Zacarias Fresno Lopez, T. Cancellario, D. Fontaneto, L. Kamburska, K. Karimullah, R. Wallace, E. Walsh, Radoslav Smoľák
{"title":"A georeferenced dataset for occurrence records of the phylum Rotifera in Africa","authors":"Zacarias Fresno Lopez, T. Cancellario, D. Fontaneto, L. Kamburska, K. Karimullah, R. Wallace, E. Walsh, Radoslav Smoľák","doi":"10.4081/jlimnol.2023.2116","DOIUrl":"https://doi.org/10.4081/jlimnol.2023.2116","url":null,"abstract":"We report a dataset of all known and published occurrence records of animals of the phylum Rotifera, including Bdelloidea, Monogononta, and Seisonacea (with the exclusion of Acanthocephala) for Africa and surrounding islands and archipelagos. The dataset includes 24,704 records of 914 taxa (subspecies: 38; species: 783; genus: 76; family: 17), gathered from 610 published papers. The published literature spans from 1854 to 2022, with the highest number of records in the decades 1990-1999 and 2010-2019. The African countries with the highest number of taxa are Nigeria, Algeria, South Africa, and Democratic Republic of the Congo, whereas no records are yet available for a dozen countries. The number of species known from each country can be explained mostly by sampling efforts, measured as the number of papers published for each country up to now. The dataset is available through the Open Science Framework (OSF) and in the Global Biodiversity Information Facility (GBIF).","PeriodicalId":50164,"journal":{"name":"Journal of Limnology","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2023-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45060150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Oggioni, D. Ruggiu, G. Morabito, A. Pugnetti, K. Sparber, R. Cozza, P. Panzani, T. Ruffoni, M. Austoni
{"title":"A long-term (1986-2010) phytoplankton dataset from the LTER-Italy site Lake Candia","authors":"A. Oggioni, D. Ruggiu, G. Morabito, A. Pugnetti, K. Sparber, R. Cozza, P. Panzani, T. Ruffoni, M. Austoni","doi":"10.4081/jlimnol.2023.2122","DOIUrl":"https://doi.org/10.4081/jlimnol.2023.2122","url":null,"abstract":"In this paper we describe a 25-year (1986-2010) dataset of phytoplankton cell density abundance and biovolume in Lake Candia, a eutrophic, natural, small, and shallow lake located in north-western Italy, with data that are made available through the GBIF repository. The lake belongs to the national (LTER-Italy), European (LTER-Europe) and International (ILTER) long-term ecological research (LTER) networks. Phytoplankton samples were collected approximately monthly at the maximum depth station of the lake (7.7 m) and analysed with the inverted microscope, estimating both the cell density abundance and biovolume of each taxon. The dataset includes 10,120 georeferenced occurrences related to 545 taxa. During this 25-year period, the lake underwent profound modifications mainly related to the lake biomanipulation activities addressed to the management of aquatic macrophyte and to the evolution of the trophic condition. Making this dataset available represents a contribution to the current activities of the LTER networks for defining and reconstructing spatial and temporal dynamics and to identify and compare reliable trends.","PeriodicalId":50164,"journal":{"name":"Journal of Limnology","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46116998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Littoral chironomids and oligochaetes in the subalpine Lake Maggiore: a first dataset","authors":"S. Zaupa, A. Boggero, L. Kamburska","doi":"10.4081/jlimnol.2022.2124","DOIUrl":"https://doi.org/10.4081/jlimnol.2022.2124","url":null,"abstract":"A dataset of 227 oligochaetes and 373 chironomids occurrence records from the subalpine Lake Maggiore, a large and deep temperate lake in Northern-Western Italy and Switzerland was developed within the Interreg Italy-Switzerland 2014-2020 Parchi Verbano Ticino Project (ID:481668) funded by the European Regional Development Fund (ERDF). The lake belongs to the national (LTER-Italy), European (LTER-Europe) and International (ILTER) long-term ecological research networks. Data were collected during the summer-autumn period in 2019-2021. Chironomids (Insecta, Diptera) and oligochaetes (Annelida, Clitellata) were identified to genus/species gr./species level by the authors. All 600 occurrence records are georeferenced and organised in a standardised Darwin Core Archive format. These data gathered along the littoral areas of Lake Maggiore will contribute to the development of common implementation strategies for shared and sustainable water management level of the lake, with particular reference to the protected natural areas (sites belonging to Natura 2000 network in Italy and to the Emerald Network in Switzerland). The authors strongly believe in the great potential of open access occurrence records in biogeographical studies and ecological research in the context of global environmental changes. For that reason, the dataset has been uploaded to the Global Biodiversity Information Facility (GBIF), an intergovernmental free and open access biodiversity data infrastructure.","PeriodicalId":50164,"journal":{"name":"Journal of Limnology","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2023-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44133656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Canterbury Museum mayfly collection data resource","authors":"J. Ridden, T. Hitchings, Tim R. Hitchings","doi":"10.4081/jlimnol.2023.2097","DOIUrl":"https://doi.org/10.4081/jlimnol.2023.2097","url":null,"abstract":"A nationally significant collection of mayflies that has been amassed and curated at Canterbury Museum, Christchurch, New Zealand is described. A project to formally catalogue the backlog of this collection was completed in 2018. This collection has been primarily worked on, added to, and curated by Terry Hitchings since the early 1990s, with his son Tim Hitchings assisting this work since the late 2000s. This paper outlines this process involved in cataloguing the collection and preparing the data for publication to online biorepositories. The dataset was published to the Atlas of Living Australia (ALA) and the Global Biodiversity Information Facility (GBIF) in late 2021. This dataset contains just under 49,000 published specimen records with high quality field collection information. It represents nearly all currently described mayfly species in New Zealand. Areas of collecting focus include most of the South Island of New Zealand, with collecting gaps in South Westland and Marlborough. There are large collecting gaps throughout the North Island of New Zealand. An overview of the trends shown in the dataset is provided. Future work is identified and recommended to enhance and improve this dataset to highlight and promote freshwater ecosystems in New Zealand.","PeriodicalId":50164,"journal":{"name":"Journal of Limnology","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2023-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42040150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Castillo‐Escrivà, Á. Baltanás, A. Camacho, D. Horne, Joan Lluís Pretus, F. Mesquita‐Joanes
{"title":"IMOST: a database for non-marine ostracods in the Iberian Peninsula, the Balearic Islands and Macaronesia","authors":"A. Castillo‐Escrivà, Á. Baltanás, A. Camacho, D. Horne, Joan Lluís Pretus, F. Mesquita‐Joanes","doi":"10.4081/jlimnol.2023.2115","DOIUrl":"https://doi.org/10.4081/jlimnol.2023.2115","url":null,"abstract":"Ostracods are common microcrustaceans in inland waters, widely used as (palaeo-) environmental indicators. Information on their species distribution worldwide is extremely fragmentary, and usually biased towards some regions, hampering attaining a general view of their biogeography. The Iberian Peninsula, the Balearic Islands and Macaronesia are considered biodiversity hotspots as part of the Mediterranean Region, whose non-marine ostracod fauna was reviewed in the 1990s accounting for 88 species. Most of these data were included in the NODE database (Non-marine Ostracod Distribution in Europe). Here, we present IMOST (Ibero-Balearic and Macaronesian OSTracod database), a non-marine ostracod database for the Iberian Peninsula and the Balearic and Macaronesian Islands, incorporating data included in NODE plus many new records from recently published studies and new unpublished observations. Our database stores data in separated and standardised spreadsheets, one for each data source. Moreover, the database also offers updated, reviewed and accurate coordinates of the cited occurrence and taxonomic identification. According to the data compiled in IMOST, we updated the list of non-marine ostracods in the studied region from 88 to 118 species. Nevertheless, we expect that the actual number of species for the included regions should be higher, considering other Mediterranean countries with smaller areas but more extensive surveys (e.g. 152 species in Italy). The updated database is instrumental for our understanding of the biodiversity and biogeographic patterns of these organisms in this hotspot, as well as for analysing their species-environment relationships in a context of global changes.","PeriodicalId":50164,"journal":{"name":"Journal of Limnology","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2023-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49151965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"AMI-KMNP dataset: Occurrence records of aquatic macroinvertebrate species from a 10-year-long biodiversity survey in SE Hungary","authors":"P. Boda, A. Móra, Z. Csabai","doi":"10.4081/jlimnol.2023.2118","DOIUrl":"https://doi.org/10.4081/jlimnol.2023.2118","url":null,"abstract":"We outline a 100% georeferenced dataset of aquatic macroinvertebrate occurrence records collected from the operational area of the Körös-Maros National Park Directorate (SE Hungary) between 2012 and 2021. The species-level dataset includes 25,935 records of 644 taxa from 625 localities of wide variety of freshwater habitats from soda pans to lowland marshes and small watercourses to medium-sized and larger rivers. Four non-biting midge species are reported for the first time from the Hungarian fauna. The dataset is available through the Global Biodiversity Information Facility (GBIF).","PeriodicalId":50164,"journal":{"name":"Journal of Limnology","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2023-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42532461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Giuseppe Garlasché, Giulia Borgomaneiro, R. Piscia, M. Manca, Ester M. Eckert, D. Fontaneto
{"title":"Metabarcoding to monitor the crustacean zooplankton of a lake improves when using a reference DNA library from local samples","authors":"Giuseppe Garlasché, Giulia Borgomaneiro, R. Piscia, M. Manca, Ester M. Eckert, D. Fontaneto","doi":"10.4081/jlimnol.2023.2087","DOIUrl":"https://doi.org/10.4081/jlimnol.2023.2087","url":null,"abstract":"Biodiversity surveys through morphology provide invaluable data to inform biological monitoring efforts, involving specialised taxonomic skills that are not always available. The revolution brought by the advent of metabarcoding associated to massive sequencing is currently seen as a potential advance, even if different approaches may often provide different results. Here we test if reliable results from metabarcoding can be obtained by i) basing the analyses on a detailed knowledge of the local diversity from morphology, ii) applying tools from DNA taxonomy to create a local reference library, ii) developing custom primers, taking as example the crustacean zooplankton of a subalpine lake in Northern Italy, Lake Maggiore. We support the idea that occurrences from metabarcoding can be reliable, especially with targeted primers, but we confirm that read numbers from massive sequencing could not be related to abundance of individuals in our analyses. Data from metabarcoding can thus be used to reliably monitor species occurrence in the lake, but not changes in abundance.","PeriodicalId":50164,"journal":{"name":"Journal of Limnology","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2023-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44308908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
V. Ferrari, Arianna Gualdi, I. Bertani, D. Fontaneto, L. Kamburska, K. Karimullah, F. Marrone, U. Obertegger, G. Rossetti, R. Tiberti, T. Cancellario
{"title":"A georeferenced dataset of Italian occurrence records of the phylum Rotifera","authors":"V. Ferrari, Arianna Gualdi, I. Bertani, D. Fontaneto, L. Kamburska, K. Karimullah, F. Marrone, U. Obertegger, G. Rossetti, R. Tiberti, T. Cancellario","doi":"10.4081/jlimnol.2023.2107","DOIUrl":"https://doi.org/10.4081/jlimnol.2023.2107","url":null,"abstract":"We report a dataset of known and published occurrence records of Italian taxa from species (and subspecies) to family rank of the phylum Rotifera; we considered only Bdelloidea, Monogononta, and Seisonacea, and did not include Acanthocephala. The dataset includes 15,525 records (12,015 of which with georeferenced coordinates) of 584 valid species and subspecies names, gathered from 332 published papers. The published literature spans the period from 1838 to 2022, with the lowest number of papers published during the Second World War followed by an increasing number of papers, from 20 to more than 60 in each decade. The Italian regions with the highest number of records and species are Emilia-Romagna, Lombardy, and Piedmont, whereas no records are known for Molise. The number of species known from each region mostly mirrors sampling efforts, measured as the number of publications per region. The dataset is available through the Open Science Framework (OSF), and all the georeferenced occurrence data have been uploaded to the Global Biodiversity Information Facility (GBIF).","PeriodicalId":50164,"journal":{"name":"Journal of Limnology","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2023-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43758694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A georeferenced dataset of living and sedimentary remains of diatom community in Lake Maggiore","authors":"S. Musazzi, M. Austoni, A. Marchetto","doi":"10.4081/jlimnol.2023.2108","DOIUrl":"https://doi.org/10.4081/jlimnol.2023.2108","url":null,"abstract":"We publish a dataset on planktonic and benthic diatom occurrence in Lake Maggiore, the second Italian lake for depth and surface. Despite their extensive use in water quality biomonitoring, and their relevance among phytoplankton groups, research on benthic diatoms in Lake Maggiore are scarce. Diatoms have been collected from surface sediments, littoral stones, macrophytes and water column, in different times and with different purposes during the last 40 years of the trophic history of the lake. Dataset includes 4124 occurrences relating to 293 taxa, 269 of which were identified at species level, 16 at subspecies level and 8 at the genus level. All occurrences are georeferenced.","PeriodicalId":50164,"journal":{"name":"Journal of Limnology","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2023-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41764039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
L. Musinguzi, M. Olokotum, H. Nakiyende, R. Egessa, Vicent Kiggundu, Ghandi Willy Pabire, S. Bassa, M. Nsega, Ashiraf Kamya, Philip Rwezawula, Jessy Lugya, Godfrey Magezi, J. Naluwayiro, V. Natugonza
{"title":"Primary biodiversity data on zooplankton, macroinvertebrates, and fish from freshwater ecosystems of Uganda","authors":"L. Musinguzi, M. Olokotum, H. Nakiyende, R. Egessa, Vicent Kiggundu, Ghandi Willy Pabire, S. Bassa, M. Nsega, Ashiraf Kamya, Philip Rwezawula, Jessy Lugya, Godfrey Magezi, J. Naluwayiro, V. Natugonza","doi":"10.4081/jlimnol.2023.2117","DOIUrl":"https://doi.org/10.4081/jlimnol.2023.2117","url":null,"abstract":"Effective conservation requires reliable data and information on the status of biodiversity. The conservation of freshwater biodiversity lags behind terrestrial and marine biodiversity because data and information limitations are greatest in freshwater ecosystems. Given that freshwater ecosystems are inhabited by disproportionately more species than other ecosystems, paucity of data and information threatens many species and dependent ecosystem services. Data and information on freshwater biodiversity is limited mainly because few freshwater ecosystems are considered for regular monitoring. However, even existing data is scattered and in non-user-friendly formats, limiting accessibility and use. It is desirable to make freshwater biodiversity data and information accessible everywhere so that it attains its full potential in guiding conservation. To increase accessibility to freshwater biodiversity data in Uganda, we present 34 datasets covering three major freshwater taxa: zooplankton, macroinvertebrates, and fish within freshwater ecosystems in the country. The datasets provide occurrence records and corresponding abundance data where applicable for the three major groups. The datasets which are available through the Global Biodiversity Information Facility (GBIF) cover a long period from 1971-2021 and have a total of 56,104 occurrence records. Of these records, 8,674 records were published in 2022. The data were mobilized from primary biodiversity surveys conducted by scientists at the National Fisheries Resources Research Institute (NaFIRRI) in Uganda. The surveys covered most of the water bodies in the country. The datasets are envisaged to increase accessibility to data for freshwater conservation research, decision making and capacity building. The data has already found use in development of conservation tools and conservation status assessments.","PeriodicalId":50164,"journal":{"name":"Journal of Limnology","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2023-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47281840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}