Publication Date:
2019
Description:
Abstract
Forests dominated by European beech (Fagus sylvatica L.) are among both the most widespread in Europe and the most intensely exploited globally. One of the largest remnants of unmanaged beech forests in Europe is the Uholka‐Shyrokyi Luh forest in Transcarpathia, Ukraine, covering 8800 ha of primeval forest. In 2000, a permanent forest plot of 10 ha has been established in the Uholka massif. All living and dead trees with a Diameter at Breast Height (DBH) ≥60 mm were identified to species, DBH‐measured, stem tagged and stem mapped. Since, the plot has been remeasured in 2005, 2010, and 2015. In total, 4820 individual trees were measured with 14116 individual measurements throughout all four inventories. In spring 2018, an Airborne Laser Scan was carried out, covering the Uholka‐Shyrokyi Luh forest. This data set allows to derive a high resolution Digital Elevation Model (DEM) of the plot area. European beech covers a share of ≈ 95% of the Basal Area (BA) of all living stems. Whilst BA was relatively stable throughout all inventories (≈ 38 m2 per ha), the number of stems increased considerably between 2010 and 2015 from 290 to 430 stems per ha. Additionally, the proportion of beech stems decreased from 95% in 2010 to 86% in 2015. The continuity of the share of beech on BA and the decrease in number of stems can be traced back to disturbance events, which led to an increase of more light demanding species in the recruitment but did not alter the distribution of BA as these small trees contribute only very little to BA. The data set allows for important insights into the development, and the spatial and temporal dynamics of primeval beech forests. It can be used to quantify the demographic processes growth, mortality and recruitment, and to study inter‐ and intra‐specific effects on demographic rates, stand structure and species composition. No copyright or proprietary restrictions are associated with the use of this data set other than citation of this Data Paper.
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Print ISSN:
0012-9658
Electronic ISSN:
1939-9170
Topics:
Biology
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