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Plants respond to rapid environmental change in ways that depend on both their genetic identity and their phenotypic plasticity, impacting their survival as well as associated ecosystems. However, genetic and environmental effects on phenotype are difficult to quantify across large spatial scales and through time. Leaf hyperspectral reflectance offers a potentially robust approach to map these effects from local to landscape levels. Using a handheld field spectrometer, we analyzed leaf‐level hyperspectral reflectance of the foundation tree species Populus fremontii in wild populations and in three 6‐year‐old experimental common gardens spanning a steep climatic gradient. First, we show that genetic variation among populations and among clonal genotypes is detectable with leaf spectra, using both multivariate and univariate approaches. Spectra predicted population identity with 100% accuracy among trees in the wild, 87%–98% accuracy within a common garden, and 86% accuracy across different environments. Multiple spectral indices of plant health had significant heritability, with genotype accounting for 10%–23% of spectral variation within populations and 14%–48% of the variation across all populations. Second, we found gene by environment interactions leading to population‐specific shifts in the spectral phenotype across common garden environments. Spectral indices indicate that genetically divergent populations made unique adjustments to their chlorophyll and water content in response to the same environmental stresses, so that detecting genetic identity is critical to predicting tree response to change. Third, spectral indicators of greenness and photosynthetic efficiency decreased when populations were transferred to growing environments with higher mean annual maximum temperatures relative to home conditions. This result suggests altered physiological strategies further from the conditions to which plants are locally adapted. Transfers to cooler environments had fewer negative effects, demonstrating that plant spectra show directionality in plant performance adjustments. Thus, leaf reflectance data can detect both local adaptation and plastic shifts in plant physiology, informing strategic restoration and conservation decisions by enabling high resolution tracking of genetic and phenotypic changes in response to climate change.
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All the light we cannot see: Climate manipulations leave short and long‐term imprints in spectral reflectance of trees
Abstract Anthropogenic climate change, particularly changes in temperature and precipitation, affects plants in multiple ways. Because plants respond dynamically to stress and acclimate to changes in growing conditions, diagnosing quantitative plant‐environment relationships is a major challenge. One approach to this problem is to quantify leaf responses using spectral reflectance, which provides rapid, inexpensive, and nondestructive measurements that capture a wealth of information about genotype as well as phenotypic responses to the environment. However, it is unclear how warming and drought affect spectra. To address this gap, we used an open‐air field experiment that manipulates temperature and rainfall in 36 plots at two sites in the boreal‐temperate ecotone of northern Minnesota, USA. We collected leaf spectral reflectance (400–2400 nm) at the peak of the growing season for three consecutive years on juveniles (two to six years old) of five tree species planted within the experiment. We hypothesized that these mid‐season measurements of spectral reflectance capture a snapshot of the leaf phenotype encompassing a suite of physiological, structural, and biochemical responses to both long‐ and short‐time scale environmental conditions. We show that the imprint of environmental conditions experienced by plants hours to weeks before spectral measurements is linked to regions in the spectrum associated with stress, namely the water absorption regions of the near‐infrared and short‐wave infrared. In contrast, the environmental conditions plants experience during leaf development leave lasting imprints on the spectral profiles of leaves, attributable to leaf structure and chemistry (e.g., pigment content and associated ratios). Our analyses show that after accounting for baseline species spectral differences, spectral responses to the environment do not differ among the species. This suggests that building a general framework for understanding forest responses to climate change through spectral metrics may be possible, likely having broader implications if the common responses among species detected here represent a widespread phenomenon. Consequently, these results demonstrate that examining the entire spectrum of leaf reflectance for environmental imprints in contrast to single features (e.g., indices and traits) improves inferences about plant‐environment relationships, which is particularly important in times of unprecedented climate change.
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- Award ID(s):
- 2021898
- PAR ID:
- 10632285
- Publisher / Repository:
- Wiley
- Date Published:
- Journal Name:
- Ecology
- Volume:
- 106
- Issue:
- 5
- ISSN:
- 0012-9658
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Plants respond to rapid environmental change in ways that depend on both their genetic identity and their phenotypic plasticity, impacting their survival as well as associated ecosystems. However, genetic and environmental effects on phenotype are difficult to quantify across large spatial scales and through time. Leaf hyperspectral reflectance offers a potentially robust approach to map these effects from local to landscape levels. Using a handheld field spectrometer, we analyzed leaf‐level hyperspectral reflectance of the foundation tree species Populus fremontii in wild populations and in three 6‐year‐old experi- mental common gardens spanning a steep climatic gradient. First, we show that genetic variation among populations and among clonal genotypes is detectable with leaf spectra, using both multivariate and univariate approaches. Spectra predicted population identity with 100% accuracy among trees in the wild, 87%–98% accuracy within a common garden, and 86% accuracy across different environments. Multiple spectral indices of plant health had significant heritability, with genotype accounting for 10%–23% of spectral variation within populations and 14%–48% of the variation across all populations. Second, we found gene by environment interactions leading to population‐specific shifts in the spectral phenotype across common garden environments. Spectral indices indicate that genetically divergent populations made unique adjustments to their chlorophyll and water content in response to the same environmental stresses, so that detecting genetic identity is critical to predicting tree response to change. Third, spectral indicators of greenness and photosynthetic efficiency decreased when populations were transferred to growing environments with higher mean annual maximum temperatures relative to home conditions. This result suggests altered physiological strategies further from the conditions to which plants are locally adapted. Transfers to cooler environments had fewer negative effects, demonstrating that plant spectra show directionality in plant performance adjust- ments. Thus, leaf reflectance data can detect both local adaptation and plastic shifts in plant physiology, informing strategic restoration and conservation decisions by enabling high resolution tracking of genetic and phenotypic changes in response to climate change.more » « less
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Journal Article:
- https://doi.org/10.1002/ecy.70048
