Final Report Summary - IASIMOV (Invasive Alien Species: towards Improved MOdeling tools through Virtual ecology) In Europe and worldwide, many plant communities are increasingly becoming dominated by introduced species. Invasive alien species (IAS) have caused severe environmental changes globally by altering species composition and ecosystem function and are considered a major threat to biodiversity. Consequently the Action Plan for Biodiversity advocates a comprehensive strategy at EU level to reduce the impact of IAS. The IASIMOV project aimed at merging perspectives from plant evolutionary, functional and community ecology with those from simulation modeling to reveal the processes underlying plant invasions and improve our statistical framework for studying and preventing them. There are four research objectives on the one hand relying on theoretical modeling and on the other aiming to apply the knowledge acquired from the theoretical modeling part to empirical data in France. In particular, the project aimed at 1) developing and validating a process-based simulation model to explore how environmental and biotic filters for local community assembly are reflected in invasion patterns using virtual data; 2) testing the ability of current statistical methods to disentangle patterns resulting from overlaying filters and providing guidelines for improved method performance using simulated data; 3) applying the improved statistical methods on French grassland plant communities to explore shifts in dominant invasion processes across scales, environmental gradients and invasion stages; 4) parameterizing a landscape simulation model in order to identify the processes and the species characteristics leading to successful invasions in the French Alpine region. First, by relying on a process-based model simulating community assembly and invasion we tested the performance of the available metrics quantifying the similarity of the invader to the native community to retrieve the processes of competition and environmental filtering. Our results indicated that the best performing index was the average functional distance between the invader and all the species of the community, especially in heterogeneous landscapes. Further, we demonstrated that the detection of competition was more sensitive to the presence of biases in the data than was the detection of environmental filtering. Finally we provided guidelines for how method performance can be improved by choosing the correct metrics depending on the ecological questions and dataset under investigation.Second, we tested these theoretical predictions in a controlled experimental setting. We carried out a large experiment with the aim of relating the functional dissimilarity of a set of introduced alien species to native communities with their invasion success and with the competition experienced from the natives, under different environmental conditions (i.e. aridity). In this experiment an aridity treatment was applied to simulate environmental stress and pots with and without the native community were used to estimate competition intensity on the alien species. We found that considering intraspecific trait variability was essential in order to be able to detect a relation between functional similarity and competition strength with the natives and that whether similarity to the natives hampered or favored invasion success critically depended on the life stage under consideration (survival vs. growth vs. reproduction).Third, using permanent grasslands across France (50,000 vegetation-plots, 2000 species, 130 aliens) and building on a new classification system to quantify spread, we showed that phylogenetic and functional similarities to natives were the most important correlates of invasion success compared to intrinsic functional characteristics and introduction history. Results contrasted between spatial scales and components of invasion success. Widespread and common aliens were similar to co-occurring natives at coarse scales (indicating environmental filtering), but dissimilar at finer scales (indicating local competition). In contrast, regionally widespread but locally rare aliens showed patterns of competitive exclusion already at coarse scale. We concluded that quantifying trait differences between aliens and natives and distinguishing the components of invasion success improved our ability to understand and potentially predict alien spread at multiple scales.Finally, a key step to critically assess the risk of spread of alien species into the wild is to simulate their potential spread in a real case study and under different environmental change and management scenarios. We therefore parameterized an existing landscape simulation model (FATE-HD) for invader functional groups in order to forecast invasion success in a protected area (Ecrins National Park) in the French Alps as a function of species characteristics and of processes such as propagule pressure, climate change and land use intensification. FATE-HD allows us to simulate the spatio-temporal dynamics of interacting plant functional groups in response to climate and land use. Functional groups compete for light and for soil nutrients and have specific life-history characteristics, and were calibrated for the Ecrins National Park. Two sets of alien species were selected for modeling: the most abundant alien species already present in the surrounding Alpine region and a set of ornamental species with high potential of becoming future invaders in this area. Simulations will allow to infer their chance of success in the Ecrins National Park as a function of different scenarios of propagule pressure, climate change and land-use intensification.Overall, the outcome of the project will be of high relevance for both scientific knowledge-building in the field of invasion ecology and the support of decision makers in invasion management
