Bioelectrical impedance analysis as a means of estimating total body water in grey seals

Bowen, W. D.; Beck, Carrie A.; Iverson, Sara J.

doi:10.1139/cjz-77-3-418

Cited by 19 publications

(21 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…BIA, though useful in some studies to predict TBW content in animals (e.g., grey seals, Bowen et al 1999;moose, Hundertmark and Schwartz 2002;skunks, Hwang et al 2005;bears, Farley and Robbins 1994;and raccoons, Pitt et al 2006), contributed very little to our ability to predict TBW in porcupines. We could predict TBW very well using body mass alone.…”

Section: Discussionmentioning

confidence: 96%

“…1 can be simplified to the following (Kushner 1992;Bowen et al 1999;van Marken Lichtenbelt 2001;Hwang et al 2005):…”

Section: Methodsmentioning

confidence: 99%

“…Not all of these methods are equally practical in field situations. BIA has been used extensively to measure body composition in humans (Lukaski et al 1985;Lukaski 1989;Kushner 1992;Islam et al 1999) and is becoming more common in use with wildlife (e.g., bears (Ursus arctos L., 1758, Ursus americanus Pallas, 1780, and Ursus maritimus Phipps, 1774) (Farley and Robbins 1994;Hilderbrand et al 1998), skunks (Hwang et al 2005), raccoons (Pitt et al 2006), moose (Alces alces (L., 1758)) (Hundertmark and Schwartz 2002), ringed seals (Phoca hispida) and harp seals (Phoca groenlandica) (Gales et al 1994), gray seals (Halichoerus grypus (Fabricius, 1791)) (Bowen et al 1999), red squirrels (Tamiasciurus hudsonicus (Erxleben, 1777)), yellow-bellied marmots, snowshoe hares (Lepus americanus Erxleben, 1777) (Wirsing et al 2002), and wombats (Lasiorhinus latifrons (Owen, 1845)) (Woolnough et al 1997). BIA has some advantages over other nondestructive methods in that it requires holding a subject for only as long as it takes to connect the subject to the BIA analyzer, is relatively inexpensive, makes use of a small and easily portable device, and can be used on animals across a wide range of sizes.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The value of bioelectrical impedance analysis vs. condition indices in predicting body fat stores in North American porcupines (Erethizon dorsatum)

2006

View full text Add to dashboard Cite

We developed a predictive model to estimate body fat stores in a population of North American porcupines, Erethizon dorsatum (L., 1758). We trapped porcupines in the autumn of 2004 and spring of 2005. After collecting morphometric measurements on each animal, we used a plethysmograph to perform bioelectrical impedance analysis (BIA). We euthanized the subjects, measured two components of body composition (body fat, body water) via direct chemical analysis, and calculated lean dry mass to compare with BIA data. With regression we found the best predictive models for total body water, total body fat, percent body fat, and lean dry mass. We also estimated body condition for each animal using six different condition indices and compared the ability of the condition indices and our regression model to predict total body fat. Our model for total body fat accounted for 84% of the variation in fat measured by direct chemical analysis, and our model for percent body fat accounted for 78% of the variation. Two condition indices were significantly related to total body fat in porcupines and explained 45%-49% of the variation in observed body fat. We recommend BIA as a useful technique for estimating body fat stores in field studies of free-ranging porcupines and suggest abandonment of the use of condition indices as analogues of body fat stores in animal studies unless the indices can first be validated.Résumé : Nous avons mis au point un modèle prédictif pour estimer les réserves de graisses corporelles chez une population de porcs-épics nord-américains, Erethizon dorsatum (L., 1758). Nous avons attrapé les porcs-épics au piège à l'automne 2004 et au printemps 2005. Après avoir pris les mesures morphométriques de chaque animal, nous avons mesuré l'impédance bioélectrique à l'aide d'un pléthysmographe. Nous avons ensuite euthanasié les animaux, mesuré deux composantes de leur composition corporelle (graisses corporelles et contenu hydrique) par analyse chimique directe, calculé la masse sèche sans les graisses et comparé ces données à celles de la méthode de l'impédance bioélectrique (BIA). À l'aide de régressions, nous avons trouvé les meilleurs modèles prédictifs du contenu hydrique corporel total, des graisses corporelles totales, du pourcentage de graisses corporelles et de la masse sèche sans les graisses. Nous avons aussi estimé la condition corporelle de chaque animal à l'aide de six coefficients différents de condition et comparé la capacité de prédic-tion du contenu corporel total de graisses de ces coefficients de condition et celle de notre modèle de régression. Notre modèle du contenu corporel total de graisses explique 84 % de la variation des graisses mesurées par analyse chimique directe et notre modèle du pourcentage corporel des graisses explique 78 % de la variation. Deux des coefficients de condition sont en corrélation directe avec les graisses corporelles totales chez les porcs-épics et ils expliquent 45 % -49 % de la variation dans les graisses corporelles observées. Nous recommandons la méthode BIA co...

show abstract

Section: Discussionmentioning

confidence: 96%

“…1 can be simplified to the following (Kushner 1992;Bowen et al 1999;van Marken Lichtenbelt 2001;Hwang et al 2005):…”

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The value of bioelectrical impedance analysis vs. condition indices in predicting body fat stores in North American porcupines (Erethizon dorsatum)

2006

View full text Add to dashboard Cite

show abstract

“…Seals were weighed to the nearest 0.5 kg on Salter spring balances suspended from an aluminum tripod and anesthetized using Telazol (equal parts of teletamine and zolazepam). Males and females received an average dose of 0.45 rng kg-' body mass and 0.90 mg kg-' body mass, respectively (Bowen et al 1999).…”

Section: Methodsmentioning

confidence: 99%

An Algorithm to Improve Geolocation Positions Using Sea Surface Temperature and Diving Depth

Beck

McMillan

Bowen

2002

Marine Mammal Science

View full text Add to dashboard Cite

The at‐sea movement of marine mammals is an important component of their foraging ecology, but has been difficult to study. Geolocation timed‐data recorders (GLTDRs) estimate positions using measured light level to calculate day length and local noon. It is well known that these location estimates are imprecise (mean error of > 1°). Satellite telemetry generally provides a more accurate, but also more expensive means of monitoring movement. We evaluated the accuracy and precision of geolocation positions by comparing these locations with satellite data from Service Argos for eight free‐ranging gray seals (Halichoerns grypus) equipped with both a satellite‐linked data recorder (SDR) and a GLTDR. Geolocation positions differed by 1,026.0 ± 292.28 km from the corresponding Argos locations. We developed an algorithm to correct geolocation positions by comparing surface water temperature (ST) and dive depth collected by GLTDRs with existing sea‐surface temperature and bathymetry databases. The corrected positions were significantly closer (P < 0.025) to the Argos locations of these seals (94.2 ± 8.22 km). The original geolocation positions would have led to incorrect conclusions about the use of space by gray seals; however, the corrected positions can be reliably used to study the large‐scale spatial distribution of individuals.

show abstract

“…Seals were anesthetized using Telazol (equal parts of tiletamine and zolazepam). Males and females received an average dose of 0.45 mg/kg body mass and 0.90 mg/kg body mass, respectively (Bowen et al 1999). To extend battery life and to reduce processing fees, some transmitters were programmed to transmit 8 h/d and, depending on the duty cycle, between 25% and 100% of days were sampled over a 3to S-mo period.…”

Section: Methodsmentioning

confidence: 99%

A Three‐stage Algorithm for Filtering Erroneous Argos Satellite Locations

Austin¹,

McMillan

Bowen

2003

Marine Mammal Science

103

View full text Add to dashboard Cite

Several methods have been used to identify erroneous animal locations based on Argos satellite data. Using 15,987 satellite locations for 37 gray seals (Haliockoerus grypus), we tested a three‐stage filtering algorithm designed to address shortcomings of other filters. In stage 1, for each location, four rates of travel were calculated—the rate to each of the two previous locations and the two subsequent locations. If all four rates exceeded 2 m/sec (95th percentile of our data), the location was removed (7.25% of total locations). Stage 2 incorporated the filtering algorithm developed by McConnell et al. (1992) resulting in the rejection of 22.75% of total locations based on reasonable assumptions of straight‐line travel. At stage 3, the remaining data were evaluated against a distance threshold, defined as the 99th percentile of realized distance traveled over a period of seven days. Locations exceeding this threshold‐were rejected (0.69% of total locations). Overall, the three‐stage filter eliminated fewer locations (30.7 ± 1.62%), than the stage 2 filter alone. Most standard locations were retained, but 85.7% of location class 0, 76.6% of A, and 41.9% of B were also retained. These location classes account for most of data routinely collected but not used.

show abstract

Bioelectrical impedance analysis as a means of estimating total body water in grey seals

Cited by 19 publications

References 18 publications

The value of bioelectrical impedance analysis vs. condition indices in predicting body fat stores in North American porcupines (Erethizon dorsatum)

The value of bioelectrical impedance analysis vs. condition indices in predicting body fat stores in North American porcupines (Erethizon dorsatum)

An Algorithm to Improve Geolocation Positions Using Sea Surface Temperature and Diving Depth

A Three‐stage Algorithm for Filtering Erroneous Argos Satellite Locations

Contact Info

Product

Resources

About