Nemlineáris dinamika klasszikus növekedési modellekben (Nonlinear dynamics in classical economic growth models)

Ebben a tanulmányban a klasszikus Harrod növekedési modellt nemlineáris kiterjesztéssel, keynesi és schumpeteri tradíciók bevezetésével reprezentatív ügynök modellbe alakítjuk. A híres Lucas kritika igazolásaként megmutatjuk, hogy az intrinsic gazdasági növekedési ütemek trajektóriái vagy egy turbulens káoszba szóródnak szét, vagy egy nagyméretű rendhez vezetnek, ami elsődlegesen a megfelelő fogyasztási függvény típusától függ, s bizonyos paraméterek piaci értékei, pedig csak másodlagos szerepet játszanak. A másik meglepő eredmény empirikus, ami szerint külkereskedelmi többlet, a hazai valuta bizonyos devizapiaci értékei mellett, különös attraktorokat generálhat. _____ In this paper the classical Harrodian growth model is transformed into a representative agent model by its nonlinear extensions and the Keynesian and Schumpeterian traditions. For the proof of the celebrated Lucas critique it is shown that the trajectories of intrinsic economic growth rates either are scattered into a turbulent chaos or lead to a large scale order. It depends on the type of the appropriate consumption function, and the market values of some parameters are playing only secondary role.Another surprising result is empirical: the international trade su±cit may generate strange attractors under some exchange rate values.

Zoocoenological state of microhabitats and its seasonal dynamics in an aquatic macroinvertebrate assembly (Hydrobiological case studies on lake Balaton, No. 1.)

In the years 2002, 2003 and 2004 we collected samples of macroinvertebrates on a total of 36 occasions in Badacsony bay, in areas of open water (in the years 2003 and 2004 reed-grassy) as well as populated by reed (Phragmites australis) and cattail (Typha angustifolia). Samples were taken using a stiff hand net. The sampling site includes three microhabitats differentiated only by the aquatic plants inhabiting these areas. Our data was gathered from processing 208 individual samples. The quantity of macroinvertebrates is represented by biovolume value based on volume estimates. We can identify taxa in abundant numbers found in all water types and ooze; as well as groups associated with individual microhabitats with various aquatic plants. We can observe a notable difference between the years in the volume of invertebrate macrofauna caused by the drop of water level, and the multiplication of submerged macrophytes. There are smaller differences between the samples taken in reeds and cattail stands. In the second half of 2003 – which was a year of drought – the Najas marina appeared in open waters and allowed to support larger quantities of macroinvertebrates. In 2004 with higher water levels, the Potamogeton perfoliatus occurring in the same area has had an even more significant effect. This type of reed-grass may support the most macroinvertebrates during the summer. From the aspect of diversity relations we may suspect different characteristics. The reeds sampling site proved to be the richest, while the cattail microhabitat is close behind, open water (with submerged macrophytes) is the least diverse microhabitat.

Simulation modeling of phytoplankton dynamics in a large eutrophic river, Hungary – Danubian Phytoplankton Growth Model (DPGM)

Ecological models have often been used in order to answer questions that are in the limelight of recent researches such as the possible effects of climate change. The methodology of tactical models is a very useful tool comparison to those complex models requiring relatively large set of input parameters. In this study, a theoretical strategic model (TEGM ) was adapted to the field data on the basis of a 24-year long monitoring database of phytoplankton in the Danube River at the station of G¨od, Hungary (at 1669 river kilometer – hereafter referred to as “rkm”). The Danubian Phytoplankton Growth Model (DPGM) is able to describe the seasonal dynamics of phytoplankton biomass (mg L−1) based on daily temperature, but takes the availability of light into consideration as well. In order to improve fitting, the 24-year long database was split in two parts in accordance with environmental sustainability. The period of 1979–1990 has a higher level of nutrient excess compared with that of the 1991–2002. The authors assume that, in the above-mentioned periods, phytoplankton responded to temperature in two different ways, thus two submodels were developed, DPGM-sA and DPGMsB. Observed and simulated data correlated quite well. Findings suggest that linear temperature rise brings drastic change to phytoplankton only in case of high nutrient load and it is mostly realized through the increase of yearly total biomass.