ILUC and the Renewable Fuel Standard: hard data appears for the first time

After six years of debate — finally a database appears on actual indirect land use change.

The Partners? Including Google, UNEP, Imazon, the Center for Global Development, the University of Maryland, OSFAC, the Jane Goodall Institute

The Funders? Including USAID, the Norwegian Ministry of Climate and Environment and GEF, UKAID, DANIDA, SIDA, the Bobolink Foundation, the Netherlands Ministry of Foreign Affairs, among others.

The Collaborators? Including FAO, Greenpeace, NASA and the Rainforest Foundation UK.

What’s the verdict?

For the past five years, a theory has been going around on the impact of biofuels that goes, essentially, like this: Increases in biofuels demand will not only cause direct land use change (the conversion of, say, wheat acres to corn to produce ethanol), it will produce indirect land use change.

Namely, that an increase in biofuels demand will increase crop prices, and incentivize the conversion of, to use an oft-cited example, pastureland in Brazil into crop land. To replace that pastureland, forests will be converted to pasture, thereby releasing a whole bunch of carbon into the atmosphere. Thereby offsetting some (or all) of the direct benefit in using a renewable fuel to reduce carbon emissions

Since ILUC theory first appeared as a critique of biofuels, both the proponents of the theory and opponents have been hampered by a lack of data.

Specifically, the underlying global database of agricultural usage — and hence forest loss — has not been updated since 2002, well before energy policy shifted in the US to encourage biofuels.

It may sound absurd, but in order to calculate the forest loss impact caused by the Renewable Fuel Standard (RFS2), a database of land use has to be employed that was last updated eight years before RFS2 was first implemented in 2010. If you think that sounds like an awfully sketchy data set for such an important task, you’ll find both friends and fierce enemies in academia.

But this week — some hard data has arrived at last.

Namely, the Global Forest Watch.

As GFW self-describes, it is “a dynamic online forest monitoring and alert system that empowers people everywhere to better manage forests. For the first time, Global Forest Watch unites satellite technology, open data, and crowdsourcing to guarantee access to timely and reliable information about forests. GFW is free and follows an open data approach in putting decision-relevant information in the hands of governments, companies, NGOs, and the public. GFW is supported by a diverse partnership of organizations that contribute data, technical capabilities, funding, and expertise. The partnership is convened by the World Resources Institute.” You can check out the full GFW site here.

It’s goal? Hard data.

What we found interesting is this. ILUC predicts significant deforestation in the Amazon as a result of RFS2.

So let’s look at 2000-2007 – the years before RFS2, to get a baseline. Pink represents forest loss. Blue represents forest gain.

Right away you see all the reasons people get agitated about the Amazon. Lot of pink.

So, let’s go to 2007-2013.

What do we see. A whole lot of blue – meaning forest gain, not forest loss. Not much pink at all. You just can’t see the effects predicted by ILUC.

Which suggests that indirect land use change theory, as formulated, may be nullified by the observational data. Or, that the Global Forest Watch data is fundamentally flawed. We’ll see how the battle over that plays out.