How to characterize the decline of natural Pinus sylvestris var. Mongolica forests on sandy land?

In recent years, the natural Pinus sylvestris var. mongolica (Mongolian pine) forests on the Hulunbuir sandy lands in northeastern China have experienced substantial decline, with the affected area continuously expanding. Although this decline is often linked to combined effects of human disturbance and climate change, understanding its underlying mechanisms first requires defining the key decline characteristics, such as the minimum detectable area, severity grades, and spatial distribution patterns. However, previous studies have lacked clear quantitative criteria for determining when a stand can be considered in decline, leading to inconsistencies in assessment across different spatial scales. In this study, we used multispectral unmanned aerial vehicle (UAV) imagery and a random forest algorithm to evaluate vegetation indices for detecting forest decline. The species–area curve and upscaling methods were applied to determine the minimum detectable area and to map decline distribution. The results indicated that the Green Normalized Difference Vegetation Index (GNDVI) is a reliable indicator of Mongolian pine decline. The optimal survey area for accurate assessment was 3.24 ha, and the decline severity could be classified into three levels: severe (VGNDVI < 0.57), mild (0.57–0.63), and normal (> 0.63). Over the study region, approximately 1 % of the forest area showed signs of decline, with severe cases being sparsely distributed. Overall, this study identifies GNDVI as an effective indicator and clarifies the characteristic scales and spatial patterns of Mongolian pine decline, providing a scientific foundation for precision monitoring and restoration planning. • The Green Normalized Difference Vegetation Index (GNDVI) effectively identifies the decline of Mongolian pine. • A minimum decline area of 3.24 ha was identified for Mongolian pine. • Established the classification criteria for three-level decline.

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Journal
Global Ecology and Conservation
Published
2025-11-05
DOI
https://doi.org/10.1016/j.gecco.2025.e03955
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
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article

How to characterize the decline of natural Pinus sylvestris var. Mongolica forests on sandy land?

Mingxi Zhang, Jiaojun Zhu, Jinnan Ge, Ke Qi et al.
Global Ecology and Conservation
Remote Sensing in Agriculture
article

How to characterize the decline of natural Pinus sylvestris var. Mongolica forests on sandy land?

Mingxi Zhang, Jiaojun Zhu, Jinnan Ge, Ke Qi, Xiaolin Zhang, Xiao Zheng, Heng Tian, Lining Song
article en

Abstract

In recent years, the natural Pinus sylvestris var. mongolica (Mongolian pine) forests on the Hulunbuir sandy lands in northeastern China have experienced substantial decline, with the affected area continuously expanding. Although this decline is often linked to combined effects of human disturbance and climate change, understanding its underlying mechanisms first requires defining the key decline characteristics, such as the minimum detectable area, severity grades, and spatial distribution patterns. However, previous studies have lacked clear quantitative criteria for determining when a stand can be considered in decline, leading to inconsistencies in assessment across different spatial scales. In this study, we used multispectral unmanned aerial vehicle (UAV) imagery and a random forest algorithm to evaluate vegetation indices for detecting forest decline. The species–area curve and upscaling methods were applied to determine the minimum detectable area and to map decline distribution. The results indicated that the Green Normalized Difference Vegetation Index (GNDVI) is a reliable indicator of Mongolian pine decline. The optimal survey area for accurate assessment was 3.24 ha, and the decline severity could be classified into three levels: severe (VGNDVI < 0.57), mild (0.57–0.63), and normal (> 0.63). Over the study region, approximately 1 % of the forest area showed signs of decline, with severe cases being sparsely distributed. Overall, this study identifies GNDVI as an effective indicator and clarifies the characteristic scales and spatial patterns of Mongolian pine decline, providing a scientific foundation for precision monitoring and restoration planning. • The Green Normalized Difference Vegetation Index (GNDVI) effectively identifies the decline of Mongolian pine. • A minimum decline area of 3.24 ha was identified for Mongolian pine. • Established the classification criteria for three-level decline.

Global Ecology and ConservationVol. 64
Liaoning University (CN), Chinese Academy of Sciences (CN), Fanjingshan National Nature Reserve (CN), Institute of Applied Ecology (CN), University of Chinese Academy of Sciences (CN)
Openalex Percentile: Top 68%
Remote Sensing in Agriculture
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