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CASE STUDY DETAIL: Purepecha Region, Mexico

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Coverage

Purepecha Region, Mexico

Project time

2005 2009

Objectives/scope

1) Identify single localities that face concomitant conditions of high fuelwood consumption and insufficient fuelwood resources, within a selected fuelwood hot spot from the national analysis, and 2) Quantify the amount of fuelwood extracted on a non-renewable basis.

Institutional settings

UNAM - FAO

Scale/resolution

1:50,000 / 100 m (1 ha/pixel)

Demand features

Input variables: 1) Fuelwood consumption, 2) Number of FW users, 3) Density of FW users, 4) Percentage of houses that use FW (i.e. saturation), 5) Percentage of people belonging to an ethnic group -as a FW consumption resilience indicator-

Supply features

Input variables: 1) Fuelwood production by land cover class: Landsat images for 1986 and 2000 (30 m resolution) were classified into two 14 class land cover maps. Productivity estimates by land cover class were calculated from field data on aboveground biomass and age of stands. This field survey was used also for map validation. 2) As with the Mexico national study, land cover changes between years 1986 and 2000, which affects fuelwood production in the mid term where incorporated within the multi-criteria analysis.

Integration features

Balance as the difference between FW supply and demand

Woodshed/bio-shed analysis

Not implemented

Integration with other aspects

Input variable: 1) Balance as the difference between FW supply and demand. A Geographic Multicriteria Analysis (GMCA) was applied to integrate weak-correlated supply and demand variables into a single adimensional index, which highlighted critical areas of fuelwood hot spots.

Findings/conclusions

Twenty localities, out of a total of 90, were identified as critical in terms of six indicators related to fuelwood use and availability of fuelwood resources. Fuelwood supply/demand balances varied among localities from -16.2 +/- 2.5 Gg to 4.4 +/- 2.6 Gg y-1, while fractions of non-renewable fuelwood varied from 0 to 96%. These results support the idea that fuelwood balances and non-renewable fuelwood fractions (mandatory inputs for Clean Development Mechanism (CDM) biomass projects) must be calculated on a locality by locality basis if gross under or over-estimations want to be avoided in the final carbon accounting.

Publications

Ghilardi A, Guerrero G, Masera O. 2009. A GIS-based methodology for highlighting fuelwood supply/demand imbalances at the local level: A case study for Central Mexico. Biomass and Bioenergy 33 (2009) 957-972.