Usefulness of volunteer data to measure the large scale decline of “common” toad populations

Measuring a species decline is pivotal to evaluate their conservation status, but an accurate assessment of demographic trends requires observations collected across broad spatial and temporal scales. Volunteers can help to collect information over large scales, but their data may be affected by heterogeneity for sampling efforts and protocols, which may influence detection probability. Ignoring this issue may conduct to misleading conclusions. Here we show that data collected by different volunteer groups can be integrated with measures of sampling efforts, to obtain information on large scale demographic trends. We collected data on 33 common toad (Bufo bufo) populations across Italy for the period 1993–2010. We used two approaches (meta-analysis; analysis of average change in population size) to evaluate the overall demographic trend. We incorporated measures of volunteer sampling efforts into analyses, to take into account changes in detection probability. Toad abundance significantly declined in the last decade. From 2000 to 2010, 70% of populations showed a strong decline, and only 10% increased. Trends were heterogeneous among populations, but taking into account sampling effort reduced heterogeneity by 40%. We detected a 76% cumulative average decline of toad populations, despite an increasing mean sampling effort. The widespread toad decline rises concern for its future, also because the causes remain unclear. Volunteer data can be extremely useful to identify large scale population trends, if information on sampling effort are recorded and used to adjust counts.

► We used volunteer data to assess whether the common toad is declining at large scale.
► We collected data on 33 toad populations across Italy for the period 1993–2010.
► From 2000 to 2010, 70% of populations showed a strong decline.
► We detected a 76% decline in population size across the whole area in 10 years.
► Volunteer data adjusted for sampling effort can help to identify broad scale trends.