Abstract
Climate challenges impose the need for successful afforestation strategies which will increase the amount of carbon sequestered from the atmosphere. In practice, this means evaluation of suitable plant species and management practices for the long-term effects to prove beneficial. In the present study we employed a clasmometric approach to look into biomass partitioning in two tree species, Populus sibirica and Ulmus pumila, which have been included in the formation of the Green Belt project in Asia. Comparing the total biomass comprised of the above ground (AG) and below ground (BG) biomass of trees grown in different irrigation and fertilization regimes, we aim to better understand where the two species invest more biomass as a tool to deal with the environmental challenges. The results suggest that these two tree species prioritize different aspects of development when faced with various challenges. U. pumilia tends to be more resistant to drought making it favorable for the semi-arid and arid regions. P. sibirica is more sensitive to the lack of water but shows greater potential in terms of biomass production (especially AG biomass) and, therefore, overall higher C-sequestration. The fertilization treatments made no significant impact on tree development on Mongolian steppe soil.
Acknowledgements
The authors gratefully thank the staffs of the Korea-Mongolia Joint Green Belt Plantation Project and the members of the Laboratory of Forest Genetics and Ecophysiology, the National University of Mongolia for their assistance in the laboratory and field works. AM and DC acknowledge the Department of Biotechnology and Life Science at the University of Insubria for providing the necessary support to the joint research project. This work is included in the activities of Task Force IUFRO “Transforming Forest Landscapes for future Climates and Human Well-being”. G.S.S. and A.D. acknowledge the University of Molise for providing the Ph. D. fellowship for A.D.
Author contributions
Conceptualization, B.N., D.C., and AM.; methodology, D.C., A.M., B.N., S.B.; software and data analysis, S.B.; data collection, S.B., Ts.A.; writing - original draft preparation, S.B., G.SS., A.D. D.C.; writing - review and editing, B.N., B.B.P., A.D.; supervision, B.N., D.C.; funding acquisition, B.N. All authors have read and agreed to the published version of the manuscript.
Disclosure statement
No potential conflict of interest was reported by the authors.
Data availability statement
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.