Research ArticleAGRICULTURE

Bigger is better: Improved nature conservation and economic returns from landscape-level mitigation

See allHide authors and affiliations

Science Advances  01 Jul 2016:
Vol. 2, no. 7, e1501021
DOI: 10.1126/sciadv.1501021
  • Fig. 1 Current land cover and land use in the study region.

    Current distributions of land cover and land use for the Ribeirão São Jerônimo watershed in the Brazilian Cerrado in southeastern Brazil.

  • Fig. 2 Comparison of the property (farm)–level and landscape (watershed)–level planning based on economic modeling of sugarcane expansion.

    (A) Landscape outcomes for the modeled watershed based on an 8.5–million ton sugarcane production target from profit maximization and FC compliance based on PL and LL mitigation planning with combined habitat protection and restoration (LL-PR), protection only (LL-P), and restoration only (LL-R). (B) Difference in cost savings [net present value (NPV) in million U.S. dollars], long-term species richness (number of bird and mammal species), water quality index (WQI), and additional mean carbon storage [in megatons of carbon (MtC)] for LL planning relative to PL planning. See the Supplementary Materials for additional results.

Supplementary Materials

  • Supplementary material for this article is available at http://advances.sciencemag.org/cgi/content/full/2/7/e1501021/DC1

    Supplementary Materials and Methods

    Supplementary Results

    fig. S1. Study area in relation to major ecological biomes of Brazil.

    fig. S2. Distributions of natural vegetation types predicted for our study area.

    fig. S3. Distributions of soil types for our study area.

    fig. S4. Optimized landscapes corresponding to each mitigation scenario.

    fig. S5. Cost savings for LL mitigation relative to PL mitigation.

    fig. S6. Sources of cost savings for LL mitigation relative to PL mitigation.

    fig. S7. Area of natural habitat across the mitigation scenarios.

    fig. S8. Types of natural habitat restored or protected under the PL and LL scenarios.

    fig. S9. Changes in habitat fragmentation for LL mitigation relative to PL mitigation.

    fig. S10. Patterns of habitat fragmentation for the different mitigation scenarios.

    fig. S11. Changes in fragmentation by habitat type for LL mitigation relative to PL mitigation.

    fig. S12. Changes in the expected number of bird and mammal species for LL mitigation relative to PL mitigation.

    fig. S13. Changes in the expected number of species by habitat specialization for LL mitigation relative to PL mitigation.

    fig. S14. Changes in the predicted carbon storage for LL mitigation relative to PL mitigation.

    fig. S15. Changes in WQI for LL mitigation relative to PL mitigation.

    fig. S16. Changes in the average predicted nitrogen and phosphorus concentrations and total loadings for LL mitigation relative to PL mitigation.

    fig. S17. Changes in average predicted turbidity and total sediment loading for LL mitigation relative to PL mitigation.

    table S1. Land cover types and definitions for the study area.

    table S2. Final yield for each scenario.

    table S3. Summary of the parameters used in the agricultural profit optimization models.

    table S4. Definitions of the parameters used in the agricultural profit optimization equations.

    table S5. Amount of habitat restored or protected under each mitigation scenario.

    table S6. Fragmentation metrics for patches of all natural habitat types grouped together.

    table S7. Fragmentation metrics for patches by habitat type.

    table S8. Data sources used to determine relevant species by taxonomic group.

    table S9. Average (±SD) habitat suitability values for land cover types in our study region.

    table S10. Average (±SD) parameters by trophic level used in the biodiversity model.

    table S11. Expected number of species based on the biodiversity model across mitigation scenarios.

    table S12. Expected number of species by habitat specialization for each mitigation scenario.

    table S13. Aggregated values for carbon storage per land cover/land use category for our study area.

    table S14. Additional carbon storage provided by each mitigation scenario.

    table S15. Minimum and maximum values for nitrogen (TN), phosphorus (TP), and turbidity concentrations in pristine areas in the Cerrado biome.

    table S16. WQI across mitigation scenarios.

    Additional Supplementary Material for this article is available at http://nature.org/TNC-Dow-Brazil.

    References (61126)

  • Supplementary Materials

    This PDF file includes:

    • Supplementary Materials and Methods
    • Supplementary Results
    • fig. S1. Study area in relation to major ecological biomes of Brazil.
    • fig. S2. Distributions of natural vegetation types predicted for our study area.
    • fig. S3. Distributions of soil types for our study area.
    • fig. S4. Optimized landscapes corresponding to each mitigation scenario.
    • fig. S5. Cost savings for LL mitigation relative to PL mitigation.
    • fig. S6. Sources of cost savings for LL mitigation relative to PL mitigation.
    • fig. S7. Area of natural habitat across the mitigation scenarios.
    • fig. S8. Types of natural habitat restored or protected under the PL and LL scenarios.
    • fig. S9. Changes in habitat fragmentation for LL mitigation relative to PL mitigation.
    • fig. S10. Patterns of habitat fragmentation for the different mitigation scenarios.
    • fig. S11. Changes in fragmentation by habitat type for LL mitigation relative to PL mitigation.
    • fig. S12. Changes in the expected number of bird and mammal species for LL mitigation relative to PL mitigation.
    • fig. S13. Changes in the expected number of species by habitat specialization for LL mitigation relative to PL mitigation.
    • fig. S14. Changes in the predicted carbon storage for LL mitigation relative to PL mitigation.
    • fig. S15. Changes in WQI for LL mitigation relative to PL mitigation.
    • fig. S16. Changes in the average predicted nitrogen and phosphorus concentrations and total loadings for LL relative to PL mitigation.
    • fig. S17. Changes in average predicted turbidity and total sediment loading for LL mitigation relative to PL mitigation.
    • table S1. Land cover types and definitions for the study area.
    • table S2. Final yield for each scenario.
    • table S3. Summary of the parameters used in the agricultural profit optimization models.
    • table S4. Definitions of the parameters used in the agricultural profit optimization equations.
    • table S5. Amount of habitat restored or protected under each mitigation scenario.
    • table S6. Fragmentation metrics for patches of all natural habitat types grouped together.
    • table S7. Fragmentation metrics for patches by habitat type.
    • table S8. Data sources used to determine relevant species by taxonomic group.
    • table S9. Average (±SD) habitat suitability values for land cover types in our study region.
    • table S10. Average (±SD) parameters by trophic level used in the biodiversity model.
    • table S11. Expected number of species based on the biodiversity model across mitigation scenarios.
    • table S12. Expected number of species by habitat specialization for each mitigation scenario.
    • table S13. Aggregated values for carbon storage per land cover/land use category for our study area.
    • table S14. Additional carbon storage provided by each mitigation scenario.
    • table S15. Minimum and maximum values for nitrogen (TN), phosphorus (TP), and turbidity concentrations in pristine areas in the Cerrado biome.
    • table S16. WQI across mitigation scenarios.
    • References (61126)

      Additional Supplementary Material for this article is available at http://nature.org/TNC-Dow-Brazil.

    Download PDF

    Files in this Data Supplement:

Navigate This Article