• Energy Research
• 2016-2025close

Abstract It is widely anticipated that climate change will negatively affect both food security and diet diversity. Diet diversity is especially critical for children as it correlates with macro and micronutrient intake important for child development. Despite these anticipated links, little empirical evidence has demonstrated a relationship between diet diversity and climate change, especially across large datasets spanning multiple global regions and with more recent climate data. Here we use survey data from 19 countries and more than 107 000 children, coupled with 30 years of precipitation and temperature data, to explore the relationship of climate to child diet diversity while controlling for other agroecological, geographic, and socioeconomic factors. We find that higher long-term temperatures are associated with decreases in overall child diet diversity, while higher rainfall in the previous year, compared to the long-term average rainfall, is associated with greater diet diversity. Examining six regions (Asia, Central America, North Africa, South America, Southeast Africa, and West Africa) individually, we find that five have significant reductions in diet diversity associated with higher temperatures while three have significant increases in diet diversity associated with higher precipitation. In West Africa, increasing rainfall appears to counterbalance the effect of rising temperature impacts on diet diversity. In some regions, the statistical effect of climate on diet diversity is comparable to, or greater than, other common development efforts including those focused on education, improved water and toilets, and poverty reduction. These results suggest that warming temperatures and increasing rainfall variability could have profound short- and long-term impacts on child diet diversity, potentially undermining widespread development interventions aimed at improving food security.

Significance We use geolocated child nutrition data from 53 developing countries to show that minor to severe droughts as well as severe periods of extreme rainfall are related to child stunting. We then explore how various geographic factors mitigate or amplify the effect of drought on child heights. Finally, we combine global data on these factors to map where child stunting is currently vulnerable to drought, finding that arid low-income countries with poor governance and political instability are where drought could have the largest effect on child stunting.

Substantial investment from both the private and public sectors will be needed to achieve the ambitious Sustainable Development Goal 2 (SDG2), which focuses on ending poverty and achieving zero hunger. To harness the private sector, high quality, transparent metrics are needed to ensure that every dollar spent reaches the most marginalized segments of a community while still helping institutions achieve their goals. Satellite-derived Earth observations will be instrumental in accelerating these investments and targeting them to the regions with the greatest need. This article proposes two quantitative metrics that could be used to evaluate the impact of private sector activities on SDG2: measuring increases in yield over baseline and ensuring input availability and affordability in all markets.

AbstractAchieving sustainable development requires understanding how human behavior and the environment interact across spatial scales. In particular, knowing how to manage tradeoffs between the environment and the economy, or between one spatial scale and another, necessitates a modeling approach that allows these different components to interact. Existing integrated local and global analyses provide key insights, but often fail to capture ‘meso-scale’ phenomena that operate at scales between the local and the global, leading to erroneous predictions and a constrained scope of analysis. Meso-scale phenomena are difficult to model because of their complexity and computational challenges, where adding additional scales can increase model run-time exponentially. These additions, however, are necessary to make models that include sufficient detail for policy-makers to assess tradeoffs. Here, we synthesize research that explicitly includes meso-scale phenomena and assess where further efforts might be fruitful in improving our predictions and expanding the scope of questions that sustainability science can answer. We emphasize five categories of models relevant to sustainability science, including biophysical models, integrated assessment models, land-use change models, earth-economy models and spatial downscaling models. We outline the technical and methodological challenges present in these areas of research and discuss seven directions for future research that will improve coverage of meso-scale effects. Additionally, we provide a specific worked example that shows the challenges present, and possible solutions, for modeling meso-scale phenomena in integrated earth-economy models.