Exploiting hot-spots; effective determination of lichen diversity in a Carpathian virgin forest

PLoS One. 2018 Sep 13;13(9):e0203540. doi: 10.1371/journal.pone.0203540. eCollection 2018.

Abstract

Although lichenized fungi are among the most reliable indicators of forest quality and represent a considerable part of forest biodiversity, methods maximizing completeness of their species lists per area are lacking. Employing a novel methodological approach including a multi-expert competition and a search for local hot-spot plots, we have obtained outstanding data about epiphytic lichen biota in a part of the largest Central European virgin forest reserve Uholka-Shyrokyi Luh situated in Ukrainian Carpathians. Our field research consisted of two four-day periods: (1) an overall floristic survey and a search for spots with raised lichen diversity, and (2) survey in four one-hectare plots established in lichen diversity hot-spots along an altitudinal gradient. Recorded alpha-diversities in plots ranged from 181-228 species, but estimated species richness is in the range 207-322 species. Detected gamma-diversity was 387 species; estimates are 409-484 species. 93% of the species found in the forest were recorded in plots, but only 65% outside the plots. This underlines the high-efficiency of the multi-expert competitive survey in diversity hot-spot plots. Species richness in each one-hectare plot was equal to the numbers of species obtained by floristic surveys of much larger old-growth forest areas in Central Europe. Gamma-diversity detected in the Uholka primeval forest far exceeded all numbers achieved in Central European old-growth forests. Our method appears to be both effective (it obtains a more nearly complete inventory of species) and practical (the resources required are not unreasonably large).

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biodiversity
  • Ecosystem
  • Environmental Monitoring
  • Forests*
  • Lichens / classification
  • Lichens / genetics*

Grants and funding

Our research was supported by a long-term research development grant RVO 67985939 and by the grant 647412 of The Charles University Grant Agency.