1. Forest dependency in lowland Bolivia
UNIVERSITY COPENHAGEN
Forest dependency in lowland Bolivia
Patricia Uberhuaga, Carsten Smith Olsen & Finn Helles
Centre for Forest, Landscape and Planning
Faculty of Life Sciences, University of Copenhagen
This 10 min presentation follow as: objective, context, main findings and conclusions

2. Objectives
To determine the importance of forest income at the rural household level in lowlands Bolivia.
To analyse and explain the variation of economic dependency of forest resources among households
This research is focussed in Bolivia in particular and the lowlands in general where people’s dependence on forest is very high – and it is home of the most indigenous territories with new land titles. Findings will contribute in addressing the forest- poverty interrelationship.
The objective and questions are based on the theoritcal foundation on poverty and forest interdependence and are articulated from the literature.

3. Context – study area
Tropical Forest (closed canopy, similar semi-valuable timber species) under 200 masl
Population: indigenous groups, & in-migrants from Bolivian highlands
Small & scattered villages.
Six villages (formal FMP, low coca production, willingness to participate, located relatively close to each other)
Households n=118
Avg. HH size 5.5
The study was undertaken in the Tropics of Cochabamba, a region of 39,560 km² (thirty nine thousand, five hundred sixty square Km) area making up 58% of this Department (covering five municipalities) in the Eastern Bolivian lowlands.
This is a rainy tropical forest under 200 meter above sea level. This is an area with the highest precipitation in LA, and normally the climate is humid and hot. The study area has aprox (one hundred 50 thousand) inhabitants living in different small and scattered communities, 60% is from the Bolivian highlands (in-migrants) and 40% are indigenous (native) (mainly Yuracares, Yuquis, Trinitarios)
There were selected six villages at the centre of this region based on basis on forest products, approved formal forest management plans (one was being elaborated, relative low coca production is relatively low (meaning that people are more open to questions on income), the communities were willing to participate in the research, and they were located relatively close to each other but with different degrees of market accessibility. The forests of the three communities are similar in composition and structure: closed canopy natural high forest characterised by timber species.

4. Total income sources Avg. income Cash Subsistence US$946 $753 $193
The table shows the contribution of the main income groups to annual HH income. Forest income accounts for 20% of total income. It was calculated based on the contribution of unprocessed, processed income and forest-wage income. Environmental income has a small overall contribution (2.3%) it includes medicinal plants, wild fruits and grassland and pasture, adding fish income (4) the non-forest environment income reaches to 6%. Agriculture production is the most important source of income. Much forest was converted into farmland to a large extent by in-migrants. Livestock is generally of little importance, even negative, composed by animal services (milk, meat, cheese, etc). From livestock was deducted ‘browse & wild grass’ used. Wage was disagregated into off-fam wages (for work on other farms) that represents 10% of the total income, and non-farm/forest wage that is also important with a share of almost 7%. Business, and otherincome plus non-farm/forest income represent cash income representing in total 20%, the same as forest income.
Avg. income
Cash
Subsistence
US$946
$753
$193

5. Relative Forest Income
Forest income is important to all groups (20%)
For the top group (24%) timber is the main source as cash
For the poorest group (19%) game meat, medicinal plants, tree leaves, wild animals are important as subsistence income
Fuelwood comes in second (11%)
Relative forest income is the share of average total forest income from total income. Forest income is important to all groups (20%) but mainly to the top group (24%) (timber). Fuelwood comes in second (11%) it importance decreases for the top group.

6. Income sources and seasonality
Q3 and Q4 represent timber harvesting (rainy season)
Q1 & Q2 present some relationship between agriculture and forest
Q3 agric. & forest income

7. Determinants of forest dependency
RFI / R=0.24
Explanatory Variables
Coefficients
p-value
HH head sex (1=female, 0=male)
0.802
Highest level of education
0.026*
HH size   #
0.666
HH head age, yrs
0.055
HH head age square, yrs
-2.36E-06
0.027*
Ethnic group of the household head
0.557
HH head born (1=local, 0=outside)
0.052
Cultivated land, ha
0.874
Forest under management plan, ha
0.158
HH staple crop cultivated, ha
0.116
HH skilled non-farm work, days
0.283
HH food self-sufficient (1=yes, 0=no)
0.014*
Type of Village (1=indigenous, 0=no)
0.807
Distance to market, km #
0.284
Determinant of forest income and forest dependency were analyzed by regression analysis. Two linear regression models were formulated; the first one to analyse the determinants of forest income AFI against HH characteristics as explanatory variables, and the second RFI against the same explanatory variables. We defined the expected signs based on literature review and knowledge of the context. The results for the determinants of forest income are presented in the models, HH size is negative correlated with forest income, so, higher HH size less forest income. HH head age square is negative correlated with forest income, decreasing extractive resources; cultivated land is positive correlated, more close to agricultural land more income forest, they are attached to the land and villages (they are in-migrants). For forest dependency there are not many significant variables hh head age.
'* significant at 1%, # non-expected sign

8. Conclusions
The most well off HHs have the highest absolute forest income
Overall HHs derive 20% of their income from forest and 6% from non-forest environment.
The forest dependency is highest for the top income group (timber), but lowest income group is only 5% points less
The poorest group depends a lot on subsistence income (unprocessed forest products), and rely on fuelwood & game meat
Important determinants of low forest dependency are inter alia high education level and high self-sufficiency in food production
Non forest environmental income what products slide 5 what kind of products ; relative forest income graph in determinants; relationship positive and negative ; increasing and decreasing the relationships; AFI and RFI separated conclusions

9. Acknowledgements Field assistance
Gilda Jauregui, Xavier Velázquez, Freddy Zubieta (CERES)
Freddy Cruz, Jankiel Sainz, Harry Soria, Sergio Miranda (CERES)
Regional partners
Funding sources
Advisors
Carsten S. Olsen (LIFE) / Rosario Leon (Bolivia)
Villages and local organizations
Cochabamba
SANREM Project