[in Japanese]

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Biodiversity map can be a powerful tool for consensus-building among various stakeholders such as government, business, scientists, and the public. Today, more and more people can collect, manage, and analyze spatial data easily with open source GIS software and free WebGIS services. However, wildlife distribution data at the national scale are still not sufficient. We used the biodiversity mapping by the Ministry of the Environment published in 2012 to illustrate the major issues in collecting wildlife data in the future. First issue is location accuracy. Many distribution data especially old ones are recorded in various different formats. Additionally, many endangered species distribution data are not open to public for conservation reasons. Second issue is accuracy of species identification. The identification of endangered species is difficult for non-experts, and taxonomical classifications change rather frequently. Third issue is data update. Many science museums now have difficulties in continuing specimen collection activities, and the government is also reducing the budget for national research on wildlife distribution. Forth issue is data bias. Although essential for biodiversity mapping, spatial analyses of data from wide range of different sources such as museum specimens, wildlife hunting records, and environmental impact assessments faces limitation, due to different objectives of data collections and varying data accuracy. To cope with such issues, we need a standardized platform for the collection of wildlife distribution data and predictive model to complement field-data gaps.

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To be effective in biodiversity conservation, spatial conservation planning should consider the complementarity among planning units. Complementarity is one of the central concepts in spatial conservation prioritization, and complementarity analysis based on the concept is becoming a major method both in research and in practice dealing with spatial problems in conservation planning. Marxan is the most popular tool to implement the complementarity analysis that can give us the most efficient solutions, a set of prioritized areas, based on conservation features, their spatial distributions and conservation target set to each of them. Efficiency here is defined as a function of size, shape and arrangement of prioritized areas, and conservation cost of selected planning units, and degree to which each of conservation targets has been attained. Recently, complementarity analysis using Marxan was applied to a nation-wide biodiversity mapping project for the first time in Japan. Specifically, it was used to identify the set of candidate areas for the efficient conservation of endangered vascular plants in the county. The number of applications of complementarity analysis to conservation practices is expected to grow rapidly at every taxa and spatial scales from national to local. Practitioners, however, must always keep in mind that results and effectiveness of the analysis can be very sensitive to uncertainty in available information on spatial distribution of conservation features and to adequacy of conservation actions taken in the selected planning units.

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Appropriate wildlife management is important in order to resolve human-wildlife conflicts. The objective of this study is to clarify the relationship between animal distribution and landscape information. In particular, we evaluated the effect of spatial scale (extent and grain size) in predicting animal distribution. Our target species are Asiatic black bear (Ursus thibetanus), Japanese macaques (Macaca fuscata), and wild boar (Sus scrofa). Honshu (the mainland of Japan) and Niigata Prefecture were defined for two types of spatial extent. Furthermore we detected landscape information from 30 m and 500 m-spatial resolutions for grain size in Niigata Prefecture. Logistic regression analysis was applied for predicting animal distributions. Extent influenced the contribution of selected ecological indicators for animal distribution. For the prediction of Asiatic black bear's distribution, agricultural area, conifer forest, broad-leaved forest and snowy area were preferred predictors at the spatial scale of Honshu. At the spatial scale of Niigata Prefecture, however, agricultural area was avoided, while conifer forest and snowy area were preferred predictors. For the prediction of Japanese macaque's distribution, agricultural area, conifer forest, broad-leaved forest and water area were preferred, while snowy area was avoided at the Honshu scale. However, agricultural area was avoided, while conifer forest and snowy area were preferred at the scale of Niigata Prefecture. For the prediction of wild boar's distribution, agricultural area, urban area, conifer forest, broad-leaved forest and water area were preferred, while snowy area was avoided at the Honshu scale. At the Niigata Prefecture scale, however, only high snow depth area was preferred predictor. Predictions of the distribution of Asiatic black bear at both Honshu scale and Niigata scale were very accurate. Predicting the distribution of Japanese macaques at the Honshu scale had slightly lower accuracy. Predicting the distribution of wild boar at the Honshu scale was reasonable, but that result at the Niigata scale was poor. Effects of grain size in the prediction of animal distribution were not clear. We suggest that the influence of extent in the prediction of animal distribution is important.

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We examined the relationships between the distribution of an endangered cherry species, Cerasus tamaclivorum, and Tama new-town (NT) development on the Tama Hills. In total, 177 individuals were found in 27 sites in Hachioji city, Machida city and Tama city. Of these, 81.9% were found in urban parks and urban green areas in the NT area, and 17.5% were found in an area secondary forest (Kataso-yato), surrounding NT. In NT, all of these habitats had been developed by the Tokyo Metropolitan government, but their management was transferred to the current owners including city government. Our tree-ring analysis suggests that large individuals of the species were seedlings or saplings when the development of NT started in 1980's. We also found that the managers have recognized some individuals as "Yamazakura" (Cerasus jamasakura (Siebold ex Koidz.) H.Ohba). This circumstance, confirmed by documents on NT development by the Tokyo Metropolitan government suggests that the secondary forests like Kataso-yato might be an original habitat and sources of the transplanted saplings to NT area. Therefore, Kataso-yato remains the original habitat of C. tamaclivorum, and planting of this species by the Tokyo Metropolitan government during NT development can be considered as the main factor cause of the present distribution. However, we also found that some populations of the species went extinct in a decade. Nevertheless, the population of sproutings has increased as a result of restarting the secondary forest management by volunteers in Kataso-yato. Appropriate management of secondary forest, such as by periodic logging and mowing, is important for the conservation and sustainable use of C. tamaclivorum.

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We investigated the population size structure of Glehnia littoralis at three beaches, Nishikinohama, Okadaura, and Satoumi-koen Park, in Osaka in 2008 and 2013. There was a correlation between leaf size and the number of seeds produced. Population Size structure was greater at Okadaura than at the other beaches. Therefore, it was estimated that the greatest seed production occurred at Okadaura. Okadaura is located in the Kashii river estuary, and it was believed that seeds could easily be carried to the offshore. We therefore consider that Okadaura is the most important source of seeds among the three beaches.

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