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A parameter-free model predicts patterns of commuting, phone calls and trade using only population density at all intermediate points. Accurate prediction of population movement Since the 1940s, planners needing to predict population movement, transport-network usage and even epidemics have turned to a model based on the 'gravity law'. This assumes that the number of individuals travelling between two locations is proportional to the population at the source and destination, and decays with distance. This approach has its limitations, because it looks at the flow between two specific points only. Here, Albert-László Barabási and colleagues present an alternative model that takes into account population density at all intermediate points. Their parameter-free radiation model predicts a range of phenomena — from commuting and migrations to phone calls — much more accurately than the gravity model. Needing only data on population densities, which are easy to measure, the system can be used to predict commuting and transport patterns even in areas where data are not collected systematically. Introduced in its contemporary form in 1946 (ref. 1 ), but with roots that go back to the eighteenth century 2 , the gravity law 1 , 3 , 4 is the prevailing framework with which to predict population movement 3 , 5 , 6 , cargo shipping volume 7 and inter-city phone calls 8 , 9 , as well as bilateral trade flows between nations 10 . Despite its widespread use, it relies on adjustable parameters that vary from region to region and suffers from known analytic inconsistencies. Here we introduce a stochastic process capturing local mobility decisions that helps us analytically derive commuting and mobility fluxes that require as input only information on the population distribution. The resulting radiation model predicts mobility patterns in good agreement with mobility and transport patterns observed in a wide range of phenomena, from long-term migration patterns to communication volume between different regions. Given its parameter-free nature, the model can be applied in areas where we lack previous mobility measurements, significantly improving the predictive accuracy of most of the phenomena affected by mobility and transport processes 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 .

Feeding a growing world sustainably In the coming years, continued population growth, rising incomes, increasing meat and dairy consumption and expanding biofuel use will place unprecedented demands on the world's agriculture and natural resources. Can we meet society's growing food needs while reducing agriculture's environmental harm? Here, an international team of environmental and agricultural scientists uses new geospatial data and models to identify four strategies that could double food production while reducing environmental impacts. First, halt agricultural expansion. Second, close 'yield gaps' on underperforming lands. Third, increase cropping efficiency. And finally, we need to change our diets and shift crop production away from livestock feed, bioenergy crops and other non-food applications. Increasing population and consumption are placing unprecedented demands on agriculture and natural resources. Today, approximately a billion people are chronically malnourished while our agricultural systems are concurrently degrading land, water, biodiversity and climate on a global scale. To meet the world’s future food security and sustainability needs, food production must grow substantially while, at the same time, agriculture’s environmental footprint must shrink dramatically. Here we analyse solutions to this dilemma, showing that tremendous progress could be made by halting agricultural expansion, closing ‘yield gaps’ on underperforming lands, increasing cropping efficiency, shifting diets and reducing waste. Together, these strategies could double food production while greatly reducing the environmental impacts of agriculture.

Potato (Solanum tuberosum L.) is the world's most important non-grain food crop and is central to global food security. It is clonally propagated, highly heterozygous, autotetraploid, and suffers acute inbreeding depression. Here we use a homozygous doubled-monoploid potato clone to sequence and assemble 86% of the 844-megabase genome. We predict 39,031 protein-coding genes and present evidence for at least two genome duplication events indicative of a palaeopolyploid origin. As the first genome sequence of an asterid, the potato genome reveals 2,642 genes specific to this large angiosperm clade. We also sequenced a heterozygous diploid clone and show that gene presence/absence variants and other potentially deleterious mutations occur frequently and are a likely cause of inbreeding depression. Gene family expansion, tissue-specific expression and recruitment of genes to new pathways contributed to the evolution of tuber development. The potato genome sequence provides a platform for genetic improvement of this vital crop.

Synthetic nitrogen (N) fertilizer has played a key role in enhancing food production and keeping half of the world's population adequately fed. However, decades of N fertilizer overuse in many parts of the world have contributed to soil, water, and air pollution; reducing excessive N losses and emissions is a central environmental challenge in the 21st century. China's participation is essential to global efforts in reducing N-related greenhouse gas (GHG) emissions because China is the largest producer and consumer of fertilizer N. To evaluate the impact of China's use of N fertilizer, we quantify the carbon footprint of China's N fertilizer production and consumption chain using life cycle analysis. For every ton of N fertilizer manufactured and used, 13.5 tons of CO₂-equivalent (eq) (tCO₂-eq) is emitted, compared with 9.7 t CO₂-eq in Europe. Emissions in China tripled from 1980 [131 terrogram (Tg) of CO₂-eq (Tg CO₂-eq)] to 2010 (452 Tg CO₂-eq). N fertilizer-related emissions constitute about 7% of GHG emissions from the entire Chinese economy and exceed soil carbon gain resulting from N fertilizer use by several-fold. We identified potential emission reductions by comparing prevailing technologies and management practices in China with more advanced options worldwide. Mitigation opportunities indude improving methane recovery during coal mining, enhancing energy efficiency in fertilizer manufacture, and minimizing N overuse in field-level crop production. We find that use of advanced technologies could cut N fertilizer-related emissions by 20-63%, amounting to 102-357 Tg CO₂-eq annually. Such reduction would decrease China's total GHG emissions by 2-6%, which is significant on a global scale.

In recent years, agricultural growth in China has accelerated remarkably, but most of this growth has been driven by increased yield per unit area rather than by expansion of the cultivated area. Looking towards 2030, to meet the demand for grain and to feed a growing population on the available arable land, it is suggested that annual crop production should be increased to around 580 Mt and that yield should increase by at least 2% annually. Crop production will become more difficult with climate change, resource scarcity (e.g. land, water, energy, and nutrients) and environmental degradation (e.g. declining soil quality, increased greenhouse gas emissions, and surface water eutrophication). To pursue the fastest and most practical route to improved yield, the near-term strategy is application and extension of existing agricultural technologies. This would lead to substantial improvement in crop and soil management practices, which are currently suboptimal. Two pivotal components are required if we are to follow new trajectories. First, the disciplines of soil management and agronomy need to be given increased emphasis in research and teaching, as part of a grand food security challenge. Second, continued genetic improvement in crop varieties will be vital. However, our view is that the biggest gains from improved technology will come most immediately from combinations of improved crops and improved agronomical practices. The objectives of this paper are to summarize the historical trend of crop production in China and to examine the main constraints to the further increase of crop productivity. The paper provides a perspective on the challenge faced by science and technology in agriculture which must be met both in terms of increased crop productivity but also in increased resource use efficiency and the protection of environmental quality.

Contemporary humans exhibit spectacular biological success derived from cumulative culture and cooperation. The origins of these traits may be related to our ancestral group structure. Because humans lived as foragers for 95% of our species' history, we analyzed co-residence patterns among 32 present-day foraging societies (total n = 5067 individuals, mean experienced band size = 28.2 adults). We found that hunter-gatherers display a unique social structure where (i) either sex may disperse or remain in their natal group, (ii) adult brothers and sisters often co-reside, and (iii) most individuals in residential groups are genetically unrelated. These patterns produce large interaction networks of unrelated adults and suggest that inclusive fitness cannot explain extensive cooperation in hunter-gatherer bands. However, large social networks may help to explain why humans evolved capacities for social learning that resulted in cumulative culture.

This Perspective discusses the emerging advances in plant membrane transporters, which can be used to improve crop yields, nutritional value, and environmental stress resistance. Enhanced plant membrane transporters Transport proteins embedded in the cell membranes are key targets for improving the efficiency with which plants take up and use water and nutrients. In this Perspective article, Julian Schroeder et al . discuss recent work on the development of specialized plant membrane transporters that can enhance crop yields, increase nutritional value and boost resistance to stresses including pathogens. Promising lines of development include aluminium-tolerant cereals that thrive in acid soil, salt-tolerant varieties that grow in soils affected by salinity or sodium toxicity, and plants containing high levels of the iron and zinc micronutrients often scarce in predominantly plant-based diets in developing countries. With the global population predicted to grow by at least 25 per cent by 2050, the need for sustainable production of nutritious foods is critical for human and environmental health. Recent advances show that specialized plant membrane transporters can be used to enhance yields of staple crops, increase nutrient content and increase resistance to key stresses, including salinity, pathogens and aluminium toxicity, which in turn could expand available arable land.

Investments aimed at improving agricultural adaptation to climate change inevitably favor some crops and regions over others. An analysis of climate risks for crops in 12 food-insecure regions was conducted to identify adaptation priorities, based on statistical crop models and climate projections for 2030 from 20 general circulation models. Results indicate South Asia and Southern Africa as two regions that, without sufficient adaptation measures, will likely suffer negative impacts on several crops that are important to large food-insecure human populations. We also find that uncertainties vary widely by crop, and therefore priorities will depend on the risk attitudes of investment institutions.

Another day another dollar The website wheresgeorge.com invites its users to enter the serial numbers of their US dollar bills and track them across America and beyond. Why? “For fun and because it had not been done yet”, they say. But the dataset accumulated since December 1998 has provided the ideal raw material to test the mathematical laws underlying human travel, and that has important implications for the epidemiology of infectious diseases. Analysis of the trajectories of over half a million dollar bills shows that human dispersal is described by a ‘two-parameter continuous-time random walk’ model: our travel habits conform to a type of random proliferation known as ‘superdiffusion’. And with that much established, it should soon be possible to develop a new class of models to account for the spread of human disease. The dynamic spatial redistribution of individuals is a key driving force of various spatiotemporal phenomena on geographical scales. It can synchronize populations of interacting species, stabilize them, and diversify gene pools 1 , 2 , 3 . Human travel, for example, is responsible for the geographical spread of human infectious disease 4 , 5 , 6 , 7 , 8 , 9 . In the light of increasing international trade, intensified human mobility and the imminent threat of an influenza A epidemic 10 , the knowledge of dynamical and statistical properties of human travel is of fundamental importance. Despite its crucial role, a quantitative assessment of these properties on geographical scales remains elusive, and the assumption that humans disperse diffusively still prevails in models. Here we report on a solid and quantitative assessment of human travelling statistics by analysing the circulation of bank notes in the United States. Using a comprehensive data set of over a million individual displacements, we find that dispersal is anomalous in two ways. First, the distribution of travelling distances decays as a power law, indicating that trajectories of bank notes are reminiscent of scale-free random walks known as Lévy flights. Second, the probability of remaining in a small, spatially confined region for a time T is dominated by algebraically long tails that attenuate the superdiffusive spread. We show that human travelling behaviour can be described mathematically on many spatiotemporal scales by a two-parameter continuous-time random walk model to a surprising accuracy, and conclude that human travel on geographical scales is an ambivalent and effectively superdiffusive process.

We present a framework for prioritizing adaptation approaches at a range of timeframes. The framework is illustrated by four case studies from developing countries, each with associated characterization of uncertainty. Two cases on near-term adaptation planning in Sri Lanka and on stakeholder scenario exercises in East Africa show how the relative utility of capacity vs. impact approaches to adaptation planning differ with level of uncertainty and associated lead time. An additional two cases demonstrate that it is possible to identify uncertainties that are relevant to decision making in specific timeframes and circumstances. The case on coffee in Latin America identifies altitudinal thresholds at which incremental vs. transformative adaptation pathways are robust options. The final case uses three crop–climate simulation studies to demonstrate how uncertainty can be characterized at different time horizons to discriminate where robust adaptation options are possible. We find that impact approaches, which use predictive models, are increasingly useful over longer lead times and at higher levels of greenhouse gas emissions. We also find that extreme events are important in determining predictability across a broad range of timescales. The results demonstrate the potential for robust knowledge and actions in the face of uncertainty.