In the past decades, agricultural land abandonment and declining land-use intensity became common, especially in the Mediterranean countries of Southern Europe. In some areas this development opened up possibilities for rewilding and the recolonization or expansion of large mammal populations. Yet, in some instances, co-occurrence of wild mammals and free-ranging domestic herbivores might lead to potential conflicts. It is therefore necessary to study the ecological interactions between wild and domestic mammal species to understand the effects of land abandonment and rewilding on biodiversity and ecosystem services. Camera traps are an effective tool for studying species interactions and occupancy dynamics as they allow for long-term monitoring with minimal interference. We conducted a long-term monitoring program with camera traps in the Peneda-Gerês National Park in Northern Portugal. The area has undergone large land-use changes following the abandonment of agricultural areas in the past 60 years. While agro-pastoral activities, especially the breeding of free-ranging horses and cattle, are still common in the area, the intensity of these activities has decreased significantly, promoting natural succession and an increase or return of several large mammal species in recent years. Our project aims at (1) assessing the population trends of the medium and large sized mammals in the area over time; (2) analyzing the effects of passive rewilding on occurrence, abundance and behavior; and (3) understanding potential interactions or conflicts between wild and domestic herbivores.    

Our publication provides a dataset from long-term camera trap monitoring in the Peneda-Gerês National Park between 2015 and 2021. We established a 16 km² grid of 64 cameras deployed yearly during the summer months. In this paper we publish the data and images collected between 2015 and 2021, using both the Camtrap DP standard and the GBIF Darwin Event Core. We obtained a total of 934,810 pictures on 41,234 trap nights. The pictures were automatically grouped into sequences with each sequence representing a distinct occurrence event, resulting in 80,191 occurrences. Out of those, 14,442 contained observations of a species, while the remaining were either blank or the species was not identifiable. We only obtained the information concerning whether a species was present or absent on a picture, disregarding the number of individuals. Most observations were of domestic cattle (Bos taurus) and horses (Equus caballus) followed by European roe deer (Capreolus capreolus) and wild boar (Sus scrofa). Further observations include red fox (Vulpes vulpes), gray wolf (Canis lupus), Eurasian badger (Meles meles), stone marten (Martes foina), common genet (Genetta genetta), Iberian ibex (Capra pyrenaica) and red deer (Cervus elaphus). We estimated occupancy and densities for the most common species. The project is on-going and additional data will be included in the future. The dataset is freely available for ecological analysis but also for training machine learning systems in automated image classification as all pictures have been manually classified.