Biodiversity is key for human and environmental health. Available dietary and ecological indicators are not designed to assess the intricate relationship between food biodiversity and diet quality. We applied biodiversity indicators to dietary intake data from and assessed associations with diet quality of women and young children. Data from 24-hour diet recalls (55% in the wet season) of n = 6,226 participants (34% women) in rural areas from seven low- and middle-income countries were analyzed. Mean adequacies of vitamin A, vitamin C, folate, calcium, iron, and zinc and diet diversity score (DDS) were used to assess diet quality. Associations of biodiversity indicators with nutrient adequacy were quantified using multilevel models, receiver operating characteristic curves, and test sensitivity and specificity. A total of 234 different species were consumed, of which <30% were consumed in more than one country. Nine species were consumed in all countries and provided, on average, 61% of total energy intake and a significant contribution of micronutrients in the wet season. Compared with Simpson’s index of diversity and functional diversity, species richness (SR) showed stronger associations and better diagnostic properties with micronutrient adequacy. For every additional species consumed, dietary nutrient adequacy increased by 0.03 (P < 0.001). Diets with higher nutrient adequacy were mostly obtained when both SR and DDS were maximal. Adding SR to the minimum cutoff for minimum diet diversity improved the ability to detect diets with higher micronutrient adequacy in women but not in children. Dietary SR is recommended as the most appropriate measure of food biodiversity in diets.
Food consumption accounts for an important proportion of the world GHG emissions per capita. Previous studies have delved into the nature of dietary patterns, showing that GHG reductions can be achieved in diets if certain foods are consumed rather than other, more GHG intensive products. For instance, vegetarian and low-meat diets have proved to be less carbon intensive than diets that are based on ruminant meat. These environmental patterns, increasingly analyzed in developed nations, are yet to be assessed in countries liked Peru where food purchase represents a relatively high percentage of the average household expenditure, ranging from 38% to 51% of the same. Therefore, food consumption can be identified as a potential way to reduce GHG emissions in Peru. However, the Peruvian government lacks a specific strategy to mitigate emissions in this sector, despite the recent ratification of the Paris Accord. In view of this, the main objective of this study is to analyze the environmental impacts of a set of 47 Peruvian food diet profiles, including geographical and socioeconomic scenarios. In order to do this, Life Cycle Assessment was used as the methodological framework to obtain the overall impacts of the components in the dietary patterns observed and primary data linked to the composition of diets were collected from the Peruvian National Institute for Statistics (INEI). Life cycle inventories for the different products that are part of the Peruvian diet were obtained from a set of previous scientific articles and reports regarding food production. Results were computed using the IPCC 2013 assessment method to estimate GHG emissions. Despite variations in GHG emissions from a geographical perspective, no significant differences were observed between cities located in the three Peruvian natural regions (i.e., coast, Andes and Amazon basin). In contrast, there appears to be a strong, positive correlation between GHG emissions and social expenditure or academic status. When compared to GHG emissions computed in the literature for developed nations, where the average caloric intake is substantially higher, diet-related emissions in Peru were in the low range. Our results could be used as a baseline for policy support to align nutritional and health policies in Peru with the need to reduce the environmental impacts linked to food production.
Aquaculture accounts for almost one-half of global fish consumption. Understanding the regional impact of climate fluctuations on aquaculture production thus is critical for the sustainability of this crucial food resource. The objective of this work was to understand the role of climate fluctuations and climate change in subtropical coastal estuarine environments within the context of aquaculture practices in Heʻeia Fishpond, Oʻahu Island, Hawaiʻi. To the best of our knowledge, this was the first study of climate effects on traditional aquaculture systems in the Hawaiian Islands. Data from adjacent weather stations were analyzed together with in situwater quality instrument deployments spanning a 12-year period (November 2004 –November 2016). We found correlations between two periods with extremely high fish mortality at Heʻeia Fishpond (May and October 2009) and slackening trade winds in the week preceding each mortality event, as well as surface water temperatures elevated 2–3°C higher than the background periods (March-December 2009). We posit that the lack of trade wind-driven surface water mixing enhanced surface heating and stratification of the water column, leading to hypoxic conditions and stress on fish populations, which had limited ability to move within net pen enclosures. Elevated water temperature and interruption of trade winds previously have been linked to the onset of El Niño in Hawaiʻi. Our results provide empirical evidence regarding El Niño effects on the coastal ocean, which can inform resource management efforts about potential impact of climate variation on aquaculture production. Finally, we provide recommendations for reducing the impact of warming events on fishponds, as these events are predicted to increase in magnitude and frequency as a consequence of global warming.
Rivers provide unrivaled opportunity for clean energy via hydropower, but little is known about the potential impact of dam-building on the food security these rivers provide. In tropical rivers, rainfall drives a periodic flood pulse fueling fish production and delivering nutrition to more than 150 million people worldwide. Hydropower will modulate this flood pulse, thereby threatening food security. We identified variance components of the Mekong River flood pulse that predict yield in one of the largest freshwater fisheries in the world. We used these variance components to design an algorithm for a managed hydrograph to explore future yields. This algorithm mimics attributes of discharge variance that drive fishery yield: prolonged low flows followed by a short flood pulse. Designed flows increased yield by a factor of 3.7 relative to historical hydrology. Managing desired components of discharge variance will lead to greater efficiency in the Lower Mekong Basin food system.
The impact of human activities on our planet's natural systems has been intensifying rapidly in the past several decades, leading to disruption and transformation of most natural systems. These disruptions in the atmosphere, oceans, and across the terrestrial land surface are not only driving species to extinction, they pose serious threats to human health and wellbeing. Characterising and addressing these threats requires a paradigm shift. In a lecture delivered to the Academy of Medical Sciences on Nov 13, 2017, I describe the scale of human impacts on natural systems and the extensive associated health effects across nearly every dimension of human health. I highlight several overarching themes that emerge from planetary health and suggest advances in the way we train, reward, promote, and fund the generation of health scientists who will be tasked with breaking out of their disciplinary silos to address this urgent constellation of health threats. I propose that protecting the health of future generations requires taking better care of Earth's natural systems.
Growing demand for agricultural commodities for food, fuel and other uses is expected to be met through an intensification of production on lands that are currently under cultivation. Intensification typically entails investments in modern technology — such as irrigation or fertilizers — and increases in cropping frequency in regions suitable for multiple growing seasons. Here we combine a process-based crop water model with maps of spatially interpolated yields for 14 major food crops to identify potential differences in food production and water use between current and optimized crop distributions. We find that the current distribution of crops around the world neither attains maximum production nor minimum water use. We identify possible alternative configurations of the agricultural landscape that, by reshaping the global distribution of crops within current rainfed and irrigated croplands based on total water consumption, would feed an additional 825 million people while reducing the consumptive use of rainwater and irrigation water by 14% and 12%, respectively. Such an optimization process does not entail a loss of crop diversity, cropland expansion or impacts on nutrient and feed availability. It also does not necessarily invoke massive investments in modern technology that in many regions would require a switch from smallholder farming to large-scale commercial agriculture with important impacts on rural livelihoods.