Seasonal change of oribatid mite communities (Acari, Oribatida) in three different types of microhabitats in an oak forest

Oribatid mites are one of the most abundant groups of the ground-dwelling mesofauna. They can be found in almost every terrestrial habitat all over the world and they are characterized by great species richness and great number of individuals. In spite of that not enough is known about their behaviour on community level and their spatial and temporal pattern in different habitats of the world. In our present study the seasonal behaviour of oribatid mite communities was analysed in three types of microhabitats in a temperate deciduous forest: in leaf litter, soil and moss. Samples were collected at a given site in a year and a half and the oribatid mite communities living there were studied on genus level along with the changes of meteorological factors characteristic of the area. The results show that corresponding to similar previous researches, the communities in our study do not have a seasonally changing, returning pattern either. Based on this, we can conclude that climatic differences and differences in other seasonally changing factors between the seasons do not have a significant role in the annual change of communities. Besides that we discovered that the communities of the three microhabitats are not completely the same. It is the oribatid mite community of the moss which differs mostly from communities in the leaf litter and in the soil. Our study calls attention among others to the fact that compositional changes of the oribatid mite communities living all over the world and their causes are unclear to date

Rainforests at the beginning of the 21st century

Rainforests are situated at low latitude where forests enjoy steady and strong radiation. Biodiversity in rainforests has been very high, for historical and climatic reasons. The number of species is very high and tends to increase with precipitation and decrease with seasonality. Disturbance, soil fertility and forest stature also influence the species richness and high turnover of species contribute to diversity. Field observation and studies revealed that large scale deforestation could alter the regional and global climate significantly. Deforestation alters the surface albedo which leads to climate change. Regional land use contributes to climate change through surface-energy budget, as well as the carbon cycle. Forest fragmentation, logging, overhunting, fire and the expanding agriculture threaten the biodiversity. Rainforest covered area has significantly shrunk in the last decades. It is hard to protect the forests because of the growing demand for agricultural area and forest-derived products. Most measures proved ineffective to slow down the destruction. Hence, more forest will be lost in the future. Conservationists should take into consideration the secondary forests because biodiversity can be high enough and it is worth protecting them

A klímaváltozás közösségökológiai hatásainak elemzései

A klímaváltozás ökológiai hatásainak elemzésével kapcsolatos tudományos eredményeink megközelítési módjukat tekintve az alábbi hat fő csoportba oszthatók: 1. Az elméleti várakozások tisztázása stratégiai modellezéssel. 2. Lehetséges hatások mértékének behatárolása Magyarország vonatkozásában, földrajzi analógiai megközelítéssel. 3. Nagy monitoring adatbázisok elemzései a már bekövetkezett változási tendenciák feltárására. 4. Természetközeli populációk és ökoszisztémák várható változásainak elemzése taktikai modellezéssel és statisztikai elemzésekkel. 5. A klímaváltozás agroökoszisztémákra gyakorolt hatásai 6. Új, hatékony és a korábbiaknál általánosabban használható bioindikátor-rendszer kidolgozása. A továbbiakban eredményeinket ezen felosztás szerinti csoportosításban ismertetjük

Comparative analysis of the relationship between phenological phenomena and meteorological indicators based on insect and plant monitoring

Climate change is one of the biggest environmental problems of the 21st century. The most sensitive indicators of the effects of the climatic changes are phenological processes of the biota. The effects of climate change which were observed the earliest are the remarkable changes in the phenology (i.e. the timing of the phenophases) of the plants and animals, which have been systematically monitored later. In our research we searched for the answer: which meteorological factors show the strongest statistical relationships with phenological phenomena based on some chosen plant and insect species (in case of which large phenological databases are available). Our study was based on two large databases: one of them is the Lepidoptera database of the Hungarian Plant Protection and Forestry Light Trap Network, the other one is the Geophytes Phenology Database of the Botanical Garden of Eötvös Loránd University. In the case of butterflies, statistically defined phenological dates were determined based on the daily collection data, while in the case of plants, observation data on blooming were available. The same meteorological indicators were applied for both groups in our study. On the basis of the data series, analyses of correlation were carried out and a new indicator, the so-called G index was introduced, summing up the number of correlations which were found to be significant on the different levels of significance. In our present study we compare the significant meteorological factors and analyse the differences based on the correlation data on plants and butterflies. Data on butterflies are much more varied regarding the effectiveness of the meteorological factors

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

An analysis of the relationship between Carbon-Dioxide Emissions and Gross Domestic Product For 139 countries within the time period 1985-2004

  The purpose of this dissertation would be to find the relationship between CO2 emission and GDP. We found that in case of the majority of countries the CO2 emission is related to national income and follows an inverted-U shaped curve. In our analysis we used the regression technique on 139 countries within the time period 1985-2004 to model and analyze the mentioned relationship and define the variables, that describe it. As it will be proved, Environmental Kuznets Curve validate the model and our hypothesis confirm other researches, therefore the inverse-u relationship proves to be correct.