Mathematical and Computational Forestry & Natural-Resource Sciences (MCFNS)

The mission of MCFNS is to publish peer-reviewed basic and applied research in Mathematical and Computational Forestry and Natural-Resource Sciences. This research can include analytical solutions, proofs, derivations, software developments, and simulations, in forest management, growth and yield modeling, and other natural resource related studies. Journal items are published collectively as part of an issue with its Table of Contents biannually, currently in March and October

Abstract thinking is useful

'The Thinker' (above) - Rodin
'In a certain sense, I hold it true that pure thought
can grasp reality, as the ancients dreamed.' - Einstein



MCFNS Scopus Ranking: Q2;  

SCImago Journal & Country Rank 



MCFNS Publications: MCFNS is covered in Clarivate Analytics services.


Beginning with V. 9 (1) 2017, this publication will be indexed and abstracted in:

♦ Emerging Sources Citation Index

Posted: 2017-11-13 More...
More Announcements...

Vol 12, No 1: MCFNS March 30, 2020

Table of Contents

Programming and Software Development

Haozhou Wang, John A. Kershaw, Ting-Ru Yang, Yung-Han Hsu, Xu Ma, Yingbing Chen

Mathematical Modeling

Xingdong Li, Hewei Gao, Chengqi Han, Yangwei Wang, Tongxin Hu, Long Sun, Yanling Guo
Vladimir Shanin, Pavel Grabarnik, Maxim Shashkov, Natalya Ivanova, Sergey Bykhovets, Pavel Frolov, Miroslav Stamenov

Growth & Yield and Quantitative Silviculture

Christopher Isaac Kirk, John-Pascal Berrill