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

Marianna Biró,Zsolt Molnár,János Bölöni

doi:10.1111/cobi.13038

Abstract

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.

Highlights

There is an increasing amount of published data on biodiversity loss, its acceleration over recent decades, and its impacts on human well-being (e.g., MA 2005; Keil et al 2015)
Long-Term Habitat Loss Trends All habitat types decreased in areal extent over the 230-year period (Fig. 1), with one exception (91N0, Pannonic inland sand dune thickets)
For 4 habitat types, the differences between the rates were

Summary

Introduction

There is an increasing amount of published data on biodiversity loss, its acceleration over recent decades, and its impacts on human well-being (e.g., MA 2005; Keil et al 2015). Historical maps and written sources before the 1950s are usually of limited reliability when it comes to habitat type and characterisitics (Keith et al 2009; Gimmi et al 2011; Kaim et al 2016); long-term studies of habitat loss are scarce (but see Batek et al 1999; Hall et al 2002; Wulf & Rujner 2011; Bradshaw 2012; Hooftman & Bullock 2012). To make reliable and detailed long-term reconstructions of habitat loss for finer-level habitat types, we developed a point-based, iterative method This method involves information transfer between data sources (information from one data base is transferred to another database) carried out on the basis of expert knowledge to overcome problems caused by data limitations, topographical incompatibilities among historical sources, and the abiotic heterogeneity of patches (e.g., Hohensinner et al 2013; Munteanu et al 2015; Kaim et al 2016)

Methods

Results

Conclusion