Spring spotlight counts provide reliable indices to track changes in population size of mountain-dwelling red deer Cervus elaphus

Monitoring changes in animal abundance is a central issue in conservation biology. Population indices may be a valuable support to wildlife managers in coarse-scale survey programs, as they normally represent more intuitive and less expensive monitoring tools if compared with absolute estimates. Reliable indices of relative abundance, however, require validation against some known standards. We used mark-resight estimates to investigate the performance of indices derived from spring spotlight surveys to track changes in a mountain-dwelling population of red deer Cervus elaphus within the Stelvio National Park, central Italian Alps. Every spring between 2008 and 2015 we conducted four sessions of roadside-counts using spotlights, recording all sightings of marked and unmarked individuals; the zero-truncated Poisson log-normal estimator was applied in a robust-design fashion to return absolute estimates of spring abundance. We then compared the mark-resight estimates with two indices of abundance, the maximum number (MNC) and the average number (ANC) of deer counted every spring in the four sampling occasions, using linear models on log-transformed data. Both the MNC and the ANC proved reliable indices of relative abundance, as their relationships with mark-resight estimates were positive and highly significant, and the beta coefficients of linear models were not significantly different from 1. The same analysis conducted on subsets of secondary sampling occasions suggested that at least 3 repeated counts every spring are necessary to consistently track changes in deer population size. The reliability of spotlight-based indices to monitoring deer population changes has been widely debated, possibly owing to inconsistent performances of the method in different landscapes. For mountain-dwelling deer populations living in similar habitats, our results suggest that spring spotlight surveys represent valuable tools in support of wildlife managers for long-term, large-scale monitoring programs; furthermore, they can provide appropriate indices to estimating population growth rates and thus modelling deer population dynamics.