Managing social dynamics to improve dairy cow health and welfare
Lead Research Organisation:
University of Cambridge
Department Name: Veterinary Medicine
Abstract
Modern dairy cattle production systems involve frequent regrouping of cows based on lactation stage, milk yield and parity. However, regrouping doubles the rate of intra-group aggression leading to 10% decreases in feed intake and rumination time resulting in reductions in milk yield of up to 9%. Regrouping also reduces lying time by 14% leading to a significantly increased risk of lameness.
Increasing the stability of cow social groups reduces aggression but factors that promote social stability in cattle groups are poorly understood. Social Network Analysis (SNA) allows the structure and patterns of groups to be quantified to define the place and role of individuals within differing group structures to explain how group dynamics operate and are influenced by factors linked to individual attributes.
Preliminary studies have shown that a small number of 'key cows' are particularly influential in the organisation of group social structure and have a disproportionate influence in maintaining group stability particularly after regrouping. Although not studied to date in cattle, keystone individuals in other species can be characterised by factors such as dominance status and temperament.
More precise definition of characteristics and roles of keystone individuals occupying network positions that maintain stability is critically important in the dairy industry in order to manage the significant negative effects of dynamic grouping on cattle welfare and productivity.
The student will achieve this by quantifying cow interactions, social preferences and network positions using direct observation which they will validate by behavioural recording. They will use SNA of interaction data to quantify network structures before and after regrouping and define the characteristics of keystone individuals that promote network stability using validated cattle temperament tests.
Combining SNA data and individual temperament profiles will identify characteristics of keystone individuals who promote network stability. Manipulation of group composition based on network roles of individuals with particular temperaments will allow management optimisation to promote group stability thereby minimising the stress factors known to detrimentally influence dairy cow health, welfare and productivity.
Increasing the stability of cow social groups reduces aggression but factors that promote social stability in cattle groups are poorly understood. Social Network Analysis (SNA) allows the structure and patterns of groups to be quantified to define the place and role of individuals within differing group structures to explain how group dynamics operate and are influenced by factors linked to individual attributes.
Preliminary studies have shown that a small number of 'key cows' are particularly influential in the organisation of group social structure and have a disproportionate influence in maintaining group stability particularly after regrouping. Although not studied to date in cattle, keystone individuals in other species can be characterised by factors such as dominance status and temperament.
More precise definition of characteristics and roles of keystone individuals occupying network positions that maintain stability is critically important in the dairy industry in order to manage the significant negative effects of dynamic grouping on cattle welfare and productivity.
The student will achieve this by quantifying cow interactions, social preferences and network positions using direct observation which they will validate by behavioural recording. They will use SNA of interaction data to quantify network structures before and after regrouping and define the characteristics of keystone individuals that promote network stability using validated cattle temperament tests.
Combining SNA data and individual temperament profiles will identify characteristics of keystone individuals who promote network stability. Manipulation of group composition based on network roles of individuals with particular temperaments will allow management optimisation to promote group stability thereby minimising the stress factors known to detrimentally influence dairy cow health, welfare and productivity.
Organisations
People |
ORCID iD |
| Gareth Pearce (Primary Supervisor) | |
| Nicholas Britten (Student) |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| BB/M011194/1 | 01/10/2015 | 31/03/2024 | |||
| 2306451 | Studentship | BB/M011194/1 | 01/10/2018 | 30/09/2022 | Nicholas Britten |
| Description | Personality in dairy cattle can be measured effectively using a series of behavioural tests and a statistical method to combine the results into behavioural traits. The outcomes of this testing can be used to predict fertility, infections, lameness and milk yield. Physiological markers, specifically heart rate and eye temperature, align with the results of the behavioural testing and can also be used to predict health and production outcomes. |
| Exploitation Route | Dairy producers could easily and reasonably cheaply use infra-red thermography to measure eye temperature and so predict disease risk and likely production in their cattle. Animals identified as being at high risk could then be assigned additional management resources to prevent disease and improve health and welfare. |
| Sectors | Agriculture, Food and Drink |