Understanding patterns and potential drivers of forest diversity in northeastern China using machine‐learning algorithms-Reference-Cited by-同舟云学术

Understanding patterns and potential drivers of forest diversity in northeastern China using machine‐learning algorithms

Published:2021-03 Issue:2 Volume:32 Page:
ISSN:1100-9233
Container-title:Journal of Vegetation Science
language:en
Short-container-title:J Veg Sci

Author:

Luo Weixue¹^ORCID,Zhang Chunyu¹^ORCID,Zhao Xiuhai¹^ORCID,Liang Jingjing²^ORCID

Affiliation:

1. Research Center of Forest Management Engineering of State Forestry and Grassland Administration Beijing Forestry University Beijing China

2. Forest Advanced Computing and Artificial Intelligence Laboratory (FACAI) Department of Forestry and Natural Resources Purdue University West Lafayette IN USA

Publisher

Wiley

Subject

Plant Science,Ecology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/jvs.13022

Reference137 articles.

1. Towards an understanding of the drivers of broad-scale patterns of rarity-weighted richness for vertebrates

2. The interpretation of biological surveys

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4. The relative effectiveness of protected areas, a logging ban, and sacred areas for old-growth forest protection in southwest China

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