, spr = spring, win = winter, PPT = precipitation, TEMP = temperature, t_1 = season preceding growing season (spring and summer) when plants were sampled. Ecologically meaningful models (EMMs) were those with DAICC < 2 and <i>R</i>² > 0.30. Model # corresponds to a priori models as described in <a href="appendix-B.php">Appendix B</a>.</p>
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