Subalpine Forest Water Use and Climate Stress

Foundational work

Much of the modern understanding of conifer water-use strategy in the Rockies traces to tree-ring isotope work showing that Engelmann spruce and subalpine fir near Gothic have historically depended on snowmelt, but with surprising flexibility. (Berkelhammer et al., 2020) analyzed multi-decadal records of oxygen isotopes in tree-ring cellulose and found that, while snowmelt was the dominant water source, there were multi-year periods when trees switched toward summer rain — particularly during wet years with vigorous growth. The authors proposed that root profiles or water-table depths shift during wetter periods, enabling trees to tap summer precipitation that would otherwise pass through quickly.

A companion deep-time study extended this view back to the last interglacial. Using subfossil wood from Colorado, (Berkelhammer et al., 2021) showed that conifers during that warm period maintained growth rates and water-use efficiency comparable to today, even though model simulations indicated roughly 30 percent higher evaporative demand. Late-season cellulose was enriched in heavy oxygen, suggesting trees relied more heavily on summer rain. The implication was provocative: a wetter summer regime helped Rocky Mountain forests endure a warmer climate in the past, and the fate of today's forests may hinge on whether the summer monsoon strengthens or weakens.

Key findings

A central insight from recent work is that subalpine trees are far more opportunistic in their water use than previously appreciated. Using daily in-situ isotope measurements and a deuterium-labeled irrigation experiment near Gothic, (Sprenger et al., 2025) found that aspen trees shifted their dominant water source to roughly 60–90 cm depth within days of a dry spell, increasing absolute uptake from deep soil by a factor of seven during drought. After intense rainfall, the same trees partially switched back to shallow soil within two days. However, this compensatory deep uptake was not enough to fully replace lost shallow water, meaning trees still experienced stress during prolonged dry periods. Snowmelt stored deep in the soil emerged as a critical drought buffer, especially for spruce, whose dense canopy intercepts much of the summer rain before it reaches the ground.

Forest stand structure turns out to strongly modulate these responses. (Berkelhammer et al., 2025) combined sap flow sensors and xylem isotope measurements across a hillslope near Gothic and found that only 40 percent of monitored trees increased their water use during the heavy snow year of 2019. Trees that responded to abundant snow were almost all in dense canopy stands, while trees in open stands were more dependent on summer rain and grew most actively in years with modest snow but strong monsoon. The authors found that dense stands paradoxically had drier surface soils, higher water stress, and more competition from shallow-rooted understory plants — a reminder that canopy structure shapes hydrology as much as climate does.

These tree-level dynamics scale up to the ecosystem carbon cycle. (Carbone et al., 2023) measured soil carbon dioxide release continuously from 2013 to 2021 in conifer and aspen stands of the upper Colorado River basin and found that summer rainfall was a stronger predictor of soil carbon flux than winter snowpack, with conifer stands particularly sensitive. Over the study period, surface soil CO2 production declined as summers grew warmer and drier. Complementing this, lidar and deep learning analysis by (Hojatimalekshah et al., 2023) showed that vertically complex canopies intercept more snow and produce shallower snowpacks beneath them, linking forest structure directly to the snow water that feeds trees the following summer.

Current frontier

While a foundational 1990s study touched on resource–physiology interactions in mountain organisms (Anderson, 1999), nearly all of the active research in this area has emerged since 2020, driven by new sensor networks, isotope laboratories, and remote sensing campaigns. Recent papers have moved from snapshots toward continuous, daily-resolution observations of the soil-plant-atmosphere system. The Bonner et al. paired open-and-forested meteorology and snow dataset (Bonner et al., 2022) from Crested Butte provides three years of detailed snow pit, depth, and weather data spanning above-average, average, and below-average snow years — a benchmark resource for testing how forests filter snow into water available to trees. At the same time, NASA's SnowEx campaign at Grand Mesa has produced spatially distributed snow depth, density, and snow water equivalent estimates by combining ground-penetrating radar, lidar, and machine learning (Meehan et al., 2024), with related work characterizing snowpack mechanical properties (Meehan, 2022) and load-bearing strength (Tedesche et al., 2025).

The trajectory is clearly toward integration: linking airborne and satellite measurements of snow and canopy with on-the-ground sap flow and isotope tracing to predict which stands are most vulnerable to declining snow and intensifying summer drought. Emerging questions focus on how root depth, canopy density, and species identity together determine drought resilience, and on whether monsoonal rainfall will continue to buffer warming as it appears to have done during the last interglacial.

Open questions

Several important uncertainties remain. It is still unclear how much deep soil water — essentially old snowmelt — is available across different slope positions and stand types, and how quickly that reservoir is replenished in low-snow years. The role of root architecture in enabling rapid source-switching is poorly mapped, especially for aspen versus conifers. Whether the North American monsoon will strengthen or weaken under continued warming is a critical climate-modeling question, because the analogy with the last interglacial only holds if summer rain increases. Finally, the feedbacks between canopy thinning, understory growth, snow interception, and tree water stress need to be tested across more watersheds before management actions — such as forest thinning to enhance downstream water yield — can be confidently recommended. The next decade of research will likely focus on combining long-term observatories like those near Gothic with basin-scale remote sensing to forecast subalpine forest futures.

References

Anderson, J. (1999). The effects of variable nutrient environments on protein concentrations in male accessory glands in Speyeria mormonia. →

Berkelhammer, M., et al. (2020). Persistence and Plasticity in Conifer Water-Use Strategies. JGR Biogeosciences. →

Berkelhammer, M., et al. (2025). Canopy structure modulates the sensitivity of subalpine forest stands to interannual snowpack and precipitation variability. Hydrology and Earth System Science. →

Berkelhammer, M., Insel, N., & Stefanescu, I. C. (2021). Wetter summers mitigated temperature stress on Rocky Mountain forests during the last interglacial warm period. Geophysical Research Letters. →

Bonner, H. M., Smyth, E., et al. (2022). A Meteorology and Snow Data Set From Adjacent Forested and Meadow Sites at Crested Butte, CO, USA. Water Resources Research. →

Carbone, M. S., et al. (2023). Interannual precipitation controls on soil CO2 fluxes in high elevation conifer and aspen forests. Environmental Research Letters. →

Hojatimalekshah, A., et al. (2023). Lidar and deep learning reveal forest structural controls on snowpack. Frontiers in Ecology and the Environment. →

Meehan, T. G. (2022). Advancements in Measuring and Modeling the Mechanical and Hydrological Properties of Snow and Firn. →

Meehan, T. G., et al. (2024). Spatially distributed snow depth, bulk density, and snow water equivalent from ground-based and airborne sensor integration at Grand Mesa, Colorado, USA. The Cryosphere. →

Sprenger, M., et al. (2025). Opportunistic short-term water uptake dynamics by subalpine trees observed via in situ water isotope measurements. Water Resources Research. →

Tedesche, M., et al. (2025). How strong is Snow? Spatial correlations of snowpack load bearing capacity and micromechanics from NASA SnowEx SnowMicroPen Data at Grand Mesa, Colorado. Cold Regions Science and Technology. →

Lidar and deep learning reveal forest structural controls on snowpack