When people ask me what I do, I tell them I am a global change scientist. Most have never met a global change scientist, so it takes some explaining. Essentially, we research how different ecosystems work in order to understand how they respond to global changes that are occurring: warming, increases in atmospheric carbon dioxide concentrations, changes in precipitation, species invasions and extinctions.
Personally, I care the most about grasslands. I spend a lot of time trying to answer questions about how grass will grow in the future.
We use a number of tools to get at how grass will be affected, but one of the best ways to understand grass is to look at what eats it. Or what is left after something has eaten it.
There is a lot of information in the fecal material of grazers. A quick observation of how "runny" it is is a good indication of the dietary quality of the animals. Scientists at Texas A&;M University's Grazer Animal Nutrition Lab have taken these observations one step further. They developed calibrations to relate the quality of cattle diet to the way it absorbs different wavelengths of light. (Technically, the technique uses near-infrared radiation spectroscopy, which uses longer wavelengths than visible light.)
So, if we want to understand what is going to happen to cattle in a warmer world, we can begin to compare the fecal material of cattle eating grass in grasslands of different temperatures.
That's a lot of work.
Luckily, it turns out that many ranchers from across the United States had been sending cattle fecal samples to the Texas A&;M lab for years. The lab had measured more than 30,000 fecal samples from cattle that were eating grass and not supplemented nutritionally.
Working with the lab, we analyzed the data in an anonymous fashion to make a map of crude protein concentrations across the United States.
The idea was if we can compare grass protein concentrations in warmer grasslands to cooler grasslands, we would be able to begin to better understand what happens as the climate warms above an individual grassland.
There are many assumptions here. As scientists, we allow our science to be incremental as we compare independent lines of evidence, such as experiments and long-term monitoring.
Two things popped out in the data. First, cattle are limited by protein throughout the year almost everywhere when they are out on pastures. The ratio of digestible organic matter to crude protein is a rough index of the relative availability of energy and protein. It was rare for there to be more protein available than energy relative to the animals" demands.
That narrowed our focus on understanding what the patterns of protein concentrations were in grass that cattle were eating. It turns out that grasslands in warmer climates had lower peak crude-protein concentrations than those in cooler climates. Looking at the Great Plains and the Upper Midwest, the highest crude-protein concentrations averaged 16 percent protein in the north but 11 percent in the south. Depending on the animal, that's enough for an extra 1.5 pounds per day.
It wasn't just how high protein concentrations got. Crude-protein concentrations were lower throughout the entire year in warmer grasslands. In the end, what we quantified is what a lot of people tell me they already knew. Wisconsin has better grass than Oklahoma.
But, getting hard numbers on this helps us immensely. We can now begin to provide better estimates for how much worse forage quality would get for a given amount of warming. It focuses us on new questions, like: Why is grass forage quality worse in warmer grasslands? How long does it take for forage quality to drop when grasslands are warmed? If warming is going to reduce forage quality, will it also reduce the weight gain of cattle? Fewer people seem to know the answers to those questions. That means we're on the right track to learning something new.
The reference for the paper describing this work is: Craine JM, Elmore AJ, Olson KC, Tolleson D (2010) Climate change and nutritional stress in cattle. Global Change Biology 16:2901-2911