From Field to Model: Monitoring Methods and Integrated Population Modelling of Alpine ibex (Capra ibex)

Climate change poses numerous threats to wildlife inhabiting mountain environments, where changes are occurring rapidly. Mountain ungulates, which play a key role in alpine ecosystems, are especially vulnerable. Many are already in an unfavourable conservation status, and their conservation is further challenged by limitations in biodemography studies and monitoring efforts. Monitoring is indeed complicated by imperfect detection (the inability to count all individuals) and by the costs and difficulties of working in rugged mountain habitats. This thesis aims to address some of these limitations and strengthen conservation strategies for mountain ungulates. Since monitoring forms the foundation of effective management, but traditional count methods (block counts) are often imprecise, I explore alternative approaches to improve reliability while reducing costs. I then focus on another key objective: understanding the drivers of population dynamics in ungulates and the effects of a changing environment on their biodemography. To achieve these objectives, I focus on the Alpine ibex (Capra ibex L., 1758) population in Gran Paradiso National Park (GPNP, Northwestern Italian Alps), which offers an exceptionally long time series of counts and individual survival data. Using simulations based on real-case parameters, I test the reliability of sample counts (counting only a portion of the total area) as a low-effort monitoring approach. Results show that surveying half of the target area is sufficient to detect relevant population trends, demonstrating how sample counts could be valuable for population monitoring. I also propose a new census framework, the Double Observer Adjusted Survey (DOAS), which improves count reliability with minimal additional effort. This method uses Double Observer repeats to estimate detectability and adjust data from full-area block counts. Both simulations and a field test confirm its reliability, indicating its suitability for cost-effective and accurate abundance estimation. Furthermore, I analyse detectability and its determinants in the study population, showing that individuals are more easily observed under certain weather conditions or terrain topography. Accounting for these factors could improve traditional block counts without replacing them. Finally, I use Integrated Population Models to reconstruct the population dynamics of the study population over the last 70 years. These analyses suggest that climate change can strongly influence ungulate dynamics and age structure through alterations in snow cover, temperature, and vegetation, and that juveniles could be the most sensitive age class and shape population trajectories. The effects of climate change could be contrasting: in GPNP, adults are showing higher survival due to milder winters, whereas kid survival fall as a consequence of population aging, leading to an overall abundance reduction. Together, these findings could improve conservation efforts for Alpine ibex and other mountain ungulates, providing practical tools for monitoring populations and understanding the ecological and environmental drivers that shape them.

Citation

Panaccio, M. (2025). From Field to Model: Monitoring Methods and Integrated Population Modelling of Alpine ibex (Capra ibex) [Unpublished doctoral thesis]. University of Chester.

URI

https://chesterrep.openrepository.com/handle/10034/629902

Type

Thesis or dissertation

Language

en