Low carbon development for Colombia

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Presentation made in a World Bank Brown bag seminar in Washington DC, April 19th 2012.

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  • New partnership model: CCAFS is not only a CGIAR program – it is actually a joint program between the CGIAR and the Earth Systems science partnership – the ESSP includes such organisations as the World Climate Research Program and Diversitas.
  • Reducir la información, pasar gráficos a otra diapositiva pues no se aprecianHay mucho texto. El cuadro no es funcional a una presentación, por el tamaño de tipografía y la naturaleza de la información. Sería preferible un gráfico de barras verticales con los principales cultivos.
  • Low carbon development for Colombia

    1. 1. From Cows to Coffee: evaluating low-carbon options in Colombia’s agricultural sector Andy Jarvis, Jeimar Tapasco, Myles Fisher, Emmanuel Zapata International Centre for Tropical Agriculture (CIAT)
    2. 2. CCAFS: the partnership! The largest global coalition of scientists working ondeveloping-country agriculture and climate change
    3. 3. CCAFS objectives 1. Identify and develop pro-poor adaptation and mitigation practices, technologies and policies for agriculture and food systems. 2. Support the inclusion of agricultural issues in climate change policies, and of climate issues in agricultural policies, at all levels.
    4. 4. The CCAFS Framework Adapting Agriculture to Climate Variability and Change Technologies, practices, partnerships and policies for: Improved 1. Adaptation to Progressive Climate Environmental Improved Change Health Rural 2. Adaptation through Managing Livelihoods Climate Risk Improved 3. Pro-poor Climate Change Mitigation Food Security 4. Integration for Decision Making • Linking Knowledge with Action • Assembling Data and Tools for Analysis and Planning • Refining Frameworks for Policy Analysis Enhanced adaptive capacity in agricultural, natural resource management, and food systems
    5. 5. The adaptation context for Colombia
    6. 6. Heavy reliance of agricultural GDP on perennial crops and livestock 3,500,000 Distribucion de cultivo Área (ha) 3,000,000 Distribucion de cultivo Pdn (Ton) 2,500,000 2,000,000 1,500,000 1,000,000 500,000 0
    7. 7. Government policies increasing agricultural land-area especially in perennials
    8. 8. …and increasing livestock production, but on less land
    9. 9. Cambio en Cambio en Cambio en Incertidumbre Cambio en meses Region Departamento Temperatura estacionalidad de entre modelos Precipitacion consecutivos media precipitacion (StDev prec) secosAmazonas Amazonas 12 2.9 1.4 0 135Amazonas Caqueta 138 2.7 -1.3 0 193Amazonas Guania 55 2.9 -3.2 0 271Amazonas Guaviare 72 2.8 -2.9 -1 209Amazonas Putumayo 117 2.6 0.6 0 170Andina Antioquia 18 2.1 1.3 0 129Andina Boyaca 50 2.7 -3.9 -1 144Andina Cundinamarca 152 2.6 -2.6 0 170Andina Huila 51 2.4 1.0 0 144Andina Norte de santander 73 2.8 -0.4 0 216Andina Santander 51 2.7 -2.4 0 158Andina Tolima 86 2.4 -3.1 0 148Caribe Atlantico -74 2.2 -2.9 2 135Caribe Bolivar 90 2.5 -1.8 0 242Caribe Cesar -119 2.6 -1.3 0 160Caribe Cordoba -11 2.3 -3.8 0 160Caribe Guajira -69 2.2 -1.8 0 86Caribe Magdalena -158 2.4 -1.8 0 153Caribe Sucre 10 2.4 -4.1 -1 207Eje Cafetero Caldas 252 2.4 -4.2 -1 174Eje Cafetero Quindio 153 2.3 -4.1 -1 145Eje Cafetero Risaralda 158 2.4 -3.5 -1 141Llanos Arauca -13 2.9 -6.4 -1 188Llanos Casanare 163 2.8 -5.7 -1 229Llanos Meta 10 2.7 -5.4 -1 180Llanos Vaupes 46 2.8 -1.4 0 192Llanos Vichada 59 2.6 -2.6 0 152Pacifico Choco -157 2.2 -1.2 0 148Sur Occidente Cauca 172 2.3 -1.6 0 168Sur Occidente Narino 155 2.2 -1.4 0 126Sur Occidente Valle del Cauca 275 2.3 -5.1 -1 166
    10. 10. A future coffee crisis?
    11. 11. Mountains as climate change gradients…. Tmedia Tmedia Tmedia Ppt total Ppt Rango anual anual anual anual an Altitudinal cambio actual futuro actual fut (ºC) 190-500 25.54 27.70 2.16 5891 501-1000 23.47 25.66 2.19 3490 1000-1500 21.29 23.50 2.21 2537 1500-2000 18.36 20.58 2.22 2519 2000-2500 15.60 17.82 2.22 2555 2500-3000 13.33 15.54 2.21 2471Temperatura media reduce por 0.51oC por cada 100m en lazona cafetero. Un cambio de 2.2oC equivale a una diferenciade 440m.
    12. 12. Suitability in Cauca• Significant changes to 2020, drastic changes to 2050• The Cauca case: reduced coffeee growing area and MECETA changes in geographic distribution. Some new opportunities.
    13. 13. Impactos en Colombia: cambio (%) en productividad a nivel Nacional Cambio adaptabilidad (%) 2050-A2 4 2 0 -2 -4 -6 -8 -10 -12 -14 Cambio adaptabilidad (%) 2050-A2 -16 -18
    14. 14. Cambios promedios por departamento Cambio promedio en adaptabilidad 15 10 Cambio promedio en adaptabilidad 5 0 -5 -10 -15
    15. 15. Dos casos diferentes: Bolivar vs. Cauca 30.00 20.00 10.00 0.00 -10.00 -20.00 Bolivar -30.00 Cauca -40.00 -50.00 -60.00
    16. 16. Crops threatening high mountain ecosystems, and water resources…
    17. 17. And a poverty/food security angle
    18. 18. The adaptation outlook• Perennial crops (66.4% ag GDP in 2007) seriously affected• Long lead times for adaptation – a coffee crop is a 20 year investment, palm, fruits and rubber is more• Likely exacerbation of equity as staple crops more sensitive than many annual cash crops• Clear geographic priorities in the Caribbean region
    19. 19. Evaluation of mitigationoptions in the Colombianagricultural sector
    20. 20. A stakeholder- and science- driven approach• Stakeholder workshop to identify medium-long list of mitigation measures – Industry, government, civil society participation• Quantification of costs and benefits of each measure – Modelling – Empirical evidence – Tools e.g. Cool Farm Tool• Prioritisation of measures based on a range of cost/benefit criteria• Stakeholder driven selection of mitigation portfolio for sector or sub-sector
    21. 21. An inevitable need to use models• Desire is to have a data-driven approach, but alone is simply not possible• Major data constraints – poor or non-existent empirical data• An approach of fitting the model to the problem (not the other way around)• Different models used to arrive at individual numbers on costs or benefits of each mitigation measure
    22. 22. Summary of interventions studies Potential $US/TonCO2 Intervention Hectares abatement Min Max (KTonCO2/ year) Increased efficiency of nitrogen fertilizer in rice 169,200 38 -267 145 sectorConversion of degraded 395,320 1,938 -188 -25pastures to fruit orchards Establishment of 521,839 11,538 -49 0.6 silvopastoral systems Pasture intensification 51,487 54 -103 -62
    23. 23. 1. Uso eficiente de fertilizantes (Arroz) Un uso más eficiente de fertilizantes permite llevar a cabo un mejor aprovechamiento del suelo y reducir las emisiones de GEI generadas por los fertilizantes nitrogenados• Medidas para uso eficiente de la fertilización en arroz – Micronivelación del terreno (Jamundí y Cúcuta) – Asistencia técnica especializada (Espinal, Guaranda, Nunchía, Valledupar, Villavicencio y Yopal). – Intervención: 169.200 ha
    24. 24. Resumen Municipio Departamento Area a intervenirCucuta Norte de Santander 16,900Espinal, Ibague, Ambalema,Campoalegre, Venadillo y Saldana Tolima 59,990Guaranda y Nechi Sucre 10,369Jamundi Valle 5,113Nunchia y Villanueva (Riego) Casanare 20,080Valledupar Cesar 3,035Villavicencio, Pto Lopez, Fte Oro yGranada Meta 36,771Yopal, Villanueva (secano) yAguazul Casanare 17,229
    25. 25. Sub-optimal nitrogen applications
    26. 26. IMPACTO EN EMISIONES
    27. 27. Private perspective: 100% investment and O&M areassumed for farmers
    28. 28. 2. Reconversion of pasturelands to fruit orchards La sustitución de pasturas degradadas por plantaciones de árboles frutales representa no solo una oportunidad económica para desarrollar nuevos mercados, sino además un potencial de mitigación de GEI• Se analizan tres especies de frutales – Aguacate (165.682 has) – Mango (193.638 has) – Cítricos*• Se buscan los nichos para estas especies con el fin de determinar el área potencial.• Intervención: 395.320 ha
    29. 29. Cultivo: Aguacate Superficie potencial (ha) Nivel de productividad respecto al promedio de la zona Departamento 85% 79% 75.5% 72% 70% TotalANTIOQUIA 3,355 3,183 11,269 11,269 23,055 52,131CALDAS - 1,548 7,828 10,925 2,839 23,140HUILA - 86 86 516 602 1,290QUINDIO 172 4,043 7,140 5,850 3,183 20,388RISARALDA 344 1,634 1,721 2,065 5,764TOLIMA 774 4,989 24,775 21,764 10,667 62,969 Total 4,301 14,193 52,732 52,045 42,411 165,682
    30. 30. Private perspective: 100% investment and O&M areassumed for farmers
    31. 31. 3. Improved pastures La actividad ganadera en pasturas degradadas resulta una reducción en la eficiencia de producción, pérdida de biodiversidad y aumento en la emisión de GEI. El mejoramiento de pasturas presenta una opción atractiva a nivel económico y ambiental.• Mejoramiento de pasturas en los departamentos: – Arauca (11.228 has) – Casanare (21.521 has) – Meta (18.738 has)• Intervención:51.487 hectáreas
    32. 32. Private perspective: 100% investment and O&M areassumed for farmers
    33. 33. 4. Silvopastoral systems (SSPi) Los sistemas silvopastoriles constituyen una opción atractiva para la reconversión de modelos de ganadería extensiva al aumentar la carga animal por hectárea, capturar carbono por medio de la plantación de árboles y un mejoramiento de la alimentación de animal reduciendo la emisión de metano.• Se plantea la reconversión a sistemas silvopastoriles en los departamentos: – Atlántico – Córdoba – Sucre – Antioquia: Bajo cauca, Nordeste, Urabá, Oriente• Intervención: 521.839 hectáreas
    34. 34. Agosto 15, 2008 Recuperación de corredores ribereños Piedemonte llanero 13 meses Octubre 22, 2008Estado inicial: Julio 17, 2007 15 meses
    35. 35. From a private perspective: 100% investment and O&M areassumed for farmers
    36. 36. AggregatedPriorities using MAC curves
    37. 37. Private perspective: 100% investment and O&M areassumed for farmers MAC curve for capture/reduction of CO2e emissions in some lines (fruit trees, rice and livestock) of the livestock sector in Colombia
    38. 38. Some challenges in the analysis
    39. 39. Mitigation of the sector, or per unit product? Emisiones CO2 proyectadas ganadería bovina 60,000 50,000 40,000GgCO2eq 30,000 20,000 10,000 - 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 AñoCardenas, 2011
    40. 40. MAC curve focuses on EFFICIENCY (US$/Ton CO2e) Between two options with the same I–C ___________________________ benefits, the option with less carbon is CO2e capture better BUT CAUTION ABOUT INTERPRETATION
    41. 41. Private perspective Publicperspective
    42. 42. Methodological considerations• Range of approaches for quantifying mitigation costs and benefits available• Estimations should be stakeholder driven, and not ignore social/cultural/economic barriers• Priorities based on efficiency of measures depend on the perspective of who is asking (e.g. government versus private)
    43. 43. Conclusions• Apparent large opportunities for win-win measures, but care needed about analysing barriers (e.g. cultural)• Co-benefit of adaptation not quantified, but significant and should be included (also to avoid mal-adaptation through mitigation incentives)• Entry point mitigation, or adaptation?
    44. 44. Email: a.jarvis@cgiar.orgInternet: http://dapa.ciat.cgiar.org

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