Spatio-Temporal Changes in Habitat Qualityand Linkage with Red-Crowned CranesUsing the InVEST Model: A Case Study atYancheng National Nature Reserve, China

The red-crowned crane is a rare species, classified as a national first-class protected animal in China.It relies on the Yancheng National Nature Reserve (YNNR) as its largest wintering habitat globally.Therefore, studying the habitat quality and spatiotemporal distribution of red-crowned cranes in the YNNR is important for their conservation and the maintenance of biodiversity.This study employed the Random Forest algorithm for land use classification and the InVEST model for habitat quality assessment, innovatively incorporating red-crowned crane survival factors and vegetation cover.The gray correlation was used to analyze the response of cranes to the habitat quality.The results showed that: (1) Despite an overall high habitat quality, a declining trend was observed, with the average habitat quality index decreasing from 0.553 in 1993 to 0.516 in 2023.(2) Habitat degradation significantly exceeded improvement by 107.37 km 2 , reflecting intensifying human impact.(3) The red-crowned crane population initially increased and subsequently declined, shifting its distribution from uniform across the YNNR to a concentration within the core area.The red-crowned crane population showed an extremely strong correlation with the areas of lowest and medium habitat quality.Finally, this study recommends controlling anthropogenic disturbances, curbing the expansion of Spartina alterniflora, and strengthening governmental oversight to protect the environment and biodiversity of the redcrowned crane habitat.

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Publication Details

Journal
Polish Journal of Environmental Studies
Published
2025-04-22
DOI
https://doi.org/10.15244/pjoes/203047
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Spatio-Temporal Changes in Habitat Qualityand Linkage with Red-Crowned CranesUsing the InVEST Model: A Case Study atYancheng National Nature Reserve, China

Zhenghao Li, Jingjing Zhou, Nan Li, Yinlong Zhang et al.
Polish Journal of Environmental Studies
Remote Sensing and LiDAR Applications
article

Spatio-Temporal Changes in Habitat Qualityand Linkage with Red-Crowned CranesUsing the InVEST Model: A Case Study atYancheng National Nature Reserve, China

Zhenghao Li, Jingjing Zhou, Nan Li, Yinlong Zhang, Yongbo Wu, Rong Chen, Yazhou Tang
article en

Abstract

The red-crowned crane is a rare species, classified as a national first-class protected animal in China.It relies on the Yancheng National Nature Reserve (YNNR) as its largest wintering habitat globally.Therefore, studying the habitat quality and spatiotemporal distribution of red-crowned cranes in the YNNR is important for their conservation and the maintenance of biodiversity.This study employed the Random Forest algorithm for land use classification and the InVEST model for habitat quality assessment, innovatively incorporating red-crowned crane survival factors and vegetation cover.The gray correlation was used to analyze the response of cranes to the habitat quality.The results showed that: (1) Despite an overall high habitat quality, a declining trend was observed, with the average habitat quality index decreasing from 0.553 in 1993 to 0.516 in 2023.(2) Habitat degradation significantly exceeded improvement by 107.37 km 2 , reflecting intensifying human impact.(3) The red-crowned crane population initially increased and subsequently declined, shifting its distribution from uniform across the YNNR to a concentration within the core area.The red-crowned crane population showed an extremely strong correlation with the areas of lowest and medium habitat quality.Finally, this study recommends controlling anthropogenic disturbances, curbing the expansion of Spartina alterniflora, and strengthening governmental oversight to protect the environment and biodiversity of the redcrowned crane habitat.

Polish Journal of Environmental Studies
Government of Jiangsu Province
Life in Land
Openalex Percentile: Top 92%
Remote Sensing and LiDAR Applications
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