Polar bear is one of the most representative species in the polar ecosystem, and its survival status is an important indicator of environmental change. To better understand and protect the species, scientists have adopted a model approach, using computer simulations and statistical analysis to delve into polar bear behavior, ecology and population dynamics.

First, the model can help researchers analyze the relationship between polar bears' habitat and prey. Polar bears use sea ice as their habitat to hunt seals, their main food source. By building mathematical models, scientists were able to simulate the effects of changes in sea ice on polar bear hunting. For example, as global temperatures rise and sea ice melts faster, fewer hunting areas make it harder for polar bears to find food. This model can predict the change of polar bear population under different scenarios and provide data support for the development of conservation measures.

In addition, the model can be used to study the physiological and behavioral characteristics of polar bears. By combining a variety of data, scientists were able to model polar bears' energy expenditure and reproductive patterns at different temperatures and food availability. These simulation results provide a theoretical basis for assessing the adaptive ability and survival strategies of polar bears. For example, polar bears may adjust hunting strategies when food is scarce, or delay mating during the breeding season, changes in behavior that could help the population better cope with environmental stress.

Based on these studies, the model can also help assess the potential impact of human activities on the survival of polar bears. For example, noise and pollution from oil exploration and shipping, as well as habitat destruction due to climate change, are challenges that polar bears must face.