Socioeconomic effects of a bottom-up multifunctional land consolidation project

Callesen, Gustav Marquard; Lundhede, Thomas Hedemark; Olsen, Søren Bøye; Schou, Jesper Sølver

doi:10.1016/j.landusepol.2022.106102

Cited by 7 publications

(6 citation statements)

References 28 publications

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“…Existing scholars noticed that some rural areas in China explored the autonomous governance mode adopted by delving into farmland fragmentation and have made remarkable achievements (Lu et al, 2019; Zhang et al, 2019). Through “bottom‐up” coordination and communication, this mode applies the organizational path of “farmer orientation, community dominance, and governmental guidance”, focuses on solving the problem of tenure fragmentation for smallholder production (Callesen et al, 2022; Wang et al, 2022). Therefore, future farmland fragmentation consolidation should not only depend on the institutional safety of policy supply, capital support, and technological promotion under the administrative mode dominance but should also absorb organizational coordination, benefit distribution, and risk prevention under autonomous governance mode (Figure 7).…”

Section: Discussionmentioning

confidence: 99%

A multidimensional assessment and analysis of farmland fragmentation in the southeast coastal area of China

et al. 2023

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Farmland fragmentation is a typical feature of arable land use in the economies dominated by smallholder production mode, and scientific evaluation of farmland fragmentation is an effective and crucial process to find and solve problems. Farmland fragmentation, as a kind of long‐standing physiographic landscape and agricultural economic phenomenon under the comprehensive effect of “human‐land‐property rights”, not only contains the scale status and spatial distribution of cultivated patches but also is featured with farming and tenure right. However, the theoretical interpretation of the multidimensional characteristics of farmland fragmentation was insufficient, and it was rare to evaluate the farmland fragmentation based on plot scale. To this end, an evaluation framework of farmland fragmentation with four dimensions and 12 indicators was constructed in this paper. Moreover, regarding Minqing County located in China's southeast coast as a case, empirical research was thus conducted. The findings indicated that the physical properties of farmland patches were depicted through scale fragmentation. Spatial fragmentation represented the spatial distribution of farmland patches. Farming fragmentation revealed agricultural production and management differences while tenure fragmentation embodied the tenure rights segmentation induced by the land distribution system. Farmland fragmentation consolidation was an effective way to solve these issues, and some differential tactics should be conducted in accordance with the path of “zoning types–obstacle factors–consolidation directions–treatment measures”.

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Section: Discussionmentioning

confidence: 99%

A multidimensional assessment and analysis of farmland fragmentation in the southeast coastal area of China

et al. 2023

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“…Industry and population are two critical influencing factors for socioeconomic development ( Mitter et al., 2020 ; Callesen et al., 2022 ). A high level of socioeconomic development can facilitate the implementation of FCAM ( Jiang et al., 2015 ; Mugiyo et al., 2021 ).…”

Section: Methodsmentioning

confidence: 99%

“…The aim of FCAM is to identify the most suitable places for the operation of agricultural machinery ( Collins et al, 2001 ; Duan et al., 2021 ; Janus and Ertunç, 2021 ; Beyer et al., 2022 ). In many countries (e.g., Japan and South Korea), FCAM is used as a land management tool to eliminate the adverse effects of land fragmentation and to improve and promote agricultural mechanization ( Callesen et al., 2022 ; Washizu and Nakano, 2022 ). The rules and regulations for FCAM projects vary from country to country ( Janus and Ertunç, 2022 ).…”

Section: Introductionmentioning

confidence: 99%

Assessing farmland suitability for agricultural machinery in land consolidation schemes in hilly terrain in China: A machine learning approach

Heng

Ma²,

Liu³

et al. 2023

Front. Plant Sci.

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Identifying available farmland suitable for agricultural machinery is the most promising way of optimizing agricultural production and increasing agricultural mechanization. Farmland consolidation suitable for agricultural machinery (FCAM) is implemented as an effective tool for increasing sustainable production and mechanized agriculture. By using the machine learning approach, this study assesses the suitability of farmland for agricultural machinery in land consolidation schemes based on four parameters, i.e., natural resource endowment, accessibility of agricultural machinery, socioeconomic level, and ecological limitations. And based on “suitability” and “potential improvement in farmland productivity”, we classified land into four zones: the priority consolidation zone, the moderate consolidation zone, the comprehensive consolidation zone, and the reserve consolidation zone. The results showed that most of the farmland (76.41%) was either basically or moderately suitable for FCAM. Although slope was often an indicator that land was suitable for agricultural machinery, other factors, such as the inferior accessibility of tractor roads, continuous depopulation, and ecological fragility, contributed greatly to reducing the overall suitability of land for FCAM. Moreover, it was estimated that the potential productivity of farmland would be increased by 720.8 kg/ha if FCAM were implemented. Four zones constituted a useful basis for determining the implementation sequence and differentiating strategies for FCAM schemes. Consequently, this zoning has been an effective solution for implementing FCAM schemes. However, the successful implementation of FCAM schemes, and the achievement a modern and sustainable agriculture system, will require some additional strategies, such as strengthening farmland ecosystem protection and promoting R&D into agricultural machinery suitable for hilly terrain, as well as more financial support.

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“…The available research mainly explains the effect of land costs on operators' cropplanting selections in terms of the factor substitution drive of land and labor [53,54] or the substitution of agricultural machinery services [47]. However, the level of development of the agricultural land transfer market is significantly correlated with the establishment of explicit land costs and formation of implicit land costs [23,40]. The pricing of land costs is more developed and the transaction procedure is clearer in countries where the land transfer market is more developed [21].…”

Section: Mechanism Of Action: Degree Of Land Transfer Market Developmentmentioning

confidence: 99%

“…However, in the current common perception, land transfer rent is, by default, characterized as the cost of land in rural China [17]. In fact, in the process of agricultural cultivation, operators spend on land includes not only the externally explicit land transfer rent but also other types of implicit costs, such as land searching [19,20], negotiating for renting the land [21,22], and finishing costs of the land after renting [23,24]. None of these costs are included in the cost of land, but they do represent actual costs associated with farmers' usage of the land.…”

Section: Introductionmentioning

confidence: 99%

How Do the Different Types of Land Costs Affect Agricultural Crop-Planting Selections in China?

Zhang

Yuan

Wang

et al. 2022

Land

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Land costs in agricultural production are rapidly becoming apparent and increasing in light of the market’s rapid development in rural China. This study examines how agricultural operators’ farming decisions are affected by explicit and implicit costs associated with land transfers. This study first categorizes explicit and implicit land costs theoretically and demonstrates that both types of land costs affect farmers’ crop-planting selections. The study then uses the most recent household survey data from the Chinese Family Database (CFD) and the China Household Finance Survey (CHFS), released in 2017, to empirically test the theoretical analysis and examine the mechanisms underlying the impact of land costs on crop-planting selections. This study makes the case that higher land costs, both explicit and implicit, cause agricultural operators to grow more crops for cash and less for food. The impact of land costs on planting selection can vary depending on the heterogeneity of production areas and geography. In terms of production area heterogeneity, the explicit cost of land has a greater influence on planting decisions in non-major food-producing areas, whereas the implicit cost of land has a greater influence on planting decisions in major food-producing areas. In terms of topographic heterogeneity, the less flat the terrain, the more growers would choose to grow cash crops. A complementary relationship between the two forms of costs is also suggested by this study’s confirmation that explicit and implicit land costs can positively reduce each other’s impact on cropping decisions. Additional mechanism research revealed that explicit and implicit land costs impact crop crop-planting selections. The explicit cost of land primarily affects the local land transfer market effect, whereas the implicit cost of land affects the land transfer service.

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Socioeconomic effects of a bottom-up multifunctional land consolidation project

Cited by 7 publications

References 28 publications

A multidimensional assessment and analysis of farmland fragmentation in the southeast coastal area of China

A multidimensional assessment and analysis of farmland fragmentation in the southeast coastal area of China

Assessing farmland suitability for agricultural machinery in land consolidation schemes in hilly terrain in China: A machine learning approach

How Do the Different Types of Land Costs Affect Agricultural Crop-Planting Selections in China?

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