Spatial replicates as an alternative to temporal replicates for occupancy modelling when surveys are based on linear features of the landscape

1- Occupancy estimates can inform biodiversity managers about the distribution of elusive species, such as the Pyrenean desman Galemys pyrenaicus, a small semi-aquatic mammal that lives along streams. Occupancy models rely on replication within a sampling site and provide estimates of the probability of detection. However, we still do not know how occupancy and detection estimates obtained from spatial vs. temporal replications differ or the appropriateness of using one or the other when cost and logistics make one approach prohibitive. Recently, the Markovian occupancy model has been developed to analyse adjacent spatial replicates and to test for spatial dependence between them. This model has already been applied to large and highly mobile mammals using trails, but never tested for any species with linear home ranges. 2- We compared detection and occupancy estimates obtained from both temporal and spatial sampling designs that were subsequently organized into four data configurations (sites with both spatial and temporal replicates, adjacent spatial replicates only, temporal replicates only at the segment and site scales). From that, five occupancy models with different assumptions (the standard occupancy model, the standard multiscale model, the multiscale model with Markovian process for detection, the Markovian detection model and the Markovian occupancy model) were used. We also assessed which occupancy model was the most appropriate for each data configuration to determine whether it is necessary to incorporate correlation into models. 3 - We found that the estimated detection probabilities were relatively high (≥0·58) and similar when the same model was applied to each data configuration. 4 - Spatial replication weakly underestimated occupancy. But when using this design, the Markovian occupancy model was the most supported and minimized the underestimation of occupancy, highlighting a spatial dependence between adjacent replicates. 5 - Synthesis and applications. We show that a survey based on adjacent spatial replicates for a mammal living along linear features of the landscape is a good compromise between cost and occupancy estimates, while using the Markovian occupancy model to estimate detection and occupancy. Our finding may have wider applications for the monitoring of species especially when temporal replicates are difficult or unrealistic. Spatial design, for surveys based on sign detection, could thus be applied for species with linear home ranges or when surveys are constrained by linear habitats.