Ecological network for species dependent on ancient broadleaf trees using Osmoderma barnabita as a model species: a new approach

Uldis Valainis (Coresponding Author), Maksims Balalaikins, Juris Soms, Dalia Bastyte-Cseh, Alvydas Gintaras, Adele Baneliene, Dana Augutis, Marija Žukovskiene, Māris Nitcis, Maksims Zolovs

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


Organisms that depend on rare and endangered microhabitats, such as old, hollow trees, have a high conservation value. • To conserve these species, it is necessary to apply methods that identify habitats suitable for their survival. • Until now, a comprehensive method has not been developed for predicting the occurrence of species associated with old, hollow trees. • Here, we developed criteria to identify habitats for organisms associated with old, hollow trees, using Osmoderma barnabita as a model species. • We used hexagonal tessellation to identify suitable habitats for hermit beetle. • Criteria for predicting the occurrence of a hermit beetle were applied in practise, and as result 47.56% of the known hermit beetle localities coincided with the hexagons where the probability of occurrence of the species was the highest. Based on these results, an ecological network was created for species dependency on old, hollow trees, using the hermit beetle as a model species. • The proposed approach makes it possible to plan and implement environmental protection measures for species living in territories spanning several countries. In this work, we propose a method to identify species occurrence in core areas and to determine ecological corridors and gaps. This method could tailor conservation planning efforts.
Original languageEnglish
Article number12554
Pages (from-to)273 -287
Number of pages15
JournalInsect Conservation and Diversity
Issue number2
Publication statusPublished - Mar 2022


  • conservation
  • hexagonal tessellation
  • modelling
  • Osmoderma
  • species occurrence

Field of Science*

  • 1.6 Biological sciences

Publication Type*

  • 1.1. Scientific article indexed in Web of Science and/or Scopus database


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