TY - JOUR
T1 - Integrating aerial and ship surveys of marine birds into a combined density surface model
T2 - a case study of wintering Common Loons
AU - Winiarski, Kristopher
AU - Burt, M Louise
AU - Rexstad, Eric
AU - Miller, David Lawrence
AU - Trocki, Carol
AU - Paton, Peter
AU - McWilliams, Scott
PY - 2014
Y1 - 2014
N2 - Biologists now use a variety of survey platforms to assess the spatial distribution and abundance of marine birds, yet few attempts have been made to integrate data from multiple survey platforms to improve model accuracy or precision. We used density surface models (DSMs) to incorporate data from two survey platforms to predict the distribution and abundance of a diving marine bird, the Common Loon (Gavia immer). We conducted strip transect surveys from a multiengine, fixed-wing aircraft and line surveys from a 28 m ship during winter 2009–2010 in a 3,800 km2 study area off the coast of Rhode Island, USA. We accounted for imperfect detection and availability bias due to Common Loon diving behavior. We incorporated spatially explicit environmental covariates (water depth and latitude) to provide predictions of the spatial distribution and abundance of wintering Common Loons. The combined-platform DSM estimated the highest Common Loon densities (>20 individuals km−2) in nearshore waters <35 m deep, with an average daily abundance of 5,538 (95% CI = 4,726–6,489) individuals in the study area. The combined-platform model offered substantial improvement in the precision of abundance estimates from the ship-platform model, and modest improvement in the precision of the aerial-platform model. The combined model had relatively low predictive power, which previous research indicates is primarily a consequence of the dynamic marine environment. We show that the DSM approach presents a flexible framework for developing spatially explicit models of a marine bird from different survey protocols.
AB - Biologists now use a variety of survey platforms to assess the spatial distribution and abundance of marine birds, yet few attempts have been made to integrate data from multiple survey platforms to improve model accuracy or precision. We used density surface models (DSMs) to incorporate data from two survey platforms to predict the distribution and abundance of a diving marine bird, the Common Loon (Gavia immer). We conducted strip transect surveys from a multiengine, fixed-wing aircraft and line surveys from a 28 m ship during winter 2009–2010 in a 3,800 km2 study area off the coast of Rhode Island, USA. We accounted for imperfect detection and availability bias due to Common Loon diving behavior. We incorporated spatially explicit environmental covariates (water depth and latitude) to provide predictions of the spatial distribution and abundance of wintering Common Loons. The combined-platform DSM estimated the highest Common Loon densities (>20 individuals km−2) in nearshore waters <35 m deep, with an average daily abundance of 5,538 (95% CI = 4,726–6,489) individuals in the study area. The combined-platform model offered substantial improvement in the precision of abundance estimates from the ship-platform model, and modest improvement in the precision of the aerial-platform model. The combined model had relatively low predictive power, which previous research indicates is primarily a consequence of the dynamic marine environment. We show that the DSM approach presents a flexible framework for developing spatially explicit models of a marine bird from different survey protocols.
KW - Abundance estimation
KW - Common Loon
KW - density surface model
KW - distance sampling
KW - Gavia immer
KW - spatial modeling
KW - spatially explicit abundance models
UR - http://www.bioone.org/doi/abs/10.1650/CONDOR-13-085.1
U2 - 10.1650/CONDOR-13-085.1
DO - 10.1650/CONDOR-13-085.1
M3 - Article
SN - 0010-5422
VL - 116
SP - 149
EP - 161
JO - Condor
JF - Condor
IS - 2
ER -