Inclusion of bedrock vadose zone in dynamic global vegetation models is key for simulating vegetation structure and functioning

Authors: Lapides, Dana; HAHM, W.J. - Simon Frasier University; FORREST, M. - Senckenberg Biodiversity And Climate Research Centre; REMPE, D.M. - University Of Texas At Austin; HICKLER, T. - Senckenberg Biodiversity And Climate Research Centre; DRALLE, D.N. - Us Forest Service (FS)

Submitted to: Biogeosciences
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/25/2024
Publication Date: 4/11/2024
Citation: Lapides, D.A., Hahm, W., Forrest, M., Rempe, D., Hickler, T., Dralle, D. 2024. Inclusion of bedrock vadose zone in dynamic global vegetation models is key for simulating vegetation structure and functioning. Biogeosciences. 21(7):1801-1826. https://doi.org/10.5194/bg-21-1801-2024.
DOI: https://doi.org/10.5194/bg-21-1801-2024

Interpretive Summary: Dynamic Global Vegetation Models (DGVMs) are our best tools for exploring how changes in climate, fire regime, and management or land use impact plant communities and thus the global carbon and hydrological cycles. While DGVMs are very powerful, they have historically struggled to capture vegetation dynamics in Mediterranean regions, where some of the most severe climatic volatility and wildfires have been observed in recent years. In Mediterranean regions, the majority of precipitation falls in the winter and must be stored on the landscape for use by plants during the growing season. This lag between water delivery and water use means that plants frequently take advantage of water stored not only in soils but in the underlying weathered bedrock. Despite increasing recognition of its importance, this "rock moisture" reservoir is rarely incorporated into vegetation and Earth system models. Here, we add a weathered bedrock component to a widely-used DGVM called LPJ-GUESS. Along with this change, we also implement an updated hydrology scheme that better matches contemporary understanding of runoff generation mechanisms. Using a case study of two sites in Northern California and model runs across the contiguous United States, we show that more accurately representing subsurface water storage and hydrology results in an increase in summer plant water use that better matches observed plant water use. These results demonstrate the importance of accounting for rock moisture in vegetation, climate, and landscape evolution models.

Technical Abstract: Across many upland environments, soils are thin and plant roots extend into fractured and weathered bedrcok where moisture and nutrients can be obtained. Root water extraction from unsaturated weathered bedrock is widespread and, in many environments, can explain gradients in vegetation community composition, transpiration, and plant sensitivity to climate. Despite increasing recognition of its importance, the "rock moisture" reservoir is rarely inorporated into vegetation and Earth system models. Here, we address this weakness in a widely used dynamic global vegetation model (DGVM, LPJ-GUESS). First, we use a water flux-tracking deficit approach to more accurately parameterize plant-accessible water storage capacity across the contiguous United States, which critically includes the water in bedrock below depths typically prescribed by soils databases. Secondly, we exploit field-based knowledge of contrasting plant-available water storage capacity in weathered bedrock across two bedrock types in the Northern California Coast Ranges as a detailed case-study. For the case study in Northern California, climate and soil water storage capacity are similar at the two study areas, but the site with thick weathered bedrock and ample rock moisture supports a mixed evergreen temperate broadleaf-needleleaf forest whereas the site with thin weathered bedrock and limited rock moisture supports an oak savannah. The distinct biomes, seasonality and magnitude of transpiration and primary productivity, and baseflow magnitudes only emerge from the DGVM when a new and simple subsurface storage structure and hydrology scheme is parameterized with storage capacities extending beyond the soil into the bedrock. Across the contiguous United States, the updated hydrology and subsurface storage improve annual evapotranspiration estimates as compared to satellite-derived products, particularly in seasonally dry regions. Specifically, the updated hydrology and subsurface storage allow for enhanced evapotranspiration through the dry season that better matches actual evapotranspiration patterns. While we made changes to both the subsurface water storage capacity and the hydrology, the most important impacts on model performance derive from changes to the subsurface water storage capacity. Our findings highlight the importance of rock moisture in explaining and predicting vegetation structure and function, particularly in seasonally dry climates. These findings motivate efforts to better incorporate the rock moisture reservoir into vegetation, climate, and landscape evolution models.