Positive impacts of farmland fragmentation on agricultural production efficiency in Qilu Lake watershed: Implications for appropriate scale management

Yu, Peiheng; Fennell, Shailaja; Chen, Yiyun; Liu, Hui; Xu, Lian-Zeng-Ji; Pan, Jiawei; Bai, Shaoyun; Gu, Shixiang

doi:10.1016/j.landusepol.2022.106108

Cited by 59 publications

(29 citation statements)

References 96 publications

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“…The results of this study indicated that risk has a vital role in peasant households’ production decisions and is related to peasant households’ choices and levels of inputs and outputs. Because agricultural production is a major source of income for peasant households, it is important for them to recognize and manage production risks [ 62 , 63 , 64 ]. Therefore, a timely approach to optimize the agricultural input and production combination can help peasant households to mitigate the negative effects of risks and to adopt adaptive measures.…”

Section: Discussionmentioning

confidence: 99%

Optimizing Agricultural Input and Production for Different Types of at-Risk Peasant Households: An Empirical Study of Typical Counties in the Yimeng Mountain Area of Northern China

Wang

Lin

2022

IJERPH

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Using typical counties in the Yimeng Mountain area of northern China as an example, this paper analyzed the household and agricultural input characteristics of different types of peasant households using survey data from 262 farm households. The target minimization of the total absolute deviations (MOTAD) model was applied to determine the optimal combinations in the allocation of agricultural input factors and production for different types of at-risk peasant households to obtain the ideal agricultural income. The relevant results are twofold. (1) The agricultural input behaviors of different types of peasant households vary significantly. The highest levels of agricultural land, labor, and yield-increasing and labor-saving inputs included I part-time peasant households (I PTPH), followed by full-time peasant households (FTPH), while the input levels of II part-time peasant households (II PTPH) and non-agricultural peasant households (NAPH) with higher levels of non-agricultural employment gradually decreased. In general, an increase in peasant households’ part-time employment revealed an inverted U-shaped trend in the agricultural input level, with a trajectory of I PTPH > FTPH > II PTPH > NAPH. (2) The current agricultural inputs and production combinations of different types of peasant households have room for improvement. It is necessary to adjust agricultural inputs and optimize production combinations to obtain target incomes. Overall, all types of peasant households must streamline labor inputs and increase capital inputs, except for I PTPH, for which capital inputs should be reduced. Following optimization, economic crops gradually replace grain crops, and the optimal agricultural incomes of peasant households will be improved. The study results provide practical policy insights for reducing agricultural production risks and improving agricultural production incomes.

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Section: Discussionmentioning

confidence: 99%

Optimizing Agricultural Input and Production for Different Types of at-Risk Peasant Households: An Empirical Study of Typical Counties in the Yimeng Mountain Area of Northern China

Wang

Lin

2022

IJERPH

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“…There is also evidence of farmland fragmentation using unmanned aerial vehicles (UAV). In the Qilu Lake watershed of China, UAVs were used to measure the forms, scenarios and drivers of farmland fragmentation and its impact on agricultural production efficiency [53]. A case study on Rwanda demonstrates that physical drivers of such fragmentation, used as a risk-management strategy, have positive impacts on the nutritional balance for food quality and food sustainability, both being the integral components of food security [51].…”

Section: Case Study 2: Degraded Land In Kisumu County Of Kenyamentioning

confidence: 99%

Planning for Sustainable Cities in Africa: Experiences, Challenges and Prospects of Monitoring Geospatial Indicators

et al. 2022

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The African continent is receiving unprecedented pressure from population growth, urbanisation, decreased agricultural productivity and changing climate. However, the continent lacks technological advancement. Therefore, there is a need to apply global data and open geospatial tools for analysis to prevent, stop and comprehend the trend and effects of land degradation, food insecurity and the unsustainability of cities. The study takes three representative indicators (climate risk, land degradation and land consumption) from FAO’s four strategic better’s to demonstrate the feasibility and applicability of global datasets to support decision makers. Three representative cities in Africa are selected for the study—Houet, Burkina Faso (West Africa); Kisumu, Kenya (East Africa); and Analamanga, Madagascar (South East Africa). The study found that eight Fokontany of the Analamanga region were at high risk from climate change; at the ward level, a maximum of 54.2% of the total degraded land area in Kisumu; and maximum land-consumption rate of 1.5 was found in Houet at the department level. The results of this study can be a basis for policymakers in planning an inclusive climate-adaptation measure and sustainable land-use frameworks and policies.

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“…In order to achieve this goal, China achieved “eighteen consecutive increases” in grain production between 2004 and 2021. Given the constraints of limited cultivated land resources and ecological carrying capacity, there is a pressing need for China to improve the efficiency of utilizing its limited cultivated land resources [ 20 ], which is an important solution to the shortage of cultivated land resources. So far, there have been many scholars conducting empirical evaluations of cultivated land utilization efficiency, with the relevant literature covering the aspects stated below: (1) As for index system construction, the evaluation index of cultivated land utilization efficiency has gradually shifted from a single index to the combination of several indexes, with consideration given to the undesirable outputs of cultivated land utilization, such as pollution emission and carbon emissions [ 21 ].…”

Section: Introductionmentioning

confidence: 99%

The Spatial and Temporal Evolution of the Coordination Degree in Regard to Farmland Transfer and Cultivated Land Green Utilization Efficiency in China

Zhou

Kuang

2022

IJERPH

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In many parts of the world, the shortage of cultivated land and the food crisis are worsening on a continued basis. Hence, the central and local governments of the PRC have successively issued various related policies to encourage the practice of farmland transfer, promote the eco-friendly utilization of cultivated land, and ameliorate the efficiency of cultivated land utilization. Under the context of large-scale farmland transfer and rural revitalization strategy in China, it is significant to ensure agricultural sustainability through the coordination of farmland transfer and the amelioration of cultivated land green utilization efficiency (CLGUE). In the present study, 30 Chinese provinces were taken as the research object, with the super-efficient SBM model, the coupling coordination degree model and the spatial analysis model applied in combination. Based on the measurement of CLGUE, a thorough analysis was conducted to explore the evolution of coordination degree in regard to farmland transfer and CLGUE in China from both spatial and temporal perspectives. The conclusions drawn from this study are as follows. Firstly, the overall CLGUE exhibited an upward tendency in the PRC, from 0.440 in 2005 to 0.913 in 2019, with a yearly growth rate of 5.47% on average. However, there were significant spatial disparities in CLGUE between different regions and provinces. Secondly, there was a steady increasing trend shown by the level of coordination degree regarding farmland transfer and CLGUE across China. Further, due to the variation in natural and economic conditions, there were significant spatial–temporal disparities in the coordination degree among these 30 provinces. Lastly, there were obvious spatial aggregation patterns at the provincial level regarding the coordination degree in farmland transfer and CLGUE across China. However, there was a declining trend in the level of spatial aggregation patterns for coordination degree.

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Positive impacts of farmland fragmentation on agricultural production efficiency in Qilu Lake watershed: Implications for appropriate scale management

Cited by 59 publications

References 96 publications

Optimizing Agricultural Input and Production for Different Types of at-Risk Peasant Households: An Empirical Study of Typical Counties in the Yimeng Mountain Area of Northern China

Optimizing Agricultural Input and Production for Different Types of at-Risk Peasant Households: An Empirical Study of Typical Counties in the Yimeng Mountain Area of Northern China

Planning for Sustainable Cities in Africa: Experiences, Challenges and Prospects of Monitoring Geospatial Indicators

The Spatial and Temporal Evolution of the Coordination Degree in Regard to Farmland Transfer and Cultivated Land Green Utilization Efficiency in China

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