Abstract

Land is a scarce resource and its depletion is related to a combination of demographic and economic factors. Hence, the changes in dietary habits and increase in world population that upturn the food demand, are intertwined with a context of increasing oil prices and rise of green capitalism that in turn impacts the demand in biofuel. A visible indicator of these phenomena is the increase, in recent years, of Large Scale Land Acquisitions (LSLAs) by private companies or states. Such land investments often lead to conflicts with local population and have raised issues regarding people’s rights, the role of different production models and land governance. The aim of this work is to show how publicly available data about LSLAs can be modeled into complex network structures, thus showing how the application of advanced network analysis techniques can be used to better understand land trade dynamics. We use data collected by the Land Matrix Initiative on LSLAs to model three land trade networks: a multi-sector network, a network centered on the mining sector and a network centered on the agriculture one. Then we provide an extended analysis of such networks which includes: (i) a structural analysis, (ii) the definition of a score, namely LSLA-score, which allows to rank the countries based on their investing/target role in the land trade network, (iii) an analysis of the land trade context which takes into account the LSLA-score ranking and the correlation between network features and several country development indicators, (iv) an analysis centered on the discover and analysis of network motifs (i.e., recurring patterns in the land trade network), which provides insights into complex and diverse relations between countries. Our analyses showed how the land trade market is massively characterized by a Global North-Global South dynamic, even if the investing power of emerging economies also has a major impact in creating relations between different sub-regions of the world. Moreover, the analyses on the mining and agriculture sectors highlighted how the role of several countries in the trade network may drastically change depending of the investment sector, showing diverse hierarchies between investor, intermediate and target countries.

Highlights

  • Demand for land embodied in trade of mineral, fossil fuels and agricultural commodities has been shown to be very significant

  • An analysis centered on the discover and analysis of network motifs, which provides an insight into statistically significant land trade schemes, and by consequence into complex relations between countries; The rest of the paper is structured as follows: Section 1 describes network modeling, discusses data and limitations aspects, and introduces an analysis of structural characteristics of the land trade networks, in Section 2 we introduce the Large Scale Land Acquisitions (LSLAs)-score and we use it to analyze the land trade context, in Section 3 we present our analysis based on network motifs, while Section 4 concludes the work

  • While the fact that land investment dynamics are global can be observed in the fact that the land trade networks are rather compact and dense, a first hint of the North-South dynamics already comes out from specific network properties that show how the networks are characterized by a strong asymmetry of the deals

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Summary

Introduction

Demand for land embodied in trade of mineral, fossil fuels and agricultural commodities has been shown to be very significant. The aim of their study is more to identify general trends that characterize different temporal phases of the land trade market, while in this work we want to focus on complex relations among countries, by considering heterogeneity of the deals, namely the intention of investment and the implementation status. An analysis centered on the discover and analysis of network motifs (i.e., recurring patterns in the land trade network), which provides an insight into statistically significant land trade schemes, and by consequence into complex relations between countries; The rest of the paper is structured as follows: Section 1 describes network modeling, discusses data and limitations aspects, and introduces an analysis of structural characteristics of the land trade networks, in Section 2 we introduce the LSLA-score and we use it to analyze the land trade context, in Section 3 we present our analysis based on network motifs, while Section 4 concludes the work

The Land Matrix land trade network
Network modeling
Data and limitations
Structural characteristics of the land trade networks
The LSLA-score
The multi-sector land trade network
Land trade in the agricultural and mining sectors
Correlation with country development indicators
Analysis based on network motifs
Motifs on the multi-sector network
Motifs on the agriculture and mining networks
Summary of findings
Findings
Concluding remarks and future work
Full Text
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