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Climate Smart Agriculture : Building Resilience to Climate Change.

Bibliographic Details
Main Author: Lipper, Leslie.
Other Authors: McCarthy, Nancy., Zilberman, David., Asfaw, Solomon., Branca, Giacomo.
Format: eBook
Language:English
Published: Cham : Springer International Publishing AG, 2017.
Edition:1st ed.
Series:Natural Resource Management and Policy Series
Subjects:
Electronic books.
Online Access:Click to View
Table of Contents:
  • Intro
  • Foreword
  • Acknowledgments
  • Contents
  • Contributors
  • Part I: Overview and Conceptual Framework
  • Introduction and Overview
  • 1 Overview of the Book
  • 1.1 Part I. Conceptual Chapters
  • 1.2 Part II. Country Case Studies
  • 1.2.1 Vulnerability Measurement and Assessment
  • 1.2.2 Policy Response to Improving Adaptation and Adaptive Capacity
  • 1.2.3 System Level Response to Improving Adaptation and Adaptive Capacity
  • 1.2.4 Farm Level Response to Improving Adaptation and Adaptive Capacity
  • 1.3 Part III. Policy Synthesis and Conclusion
  • A Short History of the Evolution of the Climate Smart Agriculture Approach and Its Links to Climate Change and Sustainable Agriculture Debates
  • 1 Introduction
  • 1.1 The Evolution of Climate Change Policy
  • 2 Overview of CSA
  • 3 Key Features and Evolution of the CSA Concept
  • 4 CSA Controversies in the Broader Policy Context
  • 4.1 The Role of Mitigation and Carbon Finance in CSA
  • 5 CSA and Sustainable Agriculture
  • 6 Conclusion
  • References
  • Economics of Climate Smart Agriculture: An Overview
  • 1 Introduction
  • 2 CSA: The Objectives of the Social Planner
  • 3 The Constraints Facing the Social Planner
  • 4 The Social Planner's Choice Set
  • 5 Towards a Socially Optimal Solution: Expected Features of Model Outcomes
  • 6 Concluding Comments
  • References
  • Innovation in Response to Climate Change
  • 1 Introduction
  • 2 The Impact of Climate Change on Agriculture and the Implications
  • 2.1 Rising Temperatures and Migrating Weather
  • 2.2 Rising Sea Levels
  • 2.3 Increased Snowmelt and Timing of Irrigation
  • 2.4 Increased Probability of Extreme Events
  • 2.5 Discussion
  • 3 Innovations for Climate Smart Agriculture
  • 3.1 Technological Innovations
  • 3.1.1 Micro, Farm-Level Approaches
  • 3.1.2 Farm System Approaches
  • 3.2 Managerial Innovations
  • 3.2.1 Micro, Farm-Level Approaches.
  • 3.2.2 Farm System Approaches
  • 3.3 Institutional Innovations
  • 3.3.1 Innovations as Part of CSA Programs
  • 3.3.2 Institutions for Enhancing Various Adaptation Strategies
  • 4 Overcoming Barriers to Innovation in the Era of Climate Change
  • 4.1 Research and Refinement
  • 4.2 Commercialization/Adoption
  • 4.3 Discussion
  • 5 Conclusion
  • References
  • Part II: Case Studies: Vulnerability Measurements and Assessment
  • Use of Satellite Information on Wetness and Temperature for Crop Yield Prediction and River Resource Planning
  • 1 Introduction
  • 2 Methodology
  • 3 Application
  • 3.1 Monitoring Crop Yield
  • 3.2 Monitoring River Flow
  • 3.3 River Basin Management: The Case of the Mekong
  • 3.3.1 Description of the Model
  • 3.3.2 Applying the BWI to the Mekong Economic Model
  • 3.3.3 Results of the Economic Model
  • 4 Concluding Discussion
  • References
  • Early Warning Techniques for Local Climate Resilience: Smallholder Rice in Lao PDR
  • 1 Introduction
  • 2 Background
  • 2.1 Overview of Climate Conditions
  • 2.2 Extreme Events
  • 2.3 Rice Production
  • 2.3.1 Production Systems
  • 2.3.2 Irrigation
  • 2.4 The Physiological Relationship Between Rice and Weather Inputs
  • 2.4.1 The Role of Water
  • 2.4.2 The Role of Temperature
  • 3 Analysis I: Estimating the Relationship Between Rice and Climate Change
  • 3.1 Methods
  • 3.1.1 Average Weather Models
  • Equation 1: Panel Model of Average Weather Effects
  • Equation 2: Panel Model of Average Weather Effects
  • 3.1.2 Modeling Extreme Events
  • Equation 3: Panel Model of Extreme Event Effects
  • 3.2 Data
  • 3.2.1 Rice Yields
  • 3.2.2 Weather Conditions
  • 3.2.3 Extreme Events
  • 3.2.4 Data Limitations
  • 3.3 Results
  • 3.3.1 Evaluating the Model
  • 4 Analysis II: Projecting Future Rice Production Under Climate Change
  • 4.1 Climate Projections
  • 4.1.1 Selecting GCM Models
  • 4.1.2 Downscaling Methods.
  • 4.1.3 Climate Projections for Lao PDR
  • 4.2 Yield Projections
  • 4.2.1 Methods
  • 4.2.2 Results
  • 5 Summary and Outlook
  • 6 Conclusions and Extensions
  • Appendix - Rice Yield Regression Model Results (Figs. 6, 7, 8, and 9)
  • References
  • Farmers' Perceptions of and Adaptations to Climate Change in Southeast Asia: The Case Study from Thailand and Vietnam
  • 1 Introduction
  • 2 Theoretical Background
  • 3 Study Regions and Data
  • 4 Empirical Strategy
  • 5 Descriptive Results
  • 6 Results of Econometric Analysis
  • 7 Summary and Conclusions
  • References
  • U.S. Maize Yield Growth and Countervailing Climate Change Impacts
  • 1 Introduction
  • 2 Data Sources and Summary Statistics
  • 3 Crop Yield Model and Climate Change Impacts
  • 4 Results and Discussion
  • 4.1 Model Results and Warming Impacts
  • 4.2 Warming Impacts Against Technological Progress
  • 5 Conclusion
  • References
  • Understanding Tradeoffs in the Context of Farm-Scale Impacts: An Application of Decision-Support Tools for Assessing Climate Smart Agriculture
  • 1 Introduction
  • 2 AgBiz Logic as a Decision Support Tool for Addressing CSA
  • 3 Addressing the Farm-Scale Tradeoffs Associated with Changes in Climate
  • 3.1 Initial Setup and Baseline Scenario
  • 3.2 Exploring Climate Change Impacts and Investments in Alternative Cropping Systems
  • 3.3 Profitability of Implementing Investment Strategies
  • 3.4 Assessing Climate Change Implications for Agricultural Leases
  • 4 Assessing Environmental Impacts
  • 5 Toward Landscape-Scale Tradeoff Analysis: Linking to the TOA-MD Platform
  • 6 Data Requirements for the TOA-MD Model and How It Links to Farm-Scale Decision Support Tools
  • 7 Conclusions
  • Appendix A: How AgBiz Logic Works and Its Web-Based Presence
  • References
  • Part III: Case Studies: Policy Response to Improving Adaptation and Adaptive Capacity.
  • Can Insurance Help Manage Climate Risk and Food Insecurity? Evidence from the Pastoral Regions of East Africa
  • 1 The Logic of Insurance as a Device to Mitigate the Impacts of Climate Change on Food Insecurity
  • 1.1 Theoretical Model of the Ex Post and Ex Ante Impacts of Insurance on Poverty
  • 1.2 Analysis of Climate Change Scenarios
  • 2 Index Insurance as a Solution: Livestock Insurance in the Pastoral Regions of East Africa
  • 2.1 Designing the IBLI Index Insurance Contract
  • 2.2 Impacts of the IBLI Contract on Ex Post Coping and Ex Ante Investment
  • 3 Limitations to Index Insurance as a Solution for Climate Change and Food Insecurity
  • 3.1 The Quality Challenge to Index Insurance
  • 3.2 IBLI's Quality Effort and Remaining Weaknesses
  • 3.3 The Way Forward
  • 4 Conclusions
  • References
  • Can Cash Transfer Programmes Promote Household Resilience? Cross-Country Evidence from Sub-Saharan Africa
  • 1 Introduction
  • 2 Overview of selected SCT Programmes in SSA
  • 3 Role of Cash Transfer for Building Resilience: Review of Selected Evidence
  • 4 Methodology
  • 4.1 Programme Evaluation Design and Data
  • 4.2 Analytical Methods
  • 5 Results and Discussion
  • 5.1 Can Cash Transfer Promote Ex-Post Risk Management?
  • 5.2 Can Cash Transfer Contribute to Managing Climate Risk?
  • 5.3 Potential of Cash Transfer to Promote Ex-Ante Risk Management
  • 5.3.1 Impacts on Accumulation of Productive Assets
  • 5.3.2 Impacts on Crop Production and Productivity
  • 5.3.3 Impacts on Non-farm Enterprises
  • 5.4 Can Cash Transfer Promote Resilience by Enhancing Food Security?
  • 5.4.1 Impact on Food Security
  • 5.4.2 Impact on Consumption Expenditure
  • 5.4.3 Impact on Dietary Diversity
  • 6 Conclusions and Implications
  • References
  • Input Subsidy Programs and Climate Smart Agriculture: Current Realities and Future Potential
  • 1 Introduction.
  • 2 Defining Climate Smart Agriculture
  • 3 ISP Implementation Modalities and CSA in Africa
  • 4 Can ISPs Promote Household-Level Ex Ante Risk Management?
  • 4.1 Review of Evidence to Date
  • 4.2 Looking Forward: Can ISPs Contribute to Climate Smart Farm Management Practices?
  • 4.3 How Confident Are We That We Know Which Farming Practices Contribute to CSA and SI?
  • 5 Can ISPs Promote System-Wide Ex Ante Risk Management?
  • 5.1 Potential Opportunities
  • 5.2 Potential Challenges
  • 6 Can ISPs Promote Household-Level Ex Post Coping Mechanisms?
  • 7 Can ISPs Promote System-Wide Ex Post Coping Potential?
  • 8 Summary and Implications for ISPs
  • 8.1 Unresolved Issues for Future Research
  • 8.2 Concluding Remarks
  • Appendix 1: Estimating the Contribution of Increased Fertilizer Use to Greenhouse Gas Emissions
  • References
  • Part IV: Case Studies: System Level Response to Improving Adaptation and Adaptive Capacity
  • Robust Decision Making for a Climate-Resilient Development of the Agricultural Sector in Nigeria
  • 1 Introduction
  • 2 Methodological Approach
  • 2.1 Climate Projections and Their Uncertainty
  • 2.2 Crop Modeling: Impacts on Yields
  • 2.3 Hydrological Modeling: Impacts on Water Availability
  • 2.4 Macro-economic Analysis
  • 2.5 Adaptation Strategies in Agriculture
  • 2.6 Costs of Adaptation Options
  • 2.7 RDMA for Irrigation Infrastructures
  • 3 Results and Discussion
  • 3.1 Climate Projections and Their Uncertainty
  • 3.2 Impact Analysis on Crop Yields
  • 3.3 Water Availability Impact Analysis
  • 3.4 Macro-economic Impacts
  • 3.5 Adaptation Options in the Agriculture and Water Sectors
  • 3.5.1 Adaptation Through Sustainable Land Management Practices
  • 3.5.2 Costs of Adaptation
  • 3.5.3 Robust Decision Making Approach for Irrigation Infrastructure
  • 4 Conclusions and Recommendations
  • References.
  • Using AgMIP Regional Integrated Assessment Methods to Evaluate Vulnerability, Resilience and Adaptive Capacity for Climate Smart Agricultural Systems.

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