文献类型：期刊文献

英文题名：Assessment and Evolutionary Characteristics of Herbaceous Vegetation Condition in Steppe Regions of the Forest-Steppe Ecotone in Northeastern China

作者：Han, Dong[1] Jia, Zhiqing[1,2] Wang, Long[1,3] Wu, Rina[4] He, Lingxianzi[2] Zhang, Jiapeng[5] Li, Lianxing[1] Tian, Jiapeng[6] Ding, Wei[6] Shang, Haili[6] Zhou, Zhijun[6]

第一作者：Han, Dong

机构：[1] Research Institute of Forestry, Chinese Academy of Forestry, CAF, Beijing, 100091, China; [2] Institute of Ecological Protection and Restoration, Chinese Academy of Forestry, CAF, Beijing, 100091, China; [3] National Academy of Forestry and Grassland Administration, Beijing, 100714, China; [4] Forestry Science and Technology Information Research Institute, Chinese Academy of Forestry, CAF, Beijing, 100091, China; [5] Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, CAS, Changchun, 130102, China; [6] Inner Mongolia Baiyin Obo Forest Farm, Chifeng, 025369, China

年份：2025

外文期刊名：SSRN

收录：EI(收录号：20250474062)

语种：英文

外文关键词：Barium compounds - Biodiversity - Biotic - Climate change - Conservation - Dynamics - Ecosystems - Environmental monitoring - Forest ecology - Forestry - Land use - Remote sensing - Vegetation

摘要：The Forest-Steppe Ecotone, a transitional zone between forest and steppe ecosystems, exhibits high ecological heterogeneity and biodiversity but is highly vulnerable to climate change and human disturbances. Recent degradation in this region poses significant threats to environmental security and the stability of steppes. Conventional remote sensing vegetation indices often inadequately capture the complex ecological dynamics of ecotones, limiting their application in monitoring vegetation changes. In this study, we investigated the Baiyin Aobao Forest Farm in Chifeng, Inner Mongolia. We used nearly 30 years of land-use data to analyze spatial dynamics and replacement patterns among forest, sparse vegetation, and steppe. Integrating Sentinel-2 imagery, we developed a composite Herbaceous Composite Evaluation Index (HCEI) by combining five remote sensing indices—NDVI, SAVI, NDMI, CI, and BI2—weighted via principal component analysis and validated with high-resolution UAV imagery. Steppe condition was classified and mapped to reveal spatial-temporal patterns from 1990 to 2022. Results indicate that 84% of steppe areas remained stable, while sparse vegetation and steppe showed dynamic complementary interactions. Vegetation indices peaked around 2019, reflecting optimal ecological conditions, followed by a decline post-2020 alongside increased surface exposure indicators, signaling degradation. Spatial distribution showed higher-quality steppes in the northeast and east, with degraded areas concentrated in the southwest. Grade I steppe peaked at 31.77% in 2019 but decreased to 29.18% by 2022; Grade V degraded steppe rose to 21.33%. Vegetation condition transitions exhibited strong spatial autocorrelation (max Moran’s I = 0.9153), and predictive modeling demonstrated high accuracy (R2 = 0.9884). Grade III steppe acted as a critical transitional state with bidirectional succession. This multi-source remote sensing framework effectively characterizes and predicts herbaceous vegetation dynamics, offering a robust basis for monitoring degradation and guiding restoration efforts, thereby improving ecological management in sensitive steppe ecotones. ? 2025, The Authors. All rights reserved.