To sustain frog populations, it is important to conserve favorable aquatic habitats. In Japan, rice paddies play an important role as breeding habitat for frog species; however, environmental changes and abandonment of rice paddies have led to declining frog populations. In this study, we conducted surveys at various aquatic habitats in a yatsuda area in the Sayama Hills to determine the characteristics of rice paddies under different management systems, and the breeding habitat preferences and favorable aquatic habitats for Japanese brown frog (Rana japonica) eggs. We found 134 egg masses at 14 study sites, and monitored them until they hatched, died, or were lost, and also recorded environmental factors, such as water temperature and depth. First, we conducted principal component analysis to determine the study site characteristics, and second, we constructed generalized additive mixed models to investigate the relationship between environmental factors and the number of new egg masses, hatching success rate, and number of days to hatch. Our results showed no clear pattern of how environmental factors changed after rice paddy abandonment, except for an increase in vegetation cover over rice paddies. Conversely, our results showed R. japonica breeding habitat preference and egg hatching success were related to various aspects of aquatic habitats. Our investigation revealed the preferred breeding habitat for R. japonica and provides key information for developing practical conservation measures regarding the overall management of rice paddies, such as irrigation and mowing, to sustain R. japonica populations in yatsuda areas.

Reintroduction is a crucial step in the conservation efforts aiming to restore ecosystems and protect threatened species. However, studies that incorporate and evaluate the effect of plant reintroduction are scarce. A study on a population of Cephalocereus polylophus, a vulnerable cactus endemic to the southern Chihuahuan Desert, allowed us to evaluate the effect of seedling reintroduction on the viability of this population. An integral projection model was used on a 5-year dataset to forecast population size over a century, and to simulate scenarios of seedling survival and protection. The study revealed an asymptotic population growth rate (λ) of 0.97 (95% CI = 0.96 – 0.99). Simulating the seedling survival and an increase in the seedling bank translated into a λ that showed only a slight increase, but remained below one, mainly because the recruitment and survival of small individuals were insufficient to compensate for the population decline. Protecting seedlings against herbivores and increasing their survival to 96.5% resulted in a larger population size (~ 5% average increase) and delayed extinction, in comparison with a no intervention and 60% survival rate scenario. This demonstrates that increasing seedling survival rates through protection and reintroduction efforts can only be conceived as a complementary conservation strategy to those focused on preserving existing individuals. Effective reintroduction strategies can help delay the extinction of the population of this cactus, but the conservation of the current population and its habitat is pivotal for its future survival.

This article reviews the essential role of mathematical models in understanding and combatting the pandemic of novel coronaviruses, in particular focusing the advance in the use of mathematical models in disease control in Japan. Highlighting the integral role of mathematical models in public health, the article introduces a model that factors in the heterogeneity of infectious contacts, concentrating on the effectiveness of testing and isolation, alongside a model that involves economic losses. The models exhibit how, given such heterogeneity, milder behavioral restrictions can still achieve suppression, rigorous testing and isolation can effectively curb the spread, and containment measures can mitigate economic losses. These models aid in grasping the complicated dynamics of disease transmission and optimizing interventions. The knowledge of population ecology is also considered effective for public health in statistical analysis, organizing concepts using dynamic mathematical models, which lead to policy proposals and deepen understanding. Evolution theory may help the understanding of virulence subject to change. However, effective prevention necessitates not only models but also the practical implementation of efficacious measures. The cooperation of various disciplines is particularly crucial in achieving a balance between health measures, economic interests, and human rights. Moreover, the article acknowledges the limitations of models and underscores the significance of real-world execution. Overall, the article advocates for a broader outlook to tackle future pandemics and related challenges, underscoring the importance of ongoing academic cooperation and global governance to effectively address emerging infectious diseases and their far-reaching implications.

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.

Between 1925 – 1929, approximately 12 non-native mountain goats (Oreamnos americanus) were translocated from Alaska and British Columbia to the foothills of the Olympic Range, USA. By 1970, descendants of these goats had colonized the entire Olympic Range and concerns about the management of this introduced species developed as damage to alpine soil and vegetation occurred. A series of removals reduced the population from 1,175 in 1983 to 389 goats by 1990, followed by a period a stasis and growth indicated again in 2011 and 2016. We used empirical demographic and genetic data to parameterize a population genetics individual-based simulation model of the Olympic Range mountain goat population. We calibrated the model to simulate the population trajectory for Olympic mountain goats from establishment in 1925 through the 1983 census, and validated model dynamics by simulating the period from 1990 to 2016. Modeled population dispersal closely tracked anecdotal reports. However, observed heterozygosity did not align with published research, suggesting a process not accounted for within the simulation model, such as a bottleneck, founder effect, or population trajectory dynamics. Sensitivity analyses showed that changes in annual reproductive rate had the greatest influence on population trajectories, followed by juvenile mortality and adult female mortality, respectively. The modeled population showed that approximately 80% of the total animals removed during the 1980’s needed to be female in order for the observed population stasis to occur. This model has the potential to be used more widely with established or introduced mountain goat populations in other regions.

Many ungulate species in Africa range in habitats that vary in type and quality over space and time, but ongoing environmental change is substantially altering their habitats. Identifying key environmental variables that regulate ungulate population densities can guide management actions for effective conservation. We studied the local population density responses of a community of sympatric ungulate species in the Tarangire Ecosystem of northern Tanzania, to a suite of environmental factors that vary over space and time, to quantify population trends, determine the primary environmental correlates of densities, and identify covariation in densities among species. We estimated seasonal densities of five commonly detected species (impala, dik-dik, Grant’s gazelle, eland, and waterbuck) based on 7 years of distance-sampling data from 41 replicate surveys of 237 line transects. We systematically analyzed the effects of spatial, seasonal, and annual environmental covariates on variation in transect species-specific densities across space and time. Despite large fluctuations in climatic factors, we documented more spatial than temporal variation in four of the five species, suggesting that spatial heterogeneity may provide some buffer against temporal variation in the environment. Protection of sufficient habitats and water sources should allow ungulates to respond to a temporally changing world by moving across space. Further, among-species covariation patterns identified two potential ungulate guilds (impala—dik-dik—waterbuck; eland—grant’s gazelle) that should aid in developing efficient and coordinated management actions.