Determining appropriate statistical distributions for modeling
animal count data is important for accurate estimation of abun-
dance, distribution, and trends. In the case of sea ducks along the
U.S. Atlantic coast, managers want to estimate local and regional
abundance to detect and track population declines, to define
areas of high and low use, and to predict the impact of future
habitat change on populations. In this paper, we used a modified
marked point process to model survey data that recorded flock
sizes of Common eiders, Long-tailed ducks, and Black, Surf, and
White-wingedscoters.Thedatacomefromanexperimentalaerial
survey, conducted by the United States Fish & Wildlife Service
(USFWS) Division of Migratory Bird Management, during which
east-west transects were flown along the Atlantic Coast from
Maine to Florida during the winters of 2009–2011. To model the
number of flocks per transect (the points), we compared the fit
offourstatisticaldistributions(zero-inflatedPoisson,zero-inflated
geometric,zero-inflatednegativebinomialandnegativebinomial)
todataonthenumberofspecies-specificseaduckflocksthatwere
recorded for each transect flown. To model the flock sizes (the
marks), we compared the fit of flock size data for each species
tosevenstatisticaldistributions:positivePoisson,positivenegative
binomial, positive geometric, logarithmic, discretized lognormal,
zeta and Yule–Simon. Akaike’s Information Criterion and Vuong’s