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Gewählte Doctoral Thesis:

Josef Schenkenfelder (2021): Dairy cow welfare in Austria – risk indicators and farmers’ motivation for improvement.
Doctoral Thesis - Institut für Nutztierwissenschaften (NUWI), BOKU-Universität für Bodenkultur, pp 132. UB BOKU obvsg FullText

Data Source: ZID Abstracts
The present thesis builds on the on-farm assessment of animal-based welfare outcome measures implemented by an Austrian dairy company. Based on a data-set of 1,221 herds, publication I identified welfare problems and associations with farm and management characteristics. Between-farm variability in herd prevalence was high, but median prevalence of severe problems was low. Positive and negative associations (generalized linear models) between outcome prevalence and the amount of milk delivered per cow, housing system and assessment period were observed. However, more pasture days and organic farming consistently showed beneficial associations. In paper II, 264 tethered and 392 loose-housed herds were allocated to target, caution and alert ranges based on recently published thresholds. Cumulative logistic regression models showed several associations between animal-, management- and resource-related exposure variables and the risk to exceed these limits but no principal risk indicator was identified. This indicates that specific factors should be considered when aiming to fall below thresholds. Such insight can be used in advising farmers, however, knowledge of underlying motivational constructs to improve welfare is essential. Publication III addressed this key role of farmers utilising Q methodology. From 34 dairy farmers, four distinct viewpoints regarding welfare improvement were identified and awareness of these differences enables advisors to tailor interventions. In conclusion, associations between welfare outcomes and risk indicators seem to be promising starting points to improve livestock welfare, if knowledge is conveyed effectively. Still, further research is suggested to investigate the validity of the identified risk indicators and to enable a more efficient mapping of farmers according to the identified typologies.

Betreuer: Winckler Christoph
1. Berater: Kantelhardt Jochen
2. Berater: Leeb Christine

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