I’m an ecologist by training—I spent my undergrad years and summers running around on mountains and in fields, counting plants. Ecology was about being a naturalist, about recognizing species and understanding the subtleties of unique systems.

But the power in ecology is in extrapolating from the fine-scale to the broad, in looking at the spatial distribution of plants in particular plot of land, and understanding how that pattern might be propagated through regions, continents, or at a global scale.

Yiqi Luo, of the University of Oklahoma, talked this morning (B41D, Ecoystem Models, Data Assimilation, and Flux Networks:  Synthesis Efforts from Regional to Global Scales II) about the tremendous leaps forward ecology has made since we’ve entered the “data-rich” age. He reminded us that by developing “ecological forecasting” techniques that incorporate a) the overwhelming amount of real-time data from networks such as Oak Ridge National Lab’s FLUXNET, which is a global network of towers that measures the exchanges of CO2, water vapor, and energy between plants and the atmosphere, and b) theory-based models of ecological function, we can respond more effectively to future ecological challenges and make better decisions in the short-term.

Basically, ecological forecasting is like weather forecasting: it takes real-time input (for instance from FLUXNET towers like in thee picture on the right) and feeds the data through models of physical responses. These models spit out information such as how the available carbon pool above a particular forest will look in five minutes, five hours, or five days from now. In theory, knowing future conditions will help land managers—and policy makers—make better decisions not only on a day-to-day level, but also in the face of catastrophic ecological events. We’re only going to put more and more pressure on the natural resource systems of the planet, and having a forecasting system that makes sense of ecological responses will be incredibly valuable.

I see the necessity of such a system, and I know how much power predictive models have had in other fields. But I can’t help but feel a little torn. I love fieldwork, and there’s valuable information that can’t be gleaned from towers—so I hope that, as we move more and more toward regional-scale ecological assessments, we keep looking at how our local environments match up with the forecasts and models. Hopefully I’ll get to do more fieldwork (if only to help refine models!) long into the future.

–Ale Borunda, Columbia University Earth and Environmental Sciences Journalism Graduate Student