Tools and examples of FinBIF data and services for research use.
This web application Protax allows you to identify any DNA sequence of a Finnish insect, as derived from the standard DNA barcode region, CO1, in FASTA format.
The application uses all insect sequences in the national barcode library, FinBOL. to determine the probability with which the sequence belongs to any particular insect taxon at a given taxonomic level (class, order, family, subfamily, tribe, genus, and species), or to a previously unknown taxon at the same taxonomic level.
Relative observation trends (2018)
This application explores whether occurrence data available through FinBIF can be used to derive trends in relative abundance of species.
As test material all available data of Finnish butterflies was downloaded. For each species absolute counts of records per year were tallied (shown in table at the bottom of page).
In addition, relative counts of each species were computed by dividing its absolute count by all counts in a group (family). This closely corresponds to the parameter “Reporting Rate”, see, e.g., Isaac et al. (2014)
A linear model can be fitted for the absolute and relative counts. This indicates whether the species has been increasing or decreasing.
The results are shown in diagrams for 3 selected species in each family. A trend can be seen in many cases, but also the fluctuations without any trend are interesting. We invite users of this tool to compare these results with trends obtained from quantitative field surveys.
The tool was programmed in R and later exported to Shiny portal by Yuliya Fetyukova (in preparation) at the University of Eastern Finland in 2015-2016. This work also inspired GBIF to build a similar exploratory tool for Relative Observation Trends.
- Fetyukova Y, Saarenmaa H (2017) Deriving trends in relative abundance for European butterflies using big data – towards Essential Biodiversity Variables for species populations. Manuscript in preparation.
- Isaac NJ, van Strien AJ, August TA, de Zeeuw MP, Roy DB (2014) Statistics for citizen science: extracting signals of change from noisy ecological data. Methods in Ecology and Evolution, 5(10), 1052-1060. doi:10.1111/2041-210X.12254