| 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'}], '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. 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.', 'num_resources': 1, 'num_tags': 8, '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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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). 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