Back to Search
Start Over
LiDAR-derived topography and forest structure predict fine-scale variation in daily surface temperatures in oak savanna and conifer forest landscapes
- Source :
- Agricultural and Forest Meteorology, Agricultural and Forest Meteorology, Elsevier Masson, 2019, 269-270, pp.192-202. ⟨10.1016/j.agrformet.2019.02.015⟩, Davis, F W, Synes, N W, Fricker, G A, McCullough, I M, Serra-Diaz, J M, Franklin, J & Flint, A L 2019, ' LiDAR-derived topography and forest structure predict fine-scale variation in daily surface temperatures in oak savanna and conifer forest landscapes ', Agricultural and Forest Meteorology, vol. 269-270, pp. 192-202 . https://doi.org/10.1016/j.agrformet.2019.02.015
- Publication Year :
- 2019
- Publisher :
- eScholarship, University of California, 2019.
-
Abstract
- International audience; In mountain landscapes, surface temperatures vary over short distances due to interacting influences of topography and overstory vegetation on local energy and water balances. At two study landscapes in the Sierra Nevada of California, characterized by foothill oak savanna at 276–481 m elevation and montane conifer forest at 1977–2135 m, we deployed 288 near-surface (5 cm above the surface) temperature sensors to sample site-scale (30 m) temperature variation related to hillslope orientation and vegetation structure and microsite-scale (2–10 m) variation related to microtopography and tree overstory. Daily near-surface maximum and minimum temperatures for the 2013 calendar year were related to topographic factors and vegetation overstory characterized using small footprint LiDAR imagery acquired by the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP). At both landscapes we recorded large site and microsite spatial variation in daily maximum temperatures, and less absolute variation in daily minimum temperatures. Generalized boosted regression trees were estimated to measure the influence of tree canopy density, understory solar radiation, cold-air drainage and pooling, ground cover and microtopography on daily maximum and minimum temperatures at site and microsite scales. Site-scale models based on indices of understory solar radiation and landscape position explained an average of 61–65% of daily variation in maximum temperature; site-scale models based on tree canopy density and landscape position explained 65–83% of variation in minimum temperatures. Models explained
- Subjects :
- 0106 biological sciences
Canopy
Atmospheric Science
010504 meteorology & atmospheric sciences
[SDV]Life Sciences [q-bio]
Microclimate
Atmospheric sciences
01 natural sciences
Insolation
Meteorology & Atmospheric Sciences
0105 earth and related environmental sciences
Global and Planetary Change
Tree canopy
Agricultural and Veterinary Sciences
Cold-air drainage
Elevation
Forestry
NEON
Understory
Microsite
Vegetation
15. Life on land
Biological Sciences
13. Climate action
Earth Sciences
Environmental science
Spatial variability
Agronomy and Crop Science
010606 plant biology & botany
Subjects
Details
- ISSN :
- 01681923
- Database :
- OpenAIRE
- Journal :
- Agricultural and Forest Meteorology, Agricultural and Forest Meteorology, Elsevier Masson, 2019, 269-270, pp.192-202. ⟨10.1016/j.agrformet.2019.02.015⟩, Davis, F W, Synes, N W, Fricker, G A, McCullough, I M, Serra-Diaz, J M, Franklin, J & Flint, A L 2019, ' LiDAR-derived topography and forest structure predict fine-scale variation in daily surface temperatures in oak savanna and conifer forest landscapes ', Agricultural and Forest Meteorology, vol. 269-270, pp. 192-202 . https://doi.org/10.1016/j.agrformet.2019.02.015
- Accession number :
- edsair.doi.dedup.....137aefe12116924b227b305460c59954
- Full Text :
- https://doi.org/10.1016/j.agrformet.2019.02.015⟩