Count trends for migratory Bald Eagles reveal differences between two populations at a spring site along the Lake Ontario shoreline

迁徙性白头海雕的数量趋势显示,安大略湖沿岸一处泉水点的两个种群之间存在差异。

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Abstract

The recovery of Bald Eagles (Haliaeetus leucophalus), after DDT and other organochlorine insecticides were banned in the United States, can be regarded as one of the most iconic success stories resulting from the Endangered Species Act. Interest remains high in the recovery and growth of the Bald Eagle population. Common to evaluating growth and recovery rates are counts at nesting sites and analyses of individuals fledged per season. But this is merely one snapshot that ignores survival rates as eagles grow to maturity. By analyzing indices from migration counts, we get a different snapshot better reflecting the survival of young birds. Different populations of Bald Eagles breed at different sites at different times of the year. Typical migration count analyses do not separate the populations. A separation of two distinct populations can be achieved at spring count sites by taking advantage of the tendency for northern summer breeding birds to migrate north in spring earlier than southern winter breeding birds who disperse north later in spring. In this paper I analyze migratory indices at a spring site along Lake Ontario. The analysis shows that eagles considered to be primarily of the northern summer breeding population showed an estimated growth rate of 5.3 ± 0.85% (SE) per year with 49% of eagles tallied in adult plumage, whereas the migrants considered to be primarily of the southern breeding population had an estimated growth rate of 14.0 ± 1.79% with only 22% in adult plumage. Together these results argue that the populations of southern breeding Bald Eagles are growing at a substantially higher rate than northern breeding eagles. These findings suggest that aggregate population indices for a species at migration counting sites can sometimes obscure important differences among separate populations at any given site and that separating counts by time period can be a useful way to check for differences among sub-populations.

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