Experimental evidence for large carnivore risk cues reducing deer browsing intensity in a temperate forest

Intensive ungulate browsing represents a major challenge for managing temperate forests, and only a clear understanding of the underlying ecological processes can help to mitigate its impact. Predator-prey interactions play a crucial role in shaping browsing patterns; however, the lack of a comprehensive understanding of these dynamics hinders the development of functional policies. Using an experimental approach, we simulated large-carnivore presence using olfactory cues to examine the effects of predation risk on deer behaviour and its consequences for browsing intensity on tree saplings. We conducted this experiment in eleven locations in the Bavarian Forest National Park (Germany), each comprising four plots with olfactory cues of wolf, lynx, cow, and water (control). In each plot, we planted 30 saplings representing the five most common tree species in the area, which we regularly monitored to assess browsing intensity and selectivity.  In addition, we set a camera trap at eac..., , , # Experimental evidence for large carnivore risk cues reducing deer browsing intensity in a temperate forest [https://doi.org/10.5061/dryad.b2rbnzsrd](https://doi.org/10.5061/dryad.b2rbnzsrd) ## Description of the data and file structure Data from: Experimental evidence for large carnivore risk cues reducing deer browsing intensity in a temperate forest The repository contains the dataframes used to run the models explained in the Manuscript, all the information on the data collection can also be found in the Manuscript. In the Supporting Information of the Manuscript are available further details of the models. The repository contains the following two dataframes: \"Browsing_data\" with all the data needed to run the Browsing intensity and the Browsing selectivity models, and \"Behavioural_data\" with all the data needed to run the Time Spent Vigilant model, Visitation Duration model and Visitation Frequency model. ### Files and variables #### File: Behavioural_data.csv **Descripti...,