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Skip to Search Results- 5Derocher, Andrew E.
- 4Lewis, Mark A.
- 2Auger-Méthé, Marie
- 2Klanjscek, Tin
- 2Molnár, Péter K.
- 1Albertsen, Christopher M.
- 2Ursus maritimus
- 1Animal Movement Paths
- 1Arctic
- 1Bioelectrical impedance analysis
- 1Body condition index
- 1Body fat
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A body composition model to estimate mammalian energy stores and metabolic rates from body mass and body length, with application to polar bears
Download2009-01-01
Derocher, Andrew E., Klanjscek, Tin, Molnár, Péter K., Lewis, Mark A., Obbard, Martyn E.
Many species experience large fluctuations in food availability and depend on energy from fat and protein stores for survival, reproduction and growth. Body condition and, more specifically, energy stores thus constitute key variables in the life history of many species. Several indices exist to...
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2011-01-01
Molnár, Péter K., Derocher, Andrew E., Klanjscek, Tin, Lewis, Mark A.
Predicting the ecological impacts of climate warming is critical for species conservation. Incorporating future warming into population models, however, is challenging because reproduction and survival cannot be measured for yet unobserved environmental conditions. In this study, we use...
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2004
Derocher, Andrew E., Skaare, Janneche U., Jenssen, Bjørn Munro, Sørmo, Eugen G., Lie, Elisabeth, Braathen, Marte, Wiig, Øystein
We studied the relationships between polychlorinated biphenyls (PCBs) and thyroid hormones (THs) and retinol within two groups of female polar bears (Ursus maritimus), females with cubs of the year (FWCOY) and females without cubs of the year (FWOCOY), and within a group of males. Concentrations...
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State-space models' dirty little secrets: Even simple linear Gaussian models can have parameter and state estimation problems
Download2016-01-01
Auger-Méthé, Marie, Field, Chris, Albertsen, Christopher M., Derocher, Andrew E., Lewis, Mark A., Jonsen, Ian D., Mills Flemming, Joanna
State-space models (SSMs) are increasingly used in ecology to model time-series such as animal movement paths and population dynamics. This type of hierarchical model is often structured to account for two levels of variability: biological stochasticity and measurement error. SSMs are flexible....