Paul Sunnucks
2018, Journal of Field Ornithology
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14 pages
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Banding allows identification of individual birds, and many investigators use data from recaptured or recovered birds to infer population parameters, including survival rates, migration rates, and recruitment rates. Such analyses often assume that band loss is negligible, but wear rates have been found to differ markedly among different band sizes, band metals, and species in the few cases where wear rates have been determined. However, rapidly wearing bands may be over-reported in the published literature relative to slowly wearing bands for two reasons. First, researchers publish reports of rapidly wearing bands as a warning to other researchers, but may not publish reports of bands wearing slowly. In addition, sampling error may result in over-or underestimation of wear rates. At the extreme, underestimates of wear rates may imply that bands gain mass while worn (i.e., have negative wear rates), whereas extreme overestimates look like rapid wear; only extreme underestimates, not extreme overestimates, are unpublishable due to their a priori implausibility. Hence, the existing literature on band-wear estimates is likely upwardly biased relative to the true distribution of wear rates across species and band metals. Using routinely archived returned bands from the Australian Bird and Bat Banding Scheme for the period from 1963 to 2005, we estimated wear rates of bands applied to 173 species, five band metals, and 236 species/band size/band metal combinations. Band wear rates were generally well-explained by band metal and species functional group, i.e., birds of prey, waterbirds (shorebirds, herons, and ibises), passerines, waterfowl (ducks, geese, and swans), rails, seabirds, parrots, and other non-passerines, but some species had highly divergent wear rates compared to other species in their functional group. We also found that published estimates of wear rates were, on average, more rapid for a given metal type than determined from our analyses. We suggest that publication biases favoring publication of estimates of more rapid wear rates may drive the contrast between estimated wear rates in our analyses and published estimates.
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