Current models used for predicting vegetation responses to climate change are often guided by the dichotomous needs to resolve either (i) internal plant water status as a proxy for physiological vulnerability or (ii) external water and carbon fluxes and atmospheric feedbacks. Yet, accurate representation of fluxes does not always equate to accurate predictions of vulnerability. We resolve this discrepancy using a hydrodynamic framework that simultaneously tracks plant water status and water uptake. We couple a minimalist plant hydraulics model with a soil moisture model and, for the first time, translate rainfall variability at multiple timescales – with explicit descriptions at daily, seasonal, and interannual timescales – into a physiologically meaningful metric for the risk of hydraulic failure. The model, parameterized with measured traits from chaparral species native to Southern California, shows that apparently similar transpiration patterns throughout the dry season can emerge from disparate plant water potential trajectories, and vice versa. The parsimonious set of parameters that captures the role of many traits across the soil–plant–atmosphere continuum is then used to establish differences in species sensitivities to shifts in seasonal rainfall statistics, showing that co‐occurring species may diverge in their risk of hydraulic failure despite minimal changes to their seasonal water use. The results suggest potential shifts in species composition in this region due to species‐specific changes in hydraulic risk. Our process‐based approach offers a quantitative framework for understanding species sensitivity across multiple timescales of rainfall variability and provides a promising avenue toward incorporating interactions of temporal variability and physiological mechanisms into drought response models.
This content will become publicly available on October 26, 2025
One of the most reliable features of natural systems is that they change through time. Theory predicts that temporally fluctuating conditions shape community composition, species distribution patterns, and life history variation, yet features of temporal variability are rarely incorporated into studies of species–environment associations. In this study, we evaluated how two components of temporal environmental variation—variability and predictability—impact plant community composition and species distribution patterns in the alpine tundra of the Southern Rocky Mountains in Colorado (USA). Using the Sensor Network Array at the Niwot Ridge Long‐Term Ecological Research site, we used in situ, high‐resolution temporal measurements of soil moisture and temperature from 13 locations (“nodes”) distributed throughout an alpine catchment to characterize the annual mean, variability, and predictability in these variables in each of four consecutive years. We combined these data with annual vegetation surveys at each node to evaluate whether variability over short (within‐day) and seasonal (2‐ to 4‐month) timescales could predict patterns in plant community composition, species distributions, and species abundances better than models that considered average annual conditions alone. We found that metrics for variability and predictability in soil moisture and soil temperature, at both daily and seasonal timescales, improved our ability to explain spatial variation in alpine plant community composition. Daily variability in soil moisture and temperature, along with seasonal predictability in soil moisture, was particularly important in predicting community composition and species occurrences. These results indicate that the magnitude and patterns of fluctuations in soil moisture and temperature are important predictors of community composition and plant distribution patterns in alpine plant communities. More broadly, these results highlight that components of temporal change provide important niche axes that can partition species with different growth and life history strategies along environmental gradients in heterogeneous landscapes.
more » « less- Award ID(s):
- 2224439
- PAR ID:
- 10556410
- Publisher / Repository:
- The Ecological Society of America
- Date Published:
- Journal Name:
- Ecology
- ISSN:
- 0012-9658
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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