Continent-Wide Tree Species Distribution Models May Mislead Regional Management Decisions: A Case Study in the Transboundary Biosphere Reserve Mura-Drava-Danube

Unravelling the impact of soil data quality on species distribution models of temperate forest woody plants

Soil properties influence plant physiology and growth, playing a fundamental role in shaping species niches in temperate forest ecosystems. Here, we investigated the impact of soil data quality on the performance of species distribution models (SDMs) of 41 woody plant species in Swiss forests. We compared models based on measured soil properties with those based on digitally mapped soil properties on regional (Swiss Forest Soil Maps) and global scales (SoilGrids). We first calibrated topo-climatic SDMs with measured soil data and plant species presences and absences from mature temperate forest stand plots. We developed further models using the same soil predictors, but with values extracted from digital soil maps at the nearest neighbouring plots of the Swiss National Forestry Inventory. The predictive power of SDMs without soil information compared to those with soil information, as well as measured soil information vs digitally mapped, was evaluated with metrics of model performance and variable contribution. On average, models with measured and digitally mapped soil properties performed significantly better than those without soil information. SDMs based on measured and Swiss Forest Soil Maps showed higher performance, especially for species with an 'extreme' niche position (e.g., preference for high or low pH), compared to those using SoilGrids. Nevertheless, if no regional soil maps are available, SoilGrids should be tested for their potential to improve SDMs. Moreover, among the tested soil predictors, pH, and clay content of the topsoil layers most improved the predictive power of SDMs for forest woody plants. In conclusion, we demonstrate the value of regional soil maps for predicting the distribution of woody species across strong environmental gradients in temperate forests. The improved accuracy of SDMs and insights into drivers of distribution may support forest managers in strategies supporting e.g. biodiversity conservation, or climate adaptation planning.

Sustainable Tourism to the Part of Transboundary UNESCO Biosphere Reserve “Mura-Drava-Danube”. A Case of Serbia, Croatia and Hungary

Biosphere reserves are protected areas vital for the preservation of living and inanimate nature, including the protection of anthropogenic values and cultural heritage. The basins of the Mura, Drava, and Danube rivers stretch through Slovenia, Croatia, Austria, Hungary, and Serbia and form a unique spatial unity. The Biosphere Reserve concept defines about 300,000 hectares of core and buffer zones and around 700,000 hectares of transition zones. This large, primarily marshy area is rich in natural and cultural heritage. This area is called “the Amazon of Europe” and represents the world’s first Transboundary UNESCO Biosphere Reserve, “Mura-Drava-Danube,” among five countries. This biosphere reserve is important for the preservation of the natural and cultural values of the entire region. Especially rare plant and animal representatives live in this unique geographical unity. Some species inhabit only this area. A total of 900,000 people living around this reserve have a rich cultural tradition and heritage that needs to be protected. The objective of the research is to examine the function that the selected protected areas have in the sustainable development of tourism. Quantitative methodology was used in the research. An analysis of the conducted questionnaire was performed using the SPSS v.21 software, as well as a comparative analysis of the attitudes of 1295 residents from three countries. Residents’ attitudes refer to the level of ecological, economic, socio-cultural, and institutional sustainability of this biosphere reserve as a tourist destination. The research results indicate that the four dimensions of sustainability have significant values and that the selected areas have an important function in the sustainable development of tourism.

Comparing environmental impacts of alien plants, insects and pathogens in protected riparian forests

The prioritization of alien species according to the magnitude of their environmental impacts has become increasingly important for the management of invasive alien species. In this study, we applied the Environmental Impact Classification of Alien Taxa (EICAT) to classify alien taxa from three different taxonomic groups to facilitate the prioritisation of management actions for the threatened riparian forests of the Mura-Drava-Danube Biosphere Reserve, South East Europe. With local experts we collated a list of 198 alien species (115 plants, 45 insects, and 38 fungi) with populations reported in southeast European forest ecosystems and included them in the EICAT. We found impact reports for 114 species. Eleven of these species caused local extinctions of a native species, 35 led to a population decrease, 51 to a reduction in performance in at least one native species and for 17 alien species no effects on individual fitness of native species were detected. Fungi had significantly highest impact and were more likely to have information on their impacts reported. Competition and parasitism were the most important impact mechanisms of alien species. This study is, to our knowledge, the first application of EICAT to all known alien species of several taxonomic groups in a protected area. The impact rankings enabled to identify taxa that generally cause high impacts and to prioritize species for the management in protected areas according to their impact magnitudes. By following a standardized impact protocol, we identified several alien species causing high impacts that do not appear on any expert-based risk list, which are relevant for policymakers. Thus, we recommend that alien species be systematically screened to identify knowledge gaps and prioritize their management with respect to spatio-temporal trends in impact magnitudes.