There are three ways to access the database, i.e. time series access for single station or Natural Regions, or full-fledged SQL-access. We shortly illustrate these three main features.
When accessing the database via www.ppodb.de the user first encounters a page where two perspectives can be chosen, i.e. single stations or Natural Regions, for a certain group of plants (Fig. 1).
For clarity, we grouped the different plant types into agricultural plants, fruits, wild growing plants and vines.
Single stations
In the single station perspective plants, corresponding phases, and stations can be selected via drop-down menus (Fig. 2). Stations can additionally be selected by clicking on respective markers in the map. Initially, a map of Central Europe is displayed where most of the stations are grouped into clusters indicated by coloured circles for a better overview. The numbers on the coloured circles indicate the number of stations which are represented by this cluster. Clicking on cluster symbols zooms into the map, where the location of single stations becomes visible. Single stations are marked by red balloons, which contain some general information about the station, like station name, longitude, latitude, altitude, number and range of years in which observations were made (Fig. 2).
Once plant, phase and station are selected, the corresponding time series can be displayed either in a graph (menu ‘plot only’), table (menu ‘data only’) or both (menu ‘data and plot’). Optionally, a trend line is provided with the calculated trend and corresponding P-value (Fig. 3).
In case the station is present in different databases, the respective observations are colour coded (Fig. 3). Note that observations from the same station and year might have been reported in different databases with differing values. We kept all reported observations in the databases, even though in these cases the day of observation of the respective phase is ambiguous.
In the Supplementary Material we provide an additional summary table with all species–phase combinations in the combined database, which are still being observed by the German Weather Service, with their number of stations and observations, and average length of time series per plant, phase and station.
Natural regions
One of the main reasons to construct this database and to merge stations from different databases was to enable the construction of long phenological time series, so-called combined time series, in order to study the effect of climate change on plant phenology (Schaber 2002; Schaber and Badeck 2002, 2003, 2005; Schaber et al. 2010). A combined times series is a sophisticated average over many time series that corrects for artefacts introduced by simple averages due to the unequal distribution of observations in time and space (Schaber et al. 2010). In Fig. 4 we show histograms of the number of time series of a certain length for single stations and Natural Regions, respectively. For Natural Regions, there is a substantial increase of long time series at the expense of short time series. There are more than 480 combined time series for certain phenological phases for certain Natural Regions covering more than 100 years.
Selecting the Natural Regions perspective in the start menu (Fig. 1), the user is presented an interface, where plant, phase and Natural Region can be selected (Fig. 5).
Again plant, phase and Natural Regions can be selected by drop down menus. Natural Regions can also be selected by clicking on the map. From this perspective, combined time series with error bars can be displayed (Fig. 6). Again, a trend can be optionally displayed.
The origin of the combined data is colour-coded as above with the extension that an estimated combined data point can come from more than one database. In the corresponding table the number of observations for each combined data point is also displayed.
SQL access
Through the ‘SQL access’-tab (see Fig. 1), the database can be accessed via SQL statements that allow all kinds of individual queries. The data for Fig. 4, e.g., can be extracted by one single SQL statement (see Fig. 4). For the summary Tables S1–S3 we also provide the respective SQL-statements as an example of the flexibility and range of queries.