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A nuanced model of soil moisture illuminates plant behavior and climate patterns

A nuanced model of soil moisture illuminates plant behavior and climate patterns
Comparison of model fit. The maps display the median R2 differences per SMAP grid between (a) the nonlinear and linear loss models, and (b) the nonlinear and τ-based linear loss models. Credit: Geophysical Research Letters (2025). DOI: 10.1029/2024GL111403

Any home gardener knows they have to tailor their watering regime for different plants. Forgetting to water their flowerbed over the weekend could spell disaster, but the trees will likely be fine. Plants have evolved different strategies to manage their water use, but soil moisture models have mostly neglected this until now.

Researchers at UC Santa Barbara and San Diego State University sought a way to move beyond simple on/off models to capture the nuanced ways that plants manage . To this end, they developed a nonlinear model that can observe these behaviors in . Their , published in Geophysical Research Letters, will improve and inform our own water management strategies.

"We found that plants don't respond to water stress in a simple, straight-line way," said senior author Kelly Caylor, a professor at UCSB's Bren School of Environmental Science & Management. "Instead, they have dynamic response patterns that reveal whether they're 'water spenders' or 'water savers.'"

How soils dry out

Water can follow many paths after it rains. It can go down: running off the surface into streams and rivers or soaking into deep aquifers. Or it can go up: either evaporating directly from the soil or getting taken in by , which transpire the water through their leaves to the atmosphere. Scientists refer to these latter two processes as evapotranspiration.

The way in which soils dry out influences ecology, weather patterns and global resource cycles. Unfortunately, scientists didn't have much large-scale data on soil drydowns until recently, so they relied heavily on numerical simulations.

"Ironically, most models do not use soil moisture data, although the soil moisture is a central component to hydrological behavior," said lead author Ryoko Araki, a joint doctoral student at UCSB and SDSU. This data has been hard to collect and difficult to incorporate into models, so scientists tend to rely on precipitation or river flow rates instead.

The classic models assume that all plants reduce transpiration at the same rate, and at similar timings. "All plants—no matter young or old, summer or winter, tree or grass, small or large," Araki said.

This makes analysis and experimentation easier, but neglects plant behavior, a large part of what drives the process. Including the interplay between plants and the soil should improve the model's accuracy and predictive power, the authors concluded. They also reasoned that, if excluding plant behavior led to a linear model, then a non-linear model might help them investigate these strategies.

Building a new model

Araki started with a linear model of evapotranspiration based on time and soil moisture. She then introduced a nonlinear variable to account for how plants change their water use in response to soil moisture itself.

Unlike scientists in decades past, Araki and her co-authors have access to a wealth of data, which they used to validate the new model with soil moisture measurements. They tapped NASA's SMAP satellite, which uses microwaves to measure average across Earth's surface.

The authors found that the nonlinear approach fit the satellite data far better than either of the two leading linear models. They also discovered that linear models tend to overestimate evapotranspiration rates, predicting that soils will dry out much faster than they actually do. A more accurate account of this process is a big deal in a state with perennial water worries.

According to Araki, some colleagues have criticized the nonlinear model as needlessly complex. While its predictions may be more accurate, they say, the additional parameter makes it more difficult to apply.

Araki acknowledges this, but counters that the results justify that tradeoff. "Even though the nonlinear model is more complicated, it fits the data better, and it captures more of the system's behaviors," she said. What's more, it provides a way to investigate plant adaptations.

It's difficult to measure how plants manage their water uptake in response to environmental conditions. "Do they keep growing as much as they can while they still have some amount of water, or do they just completely stop transpiring to prevent tissue damage?" said co-author Bryn Morgan, a former UCSB doctoral student who is now a postdoctoral fellow at MIT.

More information: Ryoko Araki et al, Nonlinear Soil Moisture Loss Function Reveals Vegetation Responses to Water Availability, Geophysical Research Letters (2025).

Journal information: Geophysical Research Letters

Citation: A nuanced model of soil moisture illuminates plant behavior and climate patterns (2025, July 8) retrieved 8 July 2025 from /news/2025-07-nuanced-soil-moisture-illuminates-behavior.html
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