Main results

Before starting the MÉTA Programme we've developed and tested a new habitat-classification system (Á-NÉR). A revised version of Á-NÉR was applied for the country survey, then we've developed a new, landscape ecology oriented hexagon-based surveying method ... More »

One of the main goals of MÉTA program was to prepare distribution maps of 86 habitat types and to estimate their extension in Hungary. Till this time we had only rough and incomplete knowledge about the vegetation cover of the country. ... More »

Human landuse of hundreds and thousands of years has had a significant effect on the natural vegetation of Hungary. Habitats were ruined, degraded or changed on considerable part of the landscape. It was the first time in Hungary to collect naturalness data of habitats and landscapes in the whole territory of the country. Naturalness was assigned to five categories. More »

Processing of the detailed habitat naturalness data gives a possibility to compare the naturalness of different regions of Hungary. More »

A highly aggregated policy-relevant biodiversity indicator was developed: the vegetation-based Natural Capital Index. We used two different weighting scheme, a linear and an exponential one. The national NCIlin, is 9.9% and NCIexp is 3.2%. Hungary has lost 90-97% of its original vegetation-based natural capital. ... More »

Altogether 28 threat types were documented (the most importants to every habitat type in all hexagon). The most endangering factors were the spread of invasive plants, overpopulated game and drainage ... More »

During the MÉTA-mapping we have mapped the effect of 15 invasive species. For maps and other details see the Hungarian web page ... More »

In the last decades land abandonment increased in Hungary, and resulted in cca. 350 000 hectars old-fields. Where do these areas occur in Hungary? See map. More »

The MÉTA database was developed according to the methodology. The survey produced 17 sort of features of 86 type of habitats along more than 260,000 hexagons covering the country. The huge amount of data is managed by a relational database management system ... More »