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Open AccessArticle

A GIS-Based Water Balance Approach Using a LiDAR-Derived DEM Captures Fine-Scale Vegetation Patterns

Department of Geography, Ohio University, Athens, OH 45701, USA
Remote Sens. 2019, 11(20), 2385; https://doi.org/10.3390/rs11202385
Received: 22 July 2019 / Revised: 13 October 2019 / Accepted: 13 October 2019 / Published: 15 October 2019
Topography exerts strong control on microclimate, resulting in distinctive vegetation patterns in areas of moderate to high relief. Using the Thornthwaite approach to account for hydrologic cycle components, a GIS-based Water Balance Toolset is presented as a means to address fine-scale species–site relationships. For each pixel within a study area, the toolset assesses inter-annual variations in moisture demand (governed by temperature and radiation) and availability (precipitation, soil storage). These in turn enable computation of climatic water deficit, the amount by which available moisture fails to meet demand. Summer deficit computed by the model correlates highly with the Standardized Precipitation–Evapotranspiration Index (SPEI) for drought at several sites across the eastern U.S. Yet the strength of the approach is its ability to model fine-scale patterns. For a 25-ha study site in central Indiana, individual tree locations were linked to summer deficit under different historical conditions: using average monthly climatic variables for 1998–2017, and for the drought year of 2012. In addition, future baseline and drought-year projections were modeled based on downscaled GCM data for 2071–2100. Although small deficits are observed under average conditions (historical or future), strong patterns linked to topography emerge during drought years. The modeled moisture patterns capture vegetation distributions described for the region, with beech and maple preferentially occurring in low-deficit settings, and oak and hickory dominating more xeric positions. End-of-century projections suggest severe deficit, which should favor oak and hickory over more mesic species. Pockets of smaller deficit persist on the landscape, but only when a fine-resolution Light Detection and Ranging (LiDAR)-derived Digital Elevation Model (DEM) is used; a coarse-resolution DEM masks fine-scale variability and compresses the range of observed values. Identification of mesic habitat microrefugia has important implications for retreating species under altered climate. Using readily available data to evaluate fine-scale patterns of moisture demand and availability, the Water Balance Toolset provides a useful approach to explore species–environment linkages. View Full-Text
Keywords: water deficit; drought; species distribution modeling; forest ecology; landscape ecology; Lilly–Dickey Woods; oak forests; eastern deciduous forest; mesophication; microrefugia water deficit; drought; species distribution modeling; forest ecology; landscape ecology; Lilly–Dickey Woods; oak forests; eastern deciduous forest; mesophication; microrefugia
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MDPI and ACS Style

Dyer, J.M. A GIS-Based Water Balance Approach Using a LiDAR-Derived DEM Captures Fine-Scale Vegetation Patterns. Remote Sens. 2019, 11, 2385.

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