Approaches To Storing And Analyzing Geobotanical Data
Approaches to storingand analyzinggeobotanical dataAlexander NovakovskiyInstitute of Biology, Komi ScientificCentre, Russian Academy of ScienceRussia, Syktyvkar
Area of the data collectingResearch isbeing conductedfrom 1950 to thepresent dayMain investigation regions: Komi republic (flatlands in the west,Northern and Subpolar Ural mountains in the east); more northernarea - Nenets region (Bolshezemelskaya Tundra, the Pechora Riverdelta, Polar Ural mountains)
Input (basic) dataThere are about 5000-6000 original releves ,collected in 1950-1990s in the vegetation plotscollection of the Institute.These releves still don’t convert into a digitalformat.
Using ExcelSince 2000-s the most of releveswere converted into digital format.Initially, Microsoft Excel was usedfor it.Excel tables are not a realdatabase, and there were a lot ofdifficulties to use these tables. Butthis form of data storage allow usto estimate some characteristics(average abundance, speciesfidelity, calculate numbers ofspecies etc.) and also makes iteasy to work with vegetation plotstables for classification purposes.
Using TurboVegLast 5-7 years releves from hard(paper) copies and Excel format werebeing converted into Turboveg format.Today there are about 3500 relevesExtra information in Turboveg databaseE coord, N coord – latitude and longitude ofthe revelePlontnr – unique identification codeLand unit – index of vegetation typeEll f, Ell n, Ell r, Ell l, Ram mois, Ram rs,Cg acid, Cg illum – Values of Ellenberg,Ramensky and Ciganov ecological scales,calculated for certain reveles according totheir species composition
Digital version of four-volume “Floraof the USSR European Northeast”Contain information about distribution of: 1500 vascular plants 2000 lichens and mossesDistribution map of Betula Nana L.and Hieracium Laevigatum Wild.
Typical way of geobotanical dataanalysisRHard copiesSPSSPC-ORDTurboVegGRAPHS
Module GRAPHSThe module GRAPHS isan Excel add-on. Afterinstallation the additionalsub-menu appears.Researchers can use anydata formats compatiblewith Microsoft Excel andall Excel abilities toprepare their dataData source – classicgeo-botanical table wherecolumns are plots(objects),– rows arespecies (properties).
Cluster analysisResult of cluster analysis (Wardclustering)Cluster analysis settingsMost common similarity indexes: Jaccard, Sorensen, correlations andconjugation between species.Methods of grouping: nearest neighbor, UPGMA, Ward's method
OrdinationAppearance of the settings window for NMSResult of ordination algorithmPCA – Principal components analysis,CA – Correspondence analysisNMS – Non-metric Multidimensional scaling
Graph theoryAppearance of the window for graphtheory t forms of graphs presentation:A – circle graph; B – tree graphs(connected graph with no cycles); C –star graph; D – connected components
Summary 5000-6000 vegetation plots in paper format (hard copy)1000-1500 Excel format2000-3000 IBIS (mostly aquatic vegetation)About 3500 releves in Turboveg formatDigital version of the “Flora of the USSR EuropeanNortheast” Herbarium, which contains more than 150,000 samplesof vascular plants and about 60,000 samples of mossand lichens
ZooCodeFamily-genus-species-subspecies – hierarchical systemSpecies name – Potentilla nivea L. (Family – Rosaceae)AA (Rosaceae), BB (Potentilla), CC (nivea)Unique key – AABBCCPotentilla gelida C.A.Mey ssp. borea-asiatica Jurtz. et R. KamAA (Rosaceae), BB (Potentilla), CD (Gelida), AF (borea-asiatica)Unique key – AABBCDAFSelect “AA*” – all species from Rosaceae familySelect “AABB*” – all species from Potentilla genus
Thank you very much for yourattention!
Approaches to storing and analyzing geobotanical data Alexander Novakovskiy Institute of Biology, Komi Scientific Centre, Russian Academy of Science Russia, Syktyvkar . Area of the data collecting Main investigation regions: Komi republic (flatlands in the west,
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