{"help": "https://pro.iepnb.gob.es/catalogo/api/3/action/help_show?name=package_show", "success": true, "result": {"access_rights": "http://inspire.ec.europa.eu/metadata-codelist/LimitationsOnPublicAccess/noLimitations", "alternate_identifier": "DOI: 10.1016/j.jenvman.2019.109320", "author": "Ascens\u00e3o, F., Yogui, D., Alves, M., Medici, E.P. y Desbiez, A.", "author_name": "Ascens\u00e3o, F., Yogui, D., Alves, M., Medici, E.P. y Desbiez, A.", "classification_variables": {"es": ""}, "conforms_to": ["https://www.boe.es/eli/es/res/2013/02/19/(4)"], "contact_email": "organismo@example.org", "contact_name": "Organismo publicador del Cat\u00e1logo", "contact_role": "http://inspire.ec.europa.eu/metadata-codelist/ResponsiblePartyRole/pointOfContact", "contact_uri": "http://datos.gob.es/recurso/sector-publico/org/Organismo/EA0000000", "contact_url": "https://organismo.example.org/", "created": "2025-05-23", "creator_user_id": "d24a314a-79ce-48c0-abd9-54cb42706da4", "dataset_scope": "non_spatial_dataset", "dcat_type": "http://purl.org/dc/dcmitype/Text", "encoding": "UTF-8", "featured": false, "graphic_overview": "https://ars.els-cdn.com/content/image/1-s2.0-S0301479719X00158-cov200h.gif", "hvd": "non_hvd", "id": "fcadbff5-6813-5a1b-8eb0-4ce902305c8f", "identifier": "fcadbff5-6813-5a1b-8eb0-4ce902305c8f", "inspire_id": "", "isopen": true, "language": "http://publications.europa.eu/resource/authority/language/SPA", "license_id": "cc-by", "license_title": "Creative Commons Attribution", "license_url": "http://www.opendefinition.org/licenses/cc-by", "lineage_process_steps": [], "lineage_source": ["Journal of Environmental Management. Vol. 248", "pag. 109320"], "maintainer": "", "maintainer_name": "", "metadata_created": "2026-06-23T14:47:14.139680", "metadata_modified": "2026-06-25T12:24:57.410756", "metadata_profile": ["https://www.w3.org/TR/vocab-dcat-3/"], "miteco_data_population": {"es": ""}, "miteco_data_territory": {"es": ""}, "miteco_dataset_type": "http://publications.europa.eu/resource/authority/dataset-type/STATISTICAL", "miteco_geo_level": "1", "modified": "2026-06-25", "name": "fcadbff5-6813-5a1b-8eb0-4ce902305c8f", "notes": "We modelled the spatiotemporal patterns of road mortality for seven medium-large mammals, using a roadkill dataset from Mato Grosso do Sul, Brazil (800 km of roads surveyed every two weeks, for two years). We related roadkill presence-absence along the road sections (1000 m) and across the survey dates with a collection of environmental variables, including land cover, forest cover, distance to rivers, temperature, precipitation and vegetation productivity. We further included two variables aiming to reflect the intrinsic spatial and temporal roadkill risk. Environmental variables were obtained through remote sensing and weather stations, allowing the estimate of the roadkill risk for the entire surveyed roads and survey periods. Overall, the models could explain a small fraction of the spatiotemporal patterns of roadkills (<0.23), probably due to species being habitat generalists, but still had reasonable discrimination power (AUC averaging 0.70 \u00b1 0.07). The intrinsic spatial and temporal roadkill risk were the most important variables, followed by land cover, climate and NDVI. We show that identifying spatiotemporal roadkill patterns may provide valuable information to define specific management actions focused on road sections and time periods, in complement to permanent road mitigation measures. Our approach thus offers a new insight into the understanding of road effects and how to plan and strategize monitoring and mitigation.", "notes_translated": {"en": "We modelled the spatiotemporal patterns of road mortality for seven medium-large mammals, using a\u00a0roadkill\u00a0dataset from Mato Grosso do Sul,\u00a0Brazil\u00a0(800\u202fkm of roads surveyed every two weeks, for two years). We related\u00a0roadkill\u00a0presence-absence along the road sections (1000\u202fm) and across the survey dates with a collection of environmental variables, including land cover, forest cover, distance to rivers, temperature, precipitation and vegetation productivity. We further included two variables aiming to reflect the intrinsic spatial and temporal roadkill risk. Environmental variables were obtained through\u00a0remote sensing\u00a0and weather stations, allowing the estimate of the roadkill risk for the entire surveyed roads and survey periods. Overall, the models could explain a small fraction of the spatiotemporal patterns of roadkills (<0.23), probably due to species being habitat\u00a0generalists, but still had reasonable discrimination power (AUC averaging 0.70\u202f\u00b1\u202f0.07). The intrinsic spatial and temporal roadkill risk were the most important variables, followed by land cover, climate and\u00a0NDVI. We show that identifying spatiotemporal roadkill patterns may provide valuable information to define specific management actions focused on road sections and time periods, in complement to permanent road\u00a0mitigation measures. Our approach thus offers a new insight into the understanding of road effects and how to plan and strategize monitoring and mitigation.", "es": "We modelled the spatiotemporal patterns of road mortality for seven medium-large mammals, using a roadkill dataset from Mato Grosso do Sul, Brazil (800 km of roads surveyed every two weeks, for two years). 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We show that identifying spatiotemporal roadkill patterns may provide valuable information to define specific management actions focused on road sections and time periods, in complement to permanent road mitigation measures. Our approach thus offers a new insight into the understanding of road effects and how to plan and strategize monitoring and mitigation."}, "num_resources": 1, "num_tags": 2, "organization": {"id": "bca483f7-26e2-4ed8-99e8-65f5b3c7a26e", "name": "iepnb", "title": "", "type": "organization", "description": "", "image_url": "", "created": "2026-06-23T14:36:08.942021", "is_organization": true, "approval_status": "approved", "state": "active"}, "owner_org": "bca483f7-26e2-4ed8-99e8-65f5b3c7a26e", "private": false, "provenance": {"en": "", "es": ""}, "publisher_email": "buzon-bdatos@miteco.es", "publisher_name": "\u00c1rea de Banco de Datos de la Naturaleza. Direcci\u00f3n General Biodiversidad, Bosques y Desertificaci\u00f3n. Ministerio para la Transici\u00f3n Ecol\u00f3gica y el Reto Demogr\u00e1fico", "publisher_type": "http://purl.org/adms/publishertype/NationalAuthority", "publisher_uri": "https://iepnb.es/catalogo/organization/iepnb", "publisher_url": "https://www.miteco.gob.es/", "purpose": {"en": "", "es": ""}, "reference": [], "schemingdcat_xls_metadata_template": false, "source": "", "spatial": "{\"type\": \"Polygon\", \"coordinates\": [[[-18.16, 27.64], [4.32, 27.64], [4.32, 43.79], [-18.16, 43.79], [-18.16, 27.64]]]}", "spatial_resolution_in_meters": "", "spatial_uri": "http://datos.gob.es/recurso/sector-publico/territorio/Pais/Espa\u00f1a", "state": "active", "study_variables": {"es": ""}, "tag_uri": ["http://inspire.ec.europa.eu/metadata-codelist/TopicCategory/environment"], "thematic_area": ["especies_silvestres"], "theme_es": ["http://datos.gob.es/kos/sector-publico/sector/medio-ambiente"], "title": "Predicting spatiotemporal patterns of road mortality for medium-large mammals.", "title_translated": {"en": "", "es": "Predicting spatiotemporal patterns of road mortality for medium-large mammals."}, "topic": "http://inspire.ec.europa.eu/metadata-codelist/TopicCategory/biota", "type": "dataset", "url": "https://iepnb.es:443/catalogo/dataset/fcadbff5-6813-5a1b-8eb0-4ce902305c8f", "version": "", "version_notes": {"en": "", "es": ""}, "contact": [{"email": "organismo@example.org", "name": "Organismo publicador del Cat\u00e1logo", "role": "http://inspire.ec.europa.eu/metadata-codelist/ResponsiblePartyRole/pointOfContact", "uri": "http://datos.gob.es/recurso/sector-publico/org/Organismo/EA0000000", "url": "https://organismo.example.org/"}], "creator": [{"name": "Ascens\u00e3o, F., Yogui, D., Alves, M., Medici, E.P. y Desbiez, A."}], "groups": [{"description": "La fragmentaci\u00f3n del h\u00e1bitat se define como el proceso durante el cual una gran extensi\u00f3n de h\u00e1bitat se transforma en una serie de parches m\u00e1s peque\u00f1os de menor superficie total aislados entre s\u00ed por una matriz de h\u00e1bitats distinta de la original", "display_name": "Fragmentaci\u00f3n del h\u00e1bitat", "id": "10439641-6830-4144-a3ab-117add931cd5", "image_display_url": "https://upload.wikimedia.org/wikipedia/commons/thumb/5/53/Green_infrastructure_2010_UE_Illustr.jpg/320px-Green_infrastructure_2010_UE_Illustr.jpg", "name": "fragmentacion-habitat", "title": "Fragmentaci\u00f3n del h\u00e1bitat"}], "publisher": [{"email": "buzon-bdatos@miteco.es", "name": "\u00c1rea de Banco de Datos de la Naturaleza. 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