Imagine a mammoth, grazing 20,000 years ago in the steppe-tundra—a vast and frigid grassland where plants grew slowly under a frigid, low-carbon atmosphere. The mammoth tramples saplings, reducing forest cover and allowing grass to flourish. It devours the grass, leaving room for fresh, new plant life to grow. The mammoth and the grass belong to an ecosystem of dazzling complexity, where every tiny factor plays a role in the exact balance of nutrients, the release of carbon, and the life cycle of every species that lived there.

Dan Zhu is a scientist who studies how land, plants, and animals all feed into the climate. She led a team of researchers that built the closest thing we have to a time-machine terrarium that lets us study the ecosystem the mammoth inhabited: a computational simulation of the tundra they occupied. The results, published in Nature Ecology & Evolution this week, help to explain one of the big mysteries about mammoths: how did such an enormous animal survive in an environment where everything struggled to grow?

The tundra in the computer

We can't build our own tundra, and the mammoths are long gone. So how do we study this? Imagine you could shrink that tundra and keep it in a terrarium, studying the complexity and understanding the interplay. Make it a time machine too: pause it, reboot it, and fast-forward it through hundreds of years at a time. This magical terrarium would let you play out hundreds of different scenarios, tweaking conditions slightly to see how they influence the ecosystem that develops.

To build the terrarium, you start by thinking about the plant life, trying out different mixtures of grasses and trees. Through this, you can tweak how much ground they cover, how much carbon and water they consume, and how much they compete for light and nutrients from the soil. With that in place, you can add in details about the climate: the temperature, humidity, amount of carbon dioxide in the atmosphere, rainfall, and snow.

This is a pretty generic terrarium so far. It doesn’t account for any of the effects of animals that live in the environment and interact with the plant life to change its dynamics. But the groundwork for the basic terrarium is already in place—Gerhard Krinner and a large group of other researchers had already crunched these numbers and put together a system that can model all of these different factors. Zhu and her colleagues built on this groundwork, adding in the grazers to see how they affected things.

This meant thinking about things like the length of the growing season and how much food that would make available for grazing animals. Outside of the growing season, only dead grass is available for animals to eat, and you need to calculate how much of it they need to eat to survive. It also meant thinking about mammals as another series of numbers: how many babies do they have, how often do they die, and how much more energy do they burn at lower temperatures?

Now the terrarium has what it needs to run on fast-forward for hundreds of years, spitting out data about the world that has been created. But before using this to answer questions about the past, Zhu and colleagues fed in the numbers for present-day ecosystems with large grazers. They wanted to be sure that the model did a reasonable job of capturing systems that we know about before using it to ask questions about ecosystems we can no longer observe.

The model passed the test: when they ran it to see what kinds of grazer populations could be sustained in ecosystems across Africa, Asia, and North America, the results matched up quite closely with real-world data. So, they turned to the mammoths.

Heavy grazers

We know mammoths were plentiful because of the abundance of bones they left behind. The survival of huge grazers on the low-vegetation tundra has been called the “productivity paradox”—why do we see such an abundance of large, hungry beasts in a sparse environment? One explanation that has been put forward is that larger animals are actually more efficient at using the food they eat.

The simulation found that this explanation worked well. The food produced by the tundra couldn’t sustain large populations of smaller grazers; as the body size of the grazers was increased, they were able to live on the lower plant growth and at lower temperatures. Bigger grazers means "more efficient exploitation of grass production," the researchers write—which in turn means "a higher grazer density supported by the same level of grass production."

The model doesn’t just help to answer questions about mammoth population sizes—it provides a good basis for understanding what ecosystems could sustain populations of large mammalian herbivores. The numbers of these mammals have been hit hard by human expansion, so figuring that out could be critical to conservation. It also helps us understand what effect large populations of grazers might have on the landscapes where they live, where their trampling and munching makes room for young, carbon-guzzling grasses to grow.

Thomas Hickler, who uses models like this to study ecosystems but wasn’t involved in this research, told Ars that the paper was a “major advance for our understanding of herbivore densities and their impacts on ecosystems.” He pointed out that there is a lot going on in these ecosystems that isn’t captured by the model and that it raises plenty of questions that it would be useful to explore in future research—something noted by the authors themselves.

But, he added, all models necessarily involve simplification, and the fact that real-world data matched up with the simulation results was heartening. In a changing world, a better understanding of the intricacies of the ecosystems around us—and how they interact with the climate—is some of the best information we have to fight population declines and extinctions.

Nature Ecology and Evolution, 2018. DOI: 10.1038/s41559-018-0481-y (About DOIs).