Climatic, hydrological and soil characteristics as a driving force of biological invasion: a case study of Hungary

Invasive plants are a serious threat to biodiversity, biological invasion is a significant problem in protected areas. In order to control their spread, we need to identify the soil, hydrological and climatic conditions which provide favorable conditions for their occurrence. Soil conditions, such as pH level, organic matter and calcium carbonate content and the rooting depth can influence the occurrence of invasive plant species. Many plant species can be associated with surface water, and thus distance from surface water can also be a determining factor for biological invasion. Mean annual temperature and precipitation are climatic factors that can also influence the spread of invasive plants. We mapped the occurrence one of the most aggressively spreading non-native plants of Eurasia (Ailanthus altissima, Asclepias syriaca, Elaeagnus angustifolia, Robinia pseudoacacia, Solidago spp.) in Hungary, using field photos from the EUROSTAT Land Use and Coverage Area Frame Survey (LUCAS) and CORINE Land Cover databases, and investigated with geostatistical methods (ANOVA test in R statistics) how spatial characteristics of infection are related to soil and climatic characteristics and habitat types of Hungary. We found that all the considered soil, hydrological and climatic factor had significant effect for the spread of the investigated invasive plant species. Our results confirm that environmental preference differs between the examined species, climate change may also have a different role on the occurrence

Applicability of Point- and Polygon-Based Vegetation Monitoring Data to Identify Soil, Hydrological and Climatic Driving Forces of Biological Invasions—A Case Study of Ailanthus altissima, Elaeagnus angustifolia and Robinia pseudoacacia

Invasive tree species are a significant threat to native flora. They modify the environment with their allelopathic substances and inhibit the growth of native species by shading, thus reducing diversity. The most effective way to control invasive plants is to prevent their spread which requires identifying the environmental parameters promoting it. Since there are several types of invasive plant databases available, determining which database type is the most relevant for investigating the occurrence of alien plants is of great importance. In this study, we compared the efficiency and reliability of point-based (EUROSTAT Land Use and Coverage Area Frame Survey (LUCAS)) and polygon-based (National Forestry Database (NFD)) databases using geostatistical methods in ArcGIS software. We also investigated the occurrence of three invasive tree species (Ailanthus altissima, Elaeagnus angustifolia, and Robinia pseudoacacia) and their relationships with soil, hydrological, and climatic parameters such as soil organic matter content, pH, calcium carbonate content, rooting depth, water-holding capacity, distance from the nearest surface water, groundwater depth, mean annual temperature, and mean annual precipitation with generalized linear models in R-studio software. Our results show that the invasion levels of the tree species under study are generally over-represented in the LUCAS point-based vegetation maps, and the point-based database requires a dataset with a larger number of samples to be reliable. Regarding the polygon-based database, we found that the occurrence of the invasive species is generally related to the investigated soil and hydrological and climatic factors

Natura 2000 Areas, Road, Railway, Water, and Ecological Networks May Provide Pathways for Biological Invasion: A Country Scale Analysis

Invasive species are a major threat to biodiversity worldwide. Controlling their rapid spread can only be effective if we consider the geographical factors that influence their occurrence. For instance, roads, railway networks, green and blue infrastructure, and elements of ecological networks (e.g., ecological corridors) can facilitate the spread of invasive species. In our study, we mapped the occurrence of five invasive plant taxa (tree of heaven, common milkweed, Russian olive, black locust, and goldenrods) in Hungary, using field photos from the EUROSTAT Land Use and Coverage Area Frame Survey (LUCAS) database from the year 2015. Species point occurrence data were compared with the spatial characteristics of linear transport infrastructure and with the green and blue infrastructure. We found that the occurrence of tree of heaven and Russian olive was strongly related to the road and railway network. The average Euclidean distance of LUCAS points infected with these species from railway embankments and roads was much smaller than that of uninfected points. However, black locust and goldenrods were more common only along the road network. According to our results, the occurrence of some investigated invasive plants was over-represented in the HEN and within Natura 2000 areas of Hungary compared to non-infected points. Our results may provide important information for predicting the rate of invasion and for applying targeted management within the HEN, and Natura 2000 protected areas

Applicability of Point- and Polygon-Based Vegetation Monitoring Data to Identify Soil, Hydrological and Climatic Driving Forces of Biological Invasions—A Case Study of <i>Ailanthus altissima</i>, <i>Elaeagnus angustifolia</i> and <i>Robinia pseudoacacia</i>

Invasive tree species are a significant threat to native flora. They modify the environment with their allelopathic substances and inhibit the growth of native species by shading, thus reducing diversity. The most effective way to control invasive plants is to prevent their spread which requires identifying the environmental parameters promoting it. Since there are several types of invasive plant databases available, determining which database type is the most relevant for investigating the occurrence of alien plants is of great importance. In this study, we compared the efficiency and reliability of point-based (EUROSTAT Land Use and Coverage Area Frame Survey (LUCAS)) and polygon-based (National Forestry Database (NFD)) databases using geostatistical methods in ArcGIS software. We also investigated the occurrence of three invasive tree species (Ailanthus altissima, Elaeagnus angustifolia, and Robinia pseudoacacia) and their relationships with soil, hydrological, and climatic parameters such as soil organic matter content, pH, calcium carbonate content, rooting depth, water-holding capacity, distance from the nearest surface water, groundwater depth, mean annual temperature, and mean annual precipitation with generalized linear models in R-studio software. Our results show that the invasion levels of the tree species under study are generally over-represented in the LUCAS point-based vegetation maps, and the point-based database requires a dataset with a larger number of samples to be reliable. Regarding the polygon-based database, we found that the occurrence of the invasive species is generally related to the investigated soil and hydrological and climatic factors