Validity of Predictive Equations for Total Body Fat in Sanderlings from Different Nonbreeding Areas

Castro, Gonzalo; Myers, J. P.

doi:10.2307/1368400

Cited by 19 publications

(14 citation statements)

References 18 publications

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“…Second, body mass usually has a fairly strong correlation with fat mass and in many cases explains more than 50% variation in fat mass (Table 2). While variation in body mass is sometimes a good indicator of variation in fat mass in birds, how good an indicator it is varies, not only among species but also among populations and between sexes (Table 2; Castro and Myers 1990). The fact that different studies of the same species can yield different results illustrates what we think is a central result in the use of morphometric indices to estimate body fat.…”

Section: Body Massmentioning

confidence: 98%

“…Sometimes, fat scores are included in the predictive models. The predictive power of such models varies considerably among species and populations, but is usually fairly good (Table 5; Castro and Myers 1990). The particular morphological traits included in best fitting models differ among species and populations, so caution is warranted when extrapolating the use of a specific equation that has not been validated in the population of interest.…”

Section: Predictive Regression Equations For Fat Massmentioning

confidence: 99%

“…The particular morphological traits included in best fitting models differ among species and populations, so caution is warranted when extrapolating the use of a specific equation that has not been validated in the population of interest. In other words, models constructed for other populations or species may underestimate or overestimate fat mass in new populations (Castro and Myers 1990;Sparling et al 1992;Seewagen 2008). Nonetheless, predictive equations are generally better at estimating fat mass than standard condition indices or fat scoring alone (DeLong and Gessaman 2001; Bergstrom and Sherry 2008;Schamber et al 2009).…”

Section: Predictive Regression Equations For Fat Massmentioning

confidence: 99%

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Morphometric indices of body condition in birds: a review

2011

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Morphometric estimates of body condition are widely used by ornithologists, but which estimates work best is a matter of debate. We review morphometric approaches (body mass, ratio and residual condition indices, predictive regression models, fat scoring, and abdominal profiles) for estimating body condition (defined as fat mass) in birds. We describe the strengths and weaknesses of each approach. Across diverse indices and species (*200 estimates total), the mean r 2 relating condition indices to mass of body fat was 0.55, and 64% of the r 2 values were greater than 0.50. But despite their generally good performance, condition indices sometimes perform poorly (i.e., r 2 is low). The data indicate that: (1) no single index was clearly best, (2) on average body mass alone, fat scores, and predictive multiple regression equations explained slightly more than 50% of the variation in fat content, (3) on average, ratio and residual indices explained slightly less than 50% of the variation in fat content, and (4) body mass alone, a variable that can be easily and reliably measured, is as good or nearly as good an indicator of fat content as any other condition index. We recommend that: (1) morphometric indicators of condition be empirically validated, (2) researchers publish their body composition data in sufficient detail that they can be used in future analyses exploring the relative merits of different condition indices, and (3) multiple regression directly on measured traits be used instead of condition indices whenever the condition index is not empirically validated.

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Section: Body Massmentioning

confidence: 98%

Section: Predictive Regression Equations For Fat Massmentioning

confidence: 99%

Section: Predictive Regression Equations For Fat Massmentioning

confidence: 99%

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Morphometric indices of body condition in birds: a review

2011

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“…To complete migration, shorebirds have to deposit large quantities of fat by feeding rapidly at these staging areas. Their high metabolic rates, often higher than those predicted on scaling curves of metabolic rates of body mass (Kersten and Piersma 1987), require that waders accumulate fat deposits that may at times be greater than 50% of their lean body mass (Castro and Myers 1990). To achieve this, they have to remain for an extended period of time at the staging areas.…”

Section: Introductionmentioning

confidence: 99%

Predation of migratory Little Stint (Calidris minuta) by Barbary Falcon (Falco pelegrinoides) is dependent on body mass and duration of stopover time

Yosef

Gołdyn

Zduniak

2010

J Ethol

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Shorebird (Charadriiformes) migration phenology is critically synchronised with prey availability at traditional staging sites that allows the birds to stage and complete the migrations. These stopovers, usually in large concentrations, make the migrants vulnerable to local predators. The body mass gained or maintained is considered to be the result of the trade-off between the risks of starvation and predation. Theoretically, heavier birds should be less adept at escaping predators, and experimental evidence showed that flight performance is impaired in heavier birds. During three migration seasons we searched pellets and prey remains taken by a pair of Barbary Falcons (Falco pelegrinoides). We discovered that many pellets contained rings from the ringing program in Eilat, Israel, and the overwhelming majority belonged to Little Stints (Calidris minuta). We checked if the body mass and length of the stopover as expressed by ringing status of the Little Stints in a particular migration season was related to the risk of predation by Barbary Falcons. We found the chance that a heavier bird would be predated was lower than that of a lighter individual, and that Stints retrapped during the same migration season were significantly more endangered by predation than those recorded only once.

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“…Raptor morphology has been shaped by many natural and sexual selection processes so that the morphometrics that best represent structural size may vary among sex and age classes (Ellegren 1992, DeLong andGessaman 2001) or across geographic areas (Castro and Myers 1990). Some morphometrics, such as culmen or tail length, may be affected by wear or seasonal growth, resulting in biased or imprecise size measures.…”

mentioning

confidence: 99%