Analyzing spatial patterns and driving factors of cropland change in China's National Protected Areas for sustainable management

Du, Bin; Ye, Sijing; Gao, Peichao; Ren, Shuyi; Liu, Chenyu; Song, Changqing

doi:10.1016/j.scitotenv.2023.169102

Cited by 10 publications

(3 citation statements)

References 73 publications

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“…to describe the relationship between independent variables and dependent variables by establishing a mathematical model (Zvizdojevićand Vukotic, 2015;Du et al, 2024), so as to predict or explain the value of dependent variables given independent variables. In this study, the quantitative relationship between the driving factor and the marine ecosystem protection pattern was determined by regression analysis.…”

Section: Regression Analysismentioning

confidence: 99%

Protection pattern and driving mechanism of typical marine ecosystems: a case study of China-ASEAN countries

Chen,

Cui,

et al. 2024

Front. Mar. Sci.

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The protection pattern of typical marine ecosystems is an overall summary of the regional marine ecosystem protection, indicating the protection status of typical marine ecosystems. The coastal waters of China and ASEAN countries have a highly diverse range of ecosystem types, including mangroves, coral reefs, and seagrass beds. The need to protect these ecosystems is urgent, but establishing marine protected areas often involves conflicts with stakeholders highly dependent on these ecosystems. By constructing an analysis model of the protection pattern and driving mechanisms of typical marine ecosystems, with a focus on the China-ASEAN region, this study aimed to analyze the characteristics of typical marine ecosystems protection patterns in China-ASEAN, evaluate the current protection status of these ecosystems, discuss the driving factors, and derive a regression function to clarify the quantitative relationship between the protection pattern and driving factors of typical marine ecosystems in the China-ASEAN region. The results indicate that there are four main driving factors influencing the protection pattern of typical marine ecosystems in China-ASEAN countries. The most significant driving factor is the Natural Geographic and Resource Factor, followed by Urbanization, Industrial Structure, and Population Size and GDP Factor. Among these, the Natural Geographic and Resource Factor and the Industrial Structure Factor have a positive impact, while the others have a negative impact. In the future, it is crucial to fully consider the diversity and distribution of marine ecosystems to promote joint efforts among China-ASEAN countries in protecting marine ecosystems through international cooperation.

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Section: Regression Analysismentioning

confidence: 99%

Protection pattern and driving mechanism of typical marine ecosystems: a case study of China-ASEAN countries

Chen,

Cui,

et al. 2024

Front. Mar. Sci.

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“…Ecological conditions are affected by a variety of factors, which can be divided into natural factors such as terrain, soil, and climate, as well as human factors including social economy, among others [17]. The analysis methods for driver identification mainly include correlation analysis, principal component analysis, linear regression analysis, geographical detectors, and spatial regression analysis [18][19][20][21]. Geographical detectors can detect both numerical and continuous data and can avoid the influence of multivariable collinearity [22].…”

Section: Introductionmentioning

confidence: 99%

Revealing the Eco-Environmental Quality of the Yellow River Basin: Trends and Drivers

Zhou,

Li,

Gao

et al. 2024

Remote Sensing

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The Yellow River Basin (YB) acts as a key barrier to ecological security and is an important experimental region for high-quality development in China. There is a growing demand to assess the ecological status in order to promote the sustainable development of the YB. The eco-environmental quality (EEQ) of the YB was assessed at both the regional and provincial scales utilizing the remote sensing-based ecological index (RSEI) with Landsat images from 2000 to 2020. Then, the Theil–Sen (T-S) estimator and Mann–Kendall (M-K) test were utilized to evaluate its variation trend. Next, the optimal parameter-based geodetector (OPGD) model was used to examine the drivers influencing the EEQ in the YB. Finally, the geographically weighted regression (GWR) model was utilized to further explore the responses of the drivers to RSEI changes. The results suggest that (1) a lower RSEI value was found in the north, while a higher RSEI value was found in the south of the YB. Sichuan (SC) and Inner Mongolia (IM) had the highest and the lowest EEQ, respectively, among the YB provinces. (2) Throughout the research period, the EEQ of the YB improved, whereas it deteriorated in both Henan (HA) and Shandong (SD) provinces. (3) The soil-available water content (AWC), annual precipitation (PRE), and distance from impervious surfaces (IMD) were the main factors affecting the spatial differentiation of RSEI in the YB. (4) The influence of meteorological factors (PRE and TMP) on RSEI changes was greater than that of IMD, and the influence of IMD on RSEI changes showed a significant increasing trend. The research results provide valuable information for application in local ecological construction and regional development planning.

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“…Understanding arable land quality and exploring ways to improve it are of great importance to governments around the world, as they are related to filling the gap in future food demand and coping with climate change and alleviating the contradiction between man and nature [22,23]. China, for instance, focuses on fortifying land protection, integrating it into their natural resource strategy [24][25][26]. Similarly, the European Union's Common Agricultural Policy (CAP) emphasizes agricultural production, global food security, and environmental concerns [27][28][29].…”

Section: Introductionmentioning

confidence: 99%

Arable Land Quality in Developing China: An Integrated Exploration from Global Challenges to Localized Solutions

Ye,

Song,

Kuzyakov

et al. 2024

Land

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Analyzing spatial patterns and driving factors of cropland change in China's National Protected Areas for sustainable management

Cited by 10 publications

References 73 publications

Protection pattern and driving mechanism of typical marine ecosystems: a case study of China-ASEAN countries

Protection pattern and driving mechanism of typical marine ecosystems: a case study of China-ASEAN countries

Revealing the Eco-Environmental Quality of the Yellow River Basin: Trends and Drivers

Arable Land Quality in Developing China: An Integrated Exploration from Global Challenges to Localized Solutions

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