Literature DB >> 19327855

Modelling the demographics of the Irish cattle population.

J O'Connor1, S J More, J M Griffin, E O'Leary.   

Abstract

In recent years, national authorities have committed very substantial resources to the creation and maintenance of databases capable of recording important animal event data, such as births, deaths and movements. This has primarily been driven by the need to ensure the quality and safety of animal products. However, it can also be used to assist policy makers in decision making. Despite the abundance of animal event data, as yet there is little published information about the use of these data to better understand the demography of cattle populations. This study reports the development of, and outputs from, a demographic model using data routinely collected from the Irish cattle population. The demographic model was based on a series of life tables detailing age-specific probabilities of survival up to a maximum of 17 years. These outputs were used to determine characteristics of the Irish cattle population, including estimated mortality rates, life expectancies and age profiles, and estimated cattle numbers by age and date. Separate life tables were developed for each of the 204 monthly birth cohorts born between January 1989 and December 2005. Within the Irish cattle population, the peak estimated mortality rate occurs at 29-33 months. The estimated life expectancy at birth of cattle in Ireland was 42 months. When the survival rates for all the cohorts within a population are calculated, then it is possible to use these rates as a model for determining future population size and answering cohort specific queries.

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Year:  2009        PMID: 19327855     DOI: 10.1016/j.prevetmed.2009.02.011

Source DB:  PubMed          Journal:  Prev Vet Med        ISSN: 0167-5877            Impact factor:   2.670


  1 in total

1.  Demographic model of the Swiss cattle population for the years 2009-2011 stratified by gender, age and production type.

Authors:  Sara Schärrer; Patrick Presi; Jan Hattendorf; Nakul Chitnis; Martin Reist; Jakob Zinsstag
Journal:  PLoS One       Date:  2014-10-13       Impact factor: 3.240

  1 in total

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