Optimal survey methods for estimating population trends are those that result in high detection probability and low temporal variance in detection probability. We compared detection probability of California black rails (Laterallus jamaicensis coturniculus) between passive and call-broadcast surveys, and we examined factors that influenced detection probability. The number of black rails detected was 13% higher on call-broadcast surveys compared to passive surveys, but the number of other marsh birds (bitterns and other species of rails) detected was 21% lower. We detected more black rails on evening surveys compared to morning surveys, but we had to cancel 42% of evening surveys due to high wind (>25 km/hr). Detection probability increased from 0500 to 0700 hr and then declined as the morning progressed, but detection probabilities did not vary among hourly time intervals during evening surveys. We failed to detect an effect of broadcast volume on number of black rails detected during paired surveys. Observer detection probability of black rails (x̄ = 75.5%) varied among observers but did not differ between passive and call-broadcast surveys. We failed to find a consistent time of year when detection probability was highest at all of our survey locations. We heard the 3 most common black rail calls in consistent proportion from March through June. As many as 15 replicate surveys may be needed to attain >90% detection probability of black rails within potential wetland habitat. We recommend that standardized black rail surveys be repeated annually to provide more precise estimates of population trend and to better determine the distribution and status of this rare species.
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1 April 2004
FACTORS AFFECTING DETECTION PROBABILITY OF CALIFORNIA BLACK RAILS
COURTNEY J. CONWAY,
CHRISTINA SULZMAN,
BARBARA E. RAULSTON
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Journal of Wildlife Management
Vol. 68 • No. 2
April 2004
Vol. 68 • No. 2
April 2004
California black rail
call broadcast
detection probability
Laterallus jamaicensis coturniculus
marshlands
monitoring
observer bias