Spatial Estimates of Soil Moisture for Understanding Ecological Potential and Risk: A Case Study for Arid and Semi-Arid Ecosystems

Michael S. O’Donnell () and Daniel J. Manier
Additional contact information
Michael S. O’Donnell: U.S. Geological Survey, Fort Collins Science Center, 2150 Centre Ave, Bldg. C, Fort Collins, CO 80526, USA
Daniel J. Manier: U.S. Geological Survey, Fort Collins Science Center, 2150 Centre Ave, Bldg. C, Fort Collins, CO 80526, USA

Land, 2022, vol. 11, issue 10, 1-37

Abstract: Soil temperature and moisture (soil-climate) affect plant growth and microbial metabolism, providing a mechanistic link between climate and growing conditions. However, spatially explicit soil-climate estimates that can inform management and research are lacking. We developed a framework to estimate spatiotemporal-varying soil moisture (monthly, annual, and seasonal) and temperature-moisture regimes as gridded surfaces by enhancing the Newhall simulation model. Importantly, our approach allows for the substitution of data and parameters, such as climate, snowmelt, soil properties, alternative potential evapotranspiration equations and air-soil temperature offsets. We applied the model across the western United States using monthly climate averages (1981–2010). The resulting data are intended to help improve conservation and habitat management, including but not limited to increasing the understanding of vegetation patterns (restoration effectiveness), the spread of invasive species and wildfire risk. The demonstrated modeled results had significant correlations with vegetation patterns—for example, soil moisture variables predicted sagebrush (R 2 = 0.51), annual herbaceous plant cover (R 2 = 0.687), exposed soil (R 2 = 0.656) and fire occurrence (R 2 = 0.343). Using our framework, we have the flexibility to assess dynamic climate conditions (historical, contemporary or projected) that could improve the knowledge of changing spatiotemporal biotic patterns and be applied to other geographic regions.

Keywords: Newhall simulation model; sagebrush biome; seasonality; site potential; snowmelt; soil temperature and moisture regimes; trends; western United States (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2073-445X/11/10/1856/pdf (application/pdf)
https://www.mdpi.com/2073-445X/11/10/1856/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jlands:v:11:y:2022:i:10:p:1856-:d:948392

Access Statistics for this article

Land is currently edited by Ms. Carol Ma

More articles in Land from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().