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Total Economics of Sustainable Land Management

Total Economics of Sustainable Land Management. Jonathan Davies Global Drylands Programme. The Silent Menace. Twelve million hectares of land where 20 million tons of grain could have been grown disappear every year due to pressure from human activities (UNCCD, 2011). .

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Total Economics of Sustainable Land Management

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  1. Total Economics of Sustainable Land Management Jonathan Davies Global Drylands Programme

  2. The Silent Menace • Twelve million hectares of land where 20 million tons of grain could have been grown disappear every year due to pressure from human activities (UNCCD, 2011). • Rising land value leading to speculation and accumulation of land. • Following the 2008 food crisis between 15 and 20 million hectares of farmland in developing countries had changed hands.

  3. 50 million people may be displaced within the next 10 years as a result of desertification. • Land degradation and drought generate global losses of at least 42 billion US dollars per year.

  4. Economic valuation as a decision-making tool

  5. What is the real cost of land degradation? Reduced water quality Water deficit Loss of biodiversity Flood Climate Change Lower food production Conflict Drought Health problems

  6. What scale matters?

  7. E-SLM: rain-fed agroforestryin Sudan • Direct values: Improved soil fertility, improved soil moisture, mulching • Indirect values: reduced run-off, higher water tables, reduced dust storms • Use “choice experiment” to examine willingness to pay for access to safe water • Will people invest the effort in agroforestry? • What information do they need to understand that it is worth while?

  8. Communal rangeland rehabilitation in Jordan • Improvements in livestock productivity • Conservation of biodiversity: marketable and non-marketable values • Improved water infiltration: • Restored hydrological cycle • Higher water table • Revival of riparian vegetation • Longer seasonal water flows • Reduced flash flooding • Lower siltation of dams

  9. Restoring communal forests in Mali • Reduced travel for fuel wood • Non timber forest products with direct marketing value • Biodiversity restoration • Improvements in hydrological cycles

  10. Modelling scenarios using remote sensing • Develop land use / land cover maps • Identify river basins • Local level validation of maps • Model outcomes of land use change (change in vegetation, change in water flows) • Choice experiment – what is the value for example of better access to water? Of reduced risk exposure? Of improved water cycles? • How representative are the sites? Is the analysis applicable to a larger scale?

  11. Goal: data at the right level to make the right decisions • What looks best in a given location is not always best at the national scale • Decide on land use objectives: best returns on investment; gross productivity; reduced risk etc. • Gross productivity is not only food – you have to consider everything of importance – if you don’t valuate it, you are likely to lose it

  12. Thank you Jonathan.davies@iucn.org

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