5 pages, The scientific advice needed to inform national and regional policies addressing the key challenges we face today must take account of disparate requirements. The complex nature of the problems addressed in this article—which encompass food and nutrition security, global health and climate change—and the multitude of their interconnections, calls for an integrated and multi-disciplinary approach that spans aspects related to the use of natural resources; the adoption of new technologies all the way to issues related to food demand and human behaviour. The scale is also important: national policies need to respond to a set of heterogeneous local conditions and requirements and should be particularly mindful of the effect on vulnerable groups of the population. At the same time, the global interconnectedness of food systems and shared natural resources also necessitates coordinated action at regional and global levels. The InterAcademy Partnership sought to develop an innovative model for integrating and analysing multidisciplinary scientific evidence to inform governments and regional policy bodies for policymaking on food and nutrition security. This approach relies on IAP’s membership of over 130 science academies grouped in four regional networks for Africa, America, Asia and Europe. Our article reviews the model, in particular with regards to interdisciplinarity, exploring examples relating to yield gap, plant breeding and food processing, and reflects on lessons learned during the project discussions and when engaging with policy-makers and other stakeholders. We propose that the framework developed can be applied to integrated assessment of other societal challenges where the scientific community can play a significant role in informing policy choices.
20 pages, As global climate change progresses, the United States (US) is expected to experience warmer temperatures as well as more frequent and severe extreme weather events, including heat waves, hurricanes, and wildfires. Each year, these events cost dozens of lives and do billions of dollars' worth of damage, but there has been limited research on how they influence human decisions about migration. Are people moving toward or away from areas most at risk from these climate threats? Here, we examine recent (2010–2020) trends in human migration across the US in relation to features of the natural landscape and climate, as well as frequencies of various natural hazards. Controlling for socioeconomic and environmental factors, we found that people have moved away from areas most affected by heat waves and hurricanes, but toward areas most affected by wildfires. This relationship may suggest that, for many, the dangers of wildfires do not yet outweigh the perceived benefits of life in fire-prone areas. We also found that people have been moving toward metropolitan areas with relatively hot summers, a dangerous public health trend if mean and maximum temperatures continue to rise, as projected in most climate scenarios. These results have implications for policymakers and planners as they prepare strategies to mitigate climate change and natural hazards in areas attracting migrants.
8 pages., Online issue., "Critics of climate science claim that climate models lack predictive skill. In fact, some of the earliest predictions made thirty years ago have performed remarkably well." ... "the bad news is that in terms of action, we are still only scratching the surface of responses needed...to prevent
'dangerous anthropogenic interference with the climate system.' The real challenges lie ahead."
25pgs, We combine farm accounting data with high-resolution meteorological data, and climate scenarios to estimate climate change impacts and adaptation potentials at the farm level. To do so, we adapt the seminal model of Moore and Lobell (2014) who applied panel data econometrics to data aggregated from the farm to the regional (subnational) level. We discuss and empirically investigate the advantages and challenges of applying such models to farm-level data, including issues of endogeneity of explanatory variables, heterogeneity of farm responses to weather shocks, measurement errors in meteorological variables, and aggregation bias. Empirical investigations into these issues reveal that endogeneity due to measurement errors in temperature and precipitation variables, as well as heterogeneous responses of farms toward climate change may be problematic. Moreover, depending on how data are aggregated, results differ substantially compared to farm-level analysis. Based on data from Austria and two climate scenarios (Effective Measures and High Emission) for 2040, we estimate that the profits of farms will decline, on average, by 4.4% (Effective Measures) and 10% (High Emission). Adaptation options help to considerably ameliorate the adverse situation under both scenarios. Our results reinforce the need for mitigation and adaptation to climate change.