Comparative Efficiency of eDNA , Camera Traps and Scat Surveys to Detect a Semi‐Aquatic Mammal Across Multiple Catchments

ABSTRACT Semi‐aquatic mammals lie at the intersection of several key conservation issues such as wetland deterioration or species invasions, and monitoring their distribution in space and time is essential to inform conservation strategies. However, gathering information about their presence is challenging due to their elusive lifestyle and generally low abundance. The Eurasian otter ( Lutra lutra ), a near‐threatened and strictly protected species in Europe, is currently recolonizing part of its historical range. Its high conservation interest, combined with a dynamic more commonly associated with range‐expanding or invasive species, makes it a particularly compelling case study. Otter monitoring has traditionally relied on scat surveys, but recent environmental DNA (eDNA) and camera‐trapping initiatives have emerged offering promising complementary tools. Yet, these approaches have rarely been formally compared, either to one another or across regions. Here, we compared the efficiency of spraint surveys, camera traps, and eDNA for detecting otters, and assessed how their performance varied among four catchments in southern France where the species is known to be present. All three methods provided otter detections with varying efficiency. Scat surveys were the most effective method, with an average detection probability of 0.71 and no strong variability between catchments. Although camera‐traps had the lowest detection rate, they provided detections at two of the four sites where no spraint was found, highlighting the complementarity of these two approaches. Detection rates varied greatly between individual cameras rather than between catchments, underscoring sensitivity to camera placement. eDNA showed important variability between catchments, with detection probabilities differing by roughly sixfold across regions. All in all, our results highlight differences in efficiency between methods and across environmental conditions, and show the value of combining approaches for future monitoring programs.