The following post is from Will Wieder, whose new paper on adding microbial physiology to Earth system models appears this week in Nature Climate Change.
As a kid my dad told me that every business was a dirt business.
This provided great motivation to work hard in school and encouraged me to consider an academic career. Who wants to go into a dirt business? But it turns out he could have been talking about what Earth’s climate system may look like for generations to come.
Soils store carbon. Lots of carbon. Far more than all of the plants on Earth and the entire atmosphere, combined. So what that huge soil carbon pool might do matters a lot to projections of what our climate may look like in the future.
My decision to go to graduate school could be boiled down to another attempt to avoid going into the dirt business. I ended up spending months in amazing forests in Costa Rica (like this) bringing red tropical dirt back to Boulder, Colorado. Great gig. Still a dirt business.
A cleaner option presented itself when I ended up in a postdoctoral position at the National Center for Atmospheric Research (NCAR). Not much dirt in the atmosphere, and little need to travel to distant lands. I traded the dirt on my hands for a keyboard, a monitor, and a wholly new challenge: trying to model the world.
NCAR builds and maintains an Earth system model that is used to ask a variety of scientific and societally relevant questions; among them, to make projections about what the world’s climate may look like a century from now.
Predicting the future is a daunting task, and one that requires we attempt to represent a host of processes that make our planet uniquely Earth. From wind and waves to clouds and trees, there is a lot of physics, chemistry, and biology that goes into computer simulations of our world — past, present, and future.
As a result, many processes are modeled in general terms, with an implicit representation of the complexity inherent in any natural system. This general representation of complex processes allows us to do a pretty good job making a computer model of a planet that looks like Earth, as we know it.
The challenge, however, is that we’re trying to project Earth as we don’t know it. Over the past decade several studies (like this, this and this) highlight that the one of greatest areas of uncertainty in our computer models comes from the response of soil systems to projected environmental change. In particular, there’s a growing chorus (from here, here, and here) calling for models that explicitly represent microbial activity.
And so I discovered that even climate modeling would throw me back into the dirt business.
As I learned from childhood through graduate studies, soils are amazingly complex, diverse systems – they are a fascinating business. A spoonful of soil from your garden has as many microbes living in it as there are people on Earth. Due to this complexity, many soil processes are simulated implicitly in Earth system models.
This means models need to explicitly consider the billions of bacteria and fungi living in a spoonful of soil because these are the organisms chewing on soil carbon. These are the organisms we generally cannot see, but that can either help store carbon in soils or send it into the atmosphere where it contributes to climate change. And we need to start thinking about their activity, globally.
This is no small task. It presents a huge challenge to soil science and Earth system modeling communities to think about what soils do from microbial to global scales. In a paper recently published in Nature Climate Change, we present a framework for how we can begin bridging these scales. We show that explicit representation of microbial activity is possible at global scales. And we highlight how doing so radically changes predictions about soil carbon responses to environmental change.
So what comes next? We test the model out some more, and compare it with observational data from the real world. We learn what the new model CAN’T do very well, and try to improve it. We try to bring modeling tools into alignment with our theoretical and observationally based understanding of soil systems.
And I finally admit that my dad was right.