pec_carlton_data

Files included: (1) pec_carlton_biomass_allocation_data.csv, (2) pec_carlton_environment_data.csv, (3) pec_carlton_germination_data.csv, (4) pec_carlton_growth_data.csv, (5) pec_carlton_non_natives_data.csv, (6) pec_carlton_scatterplot_abundance_data.cs

Linear mixed effects models with repeated measures describing effects of three grass manipulation treatments on air temperature at the soil surface in °C and soil water potential in MPa over four growing periods (day 70 to day 112).

<p>Linear mixed effects models with repeated measures describing effects of three grass manipulation treatments on air temperature at the soil surface in °C and soil water potential in MPa over four growing periods (day 70 to day 112).</p

Summary of linear mixed effects models for total, linear, and quadratic contrasts describing growth of <i>Cryptantha muricata</i> over four growing periods.

<p><i>Notes</i>: Number of individuals per treatment - Control (<i>n</i> = 17), Litter (<i>n</i> = 15), Bare Ground (<i>n</i> = 12).</p>†<p>Data were log-transformed.</p>‡<p>Data were square root transformed.</p><p>Summary of linear mixed effects models for total, linear, and quadratic contrasts describing growth of <i>Cryptantha muricata</i> over four growing periods.</p

Environmental factors measured on each of three grass removal treatments in the San Dimas Experimental Forest.

<p>Panel (A) represents air temperature at the soil surface and panel (B) represents soil water potential on each of the three grass removal treatments (Control, <i>n</i> = 25, Litter, <i>n</i> = 25, Bare Ground, <i>n</i> = 25). Data are represented by means ±SE.</p

pec_et_al_understory_diversity_environment

pec_et_al_understory_diversity_environmen

Candidate models used for inference on the productivity, richness and evenness of understory plant community responses to <i>Dendroctonus ponderosae</i>-induced tree mortality, light, soil moisture, and nutrients.

<p><i>Notes</i>: The most likely models (<i>w</i>_i>0.90; difference in evidence ratio>2.7) are shown in <b>bold</b>. AIC_C = Akaike’s Information Criterion corrected, ΔAIC_C = difference between AIC_Ci and AIC_{C best model}, <i>w</i>_i = Akaike weight, and evidence ratio = <i>w</i>_{j best model} / <i>w</i>_i.</p><p>Candidate models used for inference on the productivity, richness and evenness of understory plant community responses to <i>Dendroctonus ponderosae</i>-induced tree mortality, light, soil moisture, and nutrients.</p

Ranked relative importance of variables associated with evenness of herbaceous and woody understory showing model estimates of slope and variance.

<p>The most likely explanatory variables are shown in bold (based on model-average estimate being different from zero when the confidence interval excludes zero).</p><p>Ranked relative importance of variables associated with evenness of herbaceous and woody understory showing model estimates of slope and variance.</p

Ranked relative importance of variables associated with the productivity, richness, and evenness of the understory plant community showing model estimates of slope and variance.

<p>The most likely explanatory variables are shown in bold (based on model-average estimate being different from zero when the confidence interval excludes zero).</p><p>Ranked relative importance of variables associated with the productivity, richness, and evenness of the understory plant community showing model estimates of slope and variance.</p