{"created":"2023-07-25T09:59:02.531269+00:00","id":1769,"links":{},"metadata":{"_buckets":{"deposit":"d5669f13-ecf3-4357-b286-b8709280e055"},"_deposit":{"created_by":4,"id":"1769","owners":[4],"pid":{"revision_id":0,"type":"depid","value":"1769"},"status":"published"},"_oai":{"id":"oai:nfu.repo.nii.ac.jp:00001769","sets":["3:137"]},"author_link":["3668","3666"],"item_1_alternative_title_5":{"attribute_name":"論文名よみ","attribute_value_mlt":[{"subitem_alternative_title":"カイソウ　ベイズホウ　ニ　ヨル　クマルイ　セイソク　コタイスウ　スイテイ　ニ　ツイテ　ノ　ケントウ"}]},"item_1_biblio_info_14":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2014-09-30","bibliographicIssueDateType":"Issued"},"bibliographicPageEnd":"43","bibliographicPageStart":"15","bibliographicVolumeNumber":"130","bibliographic_titles":[{"bibliographic_title":"現代と文化 : 日本福祉大学研究紀要"},{"bibliographic_title":"Journal of culture in our time","bibliographic_titleLang":"en"}]}]},"item_1_creator_6":{"attribute_name":"著者名(日)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"山上, 俊彦"},{"creatorName":"ヤマガミ, トシヒコ","creatorNameLang":"ja-Kana"}],"nameIdentifiers":[{"nameIdentifier":"3666","nameIdentifierScheme":"WEKO"}]}]},"item_1_creator_8":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Yamagami, Toshihiko","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"3668","nameIdentifierScheme":"WEKO"}]}]},"item_1_description_11":{"attribute_name":"抄録(日)","attribute_value_mlt":[{"subitem_description":"階層ベイズ法は．複雑かつ不確実な体系をモデル化できることから近年，野生動物の生息個体数推定に用いられているところである．本論は階層ベイズ法を用いたクマ類生息個体数推定についての既存研究の内容について検討を行ったものである．その結果，捕獲数を生息密度の代理変数とした場合，循環変動と構造変動の識別や異常値の処理が困難であり，個体数が発散傾向を辿る可能性があること，捕獲数が個体数を決定するという因果関係の想定が過大推定につながる可能性が判明した．推定が精度の高いものとなるためには，モデルが依拠する理論の前提条件を満たすとともに，変数間の相互依存関係や因果関係を検証することが必要である．モデルの構築に際しては，環境変動や生息密度の上限等の外的要因や制約条件に対する野生動物の行動変化ついての洞察が求められる．適切な個体数指標を開発した上で，動態的な構造モデルを用いた変数間の整合性の検証やフィールド調査結果の活用等，他の調査との相互補完的活用が必要である．","subitem_description_type":"Other"}]},"item_1_source_id_13":{"attribute_name":"雑誌書誌ID","attribute_value_mlt":[{"subitem_source_identifier":"AA11400593","subitem_source_identifier_type":"NCID"}]},"item_1_text_2":{"attribute_name":"記事種別(日)","attribute_value_mlt":[{"subitem_text_value":"論文"}]},"item_1_text_3":{"attribute_name":"記事種別(英)","attribute_value_mlt":[{"subitem_text_language":"en","subitem_text_value":"Article"}]},"item_1_text_9":{"attribute_name":"著者所属(日)","attribute_value_mlt":[{"subitem_text_value":"日本福祉大学経済学部"}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2014-09-30"}],"displaytype":"detail","filename":"gendai130-04yamagami.pdf","filesize":[{"value":"1.2 MB"}],"format":"application/pdf","licensetype":"license_11","mimetype":"application/pdf","url":{"label":"gendai130-04yamagami","url":"https://nfu.repo.nii.ac.jp/record/1769/files/gendai130-04yamagami.pdf"},"version_id":"75d017d7-9434-4662-a977-8d40e6a003ef"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"標識再捕獲法，捕獲率，自然増加率，因果関係，構造変動，構造モデル，安定状態","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"departmental bulletin paper","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"階層ベイズ法によるクマ類生息個体数推定についての検討","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"階層ベイズ法によるクマ類生息個体数推定についての検討"},{"subitem_title":"Critiques of the Estimates of Population Size of Bear Based on Hierarchical Bayesian Method","subitem_title_language":"en"}]},"item_type_id":"1","owner":"4","path":["137"],"pubdate":{"attribute_name":"公開日","attribute_value":"2014-09-30"},"publish_date":"2014-09-30","publish_status":"0","recid":"1769","relation_version_is_last":true,"title":["階層ベイズ法によるクマ類生息個体数推定についての検討"],"weko_creator_id":"4","weko_shared_id":4},"updated":"2023-07-25T10:45:18.383835+00:00"}