Kevin Jackson, Xin Zhang
Figure 1: Classification patterns observed between SAM & SDG indicators are color coded on a version of the SAM score report card to show each SAM indicator’s relationship with the three primary SDG indicators that monitor hunger reduction. These generalized patterns are applied to each sustainability dimension (middle ring) and overall sustainability score (center circle). Given that both SAM and SDG use ‘Undernourishment’, we can consider the observed synergy-dominant pattern to reflect the fidelity of our analysis.
Patterns can be observed for hunger-related indicators with respect to the 18 SAM indicators and across various country groupings (i.e., income-based, and regional groupings). General patterns can be observed regarding: (1) if we see a higher proportion of tradeoffs or synergies among country cases, and (2) if there is a plurality for any sub-classification. Figure 1 applies our coding schema to the SAM Score Report indicating which of the 18 SAM indicators have consistent patterns of tradeoff or synergy-prevalence with all three hunger-related SDG indicators and across country groupings. Key takeaways which include:
- Social SAM Indicator ‘Food Affordability’ tends to be synergy-dominant with all three hunger-related indicators. Synergy-dominant patterns have a plurality of being ‘Synergy
- (Improving)’ meaning that, historically, increased food affordability and hunger-related conditions have both been improving.
- Economic SAM Indicators ‘Labor Productivity’ and ‘Government Support’ also tend to be synergy-dominant with all three hunger-related conditions. Synergy-dominant patterns have a plurality of being Synergy (Improving) meaning that increased agriculture expenditure and productivity has been occurring alongside reduced hunger.
- Environmental SAM Indicators (‘Greenhouse Gas Emissions’ and ‘Nitrogen Surplus’) tend to be tradeoff-dominant with all three hunger-related indicators. Furthermore, these tradeoff-dominant patterns have a plurality of being ‘Tradeoff (Worsening)’ meaning that, historically, these adverse environmental impacts of agriculture occur as hunger-related conditions improve.
- A handful of indicators across the three dimensions of agriculture sustainability have more complex classifications that differ across country groupings and/or with regards to hunger related SDG indicators which require further analysis and user feedback (See Table 1 for more details).
We can look at the data using our application at a finer scale to understand these generalized observations.
Socio-Economic Improvements Alongside Hunger Reduction
Figure 2: Notable synergies exhibited by 3 dashboard products. The first product is a (A) simplified classification matrix showcasing the consistent pattern of synergies between ‘Food Affordability’ and hunger-related SDGs. Cells are classified as either tradeoff- or synergy-dominant depending upon which correlation is more prevalent for an assessed country grouping. The second product are (B) stacked bar plots showcasing proportions of sub-classifications between ‘Food Affordability’ and hunger-related SDGs. The third product is a (C) world map displaying dominant relationship between Undernourishment and Government Support.
As mentioned previously, we expect that advances in agricultural production will contribute to reduced hunger. And what we can see from the data is improving synergies between the assessed hunger-related indicators with those of SAM’s socioeconomic indicators. More specifically, we see consistent patterns across income and regional groups of improving synergies between reduced hunger and our economic SAM indicators, ‘Labor Productivity’ and ‘Government Support’, as well as with our social SAM indicators, ‘Under-nourishment’ and ‘Food Affordability’ (Figure 2; Table 1).
Hunger Reduction & the Environment
Figure 3: Notable tradeoffs exhibited by 3 dashboard products. The first product is a (A) simplified classification matrix showcasing the consistent pattern of synergies between ‘N Surplus Reduction’ and hunger-related SDGs. Cells are classified as either tradeoff- or synergy-dominant depending upon which correlation is more prevalent for an assessed country grouping. The second product shows (B) stacked bar plots depicting proportions of sub-classifications between ‘N Surplus Reduction’ and hunger-related SDGs. The third product is a (C) world map displaying the dominant relationship between Undernourishment and Greenhouse Gas Emissions.
As nations proceed to increase agricultural production to meet increasing food demand and to address hunger reduction targets, we can expect increased environmental degradation in the form of increased pollution from surplus fertilizer use (exacerbated from nutrient use inefficiencies in agricultural production); increased deforestation/ land use change to increase production capacity, as well as increased water use and greenhouse gas emissions. In short, we expect reduced hunger to correspond to worsening trends for our environmental SAM indicators (i.e., Tradeoffs). Interestingly, we do see consistent tradeoffs across income groups and regions associated with ‘Nitrogen Surplus’ and ‘Greenhouse Gas Emissions’ (Fig. 3; Table 1); however, we observed more instances of synergies than tradeoffs for ‘Soil Erosion’ and hunger-related indicators except for tradeoffs for Low-Income and African Countries. While ‘Nitrogen Surplus’ and ‘Greenhouse Gas Emissions’ agree with our hypothesis, observed relationships with ‘Soil Erosion’ might show the overreliance on deforestation for low-income countries compared to increased production/technological efficiencies experienced by developing and developed countries.
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Supplementary Information
Table 1: Descriptions of SAM indicators with notable relationships shared with hunger-related SDG indicators.
| SAM Indicator (Abbr.) | Dim. | Description | Hunger Reduction | Under- nourishment |
Wasting | Stunting |
| Water Consumption | Environ. | The ratio of total irrigation consumption (unit: km3) of 26 crop classes or 130 primary crops and the amount of water considered as sustainable for agricultural use (unit: km3) | Mix | Tradeoff (Worsening) | Synergy (Unclear); notable prevalence of Synergy (Improving) for African Countries | Tradeoff (Worsening) |
| Nitrogen Surplus | Environ. | The nitrogen (N) surplus (unit: kg N ha-1) for country and year is defined as the difference between N inputs and outputs. | Tradeoff (Worsening) | Tradeoff (Worsening) | Tradeoff (Worsening) | Tradeoff (Worsening) |
| Greenhouse Gas Emissions | Environ. | The greenhouse gas emissions (unite: ton CO2-eq ha-1) defined as the ratio of carbon dioxide equivalent emissions (ton CO2-eq), and the agricultural land area (ha). | Tradeoff (Worsening) | Tradeoff (Worsening) | Tradeoff (Worsening) | Tradeoff (Worsening) |
| Soil Erosion | Environ. | The Soil Erosion (unite: ton ha-1) for a country and year is defined as the rate of soil loss due to agricultural activities. | Mix | General Synergy (Improving); African/Low-Income Countries in Tradeoff (Worsening) | General Synergy (Improving); African/Low-Income Countries in Tradeoff (Worsening) | General Synergy (Improving); African/Low-Income Countries in Tradeoff (Worsening) |
| Labor Productivity | Econ. | Agricultural GDP per agricultural worker for each country in each year is defined as a proxy of agricultural labor productivity. | Synergy (Improving) | Synergy (Improving) | Synergy (Improving) | Synergy (Improving) |
| Government Support | Econ. | Gov. agricultural expenditure per ag. worker includes all monetary transfers from consumers and taxpayers from gov. policies to provide services to stabilize the agricultural market, boost farmers’ income, lower farmers’ risks, improve farmers’ education, incentivize agricultural technologies, and promote agricultural productivity. | Synergy (Improving) | Synergy (Improving) | Synergy (Improving) | Synergy (Improving) |
| Trade Openness | Econ. | Trade openness is defined as the share of each nation’s total export and import values to its total GDP (OECD 2011). | Mix | Synergy (Improving) | Tradeoff (unclear) for Low-Middle-High Income Countries; Synergy (improving) for African Countries | Synergy (Improving) |
| Crop diversity | Social | Crop production diversity aims to measure the food redundancy of a country, which can provide “insurance” within a system | Mix | Mix | Mix | Mix |
| Food Affordability | Social | Food affordability reflects the resilience of the lowest 20th percentile of households in each country to short-term changes in food prices, defined as the ratio between income and food expenditure per capita | Synergy (Improving) | Synergy (Improving) | Synergy (Improving) | Synergy (Improving) |
| Under-nourishment | Social | Defined by FAOSTAT to estimate the proportion of the population whose habitual food consumption is insufficient to provide the dietary energy levels that are required to maintain a normal active and healthy life | Synergy (Improving) | Synergy (Improving) | Synergy (Improving) | Synergy (Improving) |