Cross-scale modeling of surface temperature and tree seedling establishment in mountain landscapes
| Autor: | Frank W. Davis, John Dingman, Lynn C. Sweet, Janet Franklin, Lorraine E. Flint, Ian M. McCullough, Alan L. Flint |
|---|---|
| Jazyk: | angličtina |
| Předmět: |
0106 biological sciences
010504 meteorology & atmospheric sciences Ecology biology Ecological Modeling Quercus kelloggii Microclimate Climate change Lapse rate 15. Life on land biology.organism_classification Atmospheric sciences 010603 evolutionary biology 01 natural sciences 13. Climate action Range (statistics) Spatial ecology Environmental science Spatial variability Climate model 0105 earth and related environmental sciences |
| Zdroj: | Ecological Processes. 2(1):30 |
| ISSN: | 2192-1709 |
| DOI: | 10.1186/2192-1709-2-30 |
| Popis: | Estimating surface temperature from above-ground field measurements is important for understanding the complex landscape patterns of plant seedling survival and establishment, processes which occur at heights of only several centimeters. Currently, future climate models predict temperature at 2 m above ground, leaving ground-surface microclimate not well characterized. Using a network of field temperature sensors and climate models, a ground-surface temperature method was used to estimate microclimate variability of minimum and maximum temperature. Temperature lapse rates were derived from field temperature sensors and distributed across the landscape capturing differences in solar radiation and cold air drainages modeled at a 30-m spatial resolution. The surface temperature estimation method used for this analysis successfully estimated minimum surface temperatures on north-facing, south-facing, valley, and ridgeline topographic settings, and when compared to measured temperatures yielded an R2 of 0.88, 0.80, 0.88, and 0.80, respectively. Maximum surface temperatures generally had slightly more spatial variability than minimum surface temperatures, resulting in R2 values of 0.86, 0.77, 0.72, and 0.79 for north-facing, south-facing, valley, and ridgeline topographic settings. Quasi-Poisson regressions predicting recruitment of Quercus kelloggii (black oak) seedlings from temperature variables were significantly improved using these estimates of surface temperature compared to air temperature modeled at 2 m. Predicting minimum and maximum ground-surface temperatures using a downscaled climate model coupled with temperature lapse rates estimated from field measurements provides a method for modeling temperature effects on plant recruitment. Such methods could be applied to improve projections of species’ range shifts under climate change. Areas of complex topography can provide intricate microclimates that may allow species to redistribute locally as climate changes. |
| Databáze: | OpenAIRE |
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