Plants as Proxies: Mapping Hydrophytic Intrinsic Potential (HIP) from Community Science Observations as a Soil Moisture Indicator

Abstract

Soil moisture is a critical environmental variable, with ties to forest resilience, plant community composition, and carbon storage. Increasing drought severity and hydrological fluctuations will impact forest health, altering the spatial distribution and temporal dynamics of soil moisture, underscoring the urgency of soil moisture mapping. However, modeling and mapping soil moisture is challenging in heavily forested environments where traditional remote sensing methods cannot penetrate the canopy. This is confounded by the challenges of in situ soil moisture monitoring, stemming from the high temporal and spatial heterogeneity of soil moisture. This gap leaves land managers without the fine-scale soil moisture observations necessary for management-level decision-making. Therefore, we aimed to model surface soil moisture at a resolution of 10m or less in the Skykomish watershed. First, we tested the feasibility of using a lidar-based wetland intrinsic potential (WIP) model to map surface soil moisture. The WIP explained 60% of the variance in surface soil moisture and was calibrated to estimate Volumetric Water Content (VWC). Second, building on these results, we introduce a novel method for modeling soil moisture by coupling community science plant observations with wetland indicator status. This new approach explained 62% of the variance in summer soil moisture. Third, we investigated where these models systematically over- or underpredict moisture using soil physical properties data. We found no significant link between model performance and soil physical properties; however, the plant-based model systematically underpredicts moisture at the wettest end of the moisture gradient. We demonstrate the promise of wetland mapping tools and community science for soil moisture applications, thereby furthering our ability to model the full moisture gradient at fine spatial scales in densely forested landscapes.