Hadjistylli et al. 2016

Microsatellite data set (13 loci) from 839 female whifeflies from 50 worldwide collection

Structure_input

Structure project fil

Bee visitation response variables as a function of surrounding anthropogenic land use.

<p>Bee morphotype visitation data and calculated community metrics were collected in East Contra Costa County, California. To examine in more detail the effect of anthropogenic land use on bee visitation, we created a continuous variable for land use with an index ranging from agricultural to urban land use based on proportional area of each type within a 500-axis moves from left to right, sites go from being more agricultural to more urban.</p

Box plots of bee visitation response variables in natural, agricultural, and urban sites.

<p>Bee morphotype visitation data and calculated community metrics were collected in East Contra Costa County, California.</p

Statistical output for response variables having significant relationships with the gradient of agricultural to urban land use.

<p>To examine in more detail the effect of anthropogenic land use on bee visitation, we created a continuous variable for land use with an index ranging from agriculture to urban land use based on proportional area of each type within a 500 m radius. Generalized linear mixed models were created with this calculated anthropogenic land use metric, bloom category of flowering patch, observation time period, wind, and temperature as fixed effects and site as a random effect. The morning (AM) observation time period was the model baseline for the categorical variable of observation time. Shannon diversity and evenness were fit with Gaussian distributions while all other variables were fit with Poisson distributions.</p

The 15 bee morphotypes observed and their associated genera and species in East Contra Costa County, California.

<p>The 15 bee morphotypes observed and their associated genera and species in East Contra Costa County, California.</p

Statistical output table for response variables having significant relationships with the agricultural land use type.

<p>Bee morphotype visitation data and calculated community metrics were collected in East Contra Costa County, California. Significant relationships with the agricultural land use type were calculated based on generalized linear mixed models with land use type, bloom category of flowering patch, observation time period, wind, and temperature as fixed effects and site as a random effect. The natural land use type and morning (AM) observation time period were the model baselines for the categorical variables of land use type and observation time. Shannon diversity and evenness were fit with Gaussian distributions while all other variables were fit with Poisson distributions.</p

Correlation between the percentage of viable seeds in each yellow starthistle seed head and the average number of site visits by morphotype.

<p>Bee morphotype visitation data, calculated community metrics, and yellow starthistle seed heads were collected in East Contra Costa County, California. Bee morphotypes that averaged at least one visit per 30 minute observation window were included as fixed effects in a linear mixed model fit with a binomial distribution, with site as a random effect and the ratio of viable to total seeds as the response variable. Medium hairy leg bees (effect size±SE = 0.284±0.069, p<0.001) and shield-tipped small dark bees (effect size±SE = −0.155±0.051, p = 0.002) had significant effect sizes in the model. Regression lines were added to illustrate relationships.</p

Statistical output table for response variables having significant relationships with the urban land use type.

<p>Bee morphotype visitation data and calculated community metrics were collected in East Contra Costa County, California. Significant relationships with the urban land use type were calculated based on generalized linear mixed models fit with Poisson distributions with land use type, bloom category of flowering patch, observation time period, wind, and temperature as fixed effects and site as a random effect. The natural land use type and morning (AM) observation time period were the model baselines for the categorical variables of land use type and observation time.</p

Microsatellite_Data

Microsatellite and locality dat