Appendix D. Simulation results of the three simulation scenarios to estimate trends in average arrival across years.

Simulation results of the three simulation scenarios to estimate trends in average arrival across years

Appendix C. Field methods and analyses of the butterfly surveys of the Aargau Biodiversity Monitoring Program.

Field methods and analyses of the butterfly surveys of the Aargau Biodiversity Monitoring Program

Temporal trends of air temperatures.

<p>Upper panels present temporal changes in mean temperatures for summer half-years (April to September, left panel) and for the coldest month (right panel) for the years 1995–2010 as depending on altitude. Points represent linear changes of temperatures over years, given in °C per year, for 14 meteorological stations distributed over Switzerland. Error bars are 95% confidence intervals, and grey areas represent 95% confidence intervals of the linear mixed model predictions for the average trend of temperature over years (solid line). Lower panels present mean temperatures for summer half-years (April to September, left panel) and for the coldest month (right panel). Solid lines indicate temporal trends as estimated from linear mixed models, and grey areas represent 95% confidence intervals of the model predictions.</p

Distribution of sample sites over Switzerland.

<p>Locations of the 214 analysed 1-km² sample squares from the Swiss national biodiversity monitoring program for which data for all three species groups were available (vascular plants, butterflies and breeding birds).</p

Temporal change of temperature indices of plant, butterfly and bird communities.

<p>Given are model predictions for temporal changes of community average of temperature indices (, upper panels) and of community variation in temperature indices (, lower panels) between two surveys at a sample square <i>i</i> separated by five years within the period 2003–2010, across the altitudinal range covered in the Swiss national biodiversity monitoring program. Black lines are regression lines from minimal adequate linear models, and grey areas represent bootstrapped 95% confidence intervals. Predicted values with confidence intervals that do not include zero are judged as being significantly different from zero.</p

Appendix A. Performance of the single-season phenological model.

Performance of the single-season phenological model

Appendix B. Field methods and analyses of the bird surveys of the Aargau Biodiversity Monitoring Program.

Field methods and analyses of the bird surveys of the Aargau Biodiversity Monitoring Program

Principle component analysis on seven nightingale song parameters, showing unrotated component loadings.

<p>PC1 represents song output parameters, and PC2 represents structural song parameters. Loadings of variables that made an important contribution to the components are indicated in bold. High scores on PC1 indicate high song rates but short durations of pauses and of song interruptions, and low numbers of interruptions; high scores on PC2 are mainly related to long song lengths and high percentage of songs with trills and initial whistles.</p

Mean ± SE percentage of their songs that males used to overlap playback songs, in males that later in the season were paired (n = 7), and in males that remained unpaired throughout the breeding season (bachelors; n = 14).

<p>Mean ± SE percentage of their songs that males used to overlap playback songs, in males that later in the season were paired (n = 7), and in males that remained unpaired throughout the breeding season (bachelors; n = 14).</p

Effect of playback treatment and playback period on mean ± SE song output (a) and on structural song parameters (b) by male nightingales.

<p>One group of nocturnally singing males (n = 14) received a playback from the same height as their own song perch (‘same level’), the other group (n = 13) received a playback from 3 metres higher than their own song perch (‘high’). High scores on PC1 (a) indicate high song rates but short pause durations and low numbers and durations of interruptions (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0032194#pone-0032194-t001" target="_blank">Table 1</a>). High scores on PC2 (b) indicate long song lengths and high percentages of songs with rapid broadband trills and initial whistles.</p