2 resultados para Temporal dynamics

em Corvinus Research Archive - The institutional repository for the Corvinus University of Budapest


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Based on the observation of more than 10 000 leaves of plane trees, four populations of Corythucha ciliata (Say, 1832) (Heteroptera: Tingidae) are investigated. After having introduced some parameters derived from the data, we draw spatial-temporal patterns and describe the seasonal population dynamics of Corythucha ciliata. Amongst others, the temporal change of the density of population, the state plane of larvae–adults, the inclination to accumulate, and the intraspecific competition are examined. Population and biomass dynamics is characterized for populations with and without limited nutrient source in case of different weather circumstances and effects.

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In 2002, 2003 and 2004, we took macoinvertebrate samples on a total of 36 occasions at the Badacsony bay of Lake Balaton. Our sampling site was characterised by areas of open water (in 2003 and 2004 full of reed-grass) as well as by areas covered by common reed (Phragmites australis) and narrowleaf cattail (Typha angustifolia). Samples were taken both from water body and benthic ooze by use of a stiff hand net. We have gained our data from processing 208 individual samples. We took samples frequently from early spring until late autumn for a deeper understanding of the processes of seasonal dynamics. The main seasonal patterns and temporal changes of diversity were described. We constructed a weather-dependent simulation model of the processes of seasonal dynamics in the interest of a possible further utilization of our data in climate change research. We described the total number of individuals, biovolume and diversity of all macroinvertebrate species with a single index and used the temporal trends of this index for simulation modelling. Our discrete deterministic model includes only the impact of temperature, other interactions might only appear concealed. Running the model for different climate change scenarios it became possible to estimate conditions for the 2070-2100 period. The results, however, should be treated very prudently not only because our model is very simple but also because the scenarios are the results of different models.