| packages |
[{'author': None, 'author_email': None, 'creator_user_id': '64e47517-dce0-4a13-9ab7-ef1cfcd1d892', 'doi': '10.15493/NRF.SAIAB.20232509', 'featured': 'false', 'id': '9443de7a-7bf5-46e9-b05b-a457c4ce3486', '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': '2025-09-11T14:01:12.019504', 'metadata_date': '202301-02-07T00:00', 'metadata_modified': '2025-09-12T08:45:39.553236', 'metadata_thumbnail': '', 'name': 'bathymetry_data_collected_from_ballito_birthday_november_2021', '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. This dataset consists of XYZ points below the sea surface and relative to the mean sea level. 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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': '2025-09-11T14:14:08.850568', 'metadata_date': '2023-01-27T00:00', 'metadata_modified': '2025-09-12T08:41:16.578676', 'metadata_thumbnail': '', 'name': 'bathymetry_data_collected_from_zinkwazi_november_2021', '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 the 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. 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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. 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.", '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": [[[31.52826, -29.426584], [31.577445, -29.426584], [31.577445, -29.372258], [31.52826, -29.372258], [31.52826, -29.426584]]]}', 'state': 'active', 'title': 'Bathymetry data collected from Zinkwazi, November 2021', '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.20232511', 'name': 'bathymetry_data_collected_from_zinkwazi_november_2021'}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2025-09-11T14:14:58.221011', 'description': '', 'format': '', 'format_version': '', 'hash': '', 'id': 'a7c104c4-a7b7-4a0f-9ddc-3e2daf60f617', 'last_modified': None, 'metadata_modified': '2025-09-12T08:41:16.588713', 'mimetype': None, 'mimetype_inner': None, 'name': 'Bathymetry data collected from Zinkwazi, November 2021', 'package_id': 'ed816ac3-0461-4c85-b09f-16b54b0ad3f3', 'position': 0, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://catalogue.saeon.ac.za/list/records/10.15493/NRF.SAIAB.20232511?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/NRF.SAIAB.20232516', 'featured': 'false', 'id': '209cd0fd-d80b-492e-969e-e8223d010104', 'isopen': False, 'license_id': None, 'license_title': None, 'lineage_statement': 'This dataset consists of locations below the surface of the water where the depth of water is precisely known relative to MSL. Sessile and mobile epibenthic invertebrates are organisms that are part of the benthic community.', 'maintainer': None, 'maintainer_email': None, 'metadata_created': '2025-09-11T14:21:53.400156', 'metadata_date': '2023-01-27T00:00', 'metadata_modified': '2025-09-12T08:29:23.503760', 'metadata_thumbnail': '', 'name': 'bathymetry_data_collected_from_mobile_epibenthic_invertebrate_stations_november_2022', '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 dataset is used for seabed analysis, the interpretation and creation of derivatives for geomorphological and statistical analysis in comparison with biological metrics. This dataset consists of locations below the surface of the water where the depth of water is precisely known relative to MSL. 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). 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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. 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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. 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