| packages |
[{'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. 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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. 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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/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. 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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": [[[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': 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'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 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'lineage_statement': 'The dataset shows Acacia mearnsii - bark yield estimates allocated to mesozones. 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