Village Level REDD Accounting and Benefit Sharing Systems
REDD in Tanzania REDD in Tanzania should promote sustainable rural development, climate mitigation and adaptation To work, REDD in Tanzania must incentivize village governments to manage their forests Small scale agriculture and charcoal production are primary drivers of deforestation Majority of forests at risk are in open access areas of village land Villages will not agree to put all their forests under management without strong incentives
Village Incentives: What's Needed? Nested Village Accounting Wall to wall mapping Village boundaries Self-monitoring carbon stocks with third party verifying Marketing arrangements that allow communities to get highest price possible Efficient and fair village level benefit sharing mechanisms
Carbon Stock Assessment Classify Landsat data for project start year based on ground data and high resolution imagery. 15 initial carbon plots conducted by experts and communities in each major forest class and analyzed for consistency in terms of stocks. Forest classes are combined based on carbon stocks Found that forests group with woodlands due to historical selective logging in forest Scrub, regeneration, and degraded forests also group together
Carbon Plot Methodology Using NAFORMA methodology that relies on 30 meter plots. Using general coastal woodland dbh based allometric equation developed from Kitulangalo Forest Reserve. Using root to shoot ratio for tropical dry forests from IPCC Only looking at tree biomass... all other stocks ignored at this point.
Village level carbon stocks Project plans to both monitor project and village level carbon stock changes. Estimated that 50 plots per village will give initial 15% accuracy at 95% confidence for village level stocks. Plots will be revisited every two to three years by trained community members. Project staff randomly checks 10% of plots (initial results very good). Costs are significantly less than value of carbon stock increases in areas of avoided deforestation.
Project level carbon stocks Random selection of village plots based on villages proportion of particular forest class for project area. Initial results suggest less than 10% error at 95% confidence.
Project level deforestation baseline Deforestation detected using iteratively reweighted multivariate alteration detection comparing May 2001 Landsat to Landsat May 2002, 2004, 2006, 2008 and PALSAR 2008 to PALSAR 2010. Gross loss is 2.06% per year
Nested Accounting Options Carbon Stocks Only Avoided Emissions Only Creates equal, but very weak incentive for REDD Creates stronger incentive for REDD, but also requires complicated leakage accounting Stock and Flow Accounting All credits generated against baselines, but fixed % redistributed to actors based on carbon stocks. If actor exceeds baseline, their stock credits are reduced by value of excess emissions
National Accounting and Markets Need for national accounting does not justify nationalizing carbon tenure Forcing all villages to sell to one national trust fund will: Limit options and add risk of failure Reduce value by eliminating distinctions for additional social and biodiversity benefits The national trust fund should exist, but have to compete with other carbon buyers
Ruhoma Example Deforestation detected using iteratively reweighted multivariate alteration detection comparing May 2001 Landsat forest areas to Landsat May 2002, 2004, 2006, 2008 and comparing PALSAR 2008 to PALSAR 2010. Historic Gross Deforestation Rate is 1.17% per year
Ruhoma Example Value Item Average Carbon Stocks (t/ha) 43.28 Average Post Deforestation Stocks (t/ha) 14.67 Net Emissions from Deforestation (t/ha/co2 eq) 104.9 Total Forest Area (ha) 2830 Forest Area Protected (ha) Local Average Deforestation Rate per Year 2487 (88%) 1.17% Maximum Avoided Emissions (t CO2 eq) 3056.47 Avoided Emissions Less Leakage (t CO2 eq) 2685.48 Value at $5 per t CO2 eq $13,427.39 Value in TSH (1570 TSH/USD) 21,081,007 Per Capita Value TSH 36097.62
Ruhoma Example Benefit sharing steps: 1) Hold assembly meeting 2) Approve resident lists 3) Present basis for payment and amount 4) Present, modify, and approve proposals for use of REDD funds 5) Conduct dividend payments 6) Implement projects
Why Dividend Payments? What villagers want! Touches everyone Transparent Creates a tax and service relationship Complements SACCOS alternative livelihoods
Why Individual Dividends? Easier to define individual than household Not all households are democratic More money will be spent on children by channelling their dividends to mothers More nutrition More education More health care
Concerns about dividends Dividends will be too small - it is a waste of money What is too small? Is a bag of rice or school uniform a waste of money? Village development projects are more important Communities will fund what they want and believe will actually happen How much does slash and burn agriculture contribute to building schools? The transactions costs will be too high Actually dividends are dirt cheap to implement
Scalable? Where can this system be applied? Anywhere communities earn revenue from communal resources e.g. REDD, wildlife, timber tourism, water catchments, etc. What is required? Helping villages design bylaws Helping villages stick to bylaws until they become part of the normal way of doing business (2 payment cycles?)
Under a Big Tree
Everybody Showed Up
How to spend revenue from communal natural resources?
Novel Idea: Let community members decide!
How to insure villagers decide MJUMITA has helped each REDD village to develop their own bylaws and recommended that: The village assembly have final say over use of REDD revenues All options for the use of REDD funds, including 100% dividends, should be considered Decisions should be made annually
Test Payments Made to reward participating communities that have: Completed land use planning Established village forest reserves Passed all management plans and bylaws Based on conservative estimate of potential village earnings given village efforts to date Avoided emissions only approach (Lindi) Stock and flow approach (Kilosa)