This special feature explored the evolving relationship between humans and brown bears in Hokkaido, Japan, considering shifting wildlife management policies and global biodiversity conservation efforts. Drawing on discussions from symposia held in 2023 and 2025, the collection of articles traced the historical phases of the human-bear relationship—from reverence and utilization (HBR ver.0), to extermination (HBR ver.1), protection and population recovery (HBR ver.2), and the current call for coexistence through mutual vigilance between humans and bears (HBR ver.3). As bears reduce their fear of humans, conflicts such as agricultural damage and human injuries have increased, highlighting the need for new management strategies. A distinctive aspect of Hokkaido’s strategy is categorizing bears as either nuisance or non-nuisance, based on traditional Ainu knowledge. This categorization is made possible through the long-term monitoring of the number of nuisance bears. This approach represents a form of active adaptive management that is rarely seen in large mammal conservation. The case of Hokkaido’s brown bears illustrates a broader global challenge—how a society facing population decline and wildlife recovery can sustainably coexist with large wildlife. This requires not only ethical reflection but also practical, science-based solutions.

We propose a unified method for formulating matrix population models in wildlife and fisheries management, adaptable to variations in population measurement timing and natural and human-induced mortality. For populations with a common and short breeding season, this approach applies to age-, size-, and stage-structured populations. The process is considered separately as three: survival, reproduction, and age increment or growth, with the respective matrices designated as S, B, and G. In the age-structured model, reproduction and age increment occurs simultaneously, and are expressed as a matrix model of S(BG) if the population census is taken immediately before the parturition, and (BG)S if it is taken immediately after the parturition. In the size- or stage-structured model, growth and survival proceed in parallel, and are expressed as a matrix model of (GS)B if the population census is taken just before the parturition, and B(GS) if it is taken just after the parturition. When the population census is taken at any other time, the survival rate from the parturition to the census and the survival rate from the census to the parturition can be considered separately. Furthermore, even when capture mortality is given as the number of individuals rather than a rate, a unified formulation by capture time is possible by expressing the number of captures as a vector.

COVID-19, caused by the novel coronavirus (SARS-CoV-2), is an emerging infectious disease (EID) with a relatively high infectivity and mortality rate. During the state of emergency announced by the Japanese government in the spring of 2020, citizens were requested to stay home, the number of infected people was drastically reduced without a legally-binding lockdown. It is well-acknowledged that there is a trade-off between maintaining economic activity and preventing the spread of infectious diseases. We aimed to reduce the total loss caused by the epidemic of an EID like COVID-19 in the present study. We focused on early and late stages of the epidemic and proposed a framework to reduce the total loss resulted from the damage by infection and the cost for the countermeasure. Mathematical epidemic models were used to estimate the effect of interventions on the number of deaths by infection. The total loss was converted into the monetary base and different policies were compared. In the early stage, we calculated the damage by infection when behavioral restrictions were implemented. The favorable intensity of the intervention depended on the basic reproduction number, infection fatality rate, and the economic impact. In the late stage, we calculated indicators and showed it depended on the ratio of the cost to maintain the hospitalization system to the monetary loss per deaths by infection which strategies should be adopted.