02273nas a2200205 4500008004100000245010700041210006900148520160100217653001601818653001801834653002001852653001401872653002901886653001601915653001701931653002901948100002301977700002302000856004402023 2020 eng d00aDoes the presence of an observer affect a bird's occurrence rate or singing rate during a point count?0 aDoes the presence of an observer affect a birds occurrence rate 3 a

The approach or presence of an observer may affect the behavior of nearby birds, rendering them either more or less detectable than when no observer is present due to a change in singing rates. To test whether there are systematic detection biases associated with the presence of an observer during point count bird surveys, we compared the occurrence and singing rates of birds during a 10‐min period immediately preceding the time when an observer arrived to conduct a count and during the formal count itself by extracting song information from autonomous sound recorders. We obtained recordings of 36 species of birds detected at ≥5 locations in one of three vegetation types, including burned conifer forest, green conifer/riparian streamside forest, and riparian bottomland/marshland. We found that species richness and both the probability of occurrence and singing rate for any of the species recorded were unaffected by the presence of an observer. In addition, the probability of occurrence did not differ significantly among four 2.5‐min recording sessions during 10‐min counts when an observer was present. Thus, the presence of an observer did not appear to introduce any detectable systematic bias that would make bird lists or unadjusted occurrence rates inaccurate on that basis alone. In addition, rates of bird occurrence across 2.5‐min temporal subsets of a 10‐min count did not vary in a systematic way that would violate the assumption of equal occupancy across adjacent time periods as sometimes used to build detection histories in occupancy modeling.

10abird survey10adetectability10aobserver effect10aoccupancy10apassive acousticsampling10apoint count10asinging rate10autonomous recording unit1 aHutto, Richard, L.1 aHutto, Russell, R. uhttp://doi.wiley.com/10.1111/jofo.1232903022nas a2200217 4500008004100000022001400041245010500055210006900160260001600229520213400245653002202379653003402401653001702435653002602452653001402478653001702492653001302509100002302522700002102545856023802566 2019 eng d a2045-775800aTemporally adaptive acoustic sampling to maximize detection across a suite of focal wildlife species0 aTemporally adaptive acoustic sampling to maximize detection acro cOct-08-20203 a

1. Acoustic recordings of the environment can produce species presence–absence data for characterizing populations of sound‐producing wildlife over multiple spatial scales. If a species is present at a site but does not vocalize during a scheduled audio recording survey, researchers may incorrectly conclude that the species is absent (“false negative”). The risk of false negatives is compounded when audio devices have sampling constraints, do not record continuously, and must be manually scheduled to operate at pre‐selected times of day, particularly when research programs target multiple species with acoustic availability that varies across temporal conditions.

2. We developed a temporally adaptive acoustic sampling algorithm to maximize de‐ tection probabilities for a suite of focal species amid sampling constraints. The algorithm combines user‐supplied species vocalization models with site‐specific weather forecasts to set an optimized sampling schedule for the following day. To test our algorithm, we simulated hourly vocalization probabilities for a suite of focal species in a hypothetical monitoring area for the year 2016. We conducted a factorial experiment that sampled from the 2016 acoustic environment to com‐ pare the probability of acoustic detection by a fixed (stationary) schedule versus a temporally adaptive optimized schedule under several sampling efforts and moni‐ toring durations.

3. We found that over the course of a study season, the probability of acoustically capturing a focal species (given presence) at least once via automated acous‐ tic monitoring was greater (and acoustic capture occurred earlier in the season) when using the temporally adaptive optimized schedule as compared to a fixed schedule.

4. The advantages of a temporally adaptive optimized acoustic sampling schedule are magnified when a study duration is short, sampling effort is low, and/or spe‐ cies acoustic availability is minimal. This methodology presents the opportunity to maximize acoustic monitoring sampling efforts amid constraints.

10aadaptive sampling10aautomated acoustic monitoring10abioacoustics10adetection probability10aoccupancy10aoptimization10awildlife1 aBalantic, Cathleen1 aDonovan, Therese uhttps://onlinelibrary.wiley.com/doi/abs/10.1002/ece3.5579https://onlinelibrary.wiley.com/doi/pdf/10.1002/ece3.5579https://onlinelibrary.wiley.com/doi/pdf/10.1002/ece3.5579https://onlinelibrary.wiley.com/doi/full-xml/10.1002/ece3.5579