205 research outputs found
Biome-specific rodent dynamics and hantavirus epidemiologies in Europe
Henttonen, H., Leirs, H., Kallio, E.R., Tersago, K., Voutilainen, L
Cyclic voles and shrews and non-cyclic mice in a marginal grassland within European temperate forest
Cyclic population dynamics of small mammals are not restricted to the boreal and arctic zones of Eurasia and North America, but long-term data series from lower latitudes are still less common. We demonstrated here the presence of periodic oscillations in small mammal populations in eastern Poland using 22-year (1986–2007) trapping data from marginal meadow and river valley grasslands located in the extensive temperate woodland of Białowieża Primeval Forest. The two most common species inhabiting meadows and river valleys, root vole Microtus oeconomus and common shrew Sorex araneus, exhibited synchronous periodic changes, characterised by a 3-year time lag as indicated by an autocorrelation function. Moreover, the cycles of these two species were synchronous within both habitats. Population dynamics of the striped field mouse Apodemus agrarius was not cyclic. However, this species regularly reached maximum density 1 year before the synchronized peak of root voles and common shrews, which may suggest the existence of interspecific competition. Dynamics of all three species was dominated by direct density-dependent process, whereas delayed density dependent feedback was significant only in the root vole and common shrew. Climatic factors acting in winter and spring (affecting mainly survival and initial reproduction rates) were more important than those acting in summer and autumn and affected significantly only the common shrew. High temperatures in winter and spring had positive effects on autumn-to-autumn changes in abundance of this species, whereas deep snow in combination with high rainfall in spring negatively affected population increase rates in common shrew
Population fluctuations and spatial synchrony in an arboreal rodent
Climatic conditions, trophic links between species and dispersal may induce spatial synchrony in population fluctuations. Spatial synchrony increases the extinction risk of populations and, thus, it is important to understand how synchrony-inducing mechanisms affect populations already threatened by habitat loss and climate change. For many species, it is unclear how population fluctuations vary over time and space, and what factors potentially drive this variation. In this study, we focus on factors determining population fluctuations and spatial synchrony in the Siberian flying squirrel, Pteromys volans, using long-term monitoring data from 16 Finnish populations located 2-400 km apart. We found an indication of synchronous population dynamics on a large scale in flying squirrels. However, the synchrony was not found to be clearly related to distance between study sites because the populations seemed to be strongly affected by small-scale local factors. The regularity of population fluctuations varied over time. The fluctuations were linked to changes in winter precipitation, which has previously been linked to the reproductive success of flying squirrels. Food abundance (tree mast) and predator abundance were not related to population fluctuations in this study. We conclude that spatial synchrony was not unequivocally related to distance in flying squirrels, as has been observed in earlier studies for more abundant rodent species. Our study also emphasises the role of climate in population fluctuations and the synchrony of the species
Population fluctuations and spatial synchrony in an arboreal rodent
Climatic conditions, trophic links between species and dispersal may induce spatial synchrony in population fluctuations. Spatial synchrony increases the extinction risk of populations and, thus, it is important to understand how synchrony-inducing mechanisms affect populations already threatened by habitat loss and climate change. For many species, it is unclear how population fluctuations vary over time and space, and what factors potentially drive this variation. In this study, we focus on factors determining population fluctuations and spatial synchrony in the Siberian flying squirrel, Pteromys volans, using long-term monitoring data from 16 Finnish populations located 2-400 km apart. We found an indication of synchronous population dynamics on a large scale in flying squirrels. However, the synchrony was not found to be clearly related to distance between study sites because the populations seemed to be strongly affected by small-scale local factors. The regularity of population fluctuations varied over time. The fluctuations were linked to changes in winter precipitation, which has previously been linked to the reproductive success of flying squirrels. Food abundance (tree mast) and predator abundance were not related to population fluctuations in this study. We conclude that spatial synchrony was not unequivocally related to distance in flying squirrels, as has been observed in earlier studies for more abundant rodent species. Our study also emphasises the role of climate in population fluctuations and the synchrony of the species.Peer reviewe
A new method for estimating carbon dioxide emissions from drained peatland forest soils for the greenhouse gas inventory of Finland
In peatlands drained for forestry, the soil carbon (C) or
carbon dioxide (CO2) balance is affected by both (i)Â higher
heterotrophic CO2-C release from faster decomposing soil organic matter
(SOM) and (ii)Â higher plant litter C input from more vigorously growing
forests. This balance and other greenhouse gas (GHG) sinks and sources in
managed lands are annually reported by national GHG inventories to the
United Nations Climate Change Convention. In this paper, we present a
revised, fully dynamic method for reporting the CO2 balance of drained
peatland forest soils in Finland. Our method can follow temporal changes in
tree biomass growth, tree harvesting and climatic parameters, and it is built
on empirical regression models of SOM decomposition and litter input in
drained peatland forests. All major components of aboveground and
belowground litter input from ground vegetation as well as live trees and trees that died naturally
are included, supplemented by newly acquired turnover rates of woody
plant fine roots. Annual litter input from harvesting residues is calculated
using national statistics of logging and energy use of trees. Leaching,
which also exports dissolved C from drained peatlands, is not included. The
results are reported as time series from 1990–2021 following the practice
in the GHG inventory. Our revised method produces an increasing trend of annual
emissions from 0.2 to 2.1 t CO2 ha−1 yr−1 for the period
1990–2021 in Finland (equal to a trend from 1.4 to 7.9 Mt CO2 yr−1 for the entire 4.3 Mha of drained peatland forests), with a
statistically significant difference between the years 1990 and 2021. Across the
period 1990–2021, annual emissions are on average 1.5 t CO2 ha−1 yr−1 (3.4 Mt CO2 yr−1 for 2.2 Mha area) in warmer southern
Finland and −0.14 t CO2 ha−1 yr−1 (−0.3 Mt CO2 yr−1
for 2.1 Mha area) in cooler northern Finland. When combined with data on the
CO2 sink created by the growing tree stock, in 2021 the drained peatland forest
ecosystems were a source of 1.0 t CO2 ha−1 yr−1 (2.3 Mt CO2 yr−1) in southern Finland and a sink of 1.2 t CO2 ha−1 yr−1 (2.5 Mt CO2 yr−1) in northern Finland. We
compare these results to those produced by the semi-dynamic method used earlier
in the Finnish GHG inventory and discuss the strengths and
vulnerabilities of the new revised method in comparison to more static
emission factors.</p
Team sports performance analysed through the lens of social network theory: implications for research and practice
This paper discusses how social network analyses and graph theory can be implemented in team sports performance analyses to evaluate individual (micro) and collective (macro) performance data, and how to use this information for designing practice tasks. Moreover, we briefly outline possible limitations of social network studies and provide suggestions for future research. Instead of cataloguing discrete events or player actions, it has been argued that researchers need to consider the synergistic interpersonal processes emerging between teammates in competitive performance environments. Theoretical assumptions on team coordination prompted the emergence of innovative, theoretically-driven methods for assessing collective team sport behaviours. Here, we contribute to this theoretical and practical debate by conceptualising sports teams as complex social networks. From this perspective, players are viewed as network nodes, connected through relevant information variables (e.g., a ball passing action), sustaining complex patterns of interaction between teammates (e.g., a ball passing network). Specialized tools and metrics related to graph theory could be applied to evaluate structural and topological properties of interpersonal interactions of teammates, complementing more traditional analysis methods. This innovative methodology moves beyond use of common notation analysis methods, providing a richer understanding of the complexity of interpersonal interactions sustaining collective team sports performance. The proposed approach provides practical applications for coaches, performance analysts, practitioners and researchers by establishing social network analyses as a useful approach for capturing the emergent properties of interactions between players in sports teams
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