Use of long-term data to evaluate loss and endangerment status of Natura 2000 habitats and effects of protected areas

Habitat loss is a key driver of biodiversity loss. However, hardly any long-term time series analyses of habitat loss are available above the local scale for finer-level habitat categories. We analysed, from a long-term perspective, the habitat specificity of habitat-area loss, the change in trends in habitat loss since 1989 (dissolution of the communist state), and the impact of protected areas on habitat loss in Hungary. We studied 20 seminatural habitat types in 5000 randomly selected localities over 7 periods from 1783 to 2013 based on historical maps, archival and recent aerial photos and satellite imagery, botanical descriptions, and field data. We developed a method for estimating habitat types based on information transfer between historical sources (i.e., information from a source was used to interpret or enrich information from another source). Trends in habitat loss over time were habitat specific. We identified 7 types of habitat loss over time regarding functional form: linear, exponential, linear and exponential, delayed, minimum, maximum, and disappearance. Most habitats had continuous loss from period to period. After 1986 the average annual rates of habitat loss increased, but the trend reversed after 2002. Nature conservation measures significantly affected habitat loss; net loss was halted, albeit only inside protected areas. When calculating the degree of endangerment based on short-term data (52 years), we classified only 1 habitat as critically endangered, but based on long-term data (230 years), this increased to 7 (including habitat that no longer existed). Hungary will probably reach the global Convention on Biological Diversity Target 5 but will probably not achieve the EU Biodiversity Strategy target of halting habitat loss by 2020. Long-term trend data were highly useful when we examined recent habitat-loss data in a wider context. Our method could be applied effectively in other countries to augment shorter-term data sets on trends in habitat area.