Login / Signup

Surveying lichen diversity in forests: A comparison of expert mapping and eDNA metabarcoding of bark surfaces.

Lukas DreylingSteffen BochHelge Thorsten LumbschImke Schmitt
Published in: MycoKeys (2024)
Lichens are an important part of forest ecosystems, contributing to forest biodiversity, the formation of micro-niches and nutrient cycling. Assessing the diversity of lichenised fungi in complex ecosystems, such as forests, requires time and substantial skills in collecting and identifying lichens. The completeness of inventories thus largely depends on the expertise of the collector, time available for the survey and size of the studied area. Molecular methods of surveying biodiversity hold the promise to overcome these challenges. DNA barcoding of individual lichen specimens and bulk collections is already being applied; however, eDNA methods have not yet been evaluated as a tool for lichen surveys. Here, we assess which species of lichenised fungi can be detected in eDNA swabbed from bark surfaces of living trees in central European forests. We compare our findings to an expert floristic survey carried out in the same plots about a decade earlier. In total, we studied 150 plots located in three study regions across Germany. In each plot, we took one composite sample based on six trees, belonging to the species Fagussylvatica , Piceaabies and Pinussylvestris . The eDNA method yielded 123 species, the floristic survey 87. The total number of species found with both methods was 167, of which 48% were detected only in eDNA, 26% only in the floristic survey and 26% in both methods. The eDNA contained a higher diversity of inconspicuous species. Many prevalent taxa reported in the floristic survey could not be found in the eDNA due to gaps in molecular reference databases. We conclude that, currently, eDNA has merit as a complementary tool to monitor lichen biodiversity at large scales, but cannot be used on its own. We advocate for the further development of specialised and more complete databases.
Keyphrases
  • climate change
  • cross sectional
  • single molecule
  • high resolution
  • genetic diversity
  • cystic fibrosis
  • circulating tumor
  • high density