0604097 - ÚVGZ 2025 RIV CZ eng J - Journal Article
Jakuš, Rastislav - Timsina, Binu - Štípková, Zuzana - Křenová, Zdeňka - Rokaya, Maan Bahadur
THE SILVA GABRETA BIODIVERSITY MONITORING DATABASE: ASSESSING BIOLOGICAL DIVERSITY IN THE ŠUMAVA NATIONAL PARK, CZECH REPUBLIC.
European Journal of Environmental Sciences. Roč. 14, č. 2 (2024), s. 91-104. ISSN 1805-0174. E-ISSN 2336-1964
R&D Projects: GA MŠMT LM2023048
Institutional support: RVO:86652079
Keywords : phylogenetic diversity * species richness * productivity * assemblages * maintenance * thresholds * community * ecology * water * biodiversity * database * forest disturbance * forest management * monitoring * sampling design
OECD category: Biodiversity conservation
Impact factor: 0.6, year: 2023
Method of publishing: Open access
Result website:
https://ejes.cz/index.php/ejes/article/view/1223DOI: https://doi.org/10.14712/23361964.2024.11

The Bohemian Forest spans the borders of Bavaria, Czechia and Upper Austria, and is important for studying forest biodiversity in central European mountain ecosystems. This study focuses on assessing the patterns in biodiversity in the & Scaron Sumava National Park. Species richness, Shannon diversity index, evenness and dominance were determined for 117 forest plots (large sample) and a subsample of 49 plots (small sample) using comprehensive monitoring techniques within the Silva Gabreta project, a cross-border initiative implemented together with the Bavarian Forest National Park. Data were collected for the following taxonomic groups: plants, fungi, mammals and invertebrates, using a variety of trapping methods and survey techniques. Results indicate significant differences in the number of species in the different taxonomic groups, with Lepidoptera, fungi and Bryophyta with the highest species richness and diversity, whereas groups such as Neuroptera, Curculionidae and mammals had lower values. Although most biodiversity indicators were not significantly different between the large and the small sample at the taxonomic level, species richness and Shannon diversity were higher in the small sample. This may be attributed to the trapping methods used in those plots, which are likely to have resulted in more complete captures of the species than in the plots of the large sample. The findings indicate that 49 plots are a suitable number for long-term biodiversity monitoring, provided key plots with efficient trapping setups are included. This study highlights the importance of careful plot selection and suggests that a mixed monitoring strategy, incorporating both broad taxonomic assessments and targeted approaches for specific taxa, may be the most effective for monitoring biodiversity.
Permanent Link: https://hdl.handle.net/11104/0361435