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Keywords = Lüliang Mountainous area

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26 pages, 11852 KiB  
Article
Spatiotemporal Changes and the Drivers of Ecological Environmental Quality Based on the Remote Sensing Ecological Index: A Case Study of Shanxi Province, China
by Chi Cheng and Yanqiang Wang
Land 2025, 14(5), 952; https://doi.org/10.3390/land14050952 - 28 Apr 2025
Viewed by 571
Abstract
Ecological transition zones spanning semi-humid to semi-arid regions pose distinctive monitoring challenges owing to their climatic vulnerability and geomorphic diversity. This study focuses on Shanxi Province, a typical ecologically fragile area in the Loess Plateau of China. Based on the Google Earth Engine [...] Read more.
Ecological transition zones spanning semi-humid to semi-arid regions pose distinctive monitoring challenges owing to their climatic vulnerability and geomorphic diversity. This study focuses on Shanxi Province, a typical ecologically fragile area in the Loess Plateau of China. Based on the Google Earth Engine (GEE) platform and Moderate Resolution Imaging Spectroradiometer (MODIS) datasets, we established the Remote Sensing Ecological Index (RSEI) series from 2000 to 2024 for Shanxi Province. The Theil–Sen Median, Mann–Kendall, and Hurst indices were comprehensively applied to systematically analyze the spatiotemporal differentiation patterns of ecological environmental quality. Furthermore, geodetector-based quantification elucidated the synergistic interactions among topographic, climatic, and anthropogenic drivers. The results indicate the following: (1) From 2000 to 2024, ecological restoration initiatives have shaped an “aggregate improvement-localized degradation” paradigm, with medium-quality territories persistently accounting for 30–40% of the total land area. (2) Significant spatial heterogeneity exists, with the Lüliang Mountain area in the west and the Datong Basin in the north being core degradation zones, while the Taihang Mountain area in the east shows remarkable improvement. However, Theil–Sen Median–Hurst index predictions reveal that 60.07% of the improved areas face potential trend reversal risks. (3) The driving mechanisms exhibit spatial heterogeneity, where land use type, temperature, precipitation, elevation, and slope serve as global dominant factors. This research provides scientific support for formulating differentiated ecological restoration strategies, establishing ecological compensation mechanisms, and optimizing territorial spatial planning in Shanxi Province, contributing to the achievement of sustainable development goals. Full article
(This article belongs to the Section Landscape Ecology)
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20 pages, 1242 KiB  
Article
The Impact of Forestry Technological Innovation on the Welfare of Farm Households Managing Jujube Forests (Ziziphus jujuba Mill.) in the Lüliang Mountains of the Yellow River’s Middle Reaches
by Jin Wang, Xuemei Jiang, Xingliang Chen, Jingjing Zhang, Yaquan Dou and Jing Zhang
Forests 2024, 15(9), 1592; https://doi.org/10.3390/f15091592 - 10 Sep 2024
Viewed by 952
Abstract
Jujube (Ziziphus jujuba Mill.) makes up a traditional characteristic industry with ecological significance in the Lüliang Mountain of middle reaches of the Yellow River (LMMRYR). However, low economic efficiency has reduced local farm households’ willingness to continue jujube cultivation, threatening the sustainable [...] Read more.
Jujube (Ziziphus jujuba Mill.) makes up a traditional characteristic industry with ecological significance in the Lüliang Mountain of middle reaches of the Yellow River (LMMRYR). However, low economic efficiency has reduced local farm households’ willingness to continue jujube cultivation, threatening the sustainable maintenance and development of jujube forests and the ecological environment. In response, Lüliang City implemented a technological innovation program, that is, the Jujube Forest High Grafting and Optimization Program (JFHGOP), in 2018. Based on survey data from 302 local farm households, an empirical analysis using propensity score matching and ordinary least squares methods revealed that the program significantly enhanced the economic, ecological, and social benefits for participating farm households, improving their overall welfare. Robustness tests confirmed these findings, and a heterogeneity analysis showed varied impacts across different dimensions. The program improved welfare through government support and cooperatives’ assistance. To further promote green development and farm households’ welfare, recommendations include advancing forestry innovation technology, supporting small farm households with policy, capital, and technology, optimizing subsidy mechanisms, supporting new business entities, and promoting cooperation and benefit-sharing among stakeholders. Full article
(This article belongs to the Section Forest Economics, Policy, and Social Science)
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25 pages, 12177 KiB  
Article
Spatiotemporal Evolution and Future of Carbon Storage in Resource-Based Chinese Province: A Case Study from Shanxi Using PLUS–InVEST Model Prediction
by Yuhua Jiao, Yuhui Wang, Chenghong Tu, Xuenan Hou, Chunjuan Lyu, Xiang Fan and Lu Xia
Sustainability 2024, 16(11), 4461; https://doi.org/10.3390/su16114461 - 24 May 2024
Cited by 7 | Viewed by 1948
Abstract
Resource exploitation markedly alters land use and ecological carbon storage, posing risks to carbon sinks and food security. This study analyzes land-use change from 1990 to 2020 in the resource-based province of Shanxi, China. By introducing a mineral resource driver, the PLUS model [...] Read more.
Resource exploitation markedly alters land use and ecological carbon storage, posing risks to carbon sinks and food security. This study analyzes land-use change from 1990 to 2020 in the resource-based province of Shanxi, China. By introducing a mineral resource driver, the PLUS model was used to predict four scenarios: natural development (ND), cropland protection (CP), ecological protection (EP), and dual protection of ecology and cropland (DP). The spatial and temporal evolutions of carbon storage were then analyzed using the InVEST model. Forests were predominantly distributed in mountainous areas, with croplands in southerly and central flat areas, construction lands in and around cities, and mining lands sporadically distributed across Shanxi. From 1990 to 2020, croplands and grasslands decreased, while forest, construction, and mining lands increased. Carbon storage decreased continuously, with a total loss of 15.1 × 106 t. High-value carbon storage areas were in the Lüliang, Taihang, and Taiyue Mountains, and low-value areas were in the more populous central and southern regions. Carbon storage was predicted to decline by 2035 under the ND and CP scenarios and to exceed that of 2020 under the EP and DP scenarios. The DP scenario projected an increase of 4.93 × 106 t in carbon storage by 2035. The DP scenario realizes the protection of carbon sinks in resource-based areas and maintains food security, providing a theoretical reference for achieving carbon neutrality and high-quality sustainable development in Shanxi Province. Full article
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12 pages, 4143 KiB  
Article
Spatiotemporal Variation in Full-Flowering Dates of Tree Peonies in the Middle and Lower Reaches of China’s Yellow River: A Simulation through the Panel Data Model
by Haolong Liu, Junhu Dai and Jun Liu
Sustainability 2017, 9(8), 1343; https://doi.org/10.3390/su9081343 - 1 Aug 2017
Cited by 3 | Viewed by 4528
Abstract
The spring flowering of tree peony (Paeonia suffruticosa) not only attract tens of million tourists every year, but it can also serve as a bio-indicator of climate change. Examining climate-associated spatiotemporal changes in peony flowering can contribute to the development of [...] Read more.
The spring flowering of tree peony (Paeonia suffruticosa) not only attract tens of million tourists every year, but it can also serve as a bio-indicator of climate change. Examining climate-associated spatiotemporal changes in peony flowering can contribute to the development of smarter flower-viewing tourism by providing more efficient decision-making information. We developed a panel data model for the tree peony to quantify the relationship between full-flowering date (FFD) and air temperature in the middle and lower reaches of China’s Yellow River. Then, on the basis of the model and temperature data, FFD series at 24 sites during 1955–2011 were reconstructed and the spatiotemporal variation in FFD over the region was analysed. Our results showed that the panel data model could well simulate the phenophase at the regional scale with due consideration paid to efficiency and difficulty, and the advance of peony FFD responded to the increase in February–April temperature at a rate of 3.02 days/1 °C. In addition, the simulation revealed that regional FFDs followed the latitudinal gradient and had advanced by 6–9 days over the past 57 years, at the rate of 0.8 to 1.8 days/decade. Among sub-areas, the eastern forelands of Taihang Mountains and Luliang Mountains showed more FFD advances than the other areas. Full article
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