A worldwide revolution in grassland ecology is under way, and Melinda Smith, Yale Associate Professor of Ecology and Evolutionary Biology, is at the forefront. This revolution, a collaboration known as the Nutrient Network, was initiated in 2007 by a group of ecologists at the National Center for Ecological Analysis and Synthesis (NCEAS) in Santa Barbara, CA. These scientists found themselves unable to draw from the data of multiple experiments to form meaningful conclusions concerning ecology’s central issues. That is, while many analyses addressed similar issues, their experimental methods were too varied to be conclusive as a group. Smith, one of the co-founders, explains, “We were frustrated with the lack of comparable data; we needed a way to powerfully address our questions.”
In late 2006, Smith and her colleagues drafted a proposal for a collaborative research system with a focus on the different factors that influence the make-up of grasslands: nutrients, herbivores, and human intervention. The Nutrient Network, or NutNet for short, is a volunteer-based collaboration of ecologists who carry out small experiments with the same methodology at multiple sites and then compile their results in a single database. As such, the result is a large set of comparable data that can be examined on multiple levels.
Since its founding, NutNet, now spanning 12 countries with 68 participating sites, has been received with much enthusiasm. These staggering numbers, however, come as no surprise to Smith: “It is easy to do, and there is not a lot of effort on the individual basis.” Moreover, the volunteer support “really emphasizes how much ecologists want this data. It’s very exciting!”
This past September, NutNet answered the calls for this “exciting data” with data synthesis that addressed a longstanding debate over the relationship between primary productivity and plant species richness.
For decades, it had been theorized that this productivity-richness relationship (PRR) was hump-shaped; at low levels of productivity, few species would be able to persist, and at high levels, competition would lead to a few dominant species winning out. However, experimental support for the theory was weak, and scientists were unable to effectively compare the data from previous experiments; variation in the sample sizes and different means of measuring productivity were among the central obstacles in reaching a conclusion to this longstanding issue.
To solve this problem, NutNet analyzed consistent samples from 48 sites, spanning five continents. As Smith explains, “Since all sampling [was conducted] on the same scale and done in the same way, we know that the data are directly com-parable.” In addition, the sheer bulk of the data allowed for the research to reach conclusions on three levels: the local, in which samples taken from within individual sites were compared; the regional, in which the site-level averages were compared against others of the same biogeographical region; and the global, in which all sites were compared against one another.
Ultimately, Smith and her colleagues found that there is, in fact, no consistent relationship between primary productivity and species richness on any of these levels of comparison, and thus debunking a quintessential textbook theory. Now, NutNet can further explore the underlying mechanisms that create the clearly complex relationship between the two variables of primary productivity and species richness. Or, as Smith suggests, they could even repeat the analysis in the future but with more sites and different experimental specifications.
Whatever their next step, NutNet has proven to be an incredibly effective way of answering ecology’s biggest questions. Without a doubt, ecologists around the world will continue to use this opportunity to deepen our understanding of grasslands as a whole.