Abstract
A major challenge in applied ecology consists in integrating knowledge from different datasets to produce robust ecological indicators. To estimate species distribution, occupancy models are a flexible framework that can accommodate several datasets obtained from different sampling methods. However, repeating visits at sampling sites is a prerequisite for using standard occupancy models, which may limit their use. Under certain conditions, detection/non-detection data collected during single visit can be analysed with occupancy models. To date however, single-visit occupancy models have never been used to combine several different datasets.
Here, we developed an approach that combines multi-method and single-visit occupancy models. As a case study, we estimated the distribution of Bottlenose dolphins (Tursiops truncatus) over the North-western Mediterranean Sea by combining 24,624 km of aerial surveys and 21,464 km of at-sea monitoring. We compared the outputs of single-vs. repeated-visit multi-method occupancy models, and that of single-method occupancy models.
Multi-method models allowed a better sampling coverage in both coasts and high seas and provided a better precision for occupancy estimates than single-method occupancy models using aerial surveys or at-sea surveys in isolation.
Overall, single- and repeated-visit multi-method occupancy models produced similar inference about the distribution of bottlenose dolphins. This suggests that single-visit occupancy models provide robust occupancy estimates, which open promising perspectives for the use of non-standardized datasets.
Synthesis and applications: Single-visit multi-method occupancy models can help making the best out of ecological monitoring programs by optimizing cost effectiveness through the formal combination of datasets.