| packages |
[{'author': None, 'author_email': None, 'creator_user_id': '64e47517-dce0-4a13-9ab7-ef1cfcd1d892', 'doi': '10.15493/BEA.DATA.10000080', 'featured': 'false', 'id': '964d2862-b467-40db-bb50-aaaa88880934', 'isopen': False, 'license_id': None, 'license_title': None, 'lineage_statement': '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).', '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'}], 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'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 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'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': 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'lineage_statement': 'The dataset shows Acacia mearnsii - bark yield estimates allocated to mesozones. Yield estimates were derived from Schulze R.E. and Maharaj M. (2007) and then allocated to mesozones by combining with a base mesozone layer obtained from the CSIR Geospatial Analysis Platform (GAP). The map of climatically optimum growth areas shows the main potential areas for A. mearnsii to be in a strip along the coast of the Eastern Cape, parts of the midlands and northwest of KwaZulu-Natal and a strip in Mpumalanga, with smaller patches of climatically optimum areas elsewhere.', 'maintainer': None, 'maintainer_email': None, 'metadata_created': '2025-10-17T09:32:50.896907', 'metadata_date': '2025-10-17T00:00', 'metadata_modified': '2025-10-17T09:35:51.349560', 'metadata_thumbnail': '', 'name': 'acacia_mearnsii_bark_yield_estimates_per_mesozone', 'notes': 'The dataset shows Acacia mearnsii - bark yield estimates allocated to mesozones. Yield estimates were derived from Schulze R.E. and Maharaj M. (2007) and then allocated to mesozones by combining with a base mesozone layer obtained from the CSIR Geospatial Analysis Platform (GAP). The map of climatically optimum growth areas shows the main potential areas for A. mearnsii to be in a strip along the coast of the Eastern Cape, parts of the midlands and northwest of KwaZulu-Natal and a strip in Mpumalanga, with smaller patches of climatically optimum areas elsewhere.', '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. 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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': 'Acacia mearnsii', 'id': '5c694886-9e84-460d-9f40-8e6b6d76c961', 'name': 'Acacia mearnsii', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'Agriculture', 'id': '76bc5b3e-aa3e-4117-a94e-53d07473952b', 'name': 'Agriculture', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'Commercial forestry', 'id': 'c9cdbbe0-563e-48b0-b276-8873fa70a327', 'name': 'Commercial forestry', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'Forestry distribution', 'id': 'a373ef67-e2f7-4c4c-a9f1-42afafc3032f', 'name': 'Forestry distribution', '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': 'acacia mearnsii', 'id': '8a3f959b-ce05-41a8-b046-fbcf0950cbd9', 'name': 'acacia mearnsii', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'agriculture', 'id': 'e9c2ba74-5eec-405f-bf77-5b0483eae3bf', 'name': 'agriculture', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'biomass', 'id': '3599fc01-138e-449a-8618-4697ace9ddfe', 'name': 'biomass', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'mesozones', 'id': 'ec11507b-eb72-4e46-a0b4-04378e39be8c', 'name': 'mesozones', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'yield', 'id': 'dc14a921-0c4d-4efa-b154-52a15b712556', 'name': 'yield', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'yield estimation', 'id': 'ffb78bb7-ddac-4f32-b75f-0182de795c57', 'name': 'yield estimation', '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.10000014', 'featured': 'false', 'id': 'c1c3fa77-dfe7-47d0-a780-b83e0b8f2315', 'isopen': False, 'license_id': None, 'license_title': None, 'lineage_statement': "The dataset shows climatically optimum growth areas and yield estimates of Pinus taeda allocated to mesozones. 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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. 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