1. Functional Value of Biodiversity Project Overview September 2002 The Bank - Netherlands Partnership Program

2. Outline Goals Results to date Phase II plans Current and expected impacts

3. Motivation Can biodiversity conservation ‘pay for itself’ by providing functional values? – such as flood prevention, climate mitigation, forest products, etc. If so, can poor people benefit: –As providers of these functional values? –As beneficiaries? Hydrological services appear to be potentially among the most ‘saleable’ -- but most poorly understood -- forest values.

4. Assertions Upland-dwelling poor people are the agents of deforestation that results in upland biodiversity loss and downslope flooding, sedimentation, drought, landslides. If downslope populations pay upland dwellers to alter behavior, the result can be higher economic output, poverty reduction, and biodiversity conservation. Is this assertion valid? Where? To what extent?

5. General Objective Provide a sound basis for identifying and designing policies and projects that use forest conservation as a tool for maintaining the level, quality, and regularity of water flows. “Conventional wisdom” can result in both missed opportunities and inappropriate policies

6. Goals for mainstreaming: influence… …Bankwide priority-setting, agenda-setting: Where are forest conservation/hydrology connections important? …CAS, PRSP for selected countries: What kinds of connections are important? For what subregions? Is there a poverty link? …Environmental services project design

7. At what scale does land use change affect hydrological functions? Watershed < 200km 2 Spatial arrangement of trees and crops locally affects: Erosion Sedimentation Flooding Landslides Habitat connectivity Basins > 5,000km 2 Deforestation Habitat loss Increased water yield controversial Lowland flooding Sedimentation Southern Guatemala 0 20 40 km Vertical Exaggeration x5 Agriculture Forest Water Urban Shrub Bare rock Guatemala City

8. Predicting local impacts of land use change based on topography 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 0 0.010.11 tan(Slope) log (Topographic index) Saturation Overland Flow, no Erosion Erosion No Surface Runoff Landslide Risk

9. Global significance of forest- hydrology-biodiversity interface Where is the interface* between agriculture and forested slopes? – the place where deforestation might affect water flows. Who lives there, worldwide? 20 million people? 100 million? 200 million? Where is the interface crucial to biodiversity?

10. * Restrictive definition 165 million in developing countries at the forested-slope interface *

11. * Restrictive definition

12. Buffer zones falling within areas of High Biological Distinctiveness (km2) -50,000100,000150,000200,000 Tanzania Guatemala Zaire Ethiopia Ecuador Madagascar Honduras Nepal Bolivia Venezuela Thailand Papua New Guinea Morocco Algeria Brazil Myanmar Malaysia Philippines India Peru Colombia Mexico Indonesia Area of high BDI Non-BDI Interface zones: Overwhelmingly In areas of high Biological Distinctiveness (based on WWF Global 200) Note: data missing for China

13. Extent of basins including tropical forests Source: Hydro1k – USGS EDC 2001; Terrain type: A. Nelson – World Bank (2001). Note: The shading differentiates between the upper and lower catchments of the basins. Dividing line between humid and subhumid tropics Focus area ASB site locations

14. Regional studies

15. Central America: combine data on forests and slopes…

16. ..with info on population…

17. …poverty…

18. ...and watersheds

19. Guatemala: critical watersheds where the ‘interface’ > 20% of area

20. Guatemala: poor people/km2 by watershed

21. Guatemala: poverty rate by watershed

22. Guatemala: poverty rate with critical watersheds highlighted

23. Lambert Equal Area Projection Centered at 85 W and 13 N Nicaragua: few ‘critical’ watersheds (at this scale and definition)

24. Lambert Equal Area Projection Centered at 85 W and 13 N Panama: few ‘critical’ watersheds (at this scale and definition)

25. Laos: High-poverty provinces have the most rugged terrain. 0 2 4 6 8 10 12 14 16 18 20 02468101214161820 Poverty rank (1= poorest) Hilliness rank (1=highest proportion)

26. Impacts to date: inputs to WDR 2003 Millennium Ecosystem assessment RUPES – IFAD-funded project on environment services payments for upland poor of Asia World Bank Poverty-environment study for SE Asia and Laos PRSP process

27. Expected impacts by project end Inputs into PRSP’s and CAS’s Inputs into forest policy implementation Inputs into design of possible environmental services projects Analytic tools and policy conclusions: resources for future policy and project design

28. Phase II plans Detailed hydrological modeling at three scales: –Global –Regional (Central America, SE Asia) –Watershed (Thailand, Indonesia; possible Central America) Providing info on hydrological ‘hotspots’ and affected areas and populations Link to micro-level understanding of land use options