Combining single- and repeated-visit occupancy models to make the best of monitoring surveys
AbstractA 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.