Mie and Nagoya Universities identify grazing strategies for reducing grassland degradation in arid Mongolia

A research group led by Associate Professor Yu Yoshihara and Rentaro Horie (a graduate student at the time of the study) from the Graduate School of Bioresources at Mie University, Professor Masato Shinoda and Lecturer Takafumi Miyasaka from the Graduate School of Environmental Studies at Nagoya University, and Research Associate Akito Kono from the Graduate School of Agricultural and Life Sciences at the University of Tokyo announced that they have identified the optimal grazing strategy in arid Mongolia. This approach takes into account both livestock production and grassland degradation. It was achieved through simulation using an agent-based model (ABM). Their findings were published in Scientific Reports.

Developing an optimal grazing strategy is essential for sustainable livestock production in spatially heterogeneous vegetation. An ABM is a computer simulation used in social sciences where each agent models specific behavioral characteristics, allowing for the examination of social states that emerge from their interactions.

In this study, the team applied ABM to the semi-arid steppe in Mongolia (Bayanunjuul village) as a model survey site. By spatially simulating livestock movement, the internal states of livestock influencing it (such as metabolic energy), and the external environment (such as plant biomass), they predicted the effects of various daily spatial grazing patterns of Mongolian livestock on intake energy during summer.

Sheep acted as the agents, and vegetation was represented as the environment. The environment (approximately 8×8 km) was divided into 976 grid cells. The plant parameters in each cell (such as species composition, biomass, nutrition value, and palatability) were measured.

The movement pattern of Mongolian sheep is either voluntary (free grazing) or controlled by herders. The voluntary movement pattern was determined by GPS-tracking the actual movement of sheep. For the herder-controlled movement of sheep, three types of grazing strategies were simulated in the model: moving sheep to neighboring cells with the maximum or relatively high values of (1) biomass, (2) palatability, and (3) nutrition of grass.

Furthermore, the effects were analyzed by varying the sheep stocking rate in three levels (0.5, 1, and 2 times) based on the actual number of livestock. The metabolizable energy of sheep was estimated by determining the plant biomass × metabolizable energy content of plant × palatability in each cell.

Resultingly, the metabolizable energy intake of the freely grazing sheep was found to be equivalent to or less than that of sheep controlled by herders. Notably, with the biomass-oriented grazing strategy, the grazing distribution was spatially dispersed even when the stocking rate doubled, and the metabolizable energy intake was also the highest. It demonstrated the best grazing strategy to maximize animal production while avoiding overgrazing in Mongolia is for herders to move their sheep to patches with the most abundant biomass.

Yoshihara commented: "The extensive field surveys, data analysis, and model construction required considerable effort, but I believe we have been able to present new options for grazing strategies in Mongolia. Going forward, we intend to collaborate with relevant stakeholders to apply scientific findings to grassland and livestock management. We also plan to further develop the model to extend its application to different vegetation zones and annual predictions."

Journal Information
Publication: Scientific Reports
Title: Predicting livestock intake energy at different grazing strategies using agent-based modelling of livestock
DOI: 10.1038/s41598-025-19816-8