Introduction to DNA detected biodiversity, poorly known habitats
The purpose of this use case is to help biodiversity researchers, monitoring initiatives with the selection of localities and areas for further sampling when targeting cryptic biodiversity with eDNA metabarcoding methods. It is envisioned that every new sample will update the model and recalculate priorities. DNA-based methods are highly efficient in targeting organism groups that normally receive little attention, e.g. fungi, bacteria, archaea, protists, nematodes and micro-invertebrates. Methods are simple and cost-effective, also at scales where traditional sampling regimes would be too costly in terms of money, time and labour. However, to be able to include such data in global biodiversity conservation efforts, it is necessary to both to collect a wider global sampling, and understand diversity in cryptic environments better. Therefore this case-study will focus on how a digital twin such as BioDT can be used to identify priority areas for further sampling based on some user-defined criteria/constraints such as;
- Geographical constraints (countries, user defined larger areas)
- Landscape constraints (e.g. habitat type / land use class / ecoregion constraints)
- Taxonomic constraints (bacteria, fungi, protozoa, eukaryotes)
- Prioritization parameters (e.g. heterogeneity of communities within units)
- Number of samples
The DT will focus on Denmark and use eDNA metabarcoding datasets for fungi and bacteria, as well as national maps of land-use types. It will allow the user to set basic constraints for future samples, and then use existing data to predict where further samples are best placed. Information from new samples will eventually feed into the model and provide an updated map of priority areas.