In structured populations, persistence under environmental change is threatened when abiotic factors simultaneously negatively affect survival and reproduction of several life-cycle stages. Such effects can then be exacerbated when species interactions generate reciprocal feedbacks between the demographic rates of the different species. Despite the importance of such demographic feedbacks, forecasts that account for them are severely limited as individual-based data on interacting species are perceived to be essential for such mechanistic forecasting - but are rarely available. This dataset is the input to showcase a state-of-the-art Bayesian method  to infer and  project stage-specific survival and reproduction from abundance data for several interacting species in a Mediterranean shrub community.

In order to assess community composition before, during, and after a severe drought event in Doñana National Park, 18 permanent plots of 25 m² were established in November 2007 (two years after the drought) on a gradient of drought impact. The plots were located at three sites (with six plots per site): Raposo, Marquas, and Ojillo. To avoid spatial autocorrelation, all plots were separated by at least 50 m from each other. Species plant cover was estimated from contacts with branches along transects within plots; these contacts were divided into two categories corresponding to living or dead canopy. Relative abundance of each species per plot in years after the extreme drought was calculated as the proportion of their contacts of living canopy relative to the sum of the contacts of living canopy of all species. Similarly, the total vegetation cover per plot was calculated as the summed contacts of living canopy of all species.

All data were processed in R statistical software, version 4.0.1 (and packages as described in the R scripts). Code to analyze the data is presented on https://github.com/MariaPaniw/shrub_forecast.