科研之友
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摘要
Estimating the abundance of seals inhabiting sea ice is complicated because the areas are large, the ice area and distribution may change rapidly, and it is impractical to detect and count a (typically unknown) portion of the population that is in the water, rather than hauled out on the ice. We propose a method for resolving these issues by using a series of daily estimates that are imprecise by themselves, but yield an acceptable estimate when they are combined. Population surveys of spotted seals, ribbon seals and bearded seals were conducted over 279,880 km(2) of the Bering Sea between 13 April and 26 May 2007. During that period, the sea-ice conditions and spatial distribution of seals changed dramatically. We surveyed 2748 km(2) using line transect methods from a helicopter deployed from the US Coast Guard icebreaker Healy. Corrections for incomplete availability of seals used a generalized linear mixed model for seal haul-out probability using sensors on seals with data transmitted by satellite. We accounted for incomplete detection through standard distance-sampling methods along with a double-observer model. The availability and detection models were combined in a data model for local abundance in space and time. To accommodate the shifting ice and seal movements, we then developed a hierarchical spatially-autocorrelated regression model using remotely sensed sea ice concentration data to predict abundance at each survey date. While abundance estimation was very imprecise for each date, we were able to combine them to obtain good estimates of overall population abundance even though the population was spatially dynamic. The proposed hierarchical model combined submodels and accounted for their sources of uncertainty. Spotted seals were most abundant within the study area (233,700, 95% Cl 137,300-793,100), followed by bearded seals (61,800, 95% Cl 34,900-171,600) and ribbon seals (61,100, 95% Cl 35,200-189,300). Published by Elsevier B.V.
- 出版日期2014-3
