Plant Power: A New Method to Model How Plants Move Water Globally
Earth systems models are an important tool for studying complex processes occurring around the planet, such as those in and between the atmosphere and biosphere, and they help researchers and policymakers better understand phenomena like climate change. Incorporating more data into these simulations can improve modeling accuracy; however, sometimes, this requires the arduous task of gathering millions of data points.
Researchers, including UConn Department of Natural Resources and the Environment Assistant Professor James Knighton, Pablo Sanchez-Martinez from the University of Edinburgh, and Leander Anderegg from the University of California Santa Barbara, have developed a method to bypass the need for gathering data for over 55,000 tree species to better account for how plants influence the flow of water around the planet. Their findings are published in Nature Scientific Data.
Plants play essential roles in Earth’s processes, from capturing carbon and making oxygen available for other life forms like humans. Plants are also responsible for the movement of water, says Knighton, where an estimated 60% of all rain is returned to the atmosphere through transpiration. This huge global-scale movement of water through plants is complex and currently represented by Earth system models (ESMs) in a simplified way says Knighton, where all plants in a region may be considered as a single entity (i.e., a plant functional type),
“Plant Functional Types (PFTs) are used because we don’t know a lot about the details of individual plant species,” says Knighton, a faculty member in the College of Agriculture, Health and Natural Sciences. “It would be harder to take a detailed map of vegetation over a continent and put in all the right values for each individual species so it’s easier just to consider one generic PFT.”
The problem with PFTs is that different plant species vary in their hydrologic traits – or how water moves through plants — and this oversimplification of such systemically influential traits could limit the effectiveness of available models to predict the future. Scientists have moved towards accounting for these differences by creating databases, like the TRY Plant Trait Database, where this information is collected. However, Knighton points out that only about 5,000 to 15,000 plant species have had their traits well-cataloged after several centuries of plant science.
“There are around 60,000 to 70,000 tree species on Earth, meaning that after 200 years, we know maybe 5 to 10% of what’s happening,” he says. “If that were the way we would do things, it would take us another 2,000 years or so to learn about all the plants that we needed to, and at that point, climate change has set in, and it’s too late. We can’t do that. We can’t just wait for field researchers to go out and do their studies and populate this global database. It’s still incredibly useful to conduct field studies, but those alone will not get us where we need to be fast enough.”
Knighton and his colleagues decided to address this problem and expedite the process by looking at the data for traits that are available, information like how tall a tree grows, how deep the roots descend, or how fast water flows within the plant. They then compared the history of that species and its relatedness to other species in what is called a phylogenetic test for those traits.
“We looked to see how similar trait values are between closely related species, and the idea behind that is, if these traits are critical for their survival, evolution will have preserved the trait values, they won’t be randomly dispersed,” Knighton says. “For example, if growing deep roots was critical for a certain type of plant to survive, the species that branch off from that one will probably also have deep roots, and everything that’s in that family or that genus will have a similar root structure.”
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