Ecological physiology of macropod marsupials

Sylvie Schmidt

    Research output: ThesisDoctoral Thesis

    262 Downloads (Pure)


    [Truncated abstract] There are phylogenetic, dietary, geographic and climatic effects on various standard physiological variables for placental mammals, but a 2006 study by Withers, Cooper & Larcombe found only limited phylogenetic and environmental effects for marsupials. Surprisingly, evaporative water loss (EWL) was only correlated with rainfall variability but not with aridity or other climate, lifestyle or environmental variables. This may have reflected the small data base and/or methodological problems, which made the data variable and may have masked any adaptive significance. Macropods are an interesting group of marsupials to examine environmental correlates of physiological variables as they have a continent-wide distribution spanning massive variation in climate, a broad mass range, and complex phylogenetic affiliations. Despite representing approximately 20 % of extant marsupials globally, and roughly one third of extant Australian species, they are underrepresented within the current data sets for standard physiological variables, for many species virtually nothing is known. The general aims of this thesis were to 1) develop a protocol to measure standardised physiological parameters in macropods, 2) extend the current data base for macropods (and consequently for marsupials) by measuring species with a range of body masses, phylogenetic affiliations and ecological backgrounds, and 3) examine these data for environmental correlates after correcting for allometric and phylogenetic effects. I used the tammar wallaby (Macropus eugenii) to investigate the effects of different fasting times (tf; Chapter 2), water deprivation (Chapter 3) and relative humidity (RH; Chapter 4) on standard physiological variables. A tf of 22 hrs was sufficient to ensure postabsorptivity and a meta-analysis of literature data indicated that the required tf to measure true basal metabolic rate (BMR) can only be predicted from mean retention time if strict criteria are
    Original languageEnglish
    QualificationDoctor of Philosophy
    Publication statusUnpublished - 2011


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