2010年-世界发展银行全球_Impacts_of_Climate_Change_on_Brazilian_Agriculture___Refocusing_Impact_Assessments_to_2050_55页_2mb

Summary of Impacts of Climate Change on Brazilian Agriculture – Refocusing Impact Assessments to 2050

Core Content

This report provides an analysis of the impacts of climate change on Brazilian agriculture and outlines the methodological improvements needed to better assess these impacts up to 2050. It emphasizes the importance of integrating climate modeling with land use and land cover change data, and highlights the need for enhanced data collection, validation, and use in policy and investment planning.

Main Points and Key Information

1. Economic and Agricultural Significance of Brazil

• Agriculture contributes about 5.5% of GDP (25% when agribusiness is included) and 36% of exports.
• Brazil is the world's largest producer of sugarcane, coffee, tropical fruits, and frozen concentrated orange juice.
• It also has the largest commercial cattle herd (170 million head) and is a major producer of soybeans, corn, cotton, and forest products.
• Agricultural trade balance was US$55 billion in 2009, and agriculture contributed 11.4% to GDP growth in 2010, compared to 13.8% for industry and 5.6% for services.

2. Climate Change Impacts on Agriculture

• Climate change is expected to reduce cropland with low production risk by 2050, which currently produces 85% of Brazil's major food and export crops.
• Productivity of subsistence crops in northeastern Brazil is projected to decline.
• These impacts are expected to be felt as early as 2020, with significant consequences by 2050.
• The best adaptation strategy identified is breeding heat and drought-tolerant crop and pasture varieties, which requires 10 years of R&D and US$6 million in investment.

3. Limitations of Current Climate Models

• Global Climate Models (GCMs) have coarse resolution (100–300 km), making it hard to capture regional and local climate impacts.
• Regional Climate Models (RCMs), while better, are downscaled from GCMs and still suffer from biases and errors that need correction.
• Most climate data in Brazil is not long-term or sufficiently dense, especially in the Amazon and Cerrado regions.
• Current assessments rely on one GCM and one RCM, limiting the robustness of projections.

4. Opportunities for Improvement

• Integrate global, regional, and local models with validated field data.
• Use Brazilian Regional Atmospheric Modeling System (BRAMS), which incorporates aerosols and land cover feedbacks to improve local climate projections.
• Enhance the EMBRAPA/UNICAMP Agro Zoning Model with high-resolution climate data and disaggregated land quality data at state and municipal levels.
• Improve the Brazilian Land Use Model (BLUM) by coupling it with updated climate and land use data to assess:
  • Changes in supply and demand of agricultural products.
  • Economic effects on production and profitability.
  • Distribution of land use and production across Brazil under different scenarios.

5. Key Challenges and Strategic Needs

• Brazil needs to increase productivity on existing agricultural lands and rehabilitate degraded lands without further deforestation.
• A "climate-smart" approach is essential to ensure sustainable intensification and resilience.
• The government has committed to reducing deforestation by 70% by 2020 and GHG emissions by 36–39%.
• Legal frameworks (e.g., Forest Law, Preservation Areas) define protected zones, limiting agricultural expansion in ecologically sensitive areas.

6. Agricultural Sector Evolution

• Since the 1990s, Brazil's agricultural productivity has grown more than 1.5 times the global average.
• The sector has become more capital and labor intensive, with a decline in labor use and increase in capital and land use.
• The number of rural households has increased, and the distribution of farm sizes is shifting, with smaller farms becoming more prevalent.

7. Future Agricultural Development Pathways

• Increase per area productivity of existing agricultural lands.
• Rehabilitate deforested and degraded lands for productive use.
• Promote sustainable land use in ecologically sensitive areas (Amazon, Cerrado, etc.).

Key Interventions for 2050

1. Refine climate model projections by coupling global, regional, and local modeling with validated field data.
2. Enhance Agro Zoning Models with high-resolution climate and land data.
3. Improve the BLUM model by integrating climate and land use data to assess economic and spatial impacts.
4. Improve data collection, verification, and accessibility to support better climate and land modeling.

Conclusion

• Climate change poses a significant threat to Brazilian agriculture, particularly to major food and export crops.
• Current models are inadequate for regional and local projections due to data limitations and model biases.
• A more integrated and climate-sensitive approach is needed to guide policy and investment decisions for the next several decades.
• The emergence of new markets (e.g., functional foods, ecosystem services) offers economic opportunities for smallholder farmers to adapt and thrive.