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Research and Development (R&D) is the common denominator of innovation and technological progress, supporting sustainable development and economic growth. In light of the availability of new datasets and innovative indicators, in this work, we introduce a novel perspective to analyse the international trade of goods through the lenses of the nexus R&D-industrial activities of countries. We propose two new indices, RDE and RDI, summarizing the R&D content of countries' export and import baskets-respectively-and investigate their evolution in time, during the period 1995-2017, and space. We demonstrate the potential of these indices to shed new light on the evolution of R&D choices and trade, innovation, and development. In fact, compared to standard measures of countries' development and economic growth (e.g., the Human Development Index among the others tested), these indices provide complementary information. In particular, tracing the trajectories of countries along the RDE-HDI plane, different dynamics appear for countries with increased HDI, which we speculate can be reasoned with countries' availability of natural resources. Eventually, we identify two insightful applications of the indices to investigate further countries' environmental performances as related to their role in international trade.
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Centrality metrics aim to identify the most relevant nodes in a network. In the literature, a broad set of metrics exists, measuring either local or global centrality characteristics. Nevertheless, when networks exhibit a high spectral gap, the usual global centrality measures typically do not add significant information with respect to the degree, i.e., the simplest local metric. To extract different information from this class of networks, we propose the use of the Generalized Economic Complexity index (GENEPY). Despite its original definition within the economic field, the GENEPY can be easily applied and interpreted on a wide range of networks, characterized by high spectral gap, including monopartite and bipartite network systems. Tests on synthetic and real-world networks show that the GENEPY can shed light about the node centrality, carrying information generally poorly correlated with the node number of direct connections (node degree).
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Understanding the dynamics of food trade, which involves a corresponding virtual trade in environmental resources, is relevant for its effects on the environment. Among the socioeconomic factors driving the international food market, trade agreements play a significant yet poorly understood role in facilitating access to worldwide trade. Focusing on the global trade of grain from 1993 to 2015, we investigate the role of trade agreements in activating new linkages and increasing traded volumes and their environmental implications. Through a data-driven approach, we show that the activation of a trade agreement among countries induces a more than six-fold increase in the probability of establishing a new link. Also, the presence of a trade agreement over time, not just its activation, relates to a more stable market since it reduces the probability of link deactivation by more than half. The trade links covered by agreements show larger flows and smoother inter-annual fluctuations. Furthermore, trade agreements encourage the development of more water-efficient flows by stimulating the exchange of crops with high water productivity values. The average economic water productivity of crops traded under trade agreements increases by 62% when considering total virtual water and even by 93% when focusing on blue water.
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Grão Comestível , Abastecimento de Água , Agricultura , Produtos Agrícolas , ÁguaRESUMO
The EAT-Lancet Commission has proposed a global benchmark diet to guide the shift towards healthy and sustainable dietary patterns. Yet it is unclear whether consumers' choices are convergent with those guidelines. Applying an advanced statistical analysis, we mapped the diet gap of 15 essential foods in 172 countries from 1961 to 2018. We found that countries at the highest level of development have an above-optimal consumption of animal products, fats and sugars but a sub-optimal consumption of legumes, nuts and fruits. Countries suffering from limited socio-economic progress primarily rely on carbohydrates and starchy roots. Globally, a gradual change towards healthy and sustainable dietary targets can be observed for seafood, milk products, poultry and vegetable oils. We show that if all countries adopted the EAT-Lancet diet, the water footprint would fall by 12% at a global level but increase for nearly 40% of the world's population.
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The virtual water (VW) trade associated to food is composed by the quantity of water utilized for the production of the crops exchanged on the global market. In assessing a country's water abundance or scarcity when entering the international VW trade, scholars consider only physical water availability, neglecting economic water scarcity, which indicates situations in which socio-economic obstacles impede the productive use of water. We weight the global VW trade associated to primary crops with a newly proposed composite water scarcity index (CWSI) that combines physical and economic water scarcity. 39% of VW volumes is exported from countries with a higher CWSI than the one of the destination country. Such unfair routes occur both from low- to high-income countries and among low- and middle-income countries themselves. High-income countries have a predominant role in import of CWSI-weighted VW, while low- and middle-income countries dominate among the largest CWSI-weighted VW exporters. For many of them economic water scarcity dominates over physical scarcity. The application of the CWSI elicits also a status change from net exporter to net importer for some wealthy countries and viceversa for some low- and middle-income countries. The application of CWSI allows one to quantify to what extent VW exchanges flow along environmentally and economically unfair routes, and it can inform the design of compensation policies.
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[This corrects the article DOI: 10.1371/journal.pone.0200639.].
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In 2015, the United Nations established the Agenda 2030 for sustainable development, addressing the major challenges the world faces and introducing the 17 Sustainable Development Goals (SDGs). How are countries performing in their challenge toward sustainable development? We address this question by treating countries and Goals as a complex bipartite network. While network science has been used to unveil the interconnections among the Goals, it has been poorly exploited to rank countries for their achievements. In this work, we show that the network representation of the countries-SDGs relations as a bipartite system allows one to recover aggregate scores of countries' capacity to cope with SDGs as the solutions of a network's centrality exercise. While the Goals are all equally important by definition, interesting differences self-emerge when non-standard centrality metrics, borrowed from economic complexity, are adopted. Innovation and Climate Action stand as contrasting Goals to be accomplished, with countries facing the well-known trade-offs between economic and environmental issues even in addressing the Agenda. In conclusion, the complexity of countries' paths toward sustainable development cannot be fully understood by resorting to a single, multipurpose ranking indicator, while multi-variable analyses shed new light on the present and future of sustainable development.
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Summarising the complexity of a country's economy in a single number is the holy grail for scholars engaging in data-based economics. In a field where the Gross Domestic Product remains the preferred indicator for many, economic complexity measures, aiming at uncovering the productive knowledge of countries, have been stirring the pot in the past few years. The commonly used methodologies to measure economic complexity produce contrasting results, undermining their acceptance and applications. Here we show that these methodologies - apparently conflicting on fundamental aspects - can be reconciled by adopting a neat mathematical perspective based on linear-algebra tools within a bipartite-networks framework. The obtained results shed new light on the potential of economic complexity to trace and forecast countries' innovation potential and to interpret the temporal dynamics of economic growth, possibly paving the way to a micro-foundation of the field.
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International agricultural trade triggers inter-dependency among distant countries, not only in economic terms but also under an environmental perspective. Agricultural trade has been shown to drive environmental threats pertaining to biodiversity loss and depletion and pollution of freshwater resources. Meanwhile, trade can also encourage production where it is most efficient, hence minimizing the use of natural resources required by agriculture. In this study, we provide a country-level assessment of the future international trade for 6 primary crops and 3 animal products composing 70% of the human diet caloric content. We set up four variegate socio-economic scenarios with different level of economic developments, diets habits, population growth dynamics, and levels of market liberalization. Results show that the demand of agricultural goods and the correspondent trade flow will increase with respect to current levels by 10-50% and 74-178% by 2050, respectively. The largest increase in the amount of traded goods is expected under the Economic Optimism scenario that will see an average trade flow of 2830 kcal/cap/day (i.e., nearly doubling the current per-capita flow). Most of the increase will be driven by the trade of crops for animal feeding, particularly maize will be the most traded crop. The trade networks architecture in 2050 and 2080 will be very different from the one we actually know, with a clear shift of the trade pole from the Western toward the Eastern economies. The dramatic changes of global food-sources and trade patterns will jeopardize the water resources of new regions while exacerbating the pressure in those areas that will continue serving food also in the future. In spite of this, trade may annually save around 40-60 m3 of water per person, compared to a situation where countries are self-sufficient.
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Global food prices are typically analysed in a time-series framework. We complement this approach by focusing on the spatial price dispersion of the country-pair bilateral trade in the international food trade network (IFTN), for ten relevant commodities. The main purposes are to verify if the Law of One Price (LOP) holds and to investigate the emergence of randomness in the price-formation mechanism. We distinguish between the "internal" variance, which indicates the magnitude of price discrimination, and the "external" variance, that is a measure of price dispersion. We find that, for some commodities, spatial price dispersion is remarkable and persistent over time (i.e., failure of the LOP) and that there exists a strict correlation between price spikes and peaks in spatial price variability. We test whether the price distribution can be replicated through a stochastic process of extraction. Surprisingly, the actual distribution of prices, for several commodities, is well described by a random distribution. Then, the process of data aggregation is not neutral because the information at the micro-level scale might be lost at the macro-scale, due to the complexity of the IFTN. Finally, we discuss some possible economic explanations of these outcomes and the main methodological, environmental, and policy consequences.
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Typing "Yesterday" into the search-bar of your browser provides a long list of websites with, in top places, a link to a video by The Beatles. The order your browser shows its search results is a notable example of the use of network centrality. Centrality measures the importance of the nodes in a network and it plays a crucial role in several fields, ranging from sociology to engineering, and from biology to economics. Many centrality metrics are available. However, these measures are generally based on ad hoc assumptions, and there is no commonly accepted way to compare the effectiveness and reliability of different metrics. Here we propose a new perspective where centrality definition arises naturally from the most basic feature of a network, its adjacency matrix. Following this perspective, different centrality measures naturally emerge, including degree, eigenvector, and hub-authority centrality. Within this theoretical framework, the effectiveness of different metrics is evaluated and compared. Tests on a large set of networks show that the standard centrality metrics perform unsatisfactorily, highlighting intrinsic limitations for describing the centrality of nodes in complex networks. More informative multi-component centrality metrics are proposed as the natural extension of standard metrics.
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Food Security is a long-standing concern worldwide. The expansion of global food markets brings benefits but also risks, such as shock transmission within the global network of trade relations. We focus on this last issue, from an empirical point of view, by analysing the diffusion of trade shocks-defined as relevant drops in exported quantities-during the period 1986-2011, for four major staples (wheat, maize, rice, and soy-beans) both at country level and at global scale. We find that: (i) income per capita of importing countries is relevant in shock propagation; (ii) developing countries tend to absorb most of the negative export variation (i.e., the trade shock), and (iii) global food prices and real (tonnes) flows of commodities are only weakly correlated, meaning that a quantity-based investigation provides additional information with respect to a price-based analysis. This work offers a novel framework, complementary to the price-based literature, for the measurement of the propagation of international food shocks.
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Abastecimento de Alimentos/economia , Modelos Teóricos , Comércio , Cooperação Internacional , TriticumRESUMO
This corrects the article DOI: 10.1038/srep18803.
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This paper assesses the sustainability of bioenergy production under a nexus perspective through a new efficiency type index. The index describes 1st generation biofuel production under the perspective of the implied consumption of natural resources. We consider the sustainability of energy production as a sequence of steps, each characterised by its efficiency, and propose an index which returns an overall efficiency value describing the adequacy or inadequacy of the considered processes under a nexus perspective. The direct application of the nexus index entails an indication of the possible improvements needed to move production towards most sustainable processes or places. Moreover, it allows evaluating the efficiency of the main crops currently used in biofuel production with respect to the water-food-energy nexus. The results depict countries presently capable of performing sustainable production of 1st generation biofuel from particular crops. Furthermore, the analysis of the single components of the nexus index allows understanding the effects of possible improvements (e.g. soil and water management, new generation biofuels) on the overall production efficiency under a nexus perspective.
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While deterministic age distribution models have been extensively studied and applied in various disciplines, little work has been devoted to understanding the role of stochasticity in birth and mortality terms. In this paper, we analyse a stochastic M'Kendrick-von Foerster equation in which jumps in mortality represent intense losses of population due to external events. We present explicit solutions for the probability density functions of the age distribution and the total population and for the temporal dynamics of their moments. We also derive the dynamics of the mean age of the population and its harmonic mean. The framework is then used to calculate the age distribution of salt in the soil root zone, where the accumulation of salt by atmospheric deposition is counteracted by plant uptake and by jump losses due to percolation events.
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Disentangling the relations between human migrations and water resources is relevant for food security and trade policy in water-scarce countries. It is commonly believed that human migrations are beneficial to the water endowments of origin countries for reducing the pressure on local resources. We show here that such belief is over-simplistic. We reframe the problem by considering the international food trade and the corresponding virtual water fluxes, which quantify the water used for the production of traded agricultural commodities. By means of robust analytical tools, we show that migrants strengthen the commercial links between countries, triggering trade fluxes caused by food consumption habits persisting after migration. Thus migrants significantly increase the virtual water fluxes and the use of water in the countries of origin. The flux ascribable to each migrant, i.e. the "water suitcase", is found to have increased from 321 m3/y in 1990 to 1367 m3/y in 2010. A comparison with the water footprint of individuals shows that where the water suitcase exceeds the water footprint of inhabitants, migrations turn out to be detrimental to the water endowments of origin countries, challenging the common perception that migrations tend to relieve the pressure on the local (water) resources of origin countries.
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Abastecimento de Alimentos , Migração Humana , Abastecimento de Água , Humanos , Modelos TeóricosRESUMO
By importing food and agricultural goods, countries cope with the heterogeneous global water distribution and often rely on water resources available abroad. The virtual displacement of the water used to produce such goods (known as virtual water) connects together, in a global water system, all countries participating to the international trade network. Local food-production crises, having social, economic or environmental origin, propagate in this network, modifying the virtual water trade and perturbing local and global food availability, quantified in terms of virtual water. We analyze here the possible effects of local crises by developing a new propagation model, parsimonious but grounded on data-based and statistically-verified assumptions, whose effectiveness is proved on the Argentinean crisis in 2008-09. The model serves as the basis to propose indicators of crisis impact and country vulnerability to external food-production crises, which highlight that countries with largest water resources have the highest impact on the international trade, and that not only water-scarce but also wealthy and globalized countries are among the most vulnerable to external crises. The temporal analysis reveals that global average vulnerability has increased over time and that stronger effects of crises are now found in countries with low food (and water) availability.
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Agricultura/economia , Abastecimento de Alimentos/economia , Interface Usuário-Computador , Recursos Hídricos , HumanosRESUMO
Drought stress is a dominant constraint to crop production. Breeding crops with adapted root systems for effective uptake of water represents a novel strategy to increase crop drought resistance. Due to complex interaction between root traits and high diversity of hydrological conditions, modeling provides important information for trait based selection. In this work we use a root architecture model combined with a soil-hydrological model to analyze whether there is a root system ideotype of general adaptation to drought or water uptake efficiency of root systems is a function of specific hydrological conditions. This was done by modeling transpiration of 48 root architectures in 16 drought scenarios with distinct soil textures, rainfall distributions, and initial soil moisture availability. We find that the efficiency in water uptake of root architecture is strictly dependent on the hydrological scenario. Even dense and deep root systems are not superior in water uptake under all hydrological scenarios. Our results demonstrate that mere architectural description is insufficient to find root systems of optimum functionality. We find that in environments with sufficient rainfall before the growing season, root depth represents the key trait for the exploration of stored water, especially in fine soils. Root density, instead, especially near the soil surface, becomes the most relevant trait for exploiting soil moisture when plant water supply is mainly provided by rainfall events during the root system development. We therefore concluded that trait based root breeding has to consider root systems with specific adaptation to the hydrology of the target environment.
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Unsustainable growth is typical of systems that rely on a finite pool of non-renewable resources that are tapped until they are depleted. The decrease in resource availability eventually leads these systems to a decline. Here we investigate the dynamics of systems that exhibit unsustainable growth and are prone to a collapse to an alternative ("degraded") state. For these systems the possible imminent occurrence of a collapse is difficult to avert because they keep growing as they approach the transition point. It is therefore important to identify some early warning signs that can be used to predict whether the system is approaching a critical and likely irreversible transition to an undesired and degraded state. This study evaluates whether existing theories of precursors of phase transitions based on the critical slowing down phenomenon are applicable as leading indicators of state shift in unsustainable growth dynamics. It is found that such indicators fail to serve as reliable early warning signs of the system's collapse.
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Dinâmica Populacional/estatística & dados numéricos , Animais , Ecossistema , Humanos , Conceitos Matemáticos , Modelos Biológicos , Recursos Naturais , Dinâmica não Linear , Biologia de SistemasRESUMO
The vertical root distribution of riparian vegetation plays a relevant role in soil water balance, in the partition of water fluxes into evaporation and transpiration, in the biogeochemistry of hyporheic corridors, in river morphodynamics evolution, and in bioengineering applications. The aim of this work is to assess the effect of the stochastic variability of the river level on the root distribution of phreatophytic plants. A function describing the vertical root profile has been analytically obtained by coupling a white shot noise representation of the river level variability to a description of the dynamics of root growth and decay. The root profile depends on easily determined parameters, linked to stream dynamics, vegetation and soil characteristics. The riparian vegetation of a river characterized by a high variability turns out to have a rooting system spread over larger depths, but with shallower mean root depths. In contrast, a lower river variability determines root profiles with higher mean root depths.