Change in the Structure and Productivity of the Biota of Agaricoid Basidiomycetes According to the Results of Long-Term Monitoring in Pine Forests of Perm Oblast (Southern Taiga Subzone)

2018 ◽  
Vol 11 (5) ◽  
pp. 484-493
Author(s):  
V. S. Botalov ◽  
L. G. Perevedentseva ◽  
A. S. Shishigin
2020 ◽  
Vol 8 ◽  
Author(s):  
Alexey Nesterkov ◽  
Maxim Zolotarev ◽  
Elena Belskaya ◽  
Tatyana Tuneva

Since the late 1980s, long-term monitoring of various components of natural ecosystems under conditions of industrial pollution has been carried out in the Central Urals. In the mid-2000s, similar programmes were started in the Southern Urals. As a part of these monitoring programmes, the data on invertebrates in different types of biotopes, collected with different methods and in a different time intervals, continue to be gathered. Amongst the most well-studied groups of invertebrates are spiders and harvestmen whose communities are a convenient indicator of the environment. The data collected through these monitoring programmes can also be used to study natural local biodiversity. The dataset, presented here, includes information from a long-term monitoring programme for Araneae and Opiliones that inhabit grass stands of secondary dry meadows and litter of spruce-fir, aspen-birch and pine-birch forests in the Central and Southern Urals. The dataset (available from the GBIF network at https://www.gbif.org/dataset/e170dbd1-a67f-4514-841c-5296b290ca90) describes the assemblage structure of spiders and harvestmen (list of species and their abundance), age-sex composition and seasonal and inter-annual dynamics for two large areas in the southern taiga zone of the Ural Mountains. The dataset includes 1,351 samples, which correspond to 5,462 occurrences identified during 2004–2009, 2013 and 2018. In total, we collected 10,433 specimens, representing 178 species (36% of arachnofauna of the Urals), 115 genera (54%) and 23 families (100%). Most of the data (4,939 of 5,462 occurrences, 90%) were collected in the western macro-slope of the Ural Mountains (European part of Russia), the rest in the eastern macro-slope (Asian part). All represented data were sampled in industrially undisturbed areas and are used as a local reference for ecotoxicological monitoring. The dataset provides new useful information for recording the state of biodiversity for the Central and Southern Urals and contributes to the study of biodiversity conservation.


Author(s):  
N. V. Kiseleva

In the birch-pine forests of the Ilmeny Reserve the bank vole is predominated by numbers, the pygmy wood mice being in the second place. The results of our monitoring of the numbers of these rodents for 27 years (1991–2018) are presented. 1,610 rodents were caught,of which the bank vole accounted for 52.6%, the pygmy wood mouse for 32%, and other species for 15.4%. The autumn abundance of the bank vole was 4.6±1.8 and 18.9±2.6 ind./100 trap-days for 1991–1999 and 2000 – 2018, respectively; that of the pygmy wood mouse was 2.1±1.9 and 18.9±2.6 ind./100 trap-days, respectively. Since 2000, the peak amplitude of the bank vole number has increased by 1.1– 2.5 times, that of the pygmy wood mouse has increased by 2.5–4.2 times. Since 2006, the number peaks of these rodents began to repeat after 2–3 years. Over eighteen years (2000–2018), the autumn abundance of the bank vole twice (2008 and 2017) reached its peak values, at which the reproduction of voles ceased in July or early August. The correlation coefficient of the autumn abundance of the bank vole and pygmy wood mouse for 1996–2018 was 0.64±0.1. The spring abundance of the pygmy wood mouse has begun to more often exceed the spring abundance of the bank vole. Changes in the population cycles of the bank vole and pygmy wood mouse were obviously associated with some climatic features of the recent decades.


Author(s):  
Barbara S. Minsker ◽  
Charles Davis ◽  
David Dougherty ◽  
Gus Williams

Kerntechnik ◽  
2018 ◽  
Vol 83 (6) ◽  
pp. 513-522 ◽  
Author(s):  
U. Hampel ◽  
A. Kratzsch ◽  
R. Rachamin ◽  
M. Wagner ◽  
S. Schmidt ◽  
...  

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