Publications

This paper addresses the highly relevant and timely issues of global trade and food security by developing an empirically grounded, relation-driven agent-based global trade model. Contrary to most price-driven trade models in the literature, the relation-driven agent-based global trade model focuses on the role of relational factors such as trust, familiarity, trade history and conflicts in countries' trade behaviour. Moreover, the global trade model is linked to a comprehensive nutrition formula to investigate the impact of trade on food and nutrition security, including macro and micronutrients. Preliminary results show that global trade improves the food and nutrition security of countries in Africa, Asia and Latin America. Trade also promotes a healthier and more balanced diet, as countries have access to an increased variety of food. The effect of trade in enhancing nutrition security, with an adequate supply of macro and micronutrients, is universal across nutrients and countries. As researchers call for a holistic and multifactorial approach to food security and climate change (Hammond and Dubé 2012 Proc. Natl Acad. Sci. USA 109 , 12 356–12 363. ( doi:10.1073/pnas.0913003109 )), the paper is one of the first to develop an integrated framework that consists of socio-economic, geopolitical, nutrition, environmental and agri-food systems to tackle these global challenges. Given the ongoing events of Brexit, the US–China trade war and the global COVID-19 pandemic, the paper will provide valuable insights on the role of trade in improving the food and nutrition security across countries.

SUMMARY Soil is a heterogeneous reservoir of essential elements needed for plant growth and development. Plants have evolved mechanisms to balance their nutritional needs based on availability of nutrients. This has led to genetically based variation in the elemental composition, the ‘ionome’, of plants, both within and between species. We explore this natural variation using a panel of wild‐collected, geographically widespread Arabidopsis thaliana accessions from the 1001 Genomes Project including over 1,135 accessions, and the 19 parental accessions of the Multi‐parent Advanced Generation Inter‐Cross (MAGIC) panel, all with full‐genome sequences available. We present an experimental design pipeline for high‐throughput ionomic screenings and analyses with improved normalisation procedures to account for errors and variability in conditions often encountered in large‐scale, high‐throughput data collection. We report quantification of the complete leaf and seed ionome of the entire collection using this pipeline and a digital tool, Ion Explorer , to interact with the dataset. We describe the pattern of natural ionomic variation across the A. thaliana species and identify several accessions with extreme ionomic profiles. It forms a valuable resource for exploratory genetic mapping studies to identify genes underlying natural variation in leaf and seed ionome and genetic adaptation of plants to soil conditions.

Core Ideas SOC decline, due to increased temperatures, reduces wheat and maize yields globally. CO 2 increase to 540 ppm partially compensates yield losses due to increased temperatures. Accounting for soil feedbacks is critical when evaluating climate change impacts on crop yield. A critical omission from climate change impact studies on crop yield is the interaction between soil organic carbon (SOC), nitrogen (N) availability, and carbon dioxide (CO 2 ). We used a multimodel ensemble to predict the effects of SOC and N under different scenarios of temperatures and CO 2 concentrations on maize ( Zea mays L.) and wheat ( Triticum aestivum L.) yield in eight sites across the world. We found that including feedbacks from SOC and N losses due to increased temperatures would reduce yields by 13% in wheat and 19% in maize for a 3°C rise temperature with no adaptation practices. These losses correspond to an additional 4.5% (+3°C) when compared to crop yield reductions attributed to temperature increase alone. Future CO 2 increase to 540 ppm would partially compensate losses by 80% for both maize and wheat at +3°C, and by 35% for wheat and 20% for maize at +6°C, relative to the baseline CO 2 scenario.

<title>Abstract</title> The rapid growth of urbanization in Iranian metropolises, especially Tehran, has caused significant changes in land use and cover, and consequently, a decrease in ecosystem services, including carbon storage. This study aimed to model and value changes in carbon storage in Tehran's ecological metabolism over three decades (1994–2024). Multi-temporal Landsat satellite images, advanced processing in Google Earth Engine, and the Random Forest algorithm were used for land use/cover classification. In addition, 66 urban soil samples were collected and analyzed to estimate soil organic carbon. The InVEST model was used to simulate changes in four main carbon pools (aboveground biomass, belowground biomass, soil, and dead organic matter). In addition, using economic valuation frameworks and global market reference rates, losses and benefits from carbon changes were calculated in the form of monetary indices. The results showed that over the study period, the area of ​​green spaces decreased from 14.19% in 1994 to 11.87% in 2024. These changes, along with the conversion of wasteland to construction, led to a significant reduction in carbon storage. Specifically, about 280,000 tonnes of carbon (equivalent to $7.62 million) were lost between 1994 and 2004, and more than 151,000 tonnes of carbon (equivalent to $4.11 million) between 2014 and 2024. Field-based models revealed several localized zones of carbon decline along with areas that could feasibly be restored. The results suggest that rapid urban growth and the steady loss of vegetation cover have greatly weakened the city’s capacity to retain carbon, and in turn, reduced its economic and ecological value. These observations highlight the importance of incorporating ecosystem service valuation into broader planning practices, ensuring that urban development does not undermine environmental integrity and contributes to climate resilience in large cities.

This database contains the average crop residue, manure nitrogen, manure organic carbon, net greenhouse gas emissions, and cropland area for 17 cropping systems at prefecture level during the period 2014-2018. In addition, it contained the changes of net greenhouse gas emissions caused by the optimization at prefecture level and province level. We also shared the key code for optimizing cropping systems at prefecture level and provided the all data. Users can run it the Matlab platform.

The overall global-scale consequences of climate change are dependent on the distribution of impacts across regions, and there are multiple dimensions to these impacts. This paper presents a global assessment of the potential impacts of climate change across several sectors, using a harmonised set of impacts models forced by the same climate andsocio-economic scenarios. Indicators of impact cover the water resources, river and coastal flooding, agriculture, natural environment and built environment sectors. Impacts are assessed under four SRES socio-economic and emissions scenarios, and the effects of uncertainty in the projected pattern of climate change are incorporated by constructing climate scenarios from 21 global climate models. There is considerable uncertainty in projected regional impacts across the climate model scenarios, and coherent assessments of impacts across sectors and regions therefore must be based on each model pattern separately; using ensemble means, for example, reduces variability between sectors and indicators. An example narrative assessment is presented in the paper. Under this narrative approximately 1 billion people would be exposed to increased water resources stress, around 450 million people exposed to increased river flooding, and 1.3 million extra people would be flooded in coastal floods each year. Crop productivity would fall in most regions, and residential energy demands would be reduced in most regions because reduced heating demands would offset higher cooling demands. Most of the global impacts on water stress and flooding would be in Asia, but the proportional impacts in the Middle East North Africa region would be larger. By 2050 there are emerging differences in impact between different emissions and socio-economic scenarios even though the changes in temperature and sea level are similar, and these differences are greater in 2080. However, for all the indicators, the range in projected impacts between different climate models is considerably greater than the range between emissions and socio-economic scenarios.