BOGOR, Indonesia (18 July, 2011)_High income households are responsible for 30 percent more deforestation than low income households, according to preliminary results from the Poverty and Environment Network’s (PEN) global study, suggesting that it is wealth, not poverty that is driving higher rates of land clearing.
The PEN study found that though each household clears an average of 1.3 hectares of forest annually, there is a strong tendency of higher forest clearing in the richer areas. Deforestation rates were found to be considerably larger in Latin America, which boasts some of the richest households surveyed.
Over the past eight years the study has gathered and analyzed data from over 8000 rural households. Insight into the decision-making process behind forest management will add to the extensive forest modeling and mapping research currently being conducted by CIFOR and its partners.
Ronnie Babigumira, a CIFOR Research Fellow, spent the best part of two years creating and sorting the database that makes up the PEN study. Here he describes the scale of the survey and comments on its specific findings on deforestation.
What is your role in the PEN project?
I came in to work on a data entry tool. I quickly put together a database, which we shared with the partners, and then began to enter the data. With time the datasets that were prepared, came back and we began to go through them. So that began an iterative process. Our partners send data, I check and produce reports to them and send them back and we keep going back and forth.
What is the scale of the data you are dealing with?
It is 8000 households, about 600 columns in each dataset. We have a count of 10 million data cells. Now of course, some of that is repetitive, but it is the process. But what remained is a commitment that each of these datasets would come into the public space in a state that was usable, checked and we would feel reasonably confident that the data sets were in a good place.
At the PEN conference you presented the findings on deforestation. What were they?
There has been a lot of work on deforestation, a lot of modeling. Most of it, recently using LANSAT and GIS maps, which you then link with socioeconomic data. The criticism of that approach is that you are not able to work directly with the so-called culprit’s or the change agents – the households that are at the forefront of the deforestation. So what this dataset gives us an opportunity to do is look at the land use decision making from the household perspective and understand what these households have in terms of resources.
We are trying to look at the questions; is deforestation at the household level driven by poverty or is it a wealth story? Are the poor extensifying, are they extending into the forest because they can’t intensify. Are they landless? Or is it that the wealthier households have access to resources so are the ones able to do that?
The preliminary results are not conclusive. We do not see the poverty story. At least it does not come out very strongly, because for example, we find that the wealthiest 20% were clearing 30% more than the poorest 20%. Again everything is relative, because these are poor communities. But we have an opportunity to follow up on all the great and big amounts of literature on deforestation, but bring 8000 plus households with us and see if that can inform the debate and move the conversation forward.