Development and Evaluation of a Dynamic Simulation Model of Reproductive Performance in Pasture Based Suckler Beef Systems

The reproductive performance of a beef cow herd is largely a factor of efficient animal management strategies and genetics. The complex and cumulative nature of individual management decisions on a farm system's performance over multiple years mean that robust evaluation is time consuming and costly. A dynamic deterministic simulation model (Grange Reproductive Management Model; GReMM) with the capacity to replicate herd inventory dynamics over multiple reproductive cycles was developed using the Stella Architect dynamic modelling platform. The model is representative of a pasture-based spring calving suckled beef cow herd and is initialised by specifying individual farm parameters with respect to reproductive management, such as the breeding season duration, nutrition and management of the cow and calf postpartum. The focus was on the key factors which affect the duration of the postpartum anoestrus interval (PPAI); body condition score of the cow at calving (BCSc), postpartum nutrition (PPN), access of the suckling calf to the dam and, exposure of the dam to a fertile male. Model output was displayed in the form of a shift in calving distribution, the number of calves produced per cow bred per year and, percentage of cows culled due to barrenness. Three management scenarios were investigated to represent a herd implementing current industry best practice (BASE), a herd implementing intensive levels of reproductive management (Intensive reproductive management; IRM) and a herd implementing poor levels of reproductive management (Poor reproductive management; PRM). When evaluated in terms of calving distribution over six production cycles, both PRM and IRM showed a shift in the calving spread with a higher proportion of animals calving earlier and later, respectively, in the calving season compared to the BASE. This resulted in a 5% increase and a 14% decrease in six-week calving rates relative to BASE by year six, for IRM and PRM, respectively. Correspondingly, culling rates due to barrenness reduced by 0.9% and increased by 3.3% relative to BASE for IRM and PRM, respectively. The model developed offers a realistic and intuitive dynamic simulation model capable of investigating practical on-farm management decisions on herd reproductive performance.