Research ArticleENVIRONMENTAL ENGINEERING

Assessing the land resource–food price nexus of the Sustainable Development Goals

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Science Advances  16 Sep 2016:
Vol. 2, no. 9, e1501499
DOI: 10.1126/sciadv.1501499
  • Fig. 1 Schematic diagram of the construction of SDG strategies.

    We begin with seven policy clusters, each consisting of (A) a subset of SDGs relevant to a specific theme, (B) two active policies reflecting different ambition levels associated with specific SDG targets, and (C) one null policy (BAU), which represents inaction on the relevant goals. Integrated SDG strategies are defined by specifying exactly one policy in each cluster. The BAU strategy is composed of the BAU policy in all seven domains. SDG strategies are subsequently combined with an SSP to form a complete, unique GLOBIOM scenario, and their results are projected decennially through 2050. LULUCF, land use, land-use change, and forestry.

  • Fig. 2 GLOBIOM model results describe a trade-off efficiency frontier between EI scores and food prices.

    (Left) EI scores plotted versus global food price increases for single-policy strategies. Each single-policy strategy consists of an active policy from exactly one policy cluster and the null policy in the remaining six clusters, and each generates three GLOBIOM scenarios (one for each SSP). Food price changes are expressed in percent change relative to 2010. SSP2 scenario results are individually labeled. The linear regression fit includes all three SSPs and returns a statistically significant correlation between food prices and EI scores (N = 39). (Right) The fit residuals from single-policy SSP2 strategies characterize each policy’s deviation from the overall trade-off efficiency frontier. From left to right, policies are ranked in order of increasing ratio of food price cost to EI score benefit. Policies with low (high) cost-benefit ratios are interpreted as having depressurizing (pressurizing) effects on food production systems.

  • Fig. 3 EI scores plotted against global food price increases.

    Food price changes are expressed in percent change relative to 2010 for low-pressure, single-policy, and high-pressure strategies in years 2030 (left) and 2050 (right) of the indicated scenarios. Results from unique socioeconomic scenarios are indicated separately in each legend, but linear regression fits include all three SSPs within each strategy set (N = 30). Fit statistics are reported for each set.

  • Fig. 4 Circular plots illustrating the projected consequences of low- and high-pressure SDG strategies.

    Strategy outcomes are measured by five environmental indicators—LULUCF carbon emissions, agricultural water use, deforestation, biodiversity loss, and fertilizer use—and a global food price index (FPI). Policies on the outer ring of each circle indicate the third policy in each strategy. In the left (right) hemisphere of each circle, strategies are ranked from top to bottom by EI score (food price). Colors and percentages in each cell indicate the deviation for each indicator in year 2030 of the simulation relative to 2010.

  • Table 1 Description of the policies within each cluster.

    One policy from each cluster is specified to construct an SDG strategy, which is subsequently combined with an SSP to form a complete GLOBIOM scenario. The expected pressurizing effect of each policy on food prices is indicated in the far right column, where “P” indicates pressurizing policies expected to raise food prices, and “D” indicates depressurizing policies expected to decrease food prices.

    Policy clusterPolicyDescriptionFood effect
    Energy and climate (SDGs 7, 13, and 14)BAU
    Climate-BE
    Climate-BE+
    Nominal primary energy profile: no climate target
    Moderate bioenergy and nuclear energy: ΔT < 2°C
    High bioenergy and no nuclear: ΔT < 2°C

    P
    P
    Food system resilience (SDGs 1, 2, 6, 8, 9, and 12)Low flexibility
    BAU
    High flexibility
    Slow production system shifts and high waste
    Nominal production system shifts and waste
    Rapid production system shifts and low waste
    P

    D
    Agricultural productivity (SDGs 2 and 12)BAU
    +30% yield
    +50% yield
    Nominal input-neutral agricultural yield growth
    Nominal input-neutral yield growth + 30%
    Nominal input-neutral yield growth + 50%

    D
    D
    Terrestrial ecosystems (SDGs 6 and 15)BAU
    Zero def
    Zero def/grslnd
    No restrictions on land-use change
    No gross forest loss
    No gross forest or grassland loss

    P
    P
    Biodiversity conservation (SDGs 14 and 15)BAU
    Biodiversity
    Biodiversity+
    Unrestricted conversion of biodiversity hotspots
    Moderate protection of biodiversity hotspots
    No conversion of biodiversity hotspots

    P
    P
    LULUCF climate change mitigation
    (SDGs 13–15)
    BAU
    GHG $10
    GHG $50
    No tax on LULUCF emissions
    LULUCF emissions tax: US $10/tCO2eq
    LULUCF emissions tax: US $50/tCO2eq

    P
    P
    Sustainable consumption (SDGs 2, 8, and 12)Diet−
    BAU
    Diet+
    Western diet globalization
    FAO diet projections
    Reduced meat demand
    P

    D
  • Table 2 Indicators used to evaluate SDG strategies.

    Each SDG strategy is scored according to its effect on five environmental indicators of planetary boundaries—LULUCF carbon emissions, agricultural water use, deforestation, biodiversity loss, and fertilizer use—and on global food prices in years 2030 and 2050 of the simulation. The SDGs relevant to each of the planetary boundaries are indicated, thus closing the policy process and pressure-state-response (PSR) loops. All metrics refer to globally aggregated results from the GLOBIOM model.

    Pressure indicatorSDG targetsUnits
    Food price index2
    LULUCF emissions13Embedded Image
    Agricultural water use6km3
    Deforestation6, 13, and 15103 ha
    Biodiversity loss15103 ha
    Fertilizer use2 and 13103 ton

Supplementary Materials

  • Supplementary material for this article is available at http://advances.sciencemag.org/cgi/content/full/2/9/e1501499/DC1

    section S1.1. Overview of the general approach to the SDG land resource nexus.

    section S1.2. Quantitative approach to modeling trade-offs and cobenefits.

    section S1.3. Developing policy clusters in association with SDG targets.

    section S1.4. Defining SDG strategies from individual policy alternatives.

    section S2.1. The analytical framework for modeling SDG scenarios.

    section S3.1. Indicators for assessing SDG strategies.

    section S3.2. Normalized scores.

    section S3.3. EI scores.

    section S3.4. Fit statistics.

    section S3.5. Complete GLOBIOM scenario results.

    fig. S1. Diagram illustrating the conceptualization of the analysis.

    fig. S2. SDG clusters, policies, and strategies.

    fig. S3. Future primary energy supply from biomass.

    fig. S4. Short-rotation tree plantation areas.

    fig. S5. Indicators of environmental performance of Global Energy Assessment scenarios.

    fig. S6. Aggregate crop yield projections by SSP.

    fig. S7. Historical and projected global food consumption.

    fig. S8. Global consumption patterns of livestock products.

    fig. S9. Diagrammatic illustration of the GLOBIOM model.

    fig. S10. Graphical representation of interactions among policy clusters.

    fig. S11. Representation of SDG scenario output and evaluation.

    fig. S12. Spider charts showing GLOBIOM results for three SDG strategies (in three SSPs).

    fig. S13. Normality test on fit residuals from single-policy strategies.

    fig. S14. Normality test on fit residuals from depressurizing strategies.

    fig. S15. Normality test on fit residuals from pressurizing strategies.

    fig. S16. Circular plots for SSPs 1 and 3.

    table S1. Overview of definitions for three food system resilience policy cluster policies.

    table S2. Projected change in meat consumption per capita.

    table S3. SDG strategy definition table.

    table S4. GLOBIOM scenario results (values and normalized scores) for SSP1 scenarios.

    table S5. GLOBIOM scenario results (values and normalized scores) for SSP2 scenarios.

    table S6. GLOBIOM scenario results (values and normalized scores) for SSP3 scenarios.

    table S7. GLOBIOM scenario results (values and percent deviation from 2010 value, at top) for SSP1 scenarios.

    table S8. GLOBIOM scenario results (values and percent deviation from 2010 value, at top) for SSP2 scenarios.

    table S9. GLOBIOM scenario results (values and percent deviation from 2010 value, at top) for SSP3 scenarios.

    References (4972)

  • Supplementary Materials

    This PDF file includes:

    • section S1.1. Overview of the general approach to the SDG land resource nexus.
    • section S1.2. Quantitative approach to modeling trade-offs and cobenefits.
    • section S1.3. Developing policy clusters in association with SDG targets.
    • section S1.4. Defining SDG strategies from individual policy alternatives.
    • section S2.1. The analytical framework for modeling SDG scenarios.
    • section S3.1. Indicators for assessing SDG strategies.
    • section S3.2. Normalized scores.
    • section S3.3. EI scores.
    • section S3.4. Fit statistics.
    • section S3.5. Complete GLOBIOM scenario results.
    • fig. S1. Diagram illustrating the conceptualization of the analysis.
    • fig. S2. SDG clusters, policies, and strategies.
    • fig. S3. Future primary energy supply from biomass.
    • fig. S4. Short-rotation tree plantation areas.
    • fig. S5. Indicators of environmental performance of Global Energy Assessment scenarios.
    • fig. S6. Aggregate crop yield projections by SSP.
    • fig. S7. Historical and projected global food consumption.
    • fig. S8. Global consumption patterns of livestock products.
    • fig. S9. Diagrammatic illustration of the GLOBIOM model.
    • fig. S10. Graphical representation of interactions among policy clusters.
    • fig. S11. Representation of SDG scenario output and evaluation.
    • fig. S12. Spider charts showing GLOBIOM results for three SDG strategies (in three SSPs).
    • fig. S13. Normality test on fit residuals from single-policy strategies.
    • fig. S14. Normality test on fit residuals from depressurizing strategies.
    • fig. S15. Normality test on fit residuals from pressurizing strategies.
    • fig. S16. Circular plots for SSPs 1 and 3.
    • table S1. Overview of definitions for three food system resilience policy cluster policies.
    • table S2. Projected change in meat consumption per capita.
    • table S3. SDG strategy definition table.
    • table S4. GLOBIOM scenario results (values and normalized scores) for SSP1 scenarios.
    • table S5. GLOBIOM scenario results (values and normalized scores) for SSP2 scenarios.
    • table S6. GLOBIOM scenario results (values and normalized scores) for SSP3 scenarios.
    • table S7. GLOBIOM scenario results (values and percent deviation from 2010 value, at top) for SSP1 scenarios.
    • table S8. GLOBIOM scenario results (values and percent deviation from 2010 value, top) for SSP2 scenarios.
    • table S9. GLOBIOM scenario results (values and percent deviation from 2010 value, top) for SSP3 scenarios.
    • References (4972)

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