South Manchurian mixed forests (SMMFs): distribution maps (2001 & 2021) and habitat suitability models

Dzizyurova, Violetta D.; Dudov, Sergey V.; Korznikov, Kirill A.; Petrenko, Tatyana Ya.; Grishchenko, Mikhail Yu.; Krestov, Pavel V. | 2026

Description

This repository contains data and code accompanying the study "Satellite-based mapping of South Manchurian mixed forests highlights critical conservation needs", which assesses the status and threats to one of the most biodiverse temperate forests globally.

Background and Significance

The South Manchurian mixed forests (SMMF), spanning northeastern China, southern Primorsky Krai (Russia), and the Korean Peninsula, are experiencing significant degradation. They are being replaced by secondary growth, agricultural land, and anthropogenic vegetation. Precise quantification of the remaining SMMF patches is critical for their conservation.

Materials and Methods

Mapping: Integration of original geobotanical data (relevés, literature, regional maps) to train classifiers using Landsat time-series (GLAD ARD, 30m). Ensemble decision tree methods were employed.

Potential Distribution Modelling: Application of habitat suitability modelling (ecological niche modelling) using community-level presence/absence data, topographic (elevation, slope, aspect), and bioclimatic predictors (a proxy for precipitation, warmth and continentality indices).

Keywords

Abies holophylla East Asia forest map GLAD ARD Landsat Northeast Asia South Manchurian mixed forests

Related Paper

Violetta D. Dzizyurova, Sergey V. Dudov, Kirill A. Korznikov, Tatyana Ya. Petrenko, Mikhail Yu. Grishchenko, Pavel V. Krestov (2026). Satellite‐Based Mapping of South Manchurian Mixed Forests Highlights Critical Conservation Needs. Applied Vegetation Science, 29. https://doi.org/10.1111/avsc.70087

Link to the data

South Manchurian mixed forests (SMMFs): distribution maps (2001 & 2021) and habitat suitability models
Code Data
South Manchurian mixed forests (SMMFs): distribution maps (2001 & 2021) and habitat suitability models
Code Data
Open
Metadata
  • Journal:
    Applied Vegetation Science
  • Subject:
    Data analysis methods Spatial pattern
  • Continent:
    Asia
  • Biome:
    Temperate midlatitudes
  • Year:
    2026
  • Added (index entry):
    Sep 29, 2026 8:41 AM

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