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Agricultural System: Climate Change and Impact, Ecological Security and Sustainable Development

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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Agriculture".

Deadline for manuscript submissions: closed (13 March 2024) | Viewed by 7229

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Special Issue Editors

Dr. Enliang Guo

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Guest Editor

College of Geographical Science, Inner Mongolia Normal University, Hohhot 010022, China
Interests: extreme climatic change; compound dry and hot event; agrometeorological disaster; natural disaster risk assessment

Dr. Zhongyi Sun

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Guest Editor

College of Ecology and Environment, Hainan University, Haikou 570000, China
Interests: ecosystem modelling; eco-informatics

Dr. Rui Wang

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Guest Editor

School of Chemical & Environmental Engineering, Liaoning University of Technology, Jinzhou, China
Interests: environmental disasters; drought and waterlogging; crop model; vulnerability; sustainable development

Special Issue Information

Dear Colleagues,

Climate change is one of the most significant challenges facing the world today, and its impact on agriculture and ecosystems is of particular concern. The effects of climate change on agricultural productivity and natural ecosystems are far-reaching and include changes in rainfall patterns, increased frequency and intensity of extreme weather events, and changes in temperature regimes. To address these challenges, this Special Issue aims to explore the impact of climate change on agricultural systems and the environment and identify strategies for achieving sustainable development.

The purpose of this Special Issue is to provide a platform for researchers to showcase their original research and reviews related to the impact of climate change on agriculture, ecosystem sustainability, and ecological security. The goal is to contribute to the advancement of knowledge in this field and identify effective strategies for addressing the challenges posed by climate change.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but not limited to) the following:

The impact of climate change and weather-related disasters on agricultural production, food security, and livelihoods.
The impact of climate change and weather-related disasters on vegetation growth, ecosystem services, and biodiversity.
Sustainable agricultural practices and policies that promote climate resilience and ecological security.
Institutional frameworks and governance structures that support sustainable agricultural systems and ecosystem management.
Cross-disciplinary approaches to understanding and addressing the challenges of climate change and ecological security.
Policy formulation for the sustainable management of regional/global agro-ecosystems in response to climate change, extreme events, etc.

We look forward to receiving your contributions.

Dr. Enliang Guo
Dr. Zhongyi Sun
Dr. Rui Wang
Guest Editors

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Keywords

extreme events
climatic change
agrometeorological disaster
ecological security
ecosystem services
agroecology and agroecosystem

Published Papers (6 papers)

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Research

21 pages, 2126 KiB

Open AccessArticle

Temporal and Spatial Evolution Characteristics and Influencing Factors Analysis of Green Production in China’s Dairy Industry: Based on the Perspective of Green Total Factor Productivity

by Yashuo Liu and Huanan Liu

Sustainability 2023, 15(23), 16250; https://doi.org/10.3390/su152316250 - 23 Nov 2023

Viewed by 849

Abstract

Accelerating the green development of the dairy industry is an important work to promote the construction of ecological civilization and ensure the safe supply of dairy products. Existing studies lack a comprehensive analysis of the green development characteristics of China’s dairy industry. Based on the input–output system, the study measured and analyzed the green total factor productivity of China’s dairy industry in 29 provinces (cities, autonomous regions, and municipalities) since the 10th Five-Year Plan period, using the super-efficiency EBM model and the GML index based on non-directional and variable scale returns. Accelerating the green development of the dairy industry is an important work to promote the construction of ecological civilization and ensure the national nutrition intake. The existing studies lack a comprehensive understanding of the green development characteristics of China’s dairy industry. Therefore, this paper constructs an input–output system, measures and analyzes the green total factor productivity of the dairy industry in 29 provinces (cities, autonomous regions and municipalities directly under the Central Government), since the “15th Five-Year Plan” period based on the non-oriented super-efficiency EBM model and GML index with variable returns to scale. On this basis, the dynamic evolution of regional differences was explored using Kernel density estimation and the Dagum Gini coefficient, and the influencing factors of green total factor productivity in China’s dairy industry were analyzed using a two-way fixed effects model. The results show that from 2001 to 2020, the green total factor productivity of China’s dairy industry showed an overall upward trend, and presented a gradient pattern of “Northeast–East–Central–West” in turn, with green technical efficiency being the main driving force for promoting green total factor productivity in China and various regions. The gap in green total factor productivity between provinces and cities is gradually narrowing, and the polarization phenomenon is weakening. Super variation density is the main source of regional differences, and the difference between the West and the East is the largest, while the difference between the Central and the Northeast is the smallest. As for the influencing factors, industry agglomeration, economic development level, and environmental planning level have a significant positive promoting effect on the green total factor productivity of China’s dairy industry, while the level of population urbanization has a significant inhibitory effect on it. In order to promote the green and sustainable development of China’s dairy industry and promote the coordinated development of regional green, it is necessary to accelerate the efficiency of green technology while promoting the innovation of green technology, accelerate the integrated development of industry and formulate relevant policies according to local conditions to promote the coordinated development of green technology between regions. Full article

(This article belongs to the Special Issue Agricultural System: Climate Change and Impact, Ecological Security and Sustainable Development)

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15 pages, 2909 KiB

Open AccessArticle

Variation of Stem CO₂ Efflux and Estimation of Its Contribution to the Ecosystem Respiration in an Even-Aged Pure Rubber Plantation of Hainan Island

by Bo Song, Zhixiang Wu, Lu Dong, Chuan Yang and Siqi Yang

Sustainability 2023, 15(22), 16050; https://doi.org/10.3390/su152216050 - 17 Nov 2023

Viewed by 830

Abstract

The stem CO₂ efflux (Es) plays an important role in the carbon balance in forest ecosystems. However, a majority of studies focus on ecosystem flux, and little is known about the contribution of stem respiration to ecosystem respiration (Reco) for rubber (Hevea brasiliensis) plantations. We used a portable CO₂ analyzer to monitor the rate of Es in situ at different heights (1.5 m, 3.0 m and 4.5 m) in an even-aged rubber plantation from 2019 to 2020. Our results showed that Es exhibited a significant seasonal difference with a minimum value in April and a maximum in September. The mean annual rate of Es at 3.0 m in height (1.65 ± 0.52 μmol·m⁻²·s⁻¹) was slightly higher than Es at 4.5 m in height (1.56 ± 0.59 μmol·m⁻²·s⁻¹) and Es at 1.5 m in height (1.51 ± 0.48 μmol·m⁻²·s⁻¹). No obvious differences in vertical variations were found. An area-based method (Ea) and a volume-based method (Ev) were used to estimate stem respiration at stand levels. One-way ANOVA showed that Ea had no obvious differences in vertical variation (p = 0.62), and Ev indicated differences in vertical variation (p < 0.05). Therefore, the Ea chamber-based measurements at breast height were reasonable and practical extrapolation proxies of stem respiration in an even-aged rubber plantation. With the use of the area-based method, the stem carbon values released from a mature rubber forest were estimated to be 1.214 t C·hm⁻²·a⁻¹ in 2019 and 1.414 t C·hm⁻²·a⁻¹ in 2020. Ea/Reco and Ev/Reco showed seasonal changes, with a minimum value in April and a maximum value in December. The leaf area index (LAI) and soil volumetric moisture content (VWC) were the major impact factors of Ea/Reco in an even-aged pure rubber plantation. Full article

(This article belongs to the Special Issue Agricultural System: Climate Change and Impact, Ecological Security and Sustainable Development)

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15 pages, 2542 KiB

Open AccessArticle

Construction and Practice of Livelihood Efficiency Index System for Herders in Typical Steppe Area of Inner Mongolia Based on Super-Efficiency Slacks-Based Measure Model

by Gerile Qimuge, Wulan Tuya, Si Qinchaoketu and Bu He

Sustainability 2023, 15(18), 14005; https://doi.org/10.3390/su151814005 - 21 Sep 2023

Viewed by 893

Abstract

Inner Mongolia is one of the main animal husbandry production bases in China, with herders being the main animal husbandry producers. A systematic analysis of the efficiency of herding households’ livelihoods and the influencing factors is of great importance to formulate effective policies to support herding households’ livelihoods, enhance their social adaptability, and alleviate the vulnerability of poor people in herding areas. This study used a typical steppe of Inner Mongolia as the research area. It used the interview data of herding households from 2021, constructed the evaluation index system of herding households’ livelihood efficiency, analyzed the redundancy of the inputs and outputs of herding households’ livelihoods, and examined the key factors affecting herding households’ livelihood efficiency. The results indicate that (1) the pure technical effectiveness of the livelihood efficiency of typical grassland herding households in Inner Mongolia is the highest; the comprehensive technical efficiency and scale efficiency are low. The scale return of most herders’ livelihoods shows a decreasing state. (2) According to the results of the model, under the premise of the output not being reduced, reducing the amount of social capital input can effectively save resources. Without increasing the input, the room for improvement in the living level is the most obvious. (3) The pasture area, the communication network, and the access to information have significant negative effects on the efficiency of herders’ livelihoods; infrastructure and water supply have significant positive impacts. In summary, we built a model for evaluating the livelihood efficiency of herders in typical grassland areas of Inner Mongolia, which can provide a reference for the revitalization work of pastoral areas and related research in the future. Full article

(This article belongs to the Special Issue Agricultural System: Climate Change and Impact, Ecological Security and Sustainable Development)

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13 pages, 3133 KiB

Open AccessArticle

Dynamic Relationship between Agricultural Water Use and the Agricultural Economy in the Inner Mongolia Section of the Yellow River Basin

by Zhigang Ye, Ping Miao, Ning Li, Yong Wang, Fanhao Meng, Rong Zhang and Shan Yin

Sustainability 2023, 15(17), 12979; https://doi.org/10.3390/su151712979 - 28 Aug 2023

Cited by 4 | Viewed by 902

Abstract

Water is a crucial resource for agricultural development in the Yellow River Basin. However, the effects of water shortages on the region’s agricultural development are becoming increasingly evident, creating a need to examine the relationship between agricultural water use (AWU) and the agricultural economy. This study uses panel vector autoregression to analyze the relationship between AWU and the agricultural economy in the Inner Mongolia section of the Yellow River Basin from 1998 to 2018. The results indicate the following: (1) AWU in the Inner Mongolia section of the Yellow River Basin significantly declined during the study period, showing clear differences in the AWU’s effectiveness among regions; (2) agriculture in the region stabilized after significant growth, and the share of primary-sector industries in the national economy also stabilized after significant decline; (3) in the long run, AWU and the agricultural economy become cointegrated with the AWU Granger-causing agricultural economy. By deepening our understanding of agricultural water demand in the Yellow River Basin, these findings provide theoretical justification for establishing water-conserving irrigation systems and making sustainable use of water resources. Full article

(This article belongs to the Special Issue Agricultural System: Climate Change and Impact, Ecological Security and Sustainable Development)

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23 pages, 1275 KiB

Open AccessArticle

The Effect of Industrial Agglomeration on Agricultural Green Production Efficiency: Evidence from China

by Zhen Wang, Xiaoyu Zhang, Hui Lu, Xiaolan Kang and Bin Liu

Sustainability 2023, 15(16), 12215; https://doi.org/10.3390/su151612215 - 10 Aug 2023

Cited by 3 | Viewed by 1384

Abstract

Understanding how industrial agglomeration affects agricultural green production efficiency is essential for green agricultural development. This study uses the super-efficient Epsilon-Based Measure (EBM) model and Global Malmquist–Luenberger (GML) index to measure and analyze the spatial and temporal evolution characteristics and core sources of dynamics of agricultural green production efficiency in China by using panel data from 30 Chinese provinces from 2006 to 2020. It also empirically investigates the relationships between industrial agglomeration, land transfer, and agricultural production efficiency. By using fixed, intermediary, and threshold effect models, the internal links between industrial agglomeration, land transfer, and agricultural green production efficiency are examined. The findings indicate the following. (1) The green production efficiency of Chinese agriculture exhibits the regional characteristics of being “high in the west and low in the east, high in the south and low in the north” in terms of space; in terms of time, the overall trend is that green production technology efficiency is growing, with an average annual growth rate of 11.45%, and the growth primarily depends on the “single-track drive” of green technological progress. (2) Industrial agglomeration significantly affects agricultural green production efficiency, green technology efficiency, and green technology change; the corresponding coefficient values are 0.115, 0.093, and 0.022. (3) According to the mechanism-of-action results, land transfer mediates the effects of industrial agglomeration on agricultural green production efficiency, green technology efficiency, and green technology change. These effects have effect values of 28.48%, 27.91%, and 47.75%, respectively. (4) The threshold effect’s findings demonstrate a double threshold effect of industrial agglomeration on the green production efficiency of agriculture in terms of land transfer, with threshold values of 1.468 and 3.891, respectively. As a result, this study suggests adhering to the idea of synergistic development, promoting agricultural green development, strengthening the development of industrial agglomerations, promoting the quality and efficiency of industry, improving land-transfer mechanisms, and placing a focus on resource efficiency improvements, as well as other policy recommendations. Full article

(This article belongs to the Special Issue Agricultural System: Climate Change and Impact, Ecological Security and Sustainable Development)

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17 pages, 12438 KiB

Open AccessArticle

Meteorological-Data-Driven Rubber Tree Powdery Mildew Model and Its Application on Spatiotemporal Patterns: A Case Study of Hainan Island

by Jiayan Kong, Yinghe An, Xian Shi, Zhongyi Sun, Lan Wu and Wei Cui

Sustainability 2023, 15(16), 12119; https://doi.org/10.3390/su151612119 - 8 Aug 2023

Cited by 1 | Viewed by 1265

Abstract

Given that rubber is an important strategic material and the prevalence of rubber tree powdery mildew (RTPM) is a serious issue, the study of RTPM is becoming increasingly significant in aiding our understanding and managing rubber plantations. By enhancing our understanding, we may improve both the yield and quality of the rubber produced. Using meteorological station and reanalysis data, we employed factor expansion and three different feature-selection methods to screen for significant meteorological factors, ultimately constructing a data-driven RTPM disease index (RTPM-DI) model. This model was then used to analyze the spatiotemporal distribution of RTPM-DI in Hainan Island from 1980 to 2018, to reproduce and explore its patterns. The results show that (1) the RTPM-DI is dominantly negatively influenced by the average wind speed and positively affected by days with moderate rain; (2) the average wind speed and the days with moderate rain could explain 71% of the interannual variations in RTPM-DI, and a model established on the basis of these can simulate the changing RTPM-DI pattern very well (RMSE = 8.2511, MAE = 6.7765, MAPE = 0.2486, KGE = 0.9921, MSE = 68.081, RMSLE = 0.0953); (3) the model simulation revealed that during the period from 1980 to 2018, oscillating cold spots accounted for 72% of the whole area of Hainan Island, indicating a declining trend in RTPM-DI in the middle, western, southwestern, and northwestern regions. Conversely, new hot-spots and oscillating hot-spots accounted for 1% and 6% of the entire island, respectively, demonstrating an upward trend in the southeastern and northern regions. Additionally, no discernible pattern was observed for 21% of the island, encompassing the southern, eastern, and northeastern regions. It is evident that the whole island displayed significant spatial differences in the RTPM-DI pattern. The RTPM-DI model constructed in this study enhances our understanding of how climate change impacts RTPM, and it provides a useful tool for investigating the formation mechanism and control strategies of RTPM in greater depth. Full article

(This article belongs to the Special Issue Agricultural System: Climate Change and Impact, Ecological Security and Sustainable Development)

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