2012 COURSE DATES: AUGUST 4 – 17, 2012 - Sirenian International

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assumption, we divided our locations into high-sighting probability sites (>30% probability
of sighting a manatee per scan) and low-sighting probability sites (< 30% probability of
sighting a manatee per scan) (LaCommare et al. 2008). We then examined cumulative
histograms of time to first sighting for both categories. We expected that each histogram
would have a similar asymptotic curve indicating that our ability to detect manatees was
similar for high versus low-sighting probability locations.
The relationship of the index to the actual number of animals counted is also a
function of detection probability (Anderson 2001; Gibbs 2000; Gibbs et al. 1998;
Thompson 2004; Williams and Thomas 2009) – the ability to detect an animal when it is
present (MacKenzie and Royle 2005). Three classes of variables affect this: observers,
environment and species behavior. For each point scan, we counted the number of
manatees and recorded variables that might influence detection probabilities. We used a
generalized linear model (GLM) with a negative binomial distribution and a log-link
function to determine whether the number of manatees sighted was influenced by sighting
conditions. This distribution was the most appropriate for our over-dispersed (variance
greater than the mean) Poisson-distributed response variable, number of manatees (Agresti
1996; Quinn and Keough 2002). Our predictor variables were: environmental conditions
(sun glare - yes/no, precipitation -dry/light rain, cloud cover -clear/scattered clouds/partly
cloudy/overcast, Beaufort sea state -0/1/2/3, swell height -in 0.15m increments; water
clarity and time of day), and manatee behavior (disturbed/feeding/resting/social/travel/
undetermined - Table 1). Water clarity was a measure of the horizontal distance between
an underwater observer and Secchi disk held 0.5 meters under the water. Water clarity was
measured in this fashion because the vertical Secchi depth was usually greater than or equal
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