Occupancy model reveals limited detectability of lichens in a standardised large-scale monitoring

Hirschheydt G. von, Kéry M., Ekman S., Stofer S., Dietrich M., Keller C. & Scheidegger C.
Journal of Vegetation Science
35: e13255 [11 p.]
Question: What are the extent and the possible causes of imperfect detection in lichens? Because lichens are sessile and lack seasonality, they should be easier to survey than animals that can move or plants and fungi with seasonal morphology, and one could therefore expect relatively high detection probabilities. Location: 826 standardised sampling plots across Switzerland. Methods: Using repeated detection/non-detection data from a national lichen survey conducted by professional lichenologists, we estimated the mean and variation in detectability for 373 tree-living species with a multi-species occupancy model. We also quantified the effect of species conspicuousness, identifiability and observer experience on detection probability. Results: The average detection probability for a single survey was unexpectedly low with an average of 0.49 (range across species: 0.25–0.74). Conspicuous species showed higher average detectability (0.56) than inconspicuous species (0.41), and identifiability as well as previous experience with a species substantially increased the probability of a person detecting it. Accounting for experience, the mean detection probabilities of observers ranged from 0.32 to 0.69. Conclusions: Our study confirms that detection probability per survey is often far below 1 also in sessile organisms, even when a standardised survey is conducted by experts. When species are seasonal (plants, fungi, etc.), survey areas are larger, or field personnel are less experienced, as is the case for many surveys and monitoring programs, detectabilities are likely to be substantially lower. We therefore argue that imperfect detection should systematically be considered in the survey design and data analysis also for sessile organisms. Keywords: detection probability, epiphytic lichens, imperfect detection, lichen, monitoring, observer error, occupancy model, repeated surveys, sampling error, sessile organism, Switzerland.
Sunday, 28 April 2024 20:58