| user_dict |
{'id': '3c5773b7-8921-48fa-a5ce-43b29f0921f3', 'name': 'rizkiyunanda', 'fullname': 'rizkiyunanda', 'created': '2026-01-21T11:37:19.216674', 'about': 'Toto Macau dikenal sebagai salah satu pasaran favorit dalam dunia togel Asia karena jadwal result yang konsisten dan data yang mudah diakses. Banyak pemain memilih Toto Macau karena variasi jenis taruhan seperti 4D dan 5D yang memberikan fleksibilitas dalam menentukan angka. Selain itu, pengeluaran Toto Macau biasanya dirilis secara rutin sehingga memudahkan pemain dalam melakukan analisis pola. Data Toto Macau juga sering digunakan sebagai referensi prediksi oleh komunitas togel. Dengan transparansi hasil dan ritme keluaran yang stabil, Toto Macau terus menarik perhatian pemain lama maupun pendatang baru.\r\n[Toto Macau](//altascapacidadescse.org/shop/) //\r\n[Toto Macau](//www.policecoders.org/home/covid-19/communities) //\r\n[Toto Macau](//www.associationepsylon.com/projet) //\r\n[Toto Macau](//dlhkotapadang.org/struktur/) //\r\n[Toto Macau](//dlhlubuklinggau.org/struktur/) //\r\n[Toto Macau](//iccollaborative.com/bulletins) //\r\n[Toto Macau](//www.wicc2024.com/) //\r\n', 'activity_streams_email_notifications': False, 'sysadmin': False, 'state': 'active', 'image_url': '', 'display_name': 'rizkiyunanda', 'email_hash': '774ad115055a75880d9e0ce1a1f67940', 'number_created_packages': 0, 'image_display_url': '', 'datasets': [{'author': None, 'author_email': None, 'creator_user_id': '51ab5002-5dc5-4fdc-a0ab-ce13592d0d6f', 'doi': '', 'featured': 'false', 'id': 'c98c5ffa-b500-4da2-92d8-e6e634e87a0a', 'isopen': False, 'license_id': None, 'license_title': None, 'lineage_statement': 'The 2025 CBERS 4A Wide Field Imager (WPM) acquired directly and processed in-house by South Africa national Space Agency, in Pretoria, South Africa. The CBGERS4A acquired between 04 January and 29 December 2025, with a spatial resolution of 8m multispectral 4 bands (RGB, NIR) and 2m panchromatic, processed to Level2B and provided in GeoTiff format.', 'maintainer': None, 'maintainer_email': None, 'metadata_created': '2026-02-02T12:56:53.065059', 'metadata_date': '2026-02-02T00:00', 'metadata_modified': '2026-02-02T12:59:12.058630', 'metadata_thumbnail': '', 'name': '2025-cbers-4a-', 'notes': 'The 2025 CBERS 4A Wide Field Imager (WPM) acquired directly and processed in-house by South Africa national Space Agency, in Pretoria, South Africa. The CBGERS4A acquired between 04 January and 29 December 2025, with a spatial resolution of 8m multispectral 4 bands (RGB, NIR) and 2m panchromatic, processed to Level2B and provided in GeoTiff format.', 'num_resources': 1, 'num_tags': 1, 'organization': {'id': 'a959e782-51ce-4adc-b84d-f89961445cdb', 'name': 'sansa', 'title': 'SANSA', 'type': 'organization', 'description': 'SANSA was created to promote the use of space and strengthen cooperation in space-related activities while fostering research in space science, advancing scientific engineering through developing human capital, and supporting industrial development in space technologies. The research and work carried out at SANSA focuses on Earth observation, space science, space engineering and space operations. Much of this work involves monitoring the Earth for policy and decision making, resource and disaster management, food security and national security. SANSA also provides state-of-the-art facilities to monitor space weather, provide launch support and data downloads as well as supporting the growth of the local space industry.', 'image_url': '2025-07-31-061500.854757SANSALogo.jpg', 'created': '2025-04-01T13:27:03.699924', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': 'a959e782-51ce-4adc-b84d-f89961445cdb', 'private': False, 'reference_system_additional_info': '', 'spatial': '{"type": "Polygon", "coordinates": [[[16.4699, -34.8212], [32.8931, -34.8212], [32.8931, -22.1265], [16.4699, -22.1265], [16.4699, -34.8212]]]}', 'state': 'active', 'title': '2025 CBERS 4A', 'type': 'dataset', 'url': None, 'version': None, 'contact': [{'electronic_mail_address': 'customers-eo@sansa.org.za', 'individual_name': "SANSA's customer services", 'position_name': 'Customer services', 'role': 'point_of_contact'}], 'contact_information': [{'facsimile': '', 'voice': '0123345024'}], 'dataset_reference_date': [{'reference': '2026-02-02T14:52', 'reference_date_type': 1}], 'distribution_format': [{'name': 'PDF,xml', 'version': '1'}], 'metadata_language_and_character_set': [{'dataset_character_set': 'utf-8', 'dataset_language': 'English', 'metadata_character_set': 'utf-8', 'metadata_language': 'English'}], 'metadata_standard': [{'name': 'SANS 1878-1:2011', 'version': '1.1'}], 'online_resource': [{'application_profile': 'Catalogue Service', 'description': 5, 'linkage': 'https://catalogue.sansa.org.za', 'name': "SANSA's customer services"}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2026-02-02T12:58:34.722073', 'description': '', 'format': '', 'format_version': '', 'hash': '', 'id': 'baea43dc-cbcd-4ac3-aed3-464f53763855', 'last_modified': None, 'metadata_modified': '2026-02-02T12:58:34.632601', 'mimetype': None, 'mimetype_inner': None, 'name': '', 'package_id': 'c98c5ffa-b500-4da2-92d8-e6e634e87a0a', 'position': 0, 'resource_type': 'other', 'size': None, 'state': 'active', 'upload_mode': 'single', 'url': 'http://catalogue.sansa.org.za/', 'url_type': None}], 'responsible_party': [{'electronic_mail_address': 'customers-eo@sansa.org.za', 'individual_name': 'South African National Space Agency', 'position_name': 'Earth Observation', 'role': 'owner', 'website': 'www.sansa.org.za'}], 'responsible_party_contact_address': [{'administrative_area': 'Gauteng', 'city': 'Pretoria', 'delivery_point': 'Building 10, CSIR Campus, Meiring Naude Road, Brummeria ', 'postal_code': ' 0184'}], 'responsible_party_contact_info': [{'facsimile': '', 'voice': '0123345024'}], 'spatial_parameters': [{'equivalent_scale': '1:2000', 'spatial_reference_system': 'EPSG:4326', 'spatial_representation_type': '007'}], 'tags': [{'display_name': 'Imagery-Basemaps-Earth Cover', 'id': '8895be3b-53e6-43b4-b77b-571ea5ff5252', 'name': 'Imagery-Basemaps-Earth Cover', 'state': 'active', 'vocabulary_id': None}], 'topic_and_saeoss_themes': [{'iso_topic_category': 'imageryBaseMapsEarthCover'}], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': None, 'author_email': None, 'creator_user_id': '64e47517-dce0-4a13-9ab7-ef1cfcd1d892', 'doi': '10.15493/SARVA.BEEH.10000179', 'featured': 'false', 'id': '7d576f1f-8889-4cff-95b8-ef058d65f75f', 'isopen': False, 'license_id': None, 'license_title': None, 'lineage_statement': 'Papaya, or pawpaw (Carica papaya) is a tropical fruit grown widely between latitudes 32 degree N and S. High in Vitamin C, papaya is indigenous to tropical America (ARC, 2005). This fruit, initially brought to the attention of Europe around 1520, was introduced to South Africa in seed form by Jan van Riebeeck in 1652, but only grown commercially in the Lowveld of Mpumalanga for the first time in the early 20th century by a Captain Elphick (ARC, 2005). Papaya needs relatively little water in the rainy summer season in South Africa, but if irrigated every 2 weeks in the dry season it is well adapted to hot, dry areas as the fruit then matures early and is then highly palatable owing to its high sugar content (Smith, 1998). Papaya has high heat requirements, with average daily temperatures for optimum growth between 20 and 30 degree Celsius. Determination of climatically optimum growth areas for Papaya in South Africa is based on the expert knowledge of Bower (2005) and Moll (2005), climatically optimum growth areas were determined according to the four basic criteria: Criterion 1: Heat units (base 12 degree Celsius) should exceed 2 000 days per annum, Criterion 2: Optimum areas should have a low frequency of 4 consecutive days with maximum temperatures > 36 degree Celsius, Criterion 3: Monthly means of daily average temperatures in December and January should be 23 degree Celsius - 30 degree Celsius and Criterion 4: Optimum growth areas should have a low frequency of 4 consecutive days with minimum temperatures < 17 degree Celsius. Using the 50 year time series of quality controlled daily maximum and minimum temperatures generated by Schulze and Maharaj (2004) at a spatial resolution of 1 arc minute (i.e. 1` x 1` of a degree latitude/longitude), the above four temperature based criteria were first mapped individually and then superimposed to determine the climatically optimum growth areas of papaya in South Africa.', 'maintainer': None, 'maintainer_email': None, 'metadata_created': '2025-10-17T11:08:39.531145', 'metadata_date': '2025-10-17T00:00', 'metadata_modified': '2025-10-17T11:11:28.922543', 'metadata_thumbnail': '', 'name': 'climatically_optimum_growth_areas_papaya_composite_of_all_criteria', 'notes': 'Papaya, or pawpaw (Carica papaya) is a tropical fruit grown widely between latitudes 32 degree N and S. High in Vitamin C, papaya is indigenous to tropical America (ARC, 2005). This fruit, initially brought to the attention of Europe around 1520, was introduced to South Africa in seed form by Jan van Riebeeck in 1652, but only grown commercially in the Lowveld of Mpumalanga for the first time in the early 20th century by a Captain Elphick (ARC, 2005). Papaya needs relatively little water in the rainy summer season in South Africa, but if irrigated every 2 weeks in the dry season it is well adapted to hot, dry areas as the fruit then matures early and is then highly palatable owing to its high sugar content (Smith, 1998). Papaya has high heat requirements, with average daily temperatures for optimum growth between 20 and 30 degree Celsius. Determination of climatically optimum growth areas for Papaya in South Africa is based on the expert knowledge of Bower (2005) and Moll (2005), climatically optimum growth areas were determined according to the four basic criteria: Criterion 1: Heat units (base 12 degree Celsius) should exceed 2 000 days per annum, Criterion 2: Optimum areas should have a low frequency of 4 consecutive days with maximum temperatures > 36 degree Celsius, Criterion 3: Monthly means of daily average temperatures in December and January should be 23 degree Celsius - 30 degree Celsius and Criterion 4: Optimum growth areas should have a low frequency of 4 consecutive days with minimum temperatures < 17 degree Celsius. Using the 50 year time series of quality controlled daily maximum and minimum temperatures generated by Schulze and Maharaj (2004) at a spatial resolution of 1 arc minute (i.e. 1` x 1` of a degree latitude/longitude), the above four temperature based criteria were first mapped individually and then superimposed to determine the climatically optimum growth areas of papaya in South Africa.', 'num_resources': 1, 'num_tags': 11, 'organization': {'id': 'c4a18544-cded-4488-9f43-c02a1094ad39', 'name': 'saeon', 'title': 'NRF-SAEON', 'type': 'organization', 'description': 'The South African Environmental Observation Network (SAEON) is a long-term environmental observation and research facility of the National Research Foundation (NRF). SAEON’s three focus areas are environmental observation, data management and education outreach. The Department of Science, Technology and Innovation (DSTI) provides core funding for these activities. ', 'image_url': '2025-08-01-083136.289314LogoSAEON.png', 'created': '2025-05-26T07:57:06.135422', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': 'c4a18544-cded-4488-9f43-c02a1094ad39', 'private': False, 'reference_system_additional_info': '', 'spatial': '{"type": "Polygon", "coordinates": [[[16.458333, -34.841667], [32.908333, -34.841667], [32.908333, -22.141667], [16.458333, -22.141667], [16.458333, -34.841667]]]}', 'state': 'active', 'title': 'Climatically Optimum Growth Areas Papaya Composite Of All Criteria', 'type': 'dataset', 'url': None, 'version': None, 'contact': [{'electronic_mail_address': 'curation@saeon.nrf.ac.za', 'individual_name': 'SAEON', 'position_name': '', 'role': 'point_of_contact'}], 'contact_information': [{'facsimile': '', 'voice': ''}], 'dataset_reference_date': [{'reference': '2007-01-01T00:00', 'reference_date_type': 1}], 'distribution_format': [{'name': 'Electronic metadata record', 'version': '1.1'}], 'metadata_language_and_character_set': [{'dataset_character_set': 'utf-8', 'dataset_language': 'English', 'metadata_character_set': 'utf-8', 'metadata_language': 'English'}], 'online_resource': [{'application_profile': '', 'description': 2, 'linkage': 'https://catalogue.saeon.ac.za/records/10.15493/SARVA.BEEH.10000179', 'name': 'Climatically Optimum Growth Areas Papaya Composite Of All Criteria'}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2025-10-17T11:09:12.315516', 'description': '', 'format': '', 'format_version': '', 'hash': '', 'id': '7e81d0b1-3193-41ab-bc15-c5cc65df8b56', 'last_modified': None, 'metadata_modified': '2025-10-17T11:09:12.305341', 'mimetype': None, 'mimetype_inner': None, 'name': 'Climatically Optimum Growth Areas Papaya Composite Of All Criteria', 'package_id': '7d576f1f-8889-4cff-95b8-ef058d65f75f', 'position': 0, 'resource_type': 'other', 'size': None, 'state': 'active', 'upload_mode': 'single', 'url': 'https://repository.saeon.ac.za/index.php/s/2yTF8TY7xDMA8fH?opendetails=', 'url_type': None}], 'responsible_party': [{'electronic_mail_address': '', 'individual_name': 'R.E. Schulze & M. Maharaj', 'position_name': 'University of KwaZulu-Natal', 'role': 'originator', 'website': ''}], 'responsible_party_contact_address': [{'administrative_area': '', 'city': '', 'delivery_point': '', 'postal_code': ''}], 'responsible_party_contact_info': [{'facsimile': '', 'voice': ''}], 'spatial_parameters': [{'equivalent_scale': 'N/A', 'spatial_reference_system': 'EPSG: 4326', 'spatial_representation_type': '001'}], 'tags': [{'display_name': 'Commercial Crop Systems', 'id': 'ab20e5e0-5e6e-4d58-9098-7ad4dd7493c5', 'name': 'Commercial Crop Systems', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'Imagery-Basemaps-Earth Cover', 'id': '8895be3b-53e6-43b4-b77b-571ea5ff5252', 'name': 'Imagery-Basemaps-Earth Cover', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'Optimum growth area', 'id': '246aee2a-e770-40dc-8bcd-223b347a9187', 'name': 'Optimum growth area', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'agriculture', 'id': 'e9c2ba74-5eec-405f-bf77-5b0483eae3bf', 'name': 'agriculture', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'carica papaya', 'id': 'e5c271e2-a2da-4796-b3d8-d439961f384c', 'name': 'carica papaya', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'daily average temperature', 'id': 'b833fb31-eb1b-4cbc-b682-8cebe4a086cc', 'name': 'daily average temperature', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'dry season', 'id': 'e99ee17d-7f26-4071-b179-69fc0e06aa11', 'name': 'dry season', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'growth areas', 'id': '270aa94b-1ca2-41e2-a735-944a362034d0', 'name': 'growth areas', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'irrigation', 'id': '4e602a4a-0a23-427f-ad9d-d1df6a5811ac', 'name': 'irrigation', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'papaya', 'id': 'f0fff86a-9c07-421c-a298-f233bfc0fa11', 'name': 'papaya', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'rainy season', 'id': '9f1ac637-b5cc-4569-b94f-23fdc7e64d12', 'name': 'rainy season', 'state': 'active', 'vocabulary_id': None}], 'topic_and_saeoss_themes': [{'iso_topic_category': 'imageryBaseMapsEarthCover'}], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': None, 'author_email': None, 'creator_user_id': '64e47517-dce0-4a13-9ab7-ef1cfcd1d892', 'doi': '10.15493/SARVA.BEEH.10000104', 'featured': 'false', 'id': '84eba355-8f57-484b-b365-b008e6769b37', 'isopen': False, 'license_id': None, 'license_title': None, 'lineage_statement': 'Litchis, Litchi chinensis, are indigenous to subtropical southern China and were first imported to South Africa from Mauritius in the 1870s (ARC, 2005). Of the 7 000 tons of litchis produced annually in South Africa, with a gross value exceeding R25 million, about 60 percent come from Mpumalanga, 38 percent from Limpopo and 2 percent from KwaZulu-Natal (Statistics SA, 2002; NDA, 2005).', 'maintainer': None, 'maintainer_email': None, 'metadata_created': '2025-10-17T10:52:41.204356', 'metadata_date': '2025-10-17T00:00', 'metadata_modified': '2025-10-17T11:03:29.674696', 'metadata_thumbnail': '', 'name': 'climatically_optimum_growth_areas_litchis_composite_of_all_criteria', 'notes': 'Litchis, Litchi chinensis, are indigenous to subtropical southern China and were first imported to South Africa from Mauritius in the 1870s (ARC, 2005). Of the 7 000 tons of litchis produced annually in South Africa, with a gross value exceeding R25 million, about 60 percent come from Mpumalanga, 38 percent from Limpopo and 2 percent from KwaZulu-Natal (Statistics SA, 2002; NDA, 2005).', 'num_resources': 1, 'num_tags': 9, 'organization': {'id': 'c4a18544-cded-4488-9f43-c02a1094ad39', 'name': 'saeon', 'title': 'NRF-SAEON', 'type': 'organization', 'description': 'The South African Environmental Observation Network (SAEON) is a long-term environmental observation and research facility of the National Research Foundation (NRF). SAEON’s three focus areas are environmental observation, data management and education outreach. The Department of Science, Technology and Innovation (DSTI) provides core funding for these activities. ', 'image_url': '2025-08-01-083136.289314LogoSAEON.png', 'created': '2025-05-26T07:57:06.135422', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': 'c4a18544-cded-4488-9f43-c02a1094ad39', 'private': False, 'reference_system_additional_info': '', 'spatial': '{"type": "Polygon", "coordinates": [[[16.458333, -34.841667], [32.908333, -34.841667], [32.908333, -22.141667], [16.458333, -22.141667], [16.458333, -34.841667]]]}', 'state': 'active', 'title': 'Climatically Optimum Growth Areas Litchis Composite Of All Criteria', 'type': 'dataset', 'url': None, 'version': None, 'contact': [{'electronic_mail_address': 'curation@saeon.nrf.ac.za', 'individual_name': 'SAEON', 'position_name': '', 'role': 'point_of_contact'}], 'contact_information': [{'facsimile': '', 'voice': ''}], 'dataset_reference_date': [{'reference': '2007-01-01T00:00', 'reference_date_type': 1}], 'distribution_format': [{'name': 'Electronic metadata record', 'version': '1.1'}], 'metadata_language_and_character_set': [{'dataset_character_set': 'utf-8', 'dataset_language': 'English', 'metadata_character_set': 'utf-8', 'metadata_language': 'English'}], 'metadata_standard': [{'name': 'SANS 1878-1:2011', 'version': '1.1'}], 'online_resource': [{'application_profile': '', 'description': 2, 'linkage': 'https://catalogue.saeon.ac.za/records/10.15493/SARVA.BEEH.10000104', 'name': 'Climatically Optimum Growth Areas Litchis Composite Of All Criteria'}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2025-10-17T10:57:28.000498', 'description': '', 'format': '', 'format_version': '', 'hash': '', 'id': '0d6d7010-b440-48b4-b1f1-23f9e48ae3e9', 'last_modified': None, 'metadata_modified': '2025-10-17T10:57:27.994148', 'mimetype': None, 'mimetype_inner': None, 'name': 'Climatically Optimum Growth Areas Litchis Composite Of All Criteria', 'package_id': '84eba355-8f57-484b-b365-b008e6769b37', 'position': 0, 'resource_type': 'other', 'size': None, 'state': 'active', 'upload_mode': 'single', 'url': 'https://repository.saeon.ac.za/index.php/s/3E4cCsAMaj92xjw?opendetails=', 'url_type': None}], 'responsible_party': [{'electronic_mail_address': '', 'individual_name': 'R.E. Schulze & M. Maharaj', 'position_name': 'University of KwaZulu-Natal', 'role': 'originator', 'website': ''}], 'responsible_party_contact_address': [{'administrative_area': '', 'city': '', 'delivery_point': '', 'postal_code': ''}], 'responsible_party_contact_info': [{'facsimile': '', 'voice': ''}], 'spatial_parameters': [{'equivalent_scale': 'N/A', 'spatial_reference_system': 'EPSG: 4326', 'spatial_representation_type': '001'}], 'tags': [{'display_name': 'Biophysical variables', 'id': 'f1a1894f-6ab7-4e6c-8091-05cbab5811a1', 'name': 'Biophysical variables', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'Commercial cropping system', 'id': 'be02ede8-4f81-48f2-a871-0dd690bc3d8d', 'name': 'Commercial cropping system', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'Imagery-Basemaps-Earth Cover', 'id': '8895be3b-53e6-43b4-b77b-571ea5ff5252', 'name': 'Imagery-Basemaps-Earth Cover', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'Optimum growth area', 'id': '246aee2a-e770-40dc-8bcd-223b347a9187', 'name': 'Optimum growth area', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'agriculture', 'id': 'e9c2ba74-5eec-405f-bf77-5b0483eae3bf', 'name': 'agriculture', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'growth areas', 'id': '270aa94b-1ca2-41e2-a735-944a362034d0', 'name': 'growth areas', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'litchis', 'id': 'd3708a75-1f7c-44e4-a373-5b1fe3e8fc43', 'name': 'litchis', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'maximum temperature', 'id': '0d49853e-a68d-4627-a644-58f7c8ad8e96', 'name': 'maximum temperature', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'relative humidity', 'id': '716d7246-9aa8-458a-ae7e-a0a174c2dbb8', 'name': 'relative humidity', 'state': 'active', 'vocabulary_id': None}], 'topic_and_saeoss_themes': [{'iso_topic_category': 'imageryBaseMapsEarthCover'}], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': None, 'author_email': None, 'creator_user_id': '64e47517-dce0-4a13-9ab7-ef1cfcd1d892', 'doi': '10.15493/SARVA.BEEH.10000186', 'featured': 'false', 'id': 'c4572749-eea1-477c-9288-cd523ceec03a', 'isopen': False, 'license_id': None, 'license_title': None, 'lineage_statement': ' Criteria for climatically optimum growth areas for passion fruit were refined by Bower (2005). Six criteria were identified and using the 1` x 1` gridded information on temperature related parameters derived by Schulze and Maharaj (2004), the following criteria were mapped: Criterion 1: > 330 days per year with a minimum temperature exceeding 2 degree Celsius; Criterion 2: Fewer than 2 consecutive days per annum with minimum temperatures < -2 degree Celsius; Criterion 3: There should not be > 3 consecutive frost days per annum; Criterion 4: In total, there should be < 25 days per annum with frost; Criterion 5: Maximum temperatures should be < 28 degree Celsius on at least 25 days of each month; Criterion 6: Maximum temperatures should not exceed 35 degree Celsius on any two consecutive days per month. Mapped criteria were given either categorical or probabilistic weightings and when the six maps were superimposed, suitable and less suitable climatically optimum growth areas could be identified.', 'maintainer': None, 'maintainer_email': None, 'metadata_created': '2025-10-17T10:04:49.448189', 'metadata_date': '2025-10-17T00:00', 'metadata_modified': '2025-10-17T10:07:55.203305', 'metadata_thumbnail': '', 'name': 'climatically_optimum_growth_areas-_passion_fruit_composite_of_all_criteria', 'notes': 'Passion fruit are believed to have originated from southern Brazil (Kenyaweb, 2005).The most commonly commercially grown of 55 edible species of passion fruit is Passiflora edulis, which consists of perennial woody vines with each producing about 100 fruits per year (RBGK, 2005). In South Africa passion fruit ideally requires a cool subtropical climate for optimum production (Smith, 1998). The vines prefer moderate temperatures throughout the year, with monthly means of daily maxima < 29 degree Celsius. The plants are sensitive to severe frosts, and monthly means of minimum temperatures should be > 6 degree Celsius (NDA, 2005). For commercial production under rainfed conditions MAP should ideally exceed 1 200 mm and be well distributed throughout the year (NDA, 2005), as it is important to maintain the soil moist throughout the growing season to keep the vines flowering and fruiting for longer periods and prevent the fruit from shriveling and falling prematurely (Kenyaweb, 2005). Total commercial production of passion fruit in South Africa is 1 300t per season, with a range (between 1998/9 - 2003/4) in more recent from 900 - 1 700 t (NDA, 2005).The gross value is R65 million/year (NDA, 2005). Criteria for climatically optimum growth areas for passion fruit were refined by Bower (2005). Six criteria were identified and using the 1` x 1` gridded information on temperature related parameters derived by Schulze and Maharaj (2004), the following criteria were mapped: Criterion 1: > 330 days per year with a minimum temperature exceeding 2 degree Celsius; Criterion 2: Fewer than 2 consecutive days per annum with minimum temperatures < -2 degree Celsius; Criterion 3: There should not be > 3 consecutive frost days per annum; Criterion 4: In total, there should be < 25 days per annum with frost; Criterion 5: Maximum temperatures should be < 28 degree Celsius on at least 25 days of each month; Criterion 6: Maximum temperatures should not exceed 35 degree Celsius on any two consecutive days per month. Mapped criteria were given either categorical or probabilistic weightings and when the six maps were superimposed, suitable and less suitable climatically optimum growth areas could be identified. ', 'num_resources': 1, 'num_tags': 10, 'organization': {'id': 'c4a18544-cded-4488-9f43-c02a1094ad39', 'name': 'saeon', 'title': 'NRF-SAEON', 'type': 'organization', 'description': 'The South African Environmental Observation Network (SAEON) is a long-term environmental observation and research facility of the National Research Foundation (NRF). SAEON’s three focus areas are environmental observation, data management and education outreach. The Department of Science, Technology and Innovation (DSTI) provides core funding for these activities. ', 'image_url': '2025-08-01-083136.289314LogoSAEON.png', 'created': '2025-05-26T07:57:06.135422', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': 'c4a18544-cded-4488-9f43-c02a1094ad39', 'private': False, 'reference_system_additional_info': '', 'spatial': '{"type": "Polygon", "coordinates": [[[16.458333, -34.841667], [32.908333, -34.841667], [32.908333, -22.141667], [16.458333, -22.141667], [16.458333, -34.841667]]]}', 'state': 'active', 'title': 'Climatically Optimum Growth Areas (Passion Fruit) Composite Of All Criteria', 'type': 'dataset', 'url': None, 'version': None, 'contact': [{'electronic_mail_address': 'curation@saeon.nrf.ac.za', 'individual_name': 'SAEON', 'position_name': '', 'role': 'point_of_contact'}], 'contact_information': [{'facsimile': '', 'voice': ''}], 'dataset_reference_date': [{'reference': '2007-01-01T00:00', 'reference_date_type': 1}], 'distribution_format': [{'name': 'Electronic metadata record', 'version': '1.1'}], 'metadata_language_and_character_set': [{'dataset_character_set': 'utf-8', 'dataset_language': 'English', 'metadata_character_set': 'utf-8', 'metadata_language': 'English'}], 'online_resource': [{'application_profile': '', 'description': 2, 'linkage': 'https://catalogue.saeon.ac.za/records/10.15493/SARVA.BEEH.10000186', 'name': 'Climatically Optimum Growth Areas (Passion Fruit) Composite Of All Criteria'}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2025-10-17T10:05:36.992639', 'description': '', 'format': '', 'format_version': '', 'hash': '', 'id': '9d64a80d-8520-4035-b2c0-64b3a5308189', 'last_modified': None, 'metadata_modified': '2025-10-17T10:05:36.987063', 'mimetype': None, 'mimetype_inner': None, 'name': 'Climatically Optimum Growth Areas (Passion Fruit) Composite Of All Criteria', 'package_id': 'c4572749-eea1-477c-9288-cd523ceec03a', 'position': 0, 'resource_type': 'other', 'size': None, 'state': 'active', 'upload_mode': 'single', 'url': 'https://repository.saeon.ac.za/index.php/s/KDwnyqAwyrwkwrM?opendetails=', 'url_type': None}], 'responsible_party': [{'electronic_mail_address': '', 'individual_name': 'R.E. Schulze & M. Maharaj', 'position_name': 'University of KwaZulu-Natal', 'role': 'originator', 'website': ''}], 'responsible_party_contact_address': [{'administrative_area': '', 'city': '', 'delivery_point': '', 'postal_code': ''}], 'responsible_party_contact_info': [{'facsimile': '', 'voice': ''}], 'spatial_parameters': [{'equivalent_scale': 'N/A', 'spatial_reference_system': 'EPSG: 4326', 'spatial_representation_type': '001'}], 'tags': [{'display_name': 'Commercial Crop Systems', 'id': 'ab20e5e0-5e6e-4d58-9098-7ad4dd7493c5', 'name': 'Commercial Crop Systems', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'Imagery-Basemaps-Earth Cover', 'id': '8895be3b-53e6-43b4-b77b-571ea5ff5252', 'name': 'Imagery-Basemaps-Earth Cover', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'Optimum growth area', 'id': '246aee2a-e770-40dc-8bcd-223b347a9187', 'name': 'Optimum growth area', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'agriculture', 'id': 'e9c2ba74-5eec-405f-bf77-5b0483eae3bf', 'name': 'agriculture', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'frost', 'id': '8db5aa5a-71f7-4e83-9c78-4c06e6a4aa11', 'name': 'frost', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'growing season', 'id': 'fc932820-1bd3-405f-b791-07055e7210be', 'name': 'growing season', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'mean annual precipitation', 'id': '7e44e7b0-91e0-498f-b2ef-b7a5d8db9859', 'name': 'mean annual precipitation', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'passiflora edulis', 'id': '7a406d31-f5d0-4767-891d-0d651b52f80f', 'name': 'passiflora edulis', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'passion fruit', 'id': '0660e316-6de2-46e6-9b3e-1c2ae0bc43af', 'name': 'passion fruit', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'soil moisture', 'id': '3952e971-20d2-4356-910e-3e5aca562b6c', 'name': 'soil moisture', 'state': 'active', 'vocabulary_id': None}], 'topic_and_saeoss_themes': [{'iso_topic_category': 'imageryBaseMapsEarthCover'}], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': None, 'author_email': None, 'creator_user_id': '64e47517-dce0-4a13-9ab7-ef1cfcd1d892', 'doi': '10.15493/SARVA.BEEH.10000034', 'featured': 'false', 'id': '9eacac9c-41d1-4a96-8f89-899790ceddcc', 'isopen': False, 'license_id': None, 'license_title': None, 'lineage_statement': 'Eucalyptus badjensis, or the commonly named Badger Gum, is a medium to fast growing tall and low maintenance tree which can withstand low to moderate soil moisture (Australia plants, 2004). This cool climate species grows optimally at MATs ranging from 14 - 17 degree Celsius and MAPs > 725 mm (Kunz, 2004).', 'maintainer': None, 'maintainer_email': None, 'metadata_created': '2025-10-17T09:56:44.152758', 'metadata_date': '2025-10-17T00:00', 'metadata_modified': '2025-10-17T09:59:18.993025', 'metadata_thumbnail': '', 'name': 'climatically_suitable_growth_areas_for_eucalyptus_badjensis', 'notes': 'Eucalyptus badjensis, or the commonly named Badger Gum, is a medium to fast growing tall and low maintenance tree which can withstand low to moderate soil moisture (Australia plants, 2004). This cool climate species grows optimally at MATs ranging from 14 - 17 degree Celsius and MAPs > 725 mm (Kunz, 2004).', 'num_resources': 1, 'num_tags': 11, 'organization': {'id': 'c4a18544-cded-4488-9f43-c02a1094ad39', 'name': 'saeon', 'title': 'NRF-SAEON', 'type': 'organization', 'description': 'The South African Environmental Observation Network (SAEON) is a long-term environmental observation and research facility of the National Research Foundation (NRF). SAEON’s three focus areas are environmental observation, data management and education outreach. The Department of Science, Technology and Innovation (DSTI) provides core funding for these activities. ', 'image_url': '2025-08-01-083136.289314LogoSAEON.png', 'created': '2025-05-26T07:57:06.135422', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': 'c4a18544-cded-4488-9f43-c02a1094ad39', 'private': False, 'reference_system_additional_info': '', 'spatial': '{"type": "Polygon", "coordinates": [[[16.458333, -34.841667], [32.908333, -34.841667], [32.908333, -22.141667], [16.458333, -22.141667], [16.458333, -34.841667]]]}', 'state': 'active', 'title': 'Climatically Suitable Growth Areas for Eucalyptus badjensis', 'type': 'dataset', 'url': None, 'version': None, 'contact': [{'electronic_mail_address': 'curation@saeon.nrf.ac.za', 'individual_name': 'SAEON', 'position_name': '', 'role': 'point_of_contact'}], 'contact_information': [{'facsimile': '', 'voice': ''}], 'dataset_reference_date': [{'reference': '2007-01-01T00:00', 'reference_date_type': 1}], 'distribution_format': [{'name': 'Electronic metadata record', 'version': '1.1'}], 'metadata_language_and_character_set': [{'dataset_character_set': 'utf-8', 'dataset_language': 'English', 'metadata_character_set': 'utf-8', 'metadata_language': 'English'}], 'online_resource': [{'application_profile': '', 'description': 2, 'linkage': 'https://catalogue.saeon.ac.za/records/10.15493/SARVA.BEEH.10000034', 'name': 'Climatically Suitable Growth Areas for Eucalyptus badjensis'}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2025-10-17T09:57:25.829177', 'description': '', 'format': '', 'format_version': '', 'hash': '', 'id': '5d641cd0-6b18-47dc-9510-a564d9b939ad', 'last_modified': None, 'metadata_modified': '2025-10-17T09:57:25.820623', 'mimetype': None, 'mimetype_inner': None, 'name': 'Climatically Suitable Growth Areas for Eucalyptus badjensis', 'package_id': '9eacac9c-41d1-4a96-8f89-899790ceddcc', 'position': 0, 'resource_type': 'other', 'size': None, 'state': 'active', 'upload_mode': 'single', 'url': 'https://repository.saeon.ac.za/index.php/s/sD5Bteyo7ZaJ8Nz?opendetails=', 'url_type': None}], 'responsible_party': [{'electronic_mail_address': '', 'individual_name': 'R.E. 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It is a cool climate species, growing optimally at MATs between 14 and 18 degree Celsius. E. benthamii is less tolerant of low MAPs than E. badjensis, with > 850 mm MAP required for optimal growth (Kunz, 2004).This species is susceptible to snow damage (Kunz, 2004).', 'maintainer': None, 'maintainer_email': None, 'metadata_created': '2025-10-17T09:11:46.432943', 'metadata_date': '2025-10-17T00:00', 'metadata_modified': '2025-10-17T09:40:33.467393', 'metadata_thumbnail': '', 'name': 'climatically_suitable_growth_areas_for_eucalyptus_benthamii', 'notes': 'Commonly named the Camden White Oak, Eucalyptus benthamii, is a tall, smooth-barked. It is a cool climate species, growing optimally at MATs between 14 and 18 degree Celsius. E. benthamii is less tolerant of low MAPs than E. badjensis, with > 850 mm MAP required for optimal growth (Kunz, 2004).This species is susceptible to snow damage (Kunz, 2004).', 'num_resources': 1, 'num_tags': 10, 'organization': {'id': 'c4a18544-cded-4488-9f43-c02a1094ad39', 'name': 'saeon', 'title': 'NRF-SAEON', 'type': 'organization', 'description': 'The South African Environmental Observation Network (SAEON) is a long-term environmental observation and research facility of the National Research Foundation (NRF). SAEON’s three focus areas are environmental observation, data management and education outreach. The Department of Science, Technology and Innovation (DSTI) provides core funding for these activities. ', 'image_url': '2025-08-01-083136.289314LogoSAEON.png', 'created': '2025-05-26T07:57:06.135422', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': 'c4a18544-cded-4488-9f43-c02a1094ad39', 'private': False, 'reference_system_additional_info': '', 'spatial': '{"type": "Polygon", "coordinates": [[[16.458333, -34.841667], [32.908333, -34.841667], [32.908333, -22.141667], [16.458333, -22.141667], [16.458333, -34.841667]]]}', 'state': 'active', 'title': 'Climatically Suitable Growth Areas for Eucalyptus benthamii', 'type': 'dataset', 'url': None, 'version': None, 'contact': [{'electronic_mail_address': 'curation@saeon.nrf.ac.za', 'individual_name': 'SAEON', 'position_name': '', 'role': 'point_of_contact'}], 'contact_information': [{'facsimile': '', 'voice': ''}], 'dataset_reference_date': [{'reference': '2007-01-01T00:00', 'reference_date_type': 1}], 'distribution_format': [{'name': 'Electronic metadata record', 'version': '1.1'}], 'metadata_language_and_character_set': [{'dataset_character_set': 'utf-8', 'dataset_language': 'English', 'metadata_character_set': 'utf-8', 'metadata_language': 'English'}], 'online_resource': [{'application_profile': '', 'description': 2, 'linkage': 'https://catalogue.saeon.ac.za/records/10.15493/SARVA.BEEH.10000035', 'name': 'Climatically Suitable Growth Areas for Eucalyptus benthamii'}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2025-10-17T09:12:14.652792', 'description': '', 'format': '', 'format_version': '', 'hash': '', 'id': '15c38271-ed04-432b-9f2a-122f10510441', 'last_modified': None, 'metadata_modified': '2025-10-17T09:12:14.646039', 'mimetype': None, 'mimetype_inner': None, 'name': 'Climatically Suitable Growth Areas for Eucalyptus benthamii', 'package_id': '334e68b0-6184-4cb2-9cc3-19a69a8e35c8', 'position': 0, 'resource_type': 'other', 'size': None, 'state': 'active', 'upload_mode': 'single', 'url': 'https://repository.saeon.ac.za/index.php/s/cBLgd5CLASatAEB?openfile=true', 'url_type': None}], 'responsible_party': [{'electronic_mail_address': '', 'individual_name': 'R.E. Schulze & M. 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Refer to the detailed BioEnergy Atlas report in this regard. * This data was assigned to planning polygons (meso-zones) and the basis of calculation of exploitable biomass adjusted for a 20-year eradication programme (i.e. harvest 1/20th each year, supplemented by the annual increment of the remaining biomass).', 'maintainer': None, 'maintainer_email': None, 'metadata_created': '2025-10-16T14:18:41.544367', 'metadata_date': '2025-10-16T00:00', 'metadata_modified': '2025-10-17T09:39:40.740321', 'metadata_thumbnail': '', 'name': 'availability_of_exploitable_invasive_alien_plants', 'notes': 'Data was derived from the following sources: CSIR based their assessment of standing IAP biomass on work done by the ARC, supplemented by an evaluation of species that may be exploitable, typical mass of such species, and the relative ease by which these can be exploited. Refer to the detailed BioEnergy Atlas report in this regard. This data was assigned to planning polygons (meso-zones) and the basis of calculation of exploitable biomass adjusted for a 20-year eradication programme (i.e. harvest 1/20th each year, supplemented by the annual increment of the remaining biomass).', 'num_resources': 1, 'num_tags': 7, 'organization': {'id': 'c4a18544-cded-4488-9f43-c02a1094ad39', 'name': 'saeon', 'title': 'NRF-SAEON', 'type': 'organization', 'description': 'The South African Environmental Observation Network (SAEON) is a long-term environmental observation and research facility of the National Research Foundation (NRF). SAEON’s three focus areas are environmental observation, data management and education outreach. The Department of Science, Technology and Innovation (DSTI) provides core funding for these activities. ', 'image_url': '2025-08-01-083136.289314LogoSAEON.png', 'created': '2025-05-26T07:57:06.135422', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': 'c4a18544-cded-4488-9f43-c02a1094ad39', 'private': False, 'reference_system_additional_info': '', 'spatial': '{"type": "Polygon", "coordinates": [[[16.45214, -34.8341698957], [32.8925317467, -34.8341698957], [32.8925317467, -22.12503], [16.45214, -22.12503], [16.45214, -34.8341698957]]]}', 'state': 'active', 'title': 'Availability of Exploitable Invasive Alien Plants', 'type': 'dataset', 'url': None, 'version': None, 'contact': [{'electronic_mail_address': 'curation@saeon.nrf.ac.za', 'individual_name': 'Wim Hugo', 'position_name': '', 'role': 'point_of_contact'}], 'contact_information': [{'facsimile': '', 'voice': ''}], 'dataset_reference_date': [{'reference': '2015-01-01T00:00', 'reference_date_type': 1}], 'distribution_format': [{'name': 'Electronic metadata record', 'version': '1.1'}], 'metadata_language_and_character_set': [{'dataset_character_set': 'utf-8', 'dataset_language': 'English', 'metadata_character_set': 'utf-8', 'metadata_language': 'English'}], 'online_resource': [{'application_profile': '', 'description': 2, 'linkage': 'https://catalogue.saeon.ac.za/records/10.15493/BEA.DATA.10000080', 'name': 'Availability of Exploitable Invasive Alien Plants'}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2025-10-16T14:19:52.976646', 'description': '', 'format': 'GEOMAP', 'format_version': '', 'hash': '', 'id': '985a2370-8695-4a84-9428-5b46ddbaac86', 'last_modified': None, 'metadata_modified': '2025-10-16T14:19:52.966248', 'mimetype': None, 'mimetype_inner': None, 'name': 'Availability of Exploitable Invasive Alien Plants', 'package_id': '964d2862-b467-40db-bb50-aaaa88880934', 'position': 0, 'resource_type': 'other', 'size': None, 'state': 'active', 'upload_mode': 'single', 'url': 'https://catalogue.saeon.ac.za/records/10.15493/BEA.DATA.10000080', 'url_type': None}], 'responsible_party': [{'electronic_mail_address': '', 'individual_name': 'South African Environmental Observation Network', 'position_name': 'Organisation', 'role': 'resource_provider', 'website': 'catalogue.saeon.ac.za'}], 'responsible_party_contact_address': [{'administrative_area': '', 'city': '', 'delivery_point': '', 'postal_code': ''}], 'responsible_party_contact_info': [{'facsimile': '', 'voice': ''}], 'spatial_parameters': [{'equivalent_scale': 'N/A', 'spatial_reference_system': 'EPSG: 4326', 'spatial_representation_type': '001'}], 'tags': [{'display_name': 'Bioenergy', 'id': 'ca34cd72-b5a2-4f3f-81d8-61b65cd42ef8', 'name': 'Bioenergy', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'Environment', 'id': 'ad6bb22c-77f7-4d69-81bb-a19bc4bceb95', 'name': 'Environment', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'biodiversity indices', 'id': 'c8ae6871-1f36-4892-8b69-60c34802240b', 'name': 'biodiversity indices', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'ecosystem services', 'id': '201e2748-5553-4e2e-990c-31ce75892d7f', 'name': 'ecosystem services', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'energy', 'id': '1722381a-3be4-46ea-9bcd-9d89526c69f3', 'name': 'energy', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'invasive alien plants', 'id': 'ae210958-a72f-4eed-b116-a4a41c90185a', 'name': 'invasive alien plants', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'surface water', 'id': '29359c57-f6fe-440c-81c0-f128049713fd', 'name': 'surface water', 'state': 'active', 'vocabulary_id': None}], 'topic_and_saeoss_themes': [{'iso_topic_category': 'environment'}], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': None, 'author_email': None, 'creator_user_id': '64e47517-dce0-4a13-9ab7-ef1cfcd1d892', 'doi': '10.15493/SAEON.FYNBOS.10000001', 'featured': 'false', 'id': 'e66d4a36-8db1-4f93-9236-05523d2ad639', 'isopen': False, 'license_id': None, 'license_title': None, 'lineage_statement': 'A climate-aided Bayesian kriging approach is used to interpolate 20 years of daily meteorological observations (maximum and minimum temperature and precipitation) to a 1 arc-minute grid for the Cape Floristic Region of South Africa. Independent validation data revealed overall predictive performance of the interpolation to have R2 values of 0.90, 0.85, and 0.59 for maximum temperature, minimum temperature, and precipitation, respectively. A suite of ecologically-relevant climate metrics that include the uncertainty introduced by the interpolation were then generated. By providing the high resolution climate metric surfaces and uncertainties, this work facilitates richer and more robust predictive modeling in ecology and bio- geography. These data can be incorporated into ecological models to propagate the uncertainties through to the final predictions', 'maintainer': None, 'maintainer_email': None, 'metadata_created': '2025-10-16T11:32:14.831108', 'metadata_date': '2016-01-01T00:00', 'metadata_modified': '2025-10-17T09:38:59.712167', 'metadata_thumbnail': '', 'name': 'interpolated_observed_weather_data_for_the_cape_floristic_region', 'notes': 'Conservation of biodiversity demands comprehension of evolutionary and ecological patterns and processes that occur over vast spatial and temporal scales. A central goal of ecology is to understand the climatic factors that control ecological processes and this has become even more important in the face of climate change. Especially at global scales, there can be enormous uncertainty in underlying environmental data used to explain ecological processes, but that uncertainty is rarely quantified or incorporated into ecological models. In this study a climate-aided Bayesian kriging approach is used to interpolate 20 years of daily meteorological observations (maximum and minimum temperature and precipitation) to a 1 arc-minute grid for the Cape Floristic Region of South Africa. Independent validation data revealed overall predictive performance of the interpolation to have R2 values of 0.90, 0.85, and 0.59 for maximum temperature, minimum temperature, and precipitation, respectively. A suite of ecologically-relevant climate metrics that include the uncertainty introduced by the interpolation were then generated. By providing the high resolution climate metric surfaces and uncertainties, this work facilitates richer and more robust predictive modeling in ecology and bio- geography. These data can be incorporated into ecological models to propagate the uncertainties through to the final predictions.', 'num_resources': 1, 'num_tags': 6, 'organization': {'id': 'c4a18544-cded-4488-9f43-c02a1094ad39', 'name': 'saeon', 'title': 'NRF-SAEON', 'type': 'organization', 'description': 'The South African Environmental Observation Network (SAEON) is a long-term environmental observation and research facility of the National Research Foundation (NRF). SAEON’s three focus areas are environmental observation, data management and education outreach. The Department of Science, Technology and Innovation (DSTI) provides core funding for these activities. ', 'image_url': '2025-08-01-083136.289314LogoSAEON.png', 'created': '2025-05-26T07:57:06.135422', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': 'c4a18544-cded-4488-9f43-c02a1094ad39', 'private': False, 'reference_system_additional_info': '', 'spatial': '{"type": "Polygon", "coordinates": [[[17.8, -34.9], [25.8, -34.9], [25.8, -30.9], [17.8, -30.9], [17.8, -34.9]]]}', 'state': 'active', 'title': 'Interpolated observed weather data for the Cape Floristic Region', 'type': 'dataset', 'url': None, 'version': None, 'contact': [{'electronic_mail_address': 'adamw@buffalo.edu', 'individual_name': 'Adam Wilson', 'position_name': '', 'role': 'point_of_contact'}], 'contact_information': [{'facsimile': '', 'voice': ''}], 'dataset_reference_date': [{'reference': '2016-01-01T00:00', 'reference_date_type': 2}], 'distribution_format': [{'name': 'Electronic metadata record', 'version': '1.1'}], 'metadata_language_and_character_set': [{'dataset_character_set': 'utf-8', 'dataset_language': 'English', 'metadata_character_set': 'utf-8', 'metadata_language': 'English'}], 'online_resource': [{'application_profile': '', 'description': 2, 'linkage': 'https://catalogue.saeon.ac.za/records/10.15493/SAEON.FYNBOS.10000001', 'name': 'Interpolated observed weather data for the Cape Floristic Region'}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2025-10-16T11:36:41.735418', 'description': '', 'format': 'GEOMAP', 'format_version': '', 'hash': '', 'id': '7f7a6c95-c24a-417f-be2c-225aaed7e3c3', 'last_modified': None, 'metadata_modified': '2025-10-16T11:36:41.725285', 'mimetype': None, 'mimetype_inner': None, 'name': 'Interpolated observed weather data for the Cape Floristic Region', 'package_id': 'e66d4a36-8db1-4f93-9236-05523d2ad639', 'position': 0, 'resource_type': 'other', 'size': None, 'state': 'active', 'upload_mode': 'single', 'url': 'https://catalogue.saeon.ac.za/records/10.15493/SAEON.FYNBOS.10000001', 'url_type': None}], 'responsible_party': [{'electronic_mail_address': 'curation@saeon.nrf.ac.za', 'individual_name': 'South African Environmental Observation Network', 'position_name': 'Organisation', 'role': 'resource_provider', 'website': 'catalogue.saeon.ac.za'}], 'responsible_party_contact_address': [{'administrative_area': '', 'city': '', 'delivery_point': '', 'postal_code': ''}], 'responsible_party_contact_info': [{'facsimile': '', 'voice': ''}], 'spatial_parameters': [{'equivalent_scale': 'N/A', 'spatial_reference_system': 'EPSG: 4326', 'spatial_representation_type': '001'}], 'tags': [{'display_name': 'Climate science', 'id': 'b63237e7-b9c9-4d92-9a20-13bc7a956a76', 'name': 'Climate science', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'Climatology-Meteorology-Atmosphere', 'id': '48ad3286-3db6-4060-946b-92eaf1fc126d', 'name': 'Climatology-Meteorology-Atmosphere', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'atmosphere dynamics', 'id': 'd80be9c9-a5ca-418e-9e5b-a3a6dd7a3b44', 'name': 'atmosphere dynamics', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'climatology', 'id': '68f2471a-c336-4fc9-afd2-d252d6c41b7c', 'name': 'climatology', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'ecology', 'id': 'd8a5a11d-c929-4410-a2b3-65aa6b9d8263', 'name': 'ecology', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'environmental science', 'id': '30cb3d17-47d2-409e-9026-2c95191db59e', 'name': 'environmental science', 'state': 'active', 'vocabulary_id': None}], 'topic_and_saeoss_themes': [{'iso_topic_category': 'climatologyMeteorologyAtmosphere'}], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': None, 'author_email': None, 'creator_user_id': '64e47517-dce0-4a13-9ab7-ef1cfcd1d892', 'doi': '10.15493/BEA.DATA.10000074', 'featured': 'false', 'id': '653bf206-60b4-426f-8031-857ed4ffffeb', 'isopen': False, 'license_id': None, 'license_title': None, 'lineage_statement': '"Data was derived from the following sources: *The extent of sugar cane cultivation was determined from digitisation of maps published in Gers (2003). * This extent was correlated with two additional sources: crop extent published by DAFF (2014), which excludes sugar cane production and could be used as a verification of extent, and Land Use data (FAO, 2011), which could be used to verify the finer extent of cultivation. * Sugar cane theoretical yields were applied from Schulze, Hull, and Maharaj (2007).', 'maintainer': None, 'maintainer_email': None, 'metadata_created': '2025-09-25T13:51:51.505431', 'metadata_date': '2015-01-01T00:00', 'metadata_modified': '2025-10-17T09:37:57.386121', 'metadata_thumbnail': '', 'name': 'availability_of_sugar_cane_field_residues', 'notes': 'Data was derived from the following sources: *The extent of sugar cane cultivation was determined from digitisation of maps published in Gers (2003). * This extent was correlated with two additional sources: crop extent published by DAFF (2014), which excludes sugar cane production and could be used as a verification of extent, and Land Use data (FAO, 2011), which could be used to verify the finer extent of cultivation. * Sugar cane theoretical yields were applied from Schulze, Hull, and Maharaj (2007). * The total area and sugar cane production obtained from the above was correlated with published production figures (DAFF, 2014) and good correlation obtained - calculated sugar cane production of 22.5 Mt/a vs. published production in 2013/14 of 21.3 Mt/a. * Ratios of bagasse, sugar, and residue production was calculated from ratios in Hugo (2014) .', 'num_resources': 1, 'num_tags': 14, 'organization': {'id': 'c4a18544-cded-4488-9f43-c02a1094ad39', 'name': 'saeon', 'title': 'NRF-SAEON', 'type': 'organization', 'description': 'The South African Environmental Observation Network (SAEON) is a long-term environmental observation and research facility of the National Research Foundation (NRF). SAEON’s three focus areas are environmental observation, data management and education outreach. The Department of Science, Technology and Innovation (DSTI) provides core funding for these activities. ', 'image_url': '2025-08-01-083136.289314LogoSAEON.png', 'created': '2025-05-26T07:57:06.135422', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': 'c4a18544-cded-4488-9f43-c02a1094ad39', 'private': False, 'reference_system_additional_info': '', 'spatial': '{"type": "Polygon", "coordinates": [[[16.45214, -34.8341698957], [32.8925317467, -34.8341698957], [32.8925317467, -22.12503], [16.45214, -22.12503], [16.45214, -34.8341698957]]]}', 'state': 'active', 'title': 'Availability of Sugar Cane Field Residues', 'type': 'dataset', 'url': None, 'version': None, 'contact': [{'electronic_mail_address': 'curation@saeon.nrf.ac.za', 'individual_name': 'Wim Hugo', 'position_name': '', 'role': 'point_of_contact'}], 'contact_information': [{'facsimile': '', 'voice': ''}], 'dataset_reference_date': [{'reference': '2015-01-01T00:00', 'reference_date_type': 1}], 'distribution_format': [{'name': 'Electronic metadata record', 'version': '1.1'}], 'metadata_language_and_character_set': [{'dataset_character_set': 'utf-8', 'dataset_language': 'English', 'metadata_character_set': 'utf-8', 'metadata_language': 'English'}], 'online_resource': [{'application_profile': '', 'description': 2, 'linkage': 'https://catalogue.saeon.ac.za/records/10.15493/BEA.DATA.10000074', 'name': 'Availability of Sugar Cane Field Residues'}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2025-09-25T13:52:53.602259', 'description': '', 'format': '', 'format_version': '', 'hash': '', 'id': '736c3288-9873-40c9-b235-d3694cd201f3', 'last_modified': None, 'metadata_modified': '2025-09-25T13:52:53.567175', 'mimetype': None, 'mimetype_inner': None, 'name': 'Availability of Sugar Cane Field Residues', 'package_id': '653bf206-60b4-426f-8031-857ed4ffffeb', 'position': 0, 'resource_type': 'other', 'size': None, 'state': 'active', 'upload_mode': 'single', 'url': 'https://repository.saeon.ac.za/index.php/s/aa5pAfNjzabbcjF', 'url_type': None}], 'responsible_party': [{'electronic_mail_address': 'curation@saeon.nrf.ac.za', 'individual_name': 'South African Environmental Observation Network', 'position_name': 'Organisation', 'role': 'publisher', 'website': 'https://catalogue.saeon.ac.za/'}], 'responsible_party_contact_address': [{'administrative_area': '', 'city': 'Pretoria', 'delivery_point': '', 'postal_code': ''}], 'responsible_party_contact_info': [{'facsimile': '', 'voice': ''}], 'spatial_parameters': [{'equivalent_scale': 'N/A', 'spatial_reference_system': 'EPSG: 4326', 'spatial_representation_type': '001'}], 'tags': [{'display_name': 'Bioenergy', 'id': 'ca34cd72-b5a2-4f3f-81d8-61b65cd42ef8', 'name': 'Bioenergy', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'Commercial crop system', 'id': '7212f987-9a76-4d73-bf13-da41d2c5a0b1', 'name': 'Commercial crop system', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'Energy', 'id': '2e773657-95fa-4b64-9488-bb790e61bcbf', 'name': 'Energy', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'Farming', 'id': '0a7dc286-a500-49de-9647-3bbb4e46a0f5', 'name': 'Farming', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'agriculture', 'id': 'e9c2ba74-5eec-405f-bf77-5b0483eae3bf', 'name': 'agriculture', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'bagasse', 'id': '5d397292-d46b-4ffe-9868-986b0a4737e1', 'name': 'bagasse', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'biomass', 'id': '3599fc01-138e-449a-8618-4697ace9ddfe', 'name': 'biomass', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'fibre', 'id': 'b1727c3e-a49f-4b2e-b20f-3c339941f158', 'name': 'fibre', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'field residue', 'id': 'e3812ca4-f53d-4e3c-991b-93e27a697c52', 'name': 'field residue', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'ligno-cellulose', 'id': '1044ebdf-3fbd-400a-840a-691c46a9d0f6', 'name': 'ligno-cellulose', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'potential', 'id': '72c85e81-8819-41f9-9327-fb5418e73e31', 'name': 'potential', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'residue', 'id': '00467143-d7fa-48c1-b70f-20667c4b9fbe', 'name': 'residue', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'straw', 'id': '6fb6009f-3480-4660-a3f9-eb0e3724045a', 'name': 'straw', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'sugar cane', 'id': '8183afee-04eb-4a1b-94be-0d9cbb8a6d2c', 'name': 'sugar cane', 'state': 'active', 'vocabulary_id': None}], 'topic_and_saeoss_themes': [{'iso_topic_category': 'farming'}], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': None, 'author_email': None, 'creator_user_id': '64e47517-dce0-4a13-9ab7-ef1cfcd1d892', 'doi': '10.15493/BEA.DATA.10000082', 'featured': 'false', 'id': '40c74018-b618-40d0-bdfb-21db03dc6f41', 'isopen': False, 'license_id': None, 'license_title': None, 'lineage_statement': 'Data was derived from the following sources: * CSIR was commissioned by the BioEnergy Atlas to assemble known data on solid waste production from household and commercial sources in South Africa. This data was only available at provincial aggregate level, and derives from statistics published by the Department of Water and Sanitation, or recent studies funded by them. * Data from StatsSA (Census 2011) enabled the calculation of number of households within each planning zone that were serviced at the time, with the balance unserviced. * SAEON developed a model from national and international statistics linking waste water production and composition to household income. This model was used, based on StatsSA Census Data, to estimate the organic component produced by each household per planning zone (mesozone) annually. * These factors were used to disaggregate provincial production data, resulting in a value for unserviced and serviced organic wastewater from household sources to be calculated for each mesozone.', 'maintainer': None, 'maintainer_email': None, 'metadata_created': '2025-10-17T07:12:59.317624', 'metadata_date': '2025-10-17T00:00', 'metadata_modified': '2025-10-17T09:37:29.037486', 'metadata_thumbnail': '', 'name': 'serviced_and_unserviced_waste_water_organic_component', 'notes': 'Data was derived from the following sources: * CSIR was commissioned by the BioEnergy Atlas to assemble known data on solid waste production from household and commercial sources in South Africa. 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The ArcSIE tool was utilised in the Cathedral Peak research catchments, in KwaZulu-Natal, South Africa with the aim of creating an understanding of the hydropedological behaviour of the soils of three research catchments. A rule-based approach was first undertaken, followed by a case-based validation. A fuzzy membership map of each soil group was produced which integrated all inputs. The overall Kappa coefficient for Cathedral Peak-III is 0.57, for Cathedral Peak-VI is 0.59, and for Cathedral Peak-IX is 0.74. The hydropedological soil group maps achieved an appropriate representation of the complex nature of the soil-landscape relationship, with changes between one soil group and the next being gradual and continuous. Accuracies and inaccuracies within the fuzzy-membership maps can be quantified, allowing for a confidence rating in the use of these maps. 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', 'image_url': '2025-08-01-083136.289314LogoSAEON.png', 'created': '2025-05-26T07:57:06.135422', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': 'c4a18544-cded-4488-9f43-c02a1094ad39', 'private': False, 'reference_system_additional_info': '', 'spatial': '{"type": "Polygon", "coordinates": [[[29.1913018175082, -29.0085731718718], [29.2730807105465, -29.0085731718718], [29.2730807105465, -28.9799008295305], [29.1913018175082, -28.9799008295305], [29.1913018175082, -29.0085731718718]]]}', 'state': 'active', 'title': 'Digital soil mapping for hydropedological purposes of the Cathedral Peak research catchments, South Africa', 'type': 'dataset', 'url': None, 'version': None, 'contact': [{'electronic_mail_address': 'curation@saeon.nrf.ac.za', 'individual_name': 'Paul Gordijn', 'position_name': 'Field Technician', 'role': 'point_of_contact'}], 'contact_information': [{'facsimile': '', 'voice': ''}], 'dataset_reference_date': [{'reference': '2024-07-03T00:00', 'reference_date_type': 1}], 'distribution_format': [{'name': 'Electronic metadata record', 'version': '1.1'}], 'metadata_language_and_character_set': [{'dataset_character_set': 'utf-8', 'dataset_language': 'English', 'metadata_character_set': 'utf-8', 'metadata_language': 'English'}], 'metadata_standard': [{'name': 'SANS 1878-1:2011', 'version': '1.1'}], 'online_resource': [{'application_profile': '', 'description': 2, 'linkage': 'https://catalogue.saeon.ac.za/records/10.15493/SAEON.GFW.07042024', 'name': 'Digital soil mapping for hydropedological purposes of the Cathedral Peak research catchments, South Africa'}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2025-10-16T10:40:07.131567', 'description': '', 'format': 'SHP', 'format_version': '', 'hash': '', 'id': 'a82848d0-2741-42c4-8561-8480ff0eb18d', 'last_modified': None, 'metadata_modified': '2025-10-16T10:41:10.728592', 'mimetype': None, 'mimetype_inner': None, 'name': 'Digital soil mapping for hydropedological purposes of the Cathedral Peak research catchments, South Africa', 'package_id': 'e702984c-f2a0-4ff1-9462-7b9fc53e5dc3', 'position': 0, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://catalogue.saeon.ac.za/records/10.15493/SAEON.GFW.07042024', 'url_type': None}], 'responsible_party': [{'electronic_mail_address': '', 'individual_name': 'South African Environmental Observation Network', 'position_name': 'SAEON', 'role': 'resource_provider', 'website': 'catalogue.saeon.ac.za'}], 'responsible_party_contact_address': [{'administrative_area': '', 'city': '', 'delivery_point': '', 'postal_code': ''}], 'responsible_party_contact_info': [{'facsimile': '', 'voice': ''}], 'spatial_parameters': [{'equivalent_scale': 'N/A', 'spatial_reference_system': 'EPSG: 4326', 'spatial_representation_type': '001'}], 'tags': [{'display_name': 'Imagery-Basemaps-Earth Cover', 'id': '8895be3b-53e6-43b4-b77b-571ea5ff5252', 'name': 'Imagery-Basemaps-Earth Cover', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'digital soil mapping', 'id': '50ed18d2-f407-4cf5-b6a0-2fe04bf1bb98', 'name': 'digital soil mapping', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'hydropedology', 'id': 'eb38531c-24f3-49be-996a-2d8c60be898a', 'name': 'hydropedology', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'remote sensing', 'id': 'ff1b60ee-4c4d-44f9-89bc-8383e5bf5d96', 'name': 'remote sensing', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'soil', 'id': '90ec532c-460b-42c1-9a05-8b6e0be51257', 'name': 'soil', 'state': 'active', 'vocabulary_id': None}], 'topic_and_saeoss_themes': [{'iso_topic_category': 'imageryBaseMapsEarthCover'}], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': None, 'author_email': None, 'creator_user_id': '64e47517-dce0-4a13-9ab7-ef1cfcd1d892', 'doi': '10.15493/BEA.DATA.10000099', 'featured': 'false', 'id': '008cf5d6-83c0-4cfa-b833-7b04808d84c4', 'isopen': False, 'license_id': None, 'license_title': None, 'lineage_statement': 'Landcover data entries were obtained from Landsat satellite images used to generate landcover information into 72 landcover types; vegetation type is collected by SANBI; Aboveground woody biomass (carbon values) collected from high resolution data in the Savannah (CSIR- DMt/ha at 100m resolution) or from lower resolution data for the rest of the country (1km).', 'maintainer': None, 'maintainer_email': None, 'metadata_created': '2025-10-16T11:53:36.431154', 'metadata_date': '2023-06-23T00:00', 'metadata_modified': '2025-10-16T11:56:14.253772', 'metadata_thumbnail': '', 'name': 'bush_encroachment_and_land_cover_change', 'notes': 'The dataset shows landcover change between 1990 (lcov_1990) and 2013 (lcov_2013). Attribute information includes ; pagenumber, mapcode12 (vegetation type), dn_new (aboveground carbon values-DMt/ha), lcov_1990, lcov_2013, parent1990 (general landcover name), parent2013, old_new (landcover change), parent_old_new (landcover change by name), dn_ave_1990 (average for each landcover in 1990), dn_ave_2013, dn_ave_change (average carbon change between 1990 and 2013); and boolean information for the following: bush encroachment, grass encroachment, perturbation, degradation, restoration, habitat loss. Landcover data entries were obtained from Landsat satellite images used to generate landcover information into 72 landcover types; vegetation type is collected by SANBI; Aboveground woody biomass (carbon values) collected from high resolution data in the Savannah (CSIR- DMt/ha at 100m resolution) or from lower resolution data for the rest of the country (1km).', 'num_resources': 1, 'num_tags': 10, 'organization': {'id': 'c4a18544-cded-4488-9f43-c02a1094ad39', 'name': 'saeon', 'title': 'NRF-SAEON', 'type': 'organization', 'description': 'The South African Environmental Observation Network (SAEON) is a long-term environmental observation and research facility of the National Research Foundation (NRF). SAEON’s three focus areas are environmental observation, data management and education outreach. The Department of Science, Technology and Innovation (DSTI) provides core funding for these activities. ', 'image_url': '2025-08-01-083136.289314LogoSAEON.png', 'created': '2025-05-26T07:57:06.135422', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': 'c4a18544-cded-4488-9f43-c02a1094ad39', 'private': False, 'reference_system_additional_info': '', 'spatial': '{"type": "Polygon", "coordinates": [[[16.48, -34.8], [32.9, -34.8], [32.9, -22.1], [16.48, -22.1], [16.48, -34.8]]]}', 'state': 'active', 'title': 'Bush Encroachment and Land Cover Change', 'type': 'dataset', 'url': None, 'version': None, 'contact': [{'electronic_mail_address': 'curation@saeon.nrf.ac.za', 'individual_name': 'Data Curation', 'position_name': '', 'role': 'point_of_contact'}], 'contact_information': [{'facsimile': '', 'voice': ''}], 'dataset_reference_date': [{'reference': '2018-01-01T00:00', 'reference_date_type': 2}], 'distribution_format': [{'name': 'Electronic metadata record', 'version': '1.1'}], 'metadata_language_and_character_set': [{'dataset_character_set': 'utf-8', 'dataset_language': 'English', 'metadata_character_set': 'utf-8', 'metadata_language': 'English'}], 'metadata_standard': [{'name': 'SANS 1878-1:2011', 'version': '1.1'}], 'online_resource': [{'application_profile': '', 'description': '', 'linkage': 'https://catalogue.saeon.ac.za/records/10.15493/BEA.DATA.10000099', 'name': 'Bush Encroachment and Land Cover Change'}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2025-10-16T11:56:03.044528', 'description': '', 'format': 'GEOMAP', 'format_version': '', 'hash': '', 'id': 'ae0b8354-0344-4a6c-a6ec-2281da96ef1b', 'last_modified': None, 'metadata_modified': '2025-10-16T11:56:03.012500', 'mimetype': None, 'mimetype_inner': None, 'name': 'Bush Encroachment and Land Cover Change', 'package_id': '008cf5d6-83c0-4cfa-b833-7b04808d84c4', 'position': 0, 'resource_type': 'other', 'size': None, 'state': 'active', 'upload_mode': 'single', 'url': 'https://catalogue.saeon.ac.za/records/10.15493/BEA.DATA.10000099', 'url_type': None}], 'responsible_party': [{'electronic_mail_address': '', 'individual_name': 'South African Environmental Observation Network', 'position_name': 'Organisation', 'role': 'resource_provider', 'website': 'catalogue.saeon.ac.za'}], 'responsible_party_contact_address': [{'administrative_area': '', 'city': '', 'delivery_point': '', 'postal_code': ''}], 'responsible_party_contact_info': [{'facsimile': '', 'voice': ''}], 'spatial_parameters': [{'equivalent_scale': 'N/A', 'spatial_reference_system': 'EPSG: 4326', 'spatial_representation_type': '001'}], 'tags': [{'display_name': 'Imagery-Basemaps-Earth Cover', 'id': '8895be3b-53e6-43b4-b77b-571ea5ff5252', 'name': 'Imagery-Basemaps-Earth Cover', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'aboveground woody biomass', 'id': 'd70e9ece-6f66-425c-b968-27d8ca0e9b6f', 'name': 'aboveground woody biomass', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'bush encroachment', 'id': '28f6b44a-fc87-4a0f-99a9-0fe35f0778f7', 'name': 'bush encroachment', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'degradation', 'id': 'e36648ca-0354-47e6-82bc-4f6ca1e9a481', 'name': 'degradation', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'grass encroachment', 'id': '64d2ab52-5e98-4ee4-b682-f5ed25153868', 'name': 'grass encroachment', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'habitat loss', 'id': '4f029253-c65b-4fcd-a869-8275ae9723d6', 'name': 'habitat loss', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'landcover', 'id': '54b45451-0abb-47f6-81c5-47d06954721b', 'name': 'landcover', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'perturbation', 'id': '4993162e-83c9-4d6c-9ed2-4264eb57550c', 'name': 'perturbation', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'restoration', 'id': 'eba4a3e7-e03c-45d7-b834-6d5f5b1b503a', 'name': 'restoration', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'vegetation type', 'id': 'ff1a6433-60ae-47f9-be2c-4fe1b6a51655', 'name': 'vegetation type', 'state': 'active', 'vocabulary_id': None}], 'topic_and_saeoss_themes': [{'iso_topic_category': 'imageryBaseMapsEarthCover'}], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': None, 'author_email': None, 'creator_user_id': '64e47517-dce0-4a13-9ab7-ef1cfcd1d892', 'doi': '10.15493/BEA.DATA.10000068', 'featured': 'false', 'id': '9cc8eab9-ca76-46c4-add6-2232019fed39', 'isopen': False, 'license_id': None, 'license_title': None, 'lineage_statement': 'Data was derived from the following sources: * Extent of underutilised and subsistence farmland, data obtained from Department of Agriculture, Forestry, and Fisheries.On such land, Sweet Sorghum potential was calculated from data published by Schulze and Maharaj (2007) on sorghum-growing potential.', 'maintainer': None, 'maintainer_email': None, 'metadata_created': '2025-09-25T13:06:28.894530', 'metadata_date': '2014-01-01T00:00', 'metadata_modified': '2025-10-16T10:21:07.200019', 'metadata_thumbnail': '', 'name': 'production_of_sweet_sorghum_on_subsistence_and_underutilised_farmland', 'notes': 'Data was derived from the following sources: * Extent of underutilised and subsistence farmland, data obtained from Department of Agriculture, Forestry, and Fisheries. * On such land, Sweet Sorghum potential was calculated from data published by Schulze and Maharaj (2007) on sorghum-growing potential. * Grain, Sugar, and Residue production was calculated based on grain yields, and aggregated to mesozones for planning and feasibility analysis. * Grain, Sugar, and Residue ratios were derived from literature.', 'num_resources': 1, 'num_tags': 1, 'organization': {'id': 'c4a18544-cded-4488-9f43-c02a1094ad39', 'name': 'saeon', 'title': 'NRF-SAEON', 'type': 'organization', 'description': 'The South African Environmental Observation Network (SAEON) is a long-term environmental observation and research facility of the National 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SAEON’s three focus areas are environmental observation, data management and education outreach. The Department of Science, Technology and Innovation (DSTI) provides core funding for these activities. 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SAEON’s three focus areas are environmental observation, data management and education outreach. The Department of Science, Technology and Innovation (DSTI) provides core funding for these activities. 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Sessile and mobile epibenthic invertebrates are organisms that are part of the benthic community. These organisms perform crucial roles and ecosystem services that benefit the benthic community and marine environment as a whole. These organisms’ distribution is affected by many abiotic and biotic factors. This study aims to determine the distribution of both the mobile and sessile epibenthic invertebrates and to investigate the relationship between the mobile and sessile epibenthic invertebrates. The objectives are to measure the abundance and composition of both the mobile and sessile epibenthic invertebrates found on the inner continental shelf of Umhlanga, KwaZulu-Natal and to analyze the statistical relationship between the sessile epibenthic assemblage data and the mobile epibenthic assemblage data. These aims and objectives will be satisfied by sampling on the Umhlanga coast using a drop camera and a baited drop camera. Multivariate tests were run on the abundance data and a Pearson’s correlation test for the relationship between the mobile and sessile epibenthic invertebrates. This study will provide new data on the presence and abundance of understudied mobile invertebrates inhabiting unconsolidated sediments of the KZN inner continental shelf and contribute to our understanding of the relationship between sessile and mobile invertebrate epifauna on the unconsolidated inner continental shelf. It will also test and establish the usefulness of a baited drop-camera for sampling epibenthic invertebrates.", 'num_resources': 1, 'num_tags': 6, 'organization': {'id': '406569f5-01c7-4e26-93e8-f8b40b874dcc', 'name': 'south-african-institute-for-aquatic-biodiversity-saiab', 'title': 'NRF-SAIAB', 'type': 'organization', 'description': 'The South African Institute for Aquatic Biodiversity (NRF-SAIAB) is a national facility of the National Research Foundation (NRF). The NRF-SAIAB contributes to two National Operation Phakisa Labs through which South Africa has identified the potential to develop the Biodiversity Economy and the Blue Economy.', 'image_url': '2025-09-11-081630.579961SouthAfricanInstituteforAquaticBiodiversitylogo.svg.png', 'created': '2025-09-11T08:16:30.612011', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '406569f5-01c7-4e26-93e8-f8b40b874dcc', 'private': False, 'reference_system_additional_info': '', 'spatial': '{"type": "Polygon", "coordinates": [[[31.115365, -29.803761], [31.185535, -29.803761], [31.185535, -29.748017], [31.115365, -29.748017], [31.115365, -29.803761]]]}', 'state': 'active', 'title': 'Bathymetry data collected from Mobile Epibenthic Invertebrate Stations, November 2022', 'type': 'dataset', 'url': None, 'version': None, 'contact': [{'electronic_mail_address': 'T.Wanda@saiab.nrf.ac.za', 'individual_name': 'Thamsanqa Wanda', 'position_name': 'Geologist', 'role': 'point_of_contact'}], 'contact_information': [{'facsimile': '', 'voice': ''}], 'dataset_reference_date': [{'reference': '2023-01-27T00:00', 'reference_date_type': 1}], 'distribution_format': [{'name': 'Electronic metadata record', 'version': '1.1'}], 'metadata_language_and_character_set': [{'dataset_character_set': 'utf-8', 'dataset_language': 'English', 'metadata_character_set': 'utf-8', 'metadata_language': 'English'}], 'online_resource': [{'application_profile': '', 'description': 2, 'linkage': 'http://doi.org/10.15493/NRF.SAIAB.20232516', 'name': 'bathymetry_data_collected_from_mobile_epibenthic_invertebrate_stations_november_2022'}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2025-09-11T14:22:17.751814', 'description': '', 'format': '', 'format_version': '', 'hash': '', 'id': 'f6492885-e526-4883-ba79-61a161dc0806', 'last_modified': None, 'metadata_modified': '2025-09-12T08:29:23.519836', 'mimetype': None, 'mimetype_inner': None, 'name': 'Bathymetry data collected from Mobile Epibenthic Invertebrate Stations, November 2022', 'package_id': '209cd0fd-d80b-492e-969e-e8223d010104', 'position': 0, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://catalogue.saeon.ac.za/list/records/10.15493/NRF.SAIAB.20232516?search=68c2b42da71d058a420b0236&disableSidebar=false&showSearchBar=true', 'url_type': None}], 'responsible_party': [{'electronic_mail_address': '', 'individual_name': 'South African Institute for Aquatic Biodiversity ', 'position_name': 'SAIAB', 'role': 'owner', 'website': 'https://nrfsaiab.wixsite.com/gemapocean'}], 'responsible_party_contact_address': [{'administrative_area': '', 'city': 'Makhanda', 'delivery_point': 'Somerset Street', 'postal_code': '6139'}], 'responsible_party_contact_info': [{'facsimile': '', 'voice': ''}], 'spatial_parameters': [{'equivalent_scale': 'N/A', 'spatial_reference_system': 'EPSG: 4326', 'spatial_representation_type': '001'}], 'tags': [{'display_name': 'Oceans', 'id': '2547e672-a968-4048-814b-29a682525254', 'name': 'Oceans', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'SGB systems', 'id': 'e90bd4d4-da24-418e-a5b1-f9d0cf063793', 'name': 'SGB systems', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'bathymetry', 'id': '84d64091-149a-4cd4-bf97-f828e908fe76', 'name': 'bathymetry', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'hydrographic', 'id': '903bf930-556a-402c-a784-3c57de8bc65b', 'name': 'hydrographic', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'multibeam bathymetry', 'id': '1fe9236d-3571-4fe0-9305-f1b40579e991', 'name': 'multibeam bathymetry', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'reson', 'id': '4ff1fff4-deb9-4256-a9c0-f03802b2d0e7', 'name': 'reson', 'state': 'active', 'vocabulary_id': None}], 'topic_and_saeoss_themes': [{'iso_topic_category': 'oceans'}], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': None, 'author_email': None, 'creator_user_id': '64e47517-dce0-4a13-9ab7-ef1cfcd1d892', 'doi': '10.15493/BEA.DATA.250320-20', 'featured': 'false', 'id': '695aa705-9c99-41b3-983b-6bbc25d36d45', 'isopen': False, 'license_id': None, 'license_title': None, 'lineage_statement': "A cost surface using a digital elevation model (SRTM v3) [~30m] was used as the basis, with main water features (rivers and dams) and a slope threshold of 15 degrees removed as obstacles from the surface. Start points (derived from a 1km x 1km raster grid, and end points (the NGI road layer) rasterised at a 100m x 100m resolution, both using the StatsSA BSU grid projection ['+proj=aea +lat_1=-22 +lat_2=-38 +lat_0=-30 +lon_0=25 +x_0=1400000 +y_0=1300000 +datum=WGS84 +units=m +no_defs]) were used as location inputs. Non-NA raster values from these location inputs were converted to points (the centroid of each Non-NA pixel), then reprojected to the same resolution as the cost surface (e.g. EPSG:4326 - WGS 84 – Geographic). A variable resolution window was used for modelling [based on 250 start points at a time, each linked to 100 closest road points [end points] to create an extent and perform the modelling operation in reasonably sized chunks].", 'maintainer': None, 'maintainer_email': None, 'metadata_created': '2025-09-11T14:42:20.726226', 'metadata_date': '2023-01-01T00:00', 'metadata_modified': '2025-09-11T14:43:53.300875', 'metadata_thumbnail': '', 'name': 'virtual_roads_for_the_bioenergy_atlas', 'notes': "Virtual roads representing theoretical paths [roads] starting every 1km apart (across South Africa) from areas where no roads exists to the closest road segment in South Africa's National Geo-spatial Information (NGI) 2019 road layer (http://www.ngi.gov.za) -- for use in the SAEON BioEnergy Atlas feasibility model. A cost surface using a digital elevation model (SRTM v3) [~30m] was used as the basis, with main water features (rivers and dams) and a slope threshold of 15 degrees removed as obstacles from the surface. Start points (derived from a 1km x 1km raster grid, and end points (the NGI road layer) rasterised at a 100m x 100m resolution, both using the StatsSA BSU grid projection ['+proj=aea +lat_1=-22 +lat_2=-38 +lat_0=-30 +lon_0=25 +x_0=1400000 +y_0=1300000 +datum=WGS84 +units=m +no_defs]) were used as location inputs. Non-NA raster values from these location inputs were converted to points (the centroid of each Non-NA pixel), then reprojected to the same resolution as the cost surface (e.g. EPSG:4326 - WGS 84 – Geographic). A variable resolution window was used for modelling [based on 250 start points at a time, each linked to 100 closest road points [end points] to create an extent and perform the modelling operation in reasonably sized chunks]. The scikit-image python package was used to find the shortest path through each cost surface array cropped using the variable window extent, using a fully connected (i.e diagonal pixels) minimum cost path (MCU) algorithm. All outputs were merged to create a seamless Virtual roads layer with 1 051 696 individual paths covering South Africa.", 'num_resources': 1, 'num_tags': 1, 'organization': {'id': 'c4a18544-cded-4488-9f43-c02a1094ad39', 'name': 'saeon', 'title': 'NRF-SAEON', 'type': 'organization', 'description': 'The South African Environmental Observation Network (SAEON) is a long-term environmental observation and research facility of the National Research Foundation (NRF). SAEON’s three focus areas are environmental observation, data management and education outreach. The Department of Science, Technology and Innovation (DSTI) provides core funding for these activities. ', 'image_url': '2025-08-01-083136.289314LogoSAEON.png', 'created': '2025-05-26T07:57:06.135422', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': 'c4a18544-cded-4488-9f43-c02a1094ad39', 'private': False, 'reference_system_additional_info': 'Temporal extent: 2020-01-01/2021-01-01', 'spatial': '{"type": "Polygon", "coordinates": [[[18.418274, -34.421526], [32.773142, -34.421526], [32.773142, -22.771933], [18.418274, -22.771933], [18.418274, -34.421526]]]}', 'state': 'active', 'title': 'Virtual Roads for the BioEnergy Atlas', 'type': 'dataset', 'url': None, 'version': None, 'contact': [{'electronic_mail_address': 'm.pienaar@saeon.nrf.ac.za', 'individual_name': 'Marc Pienaar', 'position_name': 'Data Science Lead', 'role': 'point_of_contact'}], 'contact_information': [{'facsimile': '', 'voice': ''}], 'dataset_reference_date': [{'reference': '2023-01-01T00:00', 'reference_date_type': 1}], 'distribution_format': [{'name': 'Vector', 'version': '1.1'}], 'metadata_language_and_character_set': [{'dataset_character_set': 'utf-8', 'dataset_language': 'English', 'metadata_character_set': 'utf-8', 'metadata_language': 'English'}], 'metadata_standard': [{'name': 'SANS 1878-1:2011', 'version': '1.1'}], 'online_resource': [{'application_profile': '', 'description': 2, 'linkage': 'http://doi.org/10.15493/BEA.DATA.250320-20', 'name': 'virtual_roads_for_the_bioenergy_atlas'}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2025-09-11T14:43:39.502682', 'description': '', 'format': 'SHP', 'format_version': '', 'hash': '', 'id': '21133e12-ea91-4955-866c-62ae4330e4ac', 'last_modified': None, 'metadata_modified': '2025-09-11T14:43:39.493080', 'mimetype': None, 'mimetype_inner': None, 'name': 'Virtual Roads for the BioEnergy Atlas', 'package_id': '695aa705-9c99-41b3-983b-6bbc25d36d45', 'position': 0, 'resource_type': 'other', 'size': None, 'state': 'active', 'upload_mode': 'single', 'url': 'https://repository.saeon.ac.za/index.php/s/AR3iz9wrn4YFmcb', 'url_type': None}], 'responsible_party': [{'electronic_mail_address': '', 'individual_name': 'South African Environmental Observation Network', 'position_name': 'SAEON', 'role': 'originator', 'website': 'https://catalogue.saeon.ac.za'}], 'responsible_party_contact_address': [{'administrative_area': '', 'city': '', 'delivery_point': '', 'postal_code': ''}], 'responsible_party_contact_info': [{'facsimile': '', 'voice': ''}], 'spatial_parameters': [{'equivalent_scale': '100x100', 'spatial_reference_system': 'EPSG: 4326', 'spatial_representation_type': '001'}], 'tags': [{'display_name': 'Imagery-Basemaps-Earth Cover', 'id': '8895be3b-53e6-43b4-b77b-571ea5ff5252', 'name': 'Imagery-Basemaps-Earth Cover', 'state': 'active', 'vocabulary_id': None}], 'topic_and_saeoss_themes': [{'iso_topic_category': 'imageryBaseMapsEarthCover'}], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': None, 'author_email': None, 'creator_user_id': 'edabd58a-206b-4837-ae44-ff17c126fe88', 'doi': '10.15493/NRF.SAIAB.20232505', 'featured': 'false', 'id': '0b93f04a-5fa2-4c7c-b9a3-e3451557d702', 'isopen': False, 'license_id': None, 'license_title': None, 'lineage_statement': 'This dataset consists of XYZ points below the sea surface and relative to the mean sea level. This data was collected under the ACEP SMART ZONES MPA project (2021 – 2023) using the ACEP Geophysics and Mapping Platform.', 'maintainer': None, 'maintainer_email': None, 'metadata_created': '2025-09-11T11:33:32.895385', 'metadata_date': '2023-01-26T00:00', 'metadata_modified': '2025-09-11T11:34:14.730926', 'metadata_thumbnail': '', 'name': 'steep', 'notes': "This dataset forms part of the South African Institute for Aquatic Biodiversity (SAIAB)'s collection of Bathymetry data for the African Coelacanth Ecosystem Programme (ACEP) Smart Zones MPA. This multi-disciplinary study will begin at the start of implementation of two new MPAs (uThukela MPA and Protea Banks MPA, both proclaimed in 2019), and will generate the relevant data needed to underpin an evidence-based approach to adaptive management of the MPAs, within a “SMART” framework. This framework defines specific objectives for the different MPA zones; develops measurable indicators of success for each zone; sets achievable goals given the limited resources available for planning and management; ensures that the research findings are relevant (to both biodiversity and human stakeholders). This is a rare time-sensitive opportunity to conduct baseline surveys of the geology, benthic biodiversity (sessile and mobile species), reef-associated ichthyoplankton and mero-zooplankton and fish communities of mesophotic (40-150m) soft-coral and sponge-dominated reefs and submarine habitats located in three different management zones at the initiation of management of two brand new MPAs, against which long-term monitoring data can be compared to assess the effectiveness of the MPAs in achieving their objectives. The balanced sampling design is such that it will also initiate a “natural experiment” that over time will investigate the effect of no-take zones on fish diversity and abundance, benthic community structure, and trophic complexity. This will also enable the determination of the value of the MPA for fisheries sustainability support and resilience to disturbances caused by extrinsic factors such as pollution or climate change. Additionally, this study will assess whether the zonation plan provides for representation of all reef and canyon types within each zone or if there is unbalanced coverage for certain reefs and in certain zones. This is important to assess at the initiation of the MPA, especially to ensure that the interpretation of monitoring results in future, which compare ecosystems and fish on reefs and canyons in the mesophotic zone, are not flawed by natural differences from the outset due to the selection of zone boundaries.", 'num_resources': 1, 'num_tags': 2, 'organization': {'id': '406569f5-01c7-4e26-93e8-f8b40b874dcc', 'name': 'south-african-institute-for-aquatic-biodiversity-saiab', 'title': 'NRF-SAIAB', 'type': 'organization', 'description': 'The South African Institute for Aquatic Biodiversity (NRF-SAIAB) is a national facility of the National Research Foundation (NRF). 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This framework defines specific objectives for the different MPA zones; develops measurable indicators of success for each zone; sets achievable goals given the limited resources available for planning and management; ensures that the research findings are relevant (to both biodiversity and human stakeholders). This is a rare time-sensitive opportunity to conduct baseline surveys of the geology, benthic biodiversity (sessile and mobile species), reef-associated ichthyoplankton and mero-zooplankton and fish communities of mesophotic (40-150m) soft-coral and sponge-dominated reefs and submarine habitats located in three different management zones at the initiation of management of two brand new MPAs, against which long-term monitoring data can be compared to assess the effectiveness of the MPAs in achieving their objectives. 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