An example of a “bird book” created by schoolchildren.

<p>An example of a “bird book” created by schoolchildren.</p

A Webcast of Bird Nesting as a State-of-the-Art Citizen Science

<div><p>The quality of people’s knowledge of nature has always had a significant influence on their approach to wildlife and nature conservation. However, direct interactions of people with nature are greatly limited nowadays, especially because of urbanization and modern lifestyles. As a result, our isolation from the natural world has been growing. Here, we present an example of a state-of-the-art Citizen Science project with its educational, scientific, and popularizing benefits. We conclude that modern media and new forms of education offer an effective opportunity for inspiring children and others to have fun learning to act like scientists. This approach provides broad opportunities for developing the hitherto neglected educational potential of Citizen Science.</p></div

An example of a state-of-the-art Citizen Science project, with direct benefits for the public and for researchers.

<p>An example of a state-of-the-art Citizen Science project, with direct benefits for the public and for researchers.</p

A Webcast of Bird Nesting as a State-of-the-Art Citizen Science - Fig 3

<p>An example of data collected from the nest of a great tit (<i>P</i>. <i>major</i>) during the nesting period (i.e., from April 19 to May 23) documenting (A) the structure of the diet delivered by tit parents to nestlings (the proportions and the number of items are shown); (B) the total number of arrivals (green area), feeding deliveries (grey area), and the removal of droppings (violet area) by bird parents, including the mean daily temperature outside the nest box (black line) and inside the nest box (red line); (C) the mean daily number of arrivals, feeding deliveries, and removals of droppings by bird parents in a 6-minute period between 5 am and 7 am, including the mean daily temperature outside and inside the nest box (box: mean; whiskers: SE). For detailed information, see <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2001132#pbio.2001132.s003" target="_blank">S2 Text</a> and <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2001132#pbio.2001132.s007" target="_blank">S4 Data</a>.</p

Best models describing species richness and abundance of woodpeckers in woodland patches.

<p>For each model the number of parameters (k), variance explained by the model (r²), the Akaike information criterion score (AICc), the difference between the given model and the most parsimonious model (Δ AICc) and Akaike weight (<i>w</i>) are listed. CanOpenQ – quadratic term of canopy openness. For explanations of other variable codes: see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0094218#pone-0094218-t001" target="_blank">Table 1</a>.</p

RDA ordination of six environmental variables in relation to woodpecker species in 42 habitat patches.

<p>Species are identified by abbreviated scientific names. Labels for species occurring in less than five patches have been omitted. Explanation of variable codes see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0094218#pone-0094218-t001" target="_blank">Tables 1</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0094218#pone-0094218-t002" target="_blank">2</a>.</p

Results of forward selection of environmental variables explaining patterns in woodpecker community structure in forest patches.

<p>The analysis was performed using Monte Carlo tests with 499 permutations. Variables are ordered according to their stepwise inclusion into the model. Significant effects are emboldened. For explanations of variable codes: see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0094218#pone-0094218-t001" target="_blank">Tables 1</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0094218#pone-0094218-t002" target="_blank">2</a>.</p><p>* - Variables were not included in the stepwise procedure since they did not improve the fit of the model.</p

Estimation of each model detection probability (<i>p</i>), naive estimation of patch occupancy (ψ_r) and patch occupancy estimated after taking the imperfect detection into account (ψ_d).

<p>Models with constant detection probability fitted better than survey specific models in all species.</p

Map of the study area.

<p>Green polygons are woodland patches. Shaded area is the city of Poznań. For each woodland patch the number of woodpecker species and their abundance (in brackets) are given.</p

Pearson correlation coefficients between variables potentially influencing woodpecker species richness, abundance and patch occupancy.

<p>Significance values are given in parentheses. Statistically significant correlations are emboldened. Variable codes: Area – woodland patch area, ForCov – cover of forests within 2000 m from the patch boundary, CanOpen – tree canopy openness, Diagonal – mean diameter of trees, Deciduous – percentage of deciduous trees, Undergrowth – mean percentage shrub cover, DisCentr – distance to the city centre, Roads – density of roads within 500 m from the patch boundary, Settlement – percentage cover of human settlements within 500 m from the patch boundary, Urban – urbanization index.</p