Sampling event dataset on five-year observations of macrofungi fruit bodies in raised bogs, Western Siberia, Russia

By

Filippova, Nina
Lapshina, Elena

Type

Article

Date of Publication

2019-07-30

Original Publication

Biodiversity data journal

Volume

7

Pages

1--10

Subjects

Macrofungi , Peatlands , permanent monitoring , Phenology , plot-based protocol

Contributed by

Pensoft Publishers

Language

English

Published by

Sofia Pensoft Publishers [2013]-

Identifiers

DOI: https://doi.org/10.3897/BDJ.7.e35674
eLocator: e35674

 

Abstract

The data paper includes the results of a long-term monitoring programme for macrofungi fruiting using permanent plots located in the raised bog ecosystem in central part of Western Siberia (nearby Khanty-Mansiysk), Russia. The goal of the project was to describe the quantitative and qualitative structure and spatial variation of the community of macromycetes, to follow its dynamics seasonally and inter-annually and also elucidate the relationship between the fruiting and climate variables. A total of 263 circular 5 m2 subplots (for a total area of 1,315 m2) were inspected weekly during vegetation seasons 2014-2018 and carpophores of different fungal taxa were counted. The resulting sampling-event dataset includes 16,569 of plot-based observations (= sampling events) with corresponding 6,011 occurrence records of macromycetes identified to species or genus level. In total, 69 species were revealed during the study. About 80% of plot-based observations contain zero records and mark absence of visible fruiting bodies in a certain plot and time.<br> This is the first sampling-event dataset on plot-based observations of macrofungi published in GBIF and the first long-term series of macrofungi monitoring in a raised bog ecosystem accomplished in Western Siberia. The aim of the data paper publication was to provide the description and the link to the published data in the format of a peer-reviewed journal paper and to provide recognition for the effort by means of a scholarly article (based on Data paper definition published at https://www.gbif.org/en/data-papers).