Abstract

For elusive species living in concealing habitats (e.g. deer in a forest habitat), indirect methods such as faecal pellet counts are considered more practical means of estimating population density and abundance. Accurate estimation of deer density using the faecal standing crop (FSC) method necessitates the reliable estimation of the mean time to decay of pellet groups present during the survey. Mean time to decay is generally habitat specific, and separate estimations should be made for each habitat type in the study area. In a confined mountainous area of Greece, the habitat-specific mean time to decay of roe deer pellet groups was estimated by locating and marking fresh pellet groups on several dates in the lead up to an FSC survey and returning to the marked signs at the time of the survey to record whether or not each pellet group had survived. Several logistic models were fitted to the data, and estimations were based on a multi-model inference (MMI) approach according to information theory. The highest mean time to decay was estimated in coniferous forests, while mid-ranged values were found in maquis shrubs, and the lowest mean time to decay was observed in open areas. MMI by model averaging, based on Akaike weights, is recommended for making robust parameter estimations and for dealing with uncertainty in model selection.

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