A long-term (1986-2010) phytoplankton dataset from the LTER-Italy site Lake Candia

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如何引用

研究者應依照以下指示引用此資源。:

Oggioni A, Ruggiu D, Morabito G, Pugnetti A, Sparber K, Cozza R, Panzani P, Ruffoni T, Austoni M (2022): A long-term (1986-2010) phytoplankton dataset from the LTER-Italy site Lake Candia. v1.7. Consiglio Nazionale delle Ricerche - Istituto di Ricerca sulle Acque. Dataset/Occurrence. https://cloud.gbif.org/eca/resource?r=2022_lake_candia_phytoplankton&v=1.7

權利

研究者應尊重以下權利聲明。:

此資料的發布者及權利單位為 Consiglio Nazionale delle Ricerche - Istituto di Ricerca sulle Acque。 This work is licensed under a Creative Commons Attribution (CC-BY 4.0) License.

GBIF 註冊

此資源已向GBIF註冊，並指定以下之GBIF UUID: d8d344af-f873-47b4-b2a0-6054120f5a01。  Consiglio Nazionale delle Ricerche - Istituto di Ricerca sulle Acque 發佈此資源，並經由Participant Node Managers Committee同意向GBIF註冊成為資料發佈者。

關鍵字

Occurrence; Darwin Core; GBIF; phytoplankton; LTER-Italy; Lake Candia

聯絡資訊

地理涵蓋範圍

Lake Candia belongs to the Italian, European and International Long-Term Ecological Research (LTER) Networks: Candia (https://deims.org/c7fe4203-24b1-4d11-a573-99b99204fede). Data are georeferenced according to WGS 84 datum (EPSG:4326, https://epsg.io/4326.wkt).
Habitat type: Pelagic of lake, water column.
Biogeographic region: Within the Palearctic realm, according to the definitions of the European Environmental Agency (2017), the dataset covers the Alpine European biogeographical regions.
Country: Italy.

分類群涵蓋範圍

General description: dataset covers phytoplankton assemblages and counts. Phytoplankton counting are based on inverted microscopy following Uthermöl method (Uthermöl, 1958) and biomass of each taxa was estimated from abundance data and original measurements of cell volume (Hillebrand et al., 1999; Sun and Liu, 2003). The dataset covers Cyanobacteria with 1660 occurrences; Plantae with 1302 occurrences (28.1% of Plantae occurrences) of Charophyta and 3324 occurrences (71.8%) of Chlorophyta; Protozoa (426 occurrences); and Chromista with Ochrophyta (1736 occurrences), Cryptophyta (1213 occurrences), Myzozoa (345 occurrences), and Haptophyta (108 occurrences).

時間涵蓋範圍

取樣方法

Phytoplankton data were collected monthly from 1986 to 2010, at the point of lake maximum depth (7.7 m) as integrated samples of the euphotic water column.
Phytoplankton determinations were carried out on subsamples of the integrated sample preserved in acetic Lugol’s solution. Phytoplankton organisms were counted using the Utermöhl technique (Utermöhl, 1958), classifying the taxa to the species level, whenever possible, using a Zeiss Axiovert 10 inverted microscope at 200x and 400x until 400 cells for the most important taxa were counted. Biomass of each taxa in the sample was estimated from abundance data and original measurements of cell volume (Smayda, 1978; Hillebrand et al., 1999; Sun and Liu, 2003). Finally, total biovolume was calculated from the sum of the biovolumes of each taxon in the sample (cell number x specific cell volume).
All records are validated to the currently accepted nomenclature using the taxonomic backbone of GBIF, Algaebase: Listing of World’s Algae (Guiry and Guiry, 2022), and World Register of Marine Species WoRMS (Ahyong et al., 2022). Life Science Identifiers (LSIDs) are used to identify univocally the taxon and to facilitate data integration and interoperability.
Taxon specialists: Martina Austoni, Radiana Cozza, Giuseppe Morabito, Alessandro Oggioni, Pierisa Panzani, Alessandra Pugnetti, Teresa Ruffoni, Delio Ruggiu, Karin Sparber.

方法步驟描述:

1. Dataset includes 10120 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 available this dataset represents also a contribution to the current activities of the LTER networks, aiming on accessibility of the time series of the LTER sites, in order to reconstruct trends and dynamics and to identify and compare reliable trends.
2. The dataset was structured based on the Darwin Core standard (DwC, Wieczorek et al., 2012), with each row containing a record of the occurrence of a taxon from a sample. The columns report taxonomical (e.g. scientificName, scientificNameID, taxonRank), geographic (e.g. decimalLatitude, decimalLongitude, geodeticDatum) information, along with density and biovolume for each taxon recognised in the sample.

引用文獻

1. AAhyong S et al., 2022. World Register of Marine Species. Available from https://www.marinespecies.org at VLIZ. Accessed 2022-12-13. doi:10.14284/170.
2. Guiry MD, Guiry GM, 2022. AlgaeBase. World-wide electronic publication, National University of Ireland, Galway. https://www.algaebase.org. Accessed on 2022-12-01.
3. Oggioni A, Silver M, Ranghetti L, Tagliolato P 2022. ropensci/ReLTER: ReLTER v1.1.0.
4. Utermöhl H, 1958. Zur Vervollkommung der quantitativen Phytoplankton-Methodik, Mitt. Int. Ver. Limnol., 9, 38.

額外的詮釋資料