Keita Fukasawa’s research while affiliated with National Institute for Environmental Studies and other places

Background There is an urgent need to develop global observation networks to quantify biodiversity trends for evaluating achievements of targets of Kunming-Montreal Global Biodiversity Framework. Camera traps are a commonly used tool, with the potential to enhance global observation networks for monitoring wildlife population trends and has the capacity to constitute global observation networks by applying a unified sampling protocol. The Snapshot protocol is simple and easy for camera trapping which is applied in North America and Europe. However, there is no regional camera-trap network with the Snapshot protocol in Asia. New information We present the first dataset from a collaborative camera-trap survey using the Snapshot protocol in Japan conducted in 2023. We collected data at 90 locations across nine arrays for a total of 6162 trap-nights of survey effort. The total number of sequences with mammals and birds was 7967, including 20 mammal species and 23 avian species. Apart from humans, wild boar, sika deer and rodents were the most commonly observed taxa on the camera traps, covering 57.9% of all the animal individuals. We provide the dataset with a standard format of Wildlife Insights, but also with Camtrap DP 1.0 format. Our dataset can be used for a part of the global dataset for comparing relative abundances of wildlife and for a baseline of wildlife population trends in Japan. It can also used for training machine-learning models for automatic species identifications.

Spatial capture–recapture models (SCRs) provide an integrative statistical tool for analyzing animal movement and population patterns. Although incorporating home range formation with a theoretical basis of animal movement into SCRs can improve the prediction of animal space use in a heterogeneous landscape, this approach is challenging owing to the sparseness of recapture events. In this study, we developed an advection–diffusion capture–recapture model (ADCR), which is an extension of SCRs incorporating home range formation with advection–diffusion formalism, providing a new framework to estimate population density and landscape permeability. we tested the unbiasedness of the estimator using simulated capture–recapture data generated by a step selection function. We also compared the accuracy of population density estimates and home range shapes with those from SCR incorporating the least‐cost path and basic SCR. In addition, ADCR was applied to a real dataset of Asiatic black bear (Ursus thibetanus) in Japan to demonstrate the capacity of the ADCR to detect geographical barriers that constrain animal movements. Population density and permeability of ADCR were substantially unbiased for simulated datasets. ADCR could detect environmental signals on connectivity more sensitively and could estimate population density, home range shapes, and size variations better than the existing models. For the application to the bear dataset, ADCR could detect the effect of water bodies as a barrier to movement, which is consistent with previous studies, whereas estimates by SCR with the least‐cost path were difficult to interpret. ADCR provides unique opportunities to elucidate both individual‐ and population‐level ecological processes from capture–recapture data. By offering a formal link with step selection functions to estimate animal movement, it is suitable for simultaneously modeling capture–recapture data and animal movement data. This study provides a basis for studies of the interplay between animal movement processes and population patterns.

Infectious diseases of wildlife cause human health hazards and economic losses. However, it is unclear how outbreaks affect human behaviour in relation to countermeasures against human–wildlife conflict. To explore the effects of infectious disease outbreaks among wild boars on countermeasure choices, we analysed online auction data before and after an outbreak of classical swine fever in wild boar. Online sales of boar traps decreased by 17 % after the outbreak, whereas sales of control items increased by 73 %. These results imply that infectious disease outbreaks in wildlife shift people's countermeasures from active to passive management. Since active trapping for the control of wildlife populations is essential to the avoidance of human–wildlife conflict, our findings show that outbreaks of infectious disease can aggravate conflict. Governments, farmers and hunters need to improve population control after outbreaks of infectious disease.

Elucidating biodiversity patterns and their background processes is critical in biodiversity science. Dissimilarity, which is calculated based on multivariate biological quantities, is a major component of biodiversity. As spatial and temporal biodiversity information availability increases, the scope of dissimilarity studies has been expanded to cover various levels and types of spatiotemporal biodiversity facets (e.g. gene, community and ecosystem function), and diverse pairwise dissimilarity indices have been developed. However, further development of the dissimilarity concept is required in comparative studies on spatiotemporal structures of biodiversity compositional patterns, such as those exploring commonalities of biogeographical boundaries among taxa, compared to the conventional ones to consider higher dimensions of dissimilarity: dissimilarity of dissimilarity structures. This study proposes a novel and general concept, higher‐order dissimilarity (HOD), for quantitatively evaluating the dissimilarities of spatial or temporal dissimilarity structures among different datasets, proposes specific implementations of HOD as operational indices, and illustrates the potential resolution of scientific and practical questions through HOD. We further demonstrate the advantages of the HOD concept by applying it to actual patterns, such as long‐term and/or large‐spatial hypothetical monitoring datasets. Our conceptual framework on HOD extends the existing framework of biodiversity science and is versatile, with many potential applications in acquiring more valuable information from ever‐increasing biodiversity data.

Whereas undetected species contribute to estimation of species diversity, undetected alleles have not been used to estimated genetic diversity. Although random sampling guarantees unbiased estimation of allele frequency and genetic diversity measures, using undetected alleles may provide biased but more precise estimators useful for conservation. We newly devised kernel density estimation (KDE) for allele frequency including undetected alleles and tested it in estimation of allele frequency and nucleotide diversity using population generated by coalescent simulation as well as well as real population data. Contrary to expectations, nucleotide diversity estimated by KDE had worse bias and accuracy. Allele frequency estimated by KDE was also worse except when the sample size was small. These might be due to finity of population and/or the curse of dimensionality. In conclusion, KDE of allele frequency does not contribute to genetic diversity estimation.

Ecotourism is often viewed as a mutually beneficial solution for both people and nature; however, unregulated wildlife tourism can inadvertently harm the wildlife. To enhance management practices, we conducted a study on rabbit tourism involving Amami rabbits (Pentalagus furnessi) which can be sighted by car driving at a Natural World Heritage Site in Japan. Because the sighting rate of wildlife under different car schedules and in varying density scenarios remains unknown, our study employed wildlife disturbance experiments and model simulation to estimate the recovery rate of rabbits after being flushed by tourists in different density and car schedule scenarios. Our analysis revealed that implementing a 20-minute time lag for the following car resulted in a 90% recovery rate for Amami rabbits. Additionally, adhering to a regular car schedule provided an increase in sighting rates of the rabbit compared to random and normal schedules by approximately 1.85 and 2.4 times, respectively, under optimal conditions (maximum density and 50 cars). Finally, we evaluated the profitability of the tourism industry under different densities of rabbits and rates of the money-back guarantee. Though introducing more cars appears to generate greater profits, it may simultaneously lead to a decrease in the rabbit sighting rate and an increased likelihood of activating the money-back guarantee. In conclusion, our findings clearly showed that considering both animal behavior in response to humans and human interest (i.e., MBG) in developing a tourism management system can achieve a simultaneous resolution of profitability and reduction in the impact of overutilization.