Japan Geoscience Union Meeting 2016

Presentation information

International Session (Poster)

Symbol M (Multidisciplinary and Interdisciplinary) » M-GI General Geosciences, Information Geosciences & Simulations

[M-GI04] Open Research Data and Interoperable Science Infrastructures for Earth & Planetary Sciences

Mon. May 23, 2016 5:15 PM - 6:30 PM Poster Hall (International Exhibition Hall HALL6)

Convener:*Yasuhiro Murayama(Integrated Science Data System Research Laboratory, National Institute of Information and Communications Technology), Baptiste Cecconi(LESIA, Observatoire de Paris, CNRS, PSL Research University), Yasuhisa Kondo(Research Institute for Humanity and Nature), Reiichiro Ishii(Japan Agency of Marine-Earth Science and Technology), Daniel Crichon(Jet Propulsion Laboratory, National Aeronautics and Space Administration)

5:15 PM - 6:30 PM

[MGI04-P04] Data management for evaluating biodiversity and ecosystems conducted by GRENE-ei (Green Network of Excellence - environmental information)

*Osamu Kurashima1, Motomi Ito1, Nobuhito Ohte2, Nobuko Saigusa3, Tohru Nakashizuka4, Tsutomu Hiura5 (1.Department of General Systems Studies, Graduate School of Arts and Sciences, The University of Tokyo, 2.Department of Social Informatics, Graduate School of Informatics, Kyoto University, 3.Center for Global Environmental Research, National Institute for Environmental Studies, 4.Department of Environmental Life Sciences, Graduate School of Life Sciences, Tohoku University, 5.Field Science Center for Northern Biosphere, Hokkaido University)

Keywords:data management, biodiversity, ecosystem, interoperability, GRENE-ei, DIAS

The loss of biodiversity and its impact on ecosystem functions and services are the biggest environmental issues. It needs to assess present status of biodiversity and ecosystems to address these problems. In addition, many kinds of environmental information such as biodiversity, ecological, climatological and geographical data are required for developing indicators that are effective in assessing the conditions of biodiversity and ecosystems. However, most existing data are not comprehensively available because they are scattered among many various databases that are independent of each other. Therefore, our Green Network of Excellence - environmental information (GRENE-ei) project aimed to manage metadata about biodiversity and ecosystem information at the first. We connected existing metadata databases through cooperation with Japan Long Term Ecological Research Network (JaLTER) and Data Integration and Analysis System (DIAS). JaLTER Metacat (http://db.cger.nies.go.jp/JaLTER/) provides information such as location, availability and format of ecological observation data in Japan. We created the data element mappings between JaLTER and DIAS metadata formats and integrated JaLTER metadata catalogue into the search and discovery system for DIAS datasets (http://dias-dss.tkl.iis.u-tokyo.ac.jp/ddc/). The next step was accumulation of biodiversity and ecosystems data. We collected observational data from separate layers such as species distribution, community structure, ecosystem and flux. One of the main data sources at the species and community levels is the vegetation survey data conducted by The Ministry of the Environment, Japan. Using the output of this survey, the plant distribution database including 718,211 records with 4,683 species names was developed. The data format of this species occurrence database was compliant with the Darwin Core (http://rs.tdwg.org/dwc/) in order to maximize interoperability. The third step was the creation of spatial interpolated distribution datasets of species and community. We constructed the species distribution models (SDMs) of each plant both from the occurrence data mentioned above and environmental factors (such as climate, topography, geography and land cover data), and predicted the potential distributions of species suitable habitats in Japan. These interpolated datasets of plant species and community distribution would be an indispensable infrastructure for mapping the potential distribution of organisms that interact with plants, such as herbivore insects. Our main achievements, particularly interpolated datasets of plants, are preparing publication through DIAS data archives.