Remonti_2015_OIK_Pine marten data

Data about the selected studies on pine martens diet, the percent estimated volume of the main food types in pine marten diets, and the macronutrient balance in pine marten diets

Map of the study area (i.e. the Po-Venetian alluvial plain, < 300 m above sea level) corresponding to the potential expansion range of the pine marten in northern Italy.

<p>Pine marten locations are denoted by black triangles (N = 103). Black lines indicate regional borders. The distribution range of the pine marten in Italy is shown in the upper-right corner. Base Map used: World Terrain Base; data sources: Esri, USGS, NOAA; Reprinted from PLOS ONE under a CC BY license, with permission from ESRI, original copyright June 2009.</p

Variable importance (%) ranking by the nine distribution methods (see the methods section for abbreviations) with respect to the ensemble prediction (EP).

<p>Variable importance (%) ranking by the nine distribution methods (see the <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0158203#sec002" target="_blank">methods</a> section for abbreviations) with respect to the ensemble prediction (EP).</p

Variables used in the development of species distribution models for the pine marten in the whole study area and in the used cells; average ± standard deviations values and variance inflation factor (VIF) values are shown [H’ = − Σ(p_i × lnp_i)].

<p>Variables used in the development of species distribution models for the pine marten in the whole study area and in the used cells; average ± standard deviations values and variance inflation factor (VIF) values are shown [H’ = − Σ(p_i × lnp_i)].</p

Response curves and 95% confidence intervals (in grey) of the probability of pine marten occurrence derived by the ensemble prediction of the nine species distribution models in relation to predictor variables values.

<p>Response curves and 95% confidence intervals (in grey) of the probability of pine marten occurrence derived by the ensemble prediction of the nine species distribution models in relation to predictor variables values.</p

Model evaluation of the nine species distribution methods (see the methods section for abbreviations) and their ensemble prediction (EP).

<p>Model evaluation of the nine species distribution methods (see the <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0158203#sec002" target="_blank">methods</a> section for abbreviations) and their ensemble prediction (EP).</p

Spontaneous excitatory postsynaptic current (sEPSC) modulation after chronic exposure to cues.

A) Example traces for each chronic treatment. B) Frequency distribution of sEPSCs binned at intervals of 2 pA in control and treated MCs; a multi-peak fitting was applied to od-2. C) Mean sEPSC amplitude (left) and frequency (right) of MCs from control and treated tadpoles. D) Representative sEPSCs (averaged by 10 single sEPSCs) of MCs from different chronic treatments. E) Effects of chronic treatments on membrane time constant (τEPSC). Significant differences (p < 0.05) among treatments are indicated by * and by non-overlapping effects estimates with the vertical dashed lines.</p

Sample size (number of tadpoles tested) for each combination of chronic and acute treatments.

Sample size (number of tadpoles tested) for each combination of chronic and acute treatments.</p

Means and 95% confidence intervals for MC passive proprieties (Cm = membrane capacitance, Rm = membrane resistance, τ_m = membrane time constant).

Estimates have been obtained by non-parametric bootstrap resampling (n = 5000). Significant difference is reported in bold. (DOCX)</p

Estimated means, standard errors (SE), 95% confidence intervals (CI), and number of MCs tested for cell firing frequency.

Values were obtained from GLMMs with log link function and Gaussian error distribution using emmeans function (R package “emmeans”). (DOCX)</p