The Sustainable Development Goals (SDGs) emphasize the global and multi‐dimensional nature of sustainability and thus require improving our capacity to articulate and trace the impact of ecosystem change to measures of human well‐being. Yet, the integrated nature of these goals is challenging to assess without similarly integrated assessment tools. We present a new modeling toolkit, “Mapping Ecosystem Services to Human well‐being” (MESH), that integrates commonly used, stand‐alone ecosystem services (ES) models from the InVEST suite of models to quantify and illustrate the trade‐offs and synergies across five ecosystem services and up to 10 associated SDGs. Development of the software and its functionality were informed by a broad stakeholder consultation with ministries, non‐governmental organizations and civil society groups in West Africa to identify common barriers to uptake and application of modeling tools in developing countries. In light of this process, key features included in MESH are (1) integration of multiple ecosystem service (ES) models into a common modeling framework supported by a curated base data set, (2) built‐in scenario generation capacity to support policy analysis, (3) visualization of outcomes and trade‐offs, and (4) mapping of ecosystem service change to SDG targets and goals. We illustrate the use of MESH in a case study in the Volta basin of West Africa comparing the effectiveness of three alternative conservation prioritization approaches: (1) land cover‐based, (2) topographic‐based, and (3) an ecosystem service‐based approach to minimize the impact of agricultural expansion. We evaluate these approaches by linking changes in service supply to potential impacts on achievement of specific SDG goals and targets.

Our food choices, food production pathways and household behaviors together govern the impact that our diet has on our health as well as the environment. As the planetary population grows, there is an increasing awareness of the need to both improve the quality of our diets for health reasons and to reduce its impact on the earth. From the consumer perspective, however, it is not always clear which healthy diet options and behaviours contribute most to reductions in our dietary footprint. In this paper we model and contrast the impact of the current American diet and three recommended diets from the USDA Dietary Guidelines 2015-2020 on six dimensions of the dietary footprint: land area required, blue water use, fertilizer application, primary energy input, ammonia emissions and greenhouse gas emissions based on LCIA studies. For each diet we test the relative impacts of a shift in diet composition, caloric intake and the reduction in food waste on the dietary footprint. We find that there are multiple pathways to significantly reduce the environmental impact of our diets. Shifts in diet composition from the current diet to a vegetarian diet had the greatest impact on reducing the dietary footprint, however, combinations of reducing caloric intake from 2600kcal/d to 2000kcal/d combined with 50% reduction in food loss could achieve similar results in some cases. In line with results of other studies, we find that reducing red-meat and dairy contribute most to the dietary footprint. However, recommended increases in fruits and vegetables with dietary shifts are accompanied by significant increases in blue water use. We extrapolate our estimated of environmental impacts out to 2051 when the US population is set to reach 400 million people. By combining a number of incremental shifts in diet composition, intake level, and food loss, significant land currently under production could be spared from production for other uses while still providing a nutritious diet for all.

Dietary diversification is central to improving dietary quality and nutrition for food security. Several factors have been linked to higher diversity diets, including household wealth, market access, on-farm crop diversity and regional forest cover. How these factors combine in landscapes to shape diets, however, is not well understood. We take the Ethiopian context as a case study of how wealth, farming system type, and landscape context interact to explain household dietary profiles. Using cluster analysis on nationally representative data on household food consumption, we identify three distinct dietary profiles across rural Ethiopia: 1) A low diversity diet, 2) A diverse diet particularly rich in fruit and vegetables, and 3) A diverse diet also rich in oils, fats and sugars. We found that the low diversity diet was strongly associated with households in the bottom and middle wealth classes that were mostly involved in cereal-based farming, although not exclusively. In contrast, the diverse diet high in fruit and vegetables was primarily composed of households with coffee-agroforestry farming systems, and did not appear to be limited to any particular wealth class, although it was positively associated with forest cover. Households with a diverse diet profile also rich in oils, fats and sugars were stratified across multiple different farming types, situated closer to roads, and primarily came from the middle and top wealth classes. Finally, while forest cover was strongly associated with a dietary profile rich in fruits and vegetable and the pursuit of coffee-agroforestry farming, the forest cover in cereal-based systems was still significantly positively associated with the consumption of dark green leafy vegetables and fruits. This suggests that even small amounts of forest cover can contribute to healthy diets. These results, which illuminate how wealth, farming system type, and landscape context shape dietary profiles, have important implications for the design of effective food security policies in Ethiopia.