Biodiversity impacts of natural and managed ecosystems in the Anthropocene

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In human dominated ecosystems, biodiversity is severely threatened by anthropogenic disturbances that are mainly related to agriculture, forest and mining activities, urbanization, and the introduction of invasive alien species (IAS). The long term objective and vision of my research program is to gain a thorough understanding of biodiversity impacts of natural and managed ecosystems and the sustainable use of biodiversity in the context of accelerated global change. For the next 5 years, I will continue to evaluate the biodiversity impacts of some anthropogenic activities, such as mining and IAS introductions, using natural ecosystems as baselines, on severely disturbed ecosystems. I will study organisms, populations and communities through omics approaches to gain insights into: (1) how plant species, with their diversified symbionts, can establish and grow directly in mine tailings or become invasive; (2) how they tolerate, degrade, stabilize or store heavy metals and other pollutants; and (3) how ecosystem successional processes and trajectories can be predicted into the future. The short term objectives are to:(1) analyze the rhizomicrobiomes of two model plant species (the pioneer boreal species Alnus viridis subsp. Crispa and the invasive cosmopolitan Phragmites australis); (2) examine the role of symbiotic modulation plant holobionts in plant adaptation to environmental stresses and ecological amplitude; (3) elucidate the ecological functions of bioactive secondary metabolites using a metabolomics approach; and (4) develop spatially explicit individual based simulation models and statistical ecogenomic methods. I will use high throughput sequencing metagenomics approaches to untangle the rhizomicrobiomes of these model species. Metaphenomics approaches will be used to determine the functions being carried out by viable and active cells under given environmental conditions. Phenomics data will be collected from plant holobionts in manipulated controlled experiments. Bioactive metabolites that are related to stress resistance mechanisms will be isolated, and their roles and structures elucidated. Combined bioinformatics and machine learning (ML) algorithms will be used to decipher plant adaptation mechanisms and improve simulation models for predicting ecosystem successional processes and trajectories. This research program will contribute to improved understanding of ecosystem function and environmental sustainability and provide the necessary scientifically sound background information for making informed decisions regarding fine scale biodiversity conservation and its sustainable use. In collaboration with several universities in the North and the South, this research program will take into account the principles of equity, diversity, and inclusion (EDI) to ensure excellence in research and training of highly qualified personnel, while ensuring equal opportunities for all groups in these new research areas of metagenomics and phenomics.