Abstract Understanding how vegetation responds to drought is fundamental for understanding the broader implications of climate change on foundation tree species that support high biodiversity. Leveraging remote sensing technology provides a unique vantage point to explore these responses across and within species.We investigated interspecific drought responses of twoPopulusspecies (P.fremontii,P.angustifolia) and their naturally occurring hybrids using leaf‐level visible through shortwave infrared (VSWIR; 400–2500 nm) reflectance. AsF1hybrids backcross with either species, resulting in a range of backcross genotypes, we heretofore refer to the two species and their hybrids collectively as ‘cross types’. We additionally explored intraspecific variation inP. fremontiidrought response at the leaf and canopy levels using reflectance data and thermal unmanned aerial vehicle (UAV) imagery. We employed several analyses to assess genotype‐by‐environment (G × E) interactions concerning drought, including principal component analysis, support vector machine and spectral similarity index.Five key findings emerged: (1) Spectra of all three cross types shifted significantly in response to drought. The magnitude of these reaction norms can be ranked from hybrids>P. fremontii>P. angustifolia, suggesting differential variation in response to drought; (2) Spectral space among cross types constricted under drought, indicating spectral—and phenotypic—convergence; (3) Experimentally, populations ofP. fremontiifrom cool regions had different responses to drought than populations from warm regions, with source population mean annual temperature driving the magnitude and direction of change in VSWIR reflectance. (4) UAV thermal imagery revealed that watered, warm‐adapted populations maintained lower leaf temperatures and retained more leaves than cool‐adapted populations, but differences in leaf retention decreased when droughted. (5) These findings are consistent with patterns of local adaptation to drought and temperature stress, demonstrating the ability of leaf spectra to detect ecological and evolutionary responses to drought as a function of adaptation to different environments.Synthesis.Leaf‐level spectroscopy and canopy‐level UAV thermal data captured inter‐ and intraspecific responses to water stress in cottonwoods, which are widely distributed in arid environments. This study demonstrates the potential of remote sensing to monitor and predict the impacts of drought on scales varying from leaves to landscapes.
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Remote sensing of ploidy level in quaking aspen ( Populus tremuloides Michx.)
Abstract Ploidy level in plants may influence ecological functioning, demography and response to climate change. However, measuring ploidy level typically requires intensive cell or molecular methods.We map ploidy level variation in quaking aspen, a dominant North American tree species that can be diploid or triploid and that grows in spatially extensive clones. We identify the predictors and spatial scale of ploidy level variation using a combination of genetic and ground‐based and airborne remote sensing methods.We show that ground‐based leaf spectra and airborne canopy spectra can both classify aspen by ploidy level with a precision‐recall harmonic mean of 0.75–0.95 and Cohen's kappa ofc.0.6–0.9. Ground‐based bark spectra cannot classify ploidy level better than chance. We also found that diploids are more common on higher elevation and steeper sites in a network of forest plots in Colorado, and that ploidy level distribution varies at subkilometer spatial scales.Synthesis. Our proof‐of‐concept study shows that remote sensing of ploidy level could become feasible in this tree species. Mapping ploidy level across landscapes could provide insights into the genetic basis of species' responses to climate change.
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- PAR ID:
- 10372292
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Journal of Ecology
- Volume:
- 108
- Issue:
- 1
- ISSN:
- 0022-0477
- Page Range / eLocation ID:
- p. 175-188
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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