Analyzing phenological synchronicity using volunteered geographic information

Analyzing synchronicity in the timing of annual recurring animal and plant life cycle events is important to analyse the impact of global change on our planet. The location and timing of these events is recorded by thousands of volunteers in the context of phonological networks. Most of the current workflows analyse synchronicity without checking consistency of such volunteered geographic information. Here, we describe a workflow to analyse synchronicity in volunteered observations while accounting for possible inconsistencies in the data. The workflow uses the date and geographic locations of the observations to 1) define temperature-driven constraints; 2) spatially link the observations; 3) identify inconsistent observations; and 4) model species-specific synchronicity. This workflow was tested using flowering observations of horse chestnut (Aesculus hippocastanum) in the Netherlands for the period 2003-2015. We found inconsistent observations each year but a sensitivity analysis of the temporal trends in flowering did not find significant differences between trends estimated from the original observations or only the consistent ones. This means that the observations already have a high degree of consistency. We found a negative correlation between the measure of synchronicity in flowering onset and the cumulative temperatures of February, March and April (R = 0.77). In years with warm springs, the flowering tends to be more geographically synchronous than years with cold springs. These results show that the proposed workflow can effectively be used to analyse volunteered geographic information in phenology