Amanda Henderson

By experimentally advancing snowmelt in a sub-alpine meadow, we demonstrate that warming winters cause phenological asynchrony between host plant and arbuscular mycorrhizal fungi. Early snowmelt caused early onset of greening and diminished extraradical hyphal production by mycorrhiza. Plant-fungal asynchrony was accompanied by smaller pools of available P and N, suggesting early, direct nutrient adsorption by plants lowered host investment in mycorrhizal fungal partners. The mycorrhizal symbiosis was weakened during a critical period of nutrient exchange. These findings point to the vulnerability of belowground mutualisms to warming winters, and highlight the need to incorporate fungal phenology into predictions of ecosystem responses to climate change. Future work scaling early snowmelt effects on belowground microbes to watershed N & P dynamics, or loss of N to the atmosphere, may provide a clearer picture on the relationships between warming winter, nutrient cycling, and plant-fungal asynchrony. The AM fungal community was highly variable across the growing season, indicating that mycorrhizal responses to warming are context-dependent on seasonal variation of soil resources and trait-based community assembly. Together, our results show that warming winters disrupt the seasonal timing of plant fungal interactions, potentially triggering nutrient-limitation feedbacks with potential consequences that extend from soil microbial processes to watershed-scale N and P cycling. By revealing both the sensitivity of belowground mutualisms to warming and the strong seasonal shifts in AM fungal community structure, this study underscores the importance of integrating fungal phenology, microbial functional traits, and nutrient-cycling mechanisms into predictions of ecosystem stability under continued climate change.

Quantifying flow and transport from hillslopes is vital for understanding water quantity and quality in rivers, but remains obscure because of limited subsurface measurements. Using measured hydraulic conductivity K profiles and water balance over a single year to calibrate a transmissivity feedback model for a hillslope in the East River watershed (Colorado) proved unsatisfactory for predicting flow over the subsequent years. Well‐constrained field‐scale K were obtained by optimizing subsurface flux predictions over years having large differences in recharge, and by including estimates of interannual transfer of excess snowmelt recharge. Water and solute exports during high snowmelt recharge occur predominantly via shallow groundwater flow through weathered rock and soil because of their enlarged transmissivities under saturated conditions. Conversely, these shallow pathways are less active in snow drought years when the water table remains deeper within the weathering zone. Hillslope soil water monitoring showed that rainfall does not infiltrate deeply during summer and fall months, and revealed water losses consistent with model ET predictions. By combining water table‐dependent fluxes with pore water chemistry in different zones, time‐dependent rates of solute exports become predictable. As an example, calibrated K were combined with dissolved nitrogen concentrations in pore waters to show the snowmelt‐dependence of reactive nitrogen exported from the hillslope, further supporting the recent finding that the weathering zone is the dominant source of reactive nitrogen at this site. Subsurface export predictions can now be obtained for wide ranges of recharge based on measurements of water table elevation and profiles of pore water chemistry.

Quantifying flow and transport from hillslopes is vital for understanding surface water quality, but remains obscure because of limited subsurface measurements. A recent combination of water mass balance over a single year with the transmissivity feedback model for a lower montane hillslope in the East River watershed (Colorado) left large uncertainties in transmissivities and predicted fluxes. Because snowmelt drives subsurface flow on this hillslope, improved constraints on the transmissivity profile were obtained by optimizing flux predictions over years having large differences in precipitation minus evapotranspiration. The optimized field-scale hydraulic properties combined with water table elevations predict groundwater discharges that are consistent with wide ranges of snowmelt. As snowmelt rapidly raises the water table, solutes released primarily through bedrock weathering are largely transported out of the hillslope via its highly transmissive soil. Such pulsed water and solute exports along the soil are minimized during snow drought years. Although solute concentrations generally are lower in soils relative to the underlying weathering zone, solute exports during high recharge occur predominantly via soil because of its enlarged transmissivities under snowmelt-saturated conditions. In contrast, this shallow pathway is negligible when recharge and water table elevations are low. The multiyear calibrated subsurface properties combined with updated pore water chemistry continue to show that the weathering zone is the primary source of base cations and reactive nitrogen released from the hillslope. Subsurface export predictions can now be obtained for wide ranges of snowmelt based on measurements of water table elevation and profiles of pore water chemistry.

In recent years, the availability of airborne imaging spectroscopy (hyperspectral) data has expanded dramatically. The high spatial and spectral resolution of these data uniquely enable spatially explicit ecological studies including species mapping, assessment of drought mortality and foliar trait distributions. However, we have barely begun to unlock the potential of these data to use direct mapping of vegetation characteristics to infer subsurface properties of the critical zone. To assess their utility for Earth systems research, imaging spectroscopy data acquisitions require integration with large, coincident ground‐based datasets collected by experts in ecology and environmental and Earth science. Without coordinated, well‐planned field campaigns, potential knowledge leveraged from advanced airborne data collections could be lost. Despite the growing importance of this field, documented methods to couple such a wide variety of disciplines remain sparse. We coordinated the first National Ecological Observatory Network Airborne Observation Platform (AOP) survey performed outside of their core sites, which took place in the Upper East River watershed, Colorado. Extensive planning for sample tracking and organization allowed field and flight teams to update the ground‐based sampling strategy daily. This enabled collection of an extensive set of physical samples to support a wide range of ecological, microbiological, biogeochemical and hydrological studies. We present a framework for integrating airborne and field campaigns to obtain high‐quality data for foliar trait prediction and document an archive of coincident physical samples collected to support a systems approach to ecological research in the critical zone. This detailed methodological account provides an example of how a multi‐disciplinary and multi‐institutional team can coordinate to maximize knowledge gained from an airborne survey, an approach that could be extended to other studies. The coordination of imaging spectroscopy surveys with appropriately timed and extensive field surveys, along with high‐quality processing of these data, presents a unique opportunity to reveal new insights into the structure and dynamics of the critical zone. To our knowledge, this level of co‐aligned sampling has never been undertaken in tandem with AOP surveys and subsequent studies utilizing this archive will shed considerable light on the breadth of applications for which imaging spectroscopy data can be leveraged.