Development of a mathematical model to evaluate the rate of aggregate risk of invasive alien plant species： Fuzzy risk assessment approach

This study presents a novel approach to evaluate the rate of aggregate risk of Invasive Alien Plant Species. Using risk values and grade of importance of weights of risk factors which may reflect invasiveness of plant species are considered. We use Linguistic Ordered Weighted Averaging operator to evaluate the grade of important of weights. Since the risk values and important weights are identified from two different linguistic term sets, fuzzy set theory techniques were used to combine the two sets. The rates obtained from the model were compared with NRA risk levels and the model was validated with data from known and non-invasive species. The model is improved by weighting the risk values of risk factors. The improved model produced significant results and resulted a better tracking system for identifying potential invaders than the conventional risk assessment.

Monitoring River Restoration Efforts: Do Invasive Alien Plants Endanger the Success? A Case Study of the Traisen River

River restoration activities are challenging for the native vegetation and the colonization process. The development of invasive alien plant species (IAS) as well as the development of the pioneer vegetation cover and seed bank were observed in one year prior to construction of a new river bed and within the first two years after construction, along the downstream section of the river Traisen in Austria. One year after completion of the new river channel, the occurrence of IAS above ground decreased while the occurrence of target species increased. Furthermore, no seeds of IAS were detected in the new river bed as a result of proper management of soil movement. Despite the positive impact on the abundance of IAS, the restoration project of the river Traisen shows that the fact that such a restoration activity is a disturbance event must be taken into consideration already during the planning process. Supporting the competitiveness of native plant species is an important tool for reducing the danger of establishment of invasive alien species.

Effects of Water Extract of Erigeron canadensis L. on Seed Germination of Plants

[Objective] The paper was to explore the effect of water extract of Erigeron canadensis L. on seed germination of plants. [Method] Using constant temperature culture method, the effects of water extracts of roots, stems and leaves of E. canadensis on seed germination of 14 species of test plants （crops and weeds） were studied. [Result] Water extracts of roots, stems and leaves of E. canadensis had obvious inhibition effect on seed germination of test plants. The water extract of leaves had the strongest inhibition effect, which could completely inhibit the seed germination of Crepis tectorum L., Amaranthus tricolor L. and Chrysanthemum coronarium L. under the lower concentrations of 0.050 and 0.075 g/ml, and completely inhibit seed germination of all the plants under the concentration of 0.400 g/ml except Zea maize L. and Allium fistulosum L.; followed by water extract of stems, and the water extract of roots had the lowest the inhibition effect, except for completely restraining seed germination of Lycopersicum esculentum L. under the concentration of 0.300 g/ml, it still could not completely restrain seed germination of the other plants under the highest concentration of 0.500 g/ml. The inhibition effect of water extract of E. canadensis on seed germination of plants had obvious selectivity, which had more obvious effect on dicotyledonous plants than monocotyledonous plants. [Conclusion] The study provided reference for screening and utilization of allelochemicals of E. canadensis and research on its allelopathy mechanism.

Mapping common and glossy buckthorns (Frangula alnus and Rhamnus cathartica) using multi-date satellite imagery WorldView-3, GeoEye-1 and SPOT-7

Buckthorns(Glossy buckthorn,Frangula alnus and common buckthorn,Rhamnus cathartica)represent a threat to biodiversity.Their high competitivity lead to the replacement of native species and the inhibition of forest regeneration.Early detection strategies are therefore necessary to limit invasive alien plant species’impacts,and remote sensing is one of the techniques for early invasion detection.Few studies have used phenological remote sensing approaches to map buckthorn distribution from medium spatial resolution images.Those studies highlighted the difficulty of detecting buckthorns in low densities and in understory using this category of images.The main objective of this study was to develop an approach using multi-date very high spatial resolution satellite imagery to map buckthorns in low densities and in the understory in the Québec city area.Three machine learning classifiers(Support Vector Machines,Random Forest and Extreme Gradient Boosting)were applied to WorldView-3,GeoEye-1 and SPOT-7 satellite imagery.The Random Forest classifier performed well(Kappa=0.72).The SVM and XGBoost’s coefficient Kappa were 0.69 and 0.66,respectively.However,buckthorn distribution in understory was identified as the main limit to this approach,and LiDAR data could be used to improve buckthorn mapping in similar environments.