Multi-species occupancy model for estimating the probability of detecting amphibian species in Hungary

Research into freshwater communities often aims to link patterns of
species distribution in ponds with underlying biotic factors. However,
errors with species detection (e.g., false negatives) may underestimate
distribution and bias assessments of community structure. Occupancy models
that account for imperfect detection offer a solution to this problem.
Here, we used three methods (call/ visual encounter surveys, dip-netting
and newt trapping) to survey amphibians and fish (potential amphibian
predators) at 100 ponds in an urbanised landscape in Hungary over one
breeding season. We estimated species detection probabilities for
amphibians (all life stages combined) and fish using multi-species
occupancy models to gain insight into amphibian-fish relationships and
other survey-specific variables. We detected nine amphibian and 20 fish
species. There were relatively low but variable estimated probabilities of
detection for amphibians (mean: 0.320, 95% Bayesian credible interval:
0.142 – 0.598), with three species having detection rates < 0.1.
Probabilities of detection peaked in the middle of the breeding season and
increased with survey effort. Detection probabilities of five species were
negatively associated with the detection of fish at a pond, while there
were positive relationships between detection and emergent vegetation
cover. We found no substantial differences in detection rates among the
three survey methods. The probability of detecting fish was much higher
than for amphibians (0.588, 0.503 – 0.717) but was lower at ponds with
high emergent vegetation where amphibian detection was higher. Our results
underscore the importance of accounting for the imperfect detection of
both response organisms and potentially interacting species in aquatic
community studies. We recommend applying multi-species occupancy models to
enable inference for both common and rare species at ponds in landscapes
subjected to human disturbances.