International Trade Reshapes the Decoupling of Emissions from Economic Growth.

Efforts to stabilize the global climate change while also continuing human development depend upon "decoupling" economic growth from fossil fuel CO2 emissions. However, evaluations of such decoupling have typically relied on production-based emissions, which do not account for emissions embodied in international trade. Yet international trade can greatly change emissions accounting and reshape the decoupling between emissions and economic growth. Here, we evaluate decoupling of economic growth from different accounts of emissions in each of the 159 countries and analyze the drivers of decoupling. We find that between 1995 and 2015, although 29 countries exhibited strong decoupling of territorial emissions (growing economies and decreasing emissions), only 19 countries achieved economic growth while their consumption-based emissions decreased. Most developed countries have achieved decoupling of emissions related to domestic goods and services, but have not achieved decoupling of emissions related to imported goods and services. The U-test confirms that the domestic component of consumption-based emissions exhibits a stronger decoupling trend from gross domestic product (GDP) growth than consumption-based emissions, and emissions from imports continue to rise with GDP per capita without a corresponding decline, providing a statistical validation of the decoupling analysis. Moreover, in the countries where economic growth and consumption-based emissions are most decoupled, a key driver is decreasing emissions intensity due to technological progress─and especially reductions in the intensity of imported goods and services. Our results reveal the importance of assessing decoupling using consumption-based emissions; successful decoupling may require international cooperation and coordinated mitigation efforts of trading partners.

Interconnected and resilient: A CGE analysis of AI-driven cyberattacks in global trade.

The burgeoning interconnectedness of global trade in the digital age not only presents enticing opportunities but also harbors potent vulnerabilities of artificial intelligence (AI)-driven cyberattacks. This study explores the cascading impacts of these disruptive threats on economies, supply chains, and trade, utilizing the intricate lens of Computable General Equilibrium modeling. Through meticulously designed simulation scenarios, we illuminate the potential economic ramifications of cyberattacks, with a focus on regions heavily reliant on digital technologies and interwoven supply chains. The analysis reveals significant declines in real GDP, trade prices and volumes, and trade route disruptions across regions. Notably, economies like China, the United States, the United Kingdom, and the EU, due to their deep integration in global networks, face pronounced vulnerabilities. However, amidst this bleak landscape, hope emerges in the form of cyber resilience. The study showcases the effectiveness of proactive measures like adaptable production systems, diversified trade partners, and robust cybersecurity infrastructure in mitigating the adverse impacts of cyberattacks. Incorporating cyber resilience significantly dampens the reported negative consequences, highlighting the critical role of preparedness in combating digital warfare. This study underscores the urgent need for a global paradigm shift toward cyber resilience. Collective efforts to bolster cybersecurity infrastructures, foster international cooperation in threat intelligence, and establish open and resilient trade frameworks are crucial in navigating the treacherous labyrinth of AI-driven cyberattacks. By embracing resilience strategies and fostering global collaboration, we can pave the way for a more secure and prosperous digital future, where interconnectedness becomes a tool for progress, not a vulnerability to be exploited.

Does international trade reduce global carbon inequality? Evidence from a producer-consumer shared responsibility.

Addressing global carbon inequality constitutes an important task for both international negotiations on climate-change mitigation and the achievement of sustainable development goals. Soaring international trade might become a vigorous modifier for reducing global carbon inequality through production reallocation and economic boosts in different countries. However, this effect remains largely unexplored, not only because of little awareness of the windfall benefits from international trade but also because of debates on quantifying global carbon inequality from both production- and consumption-based perspectives. To avoid incomplete implications from a single perspective, this study first adapted a producer-consumer shared responsibility to evaluate global carbon inequality using the technology-adjusted consumption-based accounting method for 189 countries from 2006 to 2016. A dynamic panel data model was developed to examine the different channels through which international trade affects global carbon inequality in developed and developing countries. The results demonstrate that even with increasing carbon emissions, less global carbon inequality was witnessed from 2006 to 2016. International trade plays an important role in reducing global carbon inequality, mostly by stimulating the economy and increasing household income in developing countries. However, production reallocation via international trade fails in reducing the emission responsibilities of developed countries, rendering this futile in alleviating global carbon inequality. Carbon leakage that transfers carbon-intensive production across borders can lead to this unintended result, and more stringent cross-border regulations such as the carbon border adjustment mechanism can be effective. This study not only highlights the pivotal role of international trade in reducing global carbon inequality but also the future direction of international cooperation on climate change mitigation in a globalized world.

Opinion Formation in the World Trade Network.

We extend the opinion formation approach to probe the world influence of economical organizations. Our opinion formation model mimics a battle between currencies within the international trade network. Based on the United Nations Comtrade database, we construct the world trade network for the years of the last decade from 2010 to 2020. We consider different core groups constituted by countries preferring to trade in a specific currency. We will consider principally two core groups, namely, five Anglo-Saxon countries that prefer to trade in US dollar and the 11 BRICS+ that prefer to trade in a hypothetical currency, hereafter called BRI, pegged to their economies. We determine the trade currency preference of the other countries via a Monte Carlo process depending on the direct transactions between the countries. The results obtained in the frame of this mathematical model show that starting from the year 2014, the majority of the world countries would have preferred to trade in BRI than USD. The Monte Carlo process reaches a steady state with three distinct groups: two groups of countries preferring to trade in whatever is the initial distribution of the trade currency preferences, one in BRI and the other in USD, and a third group of countries swinging as a whole between USD and BRI depending on the initial distribution of the trade currency preferences. We also analyze the battle between three currencies: on one hand, we consider USD, BRI and EUR, the latter currency being pegged by the core group of nine EU countries. We show that the countries preferring EUR are mainly the swing countries obtained in the frame of the two currencies model. On the other hand, we consider USD, CNY (Chinese yuan), OPE, the latter currency being pegged to the major OPEC+ economies for which we try to probe the effective economical influence within international trade. Finally, we present the reduced Google matrix description of the trade relations between the Anglo-Saxon countries and the BRICS+.

Role of Seaports and Imported Rats in Seoul Hantavirus Circulation, Africa.

Seoul orthohantavirus (SEOV) is not considered a major public health threat on the continent of Africa. However, Africa is exposed to rodentborne SEOV introduction events through maritime traffic after exponential growth of trade with the rest of the world. Serologic studies have already detected hantavirus antibodies in human populations, and recent investigations have confirmed circulation of hantavirus, including SEOV, in rat populations. Thus, SEOV is a possible emerging zoonotic risk in Africa. Moreover, the range of SEOV could rapidly expand, and transmission to humans could increase because of host switching from the usual brown rat (Rattus norvegicus) species, which is currently invading Africa, to the more widely installed black rat (R. rattus) species. Because of rapid economic development, environmental and climatic changes, and increased international trade, strengthened surveillance is urgently needed to prevent SEOV dissemination among humans in Africa.

Impact of International Trade on the Carbon Intensity of Human Well-Being.

There has been a longstanding debate about the impact of international trade on the environment and human well-being, yet there is little known about such environment and human well-being trade-off. Here, we explore the effect of international trade on the carbon intensity of human well-being (CIWB) globally under the current global trade system and a hypothetical no-trade scenario. We found that between 1995 and 2015, CIWB of 41% of countries declined and 59% of countries increased, caused by international trade, and this resulted in a reduction of the global CIWB and a decline in CIWB inequality between countries. International trade decreased CIWB for high- and upper-middle-income countries and increased CIWB for lower- and middle-income countries. In addition, our results also show that decreases in emission intensity are the most important driver of lower CIWB and the percentage contribution of emission intensity to the improvement in CIWB increases with income. The reduction of emission intensity, population growth, and increase in life expectancy all contribute to CIWB reduction, while the consumption level is the primary factor driving CIWB growth. Our results underscore the importance of studying the impact of international trade on the CIWB of countries at different stages of development.

Impacts of Receiving International Industrial Transfer on China's Air Quality and Health Exceed Those of Export Trade.

Benefiting from international economic cooperation on income, technology diffusion, and employment, China also suffers its environmental and health impacts, from both international trade (IT), as is now widely understood, and international industrial transfer (IIT), which has been largely unrecognized. Here, we develop a comprehensive framework to estimate the impacts of exporting IT and receiving IIT. We find that China's emissions of CO2 and almost all air pollutants associated with IIT and IT together grew after 1997 but then declined after 2010, with the peak shares of national total emissions ranging 18-31% for different species. These sources further accounted for 3.8% of nationwide PM2.5 concentrations and 94,610 (76,000-112,040) premature deaths in 2012, and the values declined to 2.6% and 67,370 (52,390-81,810), respectively, for 2017. Separated, the contribution of IIT to those impacts was more than twice that of IT. Scenario analyses suggest that improving emission controls in its less-developed regions would effectively reduce the impact of economic globalization, but such a benefit could be largely offset by strengthened international economic cooperation. The outcomes provide a scientific basis for adjusting China's strategic roles in the international distribution of industrial production and its formulation of relevant environmental policies from a comprehensive perspective.

Comparing the spreading characteristics of monkeypox (MPX) and COVID-19: Insights from a quantitative model.

Climate change is acknowledged to directly affect not only the environment, economy, and society but also the transmission dynamics of infectious diseases, thereby impacting public health. The recent experiences with the spread of SARS-CoV-2 and Monkeypox have highlighted the complex and interconnected nature of infectious diseases, which are strongly linked to various determinants of health. Considering these challenges, adopting a new vision such as the trans-disciplinary approach appears to be imperative. This paper proposes a new theory about viruses' spread, based on a biological model, accounting for the optimisation of energy and material resources for organisms' survival and reproduction in the environment. The approach applies Kleiber's law scaling theory, originally developed in biology, to model community dynamics in cities. A simple equation can be used to model pathogen spread without accounting for each species' physiology by leveraging the superlinear scaling of variables with population size. This general theory offers several advantages, including the ability to explain the rapid and surprising spread of both SARS-CoV-2 and Monkeypox. The proposed model shows similarities in the spreading processes of both viruses, based on the resulting scaling factors, and opens new avenues for research. By fostering cooperation and integrating knowledge from different disciplines to effectively tackle the multifaceted dimensions of disease outbreaks, we can work towards preventing future health emergencies.

The World Animal Health Information System as a tool to support decision-making and research in animal health.

The World Animal Health Information System (WAHIS) collects and publishes a wealth of information gathered by individual countries' Veterinary Services, including detailed country-specific information on outbreaks of diseases listed by the World Organisation for Animal Health (WOAH, founded as OIE), including emerging diseases, in domestic animals and wildlife, and non-listed diseases in wildlife. The data set is one of the most comprehensive in the world, with 182 Members obliged to report this information to WOAH in a timely manner. As such, the data provide invaluable input for Veterinary Services, animal health researchers and stakeholders to gain insight into risk from infectious diseases, for example through the development of predictive models and risk assessments to address the risk from trade of animal products, globalisation, or movement of wildlife or vectors across country borders. This paper reviews previous analyses that have been conducted using WAHIS data and outlines ways in which these data can be used for preparedness and risk assessment.

Le Système mondial d'information zoosanitaire (WAHIS) collecte et publie une grande quantité d'informations recueillies auprès des Services vétérinaires nationaux, parmi lesquelles des données détaillées spécifiques aux pays sur les foyers de maladies listées par l'Organisation mondiale de la santé animale (OMSA, fondée en tant qu'OIE), dont les maladies émergentes, chez les animaux domestiques et dans la faune sauvage, ainsi que de maladies non listées affectant la faune sauvage. Cet ensemble de données est l'un des plus exhaustifs du monde puisque les 182 Membres de l'OMSA ont l'obligation de lui faire remonter ces informations dans WAHIS dans des délais spécifiés. Ces données sont précieuses pour les Services vétérinaires, les chercheurs travaillant dans le domaine de la santé animale et les parties prenantes car elles permettent de mieux comprendre les risques relatifs aux maladies infectieuses, notamment grâce aux modèles prédictifs et aux évaluations de risques pour traiter le risque lié au commerce de produits d'origine animale, à la mondialisation, aux mouvements de la faune sauvage ou aux vecteurs entre les pays. Les auteurs font le point sur des analyses antérieures qui ont été menées en utilisant les données de WAHIS et soulignent comment ces données peuvent être utilisées dans le cadre d'un travail de préparation et d'évaluation des risques.

El Sistema Mundial de Información Zoosanitaria (WAHIS) colecta y publica una gran cantidad de datos recogidos por los Servicios Veterinarios de cada país, en particular detallada información sobre brotes de enfermedades listadas por la Organización Mundial de Sanidad Animal (OMSA, fundada como OIE), incluidas las enfermedades emergentes, que hayan afectado a los animales domésticos o la fauna silvestre, así como enfermedades no listadas que afectan a la fauna silvestre. Se trata de uno de los conjuntos de datos más completos del mundo, ya que los 182 Miembros tienen la obligación de comunicar esta información a la OMSA dentro de plazos determinados. Estos datos son una fuente de información de gran utilidad para los Servicios Veterinarios, los investigadores que trabajan en sanidad animal y demás partes interesadas porque permiten mejorar la comprensión de los riesgos derivados de las enfermedades infecciosas, por ejemplo elaborando modelos predictivos y evaluaciones de riesgo que ayuden a manejar los riesgos ligados al comercio de productos de origen animal, la globalización o al movimiento transfronterizo de animales salvajes o vectores de enfermedad. Los autores repasan una serie de análisis previamente realizados con datos de WAHIS y explican en síntesis cómo pueden utilizarse estos datos con fines de preparación y evaluación de riesgos.

International trade in future avoided emissions: The case of battery electric vehicles and the United States.

The impact of international trade on greenhouse gas (GHG) emissions has primarily been viewed through the lens of emissions embodied in goods, which flow from lower-income to higher-income countries. This trade has been interpreted as allowing the high-income countries to shirk their responsibilities to address the global climate challenge by offshoring emissions. However, international trade may also have an impact on climate through flows from higher-income to lower-income countries, particularly long-lived capital and durable goods that have the potential to avoid future emissions. Given the innovation resources concentrated in higher-income countries and their historic domination of trade in such long-lived goods, this concept may balance the scales to some degree. This paper briefly develops the concept of future avoided emissions and illustrates it with the empirical case of the United States' trade in battery electric vehicles (BEVs) from 2017 to 2020.

Analyzing the carbon emission effect and systematic emission reduction mechanism of the Sino-USA manufacturing trade.

This study analyzed the theoretical mechanism of the carbon emission effect embodied in the Sino-USA manufacturing trade. We constructed a trade and carbon emission input-output model for 16 manufacturing sub-sectors in China and the USA from 2000 to 2018. A comprehensive empirical test of the systematic emission reduction mechanism was conducted. There were four main findings: (1) indirect and direct carbon emissions indicators can comprehensively analyze the link between production and demand across sectors; (2) indirect carbon emissions are higher than direct carbon emissions in half of the sectors in both China and the USA, and other sectors bear part of the carbon emissions for these sectors; (3) compared to 2000, the change in net exports of both countries is the main reason for the change in indirect carbon emissions, while the change in net exports of intermediate goods is the main reason for the change in direct carbon emissions; and (4) the Sino-USA trade surplus comes at the expense of China's environmental losses, while the USA obtains environmental benefits. Overall, the theoretical analytical framework not only comprehensively considers the interlinkages between production and demand across sectors but also provides a more reasonable evaluation of the environmental effects of Sino-USA trade. Additionally, this study provides a solid theoretical and empirical basis for China to achieve its dual-cycle and dual-carbon goals, thus promoting the rapid transformation of China's economy toward green and high-quality development.

The impact of climate disaster on international trade: Evidence from developed and developing countries.

A climate disaster can be devastating, but its challenges and losses provide some opportunities to other countries. Therefore, in this paper, we examine the impact of climate risk on international trade with a particular focus on developed and developing countries. Using a large sample of 160 countries between 2006 and 2019, we find that climate disaster is positively associated with high international trade. An increase in the climate disaster index will lead to an increase of about 5.9% in imports as a proportion of GDP. This is significant given that the mean of imports of the sample countries is 48%. Regarding the flow of trade, importation is likely to increase by about 6.7% and export to decrease by 0.65% after the occurrence of climate disasters in developing countries. Conversely, we did not find significant changes in imports and a weak association with exports for developed countries. We attribute this differential impact of climate disasters between developed and developing countries to the preparedness and risk mitigation mechanism in developed countries. The result suggests that the long-term effect of climate disasters increasing overall international trade is due to increasing imports in developing countries. Additional analyses demonstrate the robustness of these results to different model specifications and measurements of variables. Our results imply that climate change and its associated natural disasters offer more trade opportunities for developed countries than developing countries, highlighting the climate injustices between the high and low climate change contributors.

Tracing global N2O emission mitigation strategies through trade networks.

Nitrous oxide (N2O) is the third most potent greenhouse gas (GHG) and the most important ozone depleting substance. But how global N2O emissions are connected through the interwoven trade network remains unclear. This paper attempts to specifically trace anthropogenic N2O emissions via global trade networks using a multi-regional input-output model and a complex network model. Nearly one quarter of global N2O emissions can be linked to products traded internationally in 2014. The top 20 economies contribute to about 70% of the total embodied N2O emission flows. In terms of the trade embodied emissions classified by sources, cropland-, livestock-, chemistry-, and other industries-related embodied N2O emissions account for 41.9%, 31.2%, 19.9%, and 7.0%, respectively. Clustering structure of the global N2O flow network is revealed by the regional integration of 5 trading communities. Hub economies such as mainland China and the USA are collectors and distributors, and some emerging countries, such as Mexico, Brazil, India, and Russia, also exhibit dominance in different kinds of networks. This study selects the cattle sector to further verify that low production-side emission intensities and trade cooperation can lead to N2O emission reduction. In view of the impact of trade networks on global N2O emissions, achieving N2O emission reduction calls for vigorous international cooperation.

Spatio-temporal heterogeneity in the international trade resilience during COVID-19.

The COVID-19 pandemic and subsequent lockdowns have created immeasurable health and economic crises, leading to unprecedented disruptions to world trade. The COVID-19 pandemic shows diverse impacts on different economies that suffer and recover at different rates and degrees. This research aims to evaluate the spatio-temporal heterogeneity of international trade network vulnerabilities in the current crisis to understand the global production resilience and prepare for the future crisis. We applied a series of complex network analysis approaches to the monthly international trade networks at the world, regional, and country scales for the pre- and post- COVID-19 outbreak period. The spatio-temporal patterns indicate that countries and regions with an effective COVID-19 containment such as East Asia show the strongest resilience, especially Mainland China, followed by high-income countries with fast vaccine roll-out (e.g., U.S.), whereas low-income countries (e.g., Africa) show high vulnerability. Our results encourage a comprehensive strategy to enhance international trade resilience when facing future pandemic threats including effective non-pharmaceutical measures, timely development and rollout of vaccines, strong governance capacity, robust healthcare systems, and equality via international cooperation. The overall findings elicit the hidden global trading disruption, recovery, and growth due to the adverse impact of the COVID-19 pandemic.

Brazilian soybeans as feed for livestock in Europe: an insight into the nitrogen flows.

Given the agricultural demand to supply animals with food, the scope of today's soybean production and international trade can influence the nitrogen cycle. Rather than using soybeans from within the region of animal production, animal producers import nutritional supplements from distant growers. This widely opens the biogeochemical cycle of nitrogen, which reduces local recycling and increases carriage of reactive nitrogen via the supply chain. Ultimately, this potentiates the effects of a "nitrogen cascade" process. This study estimates nitrogen flows for Brazilian soybean transported to feed European livestock and attempts to quantify the understanding of how this flow can impact the nitrogen cascade effect. The hypothesis is that the growing trade of Brazilian soybean products is sufficient to spike reactive nitrogen production that can potentially cause distant environmental impacts of the nitrogen cascade. In this respect, the estimation of the nitrogen flows was evaluated using material flow analysis, and the cascade effect was quantified by means of a nitrogen cascade indicator (NCI). Notably, NCI can calculate the released amount of nitrogen in the environment along the entire supply chain of livestock products. NCI-based evaluation of Brazilian soybean products consumed by European livestock indicated the accumulation of nitrogen levels. There was also an increase in nitrogen flows in the Brazilian phase (0.058 Gg in 2007 to 139.86 Gg in 2019 for soybean meal; 584.28 Gg in 2007 to 309.78 Gg in 2019 for soybeans) accompanying a stability in European livestock production. This highlights the necessity for adjustments in nitrogen circularity between all levels of food production and improved strategies of more localised feed autonomy for sustainable global development. Supplementary Information: The online version contains supplementary material available at 10.1007/s10113-023-02034-1.

Dollar-Yuan Battle in the World Trade Network.

From the Bretton Woods agreement in 1944 till the present day, the US dollar has been the dominant currency in world trade. However, the rise of the Chinese economy has recently led to the emergence of trade transactions in Chinese yuan. Here, we mathematically analyze how the structure of international trade flows would favor a country to trade whether in US dollar or in Chinese yuan. The trade currency preference of a country is modeled as a binary variable with the properties of a spin in an Ising model. The computation of this trade currency preference is based on the world trade network built from the 2010-2020 UN Comtrade data and is determined by two multiplicative factors: the relative weight of trade volume exchanged by the country with its direct trade partners and the relative weight of its trade partners in global international trade. The performed analysis, based on the convergence of the Ising spin interactions, shows that from 2010 to present a transition took place, and the majority of the world countries would now have a preference to trade in Chinese yuan if one only considers the world trade network structure.

The COVID-19 pandemic and trade in agricultural products.

In this study, we develop a structural gravity model to analyse the effects of the ongoing COVID-19 pandemic on international trade in food and agriculture. Using detailed data on trade flows, we estimate the trade impacts of the pandemic for major sectors in food and agriculture. Supply-side impacts on trade caused by reductions in labour tend to be largest in labour-intensive sectors such as meat processing and processed fruit and vegetables. The supply-side export effects are dwarfed by the demand-side import effects, as the recessionary impact of the pandemic drives significant decreases in imports, largely in processed goods and labour-intensive commodities.

Multiperspective Analysis of Pandemic Impacts on U.S. Import Trade: What Happened, and Why?

U.S. container ports have experienced unpresented congestion since mid-2020. The congestion is generally attributed to import surges triggered by heavy spending on consumer goods during the COVID-19 pandemic. Port congestion has been compounded by the inability of importers to retrieve, receive, and process all the inbound goods they have ordered, resulting in supply chain shortfalls and economic disruption. How can the shipping industry and government organizations predict the end of the current surge and anticipate future surges? Expected seasonal variations in import volume are associated with peak holiday shopping periods; nonseasonal import surges are signaled by other factors. The research goes beyond transportation data sources to examine broader connections between import volume and indicators of economic and retail industry conditions. The strongest and most useful relationship appears to be between retail inventory indicators and containerized import growth. From January 2018 through July 2021, there was a relatively strong negative correlation between retail inventory- and import TEU indices with a 4-month lag (corresponding roughly to the time between import orders and -arrival). In the 2020 to 2021 pandemic period the negative correlation was stronger, again with a 4-month lag. These findings suggest that observers might anticipate import surges after marked, nonseasonal drops in retail inventories, and that import surges are likely to last until target inventory levels are restored. In a broader sense, an awareness of the linkages between consumer demand, retail chain responses, and containerized import volumes could better inform port, freight transportation, and government planning and policy choices.

Discerning the global phylogeographic distribution of Phyllosticta citricarpa by means of whole genome sequencing.

Phyllosticta citricarpa is a fungal pathogen causing citrus black spot (CBS). As a regulated pest in some countries, the presence of the pathogen limits the export of fruit and is therefore of agricultural and economic importance. In this study, we used high throughput sequencing data to infer the global phylogeographic distribution of this pathogen, including 71 isolates from eight countries, Argentina, Australia, Brazil, China, Cuba, Eswatini, South Africa and the United States of America. We assembled draft genomes and used a pairwise read mapping approach for the detection and enumeration of variants between isolates. We performed SSR marker discovery based on the assembled genome with the best assembly statistics, and generated genotype profiles for all isolates with 1987 SSR markers in silico. Furthermore, we identified 32,560 SNPs relative to a reference sequence followed by population genetic analyses based on the three datasets; pairwise variant counts, SSR genotypes and SNP genotypes. All three analysis approaches gave similar overall results. Possible pathways of dissemination among the populations from China, Australia, southern Africa and the Americas are postulated. The Chinese population is the most diverse, and is genetically the furthest removed from all other populations, and is therefore considered the closest to the origin of the pathogen. Isolates from Australia, Eswatini and the South African province Mpumalanga are closely associated and clustered together with those from Argentina and Brazil. The Eastern Cape, North West, and KwaZulu-Natal populations in South Africa grouped in another cluster, while isolates from Limpopo are distributed between the two aforementioned clusters. Southern African populations showed a close relationship to populations in North America, and could be a possible source of P. citricarpa populations that are now found in North America. This study represents the largest whole genome sequencing survey of P. citricarpa to date and provides a more comprehensive assessment of the population genetic diversity and connectivity of P. citricarpa from different geographic origins. This information could further assist in a better understanding of the epidemiology of the CBS pathogen, its long-distance dispersal and dissemination pathways, and can be used to refine phytosanitary regulations and management programmes for the disease.

Towards progressive regulatory approaches for agricultural applications of animal biotechnology.

Traditional breeding techniques, applied incrementally over thousands of years, have yielded huge benefits in the characteristics of agricultural animals. This is a result of significant, measurable changes to the genomes of those animal species and breeds. Genome editing techniques may now be applied to achieve targeted DNA sequence alterations, with the potential to affect traits of interest to production of agricultural animals in just one generation. New opportunities arise to improve characteristics difficult to achieve or not amenable to traditional breeding, including disease resistance, and traits that can improve animal welfare, reduce environmental impact, or mitigate impacts of climate change. Countries and supranational institutions are in the process of defining regulatory approaches for genome edited animals and can benefit from sharing approaches and experiences to institute progressive policies in which regulatory oversight is scaled to the particular level of risk involved. To facilitate information sharing and discussion on animal biotechnology, an international community of researchers, developers, breeders, regulators, and communicators recently held a series of seven virtual workshop sessions on applications of biotechnology for animal agriculture, food and environmental safety assessment, regulatory approaches, and market and consumer acceptance. In this report, we summarize the topics presented in the workshop sessions, as well as discussions coming out of the breakout sessions. This is framed within the context of past and recent scientific and regulatory developments. This is a pivotal moment for determination of regulatory approaches and establishment of trust across the innovation through-chain, from researchers, developers, regulators, breeders, farmers through to consumers.