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The role of intraspecific trait variation in functional ecology has gained traction in recent years as many papers have observed its importance in driving community diversity and ecology. Yet much of the work in this field relies on field-based trait surveys. Here, we used continuous canopy trait information derived from remote sensing data of a highly polymorphic tree species, Metrosideros polymorpha, to quantify environmental controls on intraspecific trait variation. M. polymorpha, an endemic, keystone tree species in Hawai’i, varies morphologically, chemically, and genetically across broad elevation and soil substrate age gradients, making it an ideal model organism to explore large-scale environmental drivers of intraspecific trait variation. M. polymorpha canopy reflectance (visible to shortwave infrared; 380–2510 nm) and light detection and ranging (LiDAR) data collected by the Global Airborne Observatory were modeled to canopy trait estimates of leaf mass per area, chlorophyll a and b, carotenoids, total carbon, nitrogen, phosphorus, phenols, cellulose, and top of canopy height using previously developed leaf chemometric equations. We explored how these derived traits varied across environmental gradients by extracting elevation, slope, aspect, precipitation, and soil substrate age data at canopy locations. We then obtained the feature importance values of the environmental factors in predicting each leaf trait by training random forest models to predict leaf traits individually. Of these environmental factors, elevation was the most important predictor for all canopy traits. Elevation not only affected canopy traits directly but also indirectly by influencing the relationships between soil substrate age and canopy traits as well as between nitrogen and other traits, as indicated by the change in slope between the variables at different elevation ranges. In conclusion, intraspecific variation in M. polymorpha traits derived from remote sensing adheres to known leaf economic spectrum (LES) patterns as well as interspecific LES traits previously mapped using imaging spectroscopy.
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Montane Temperate-Boreal Forests Retain the Leaf Economic Spectrum Despite Intraspecific Variability
Trait-based analyses provide powerful tools for developing a generalizable, physiologically grounded understanding of how forest communities are responding to ongoing environmental changes. Key challenges lie in (1) selecting traits that best characterize the ecological performance of species in the community and (2) determining the degree and importance of intraspecific variability in those traits. Recent studies suggest that globally evident trait correlations (trait dimensions), such as the leaf economic spectrum, may be weak or absent at local scales. Moreover, trait-based analyses that utilize a mean value to represent a species may be misleading. Mean trait values are particularly problematic if species trait value rankings change along environmental gradients, resulting in species trait crossover. To assess how plant traits (1) covary at local spatial scales, (2) vary across the dominant environmental gradients, and (3) can be partitioned within and across taxa, we collected data on 9 traits for 13 tree species spanning the montane temperate—boreal forest ecotones of New York and northern New England. The primary dimension of the trait ordination was the leaf economic spectrum, with trait variability among species largely driven by differences between deciduous angiosperms and evergreen gymnosperms. A second dimension was related to variability in nitrogen to phosphorous levels and stem specific density. Levels of intraspecific trait variability differed considerably among traits, and was related to variation in light, climate, and tree developmental stage. However, trait rankings across species were generally conserved across these gradients and there was little evidence of species crossover. The persistence of the leaf economics spectrum in both temperate and high-elevation conifer forests suggests that ecological strategies of tree species are associated with trade-offs between resource acquisition and tolerance, and may be quantified with relatively few traits. Furthermore, the assumption that species may be represented with a single trait value may be warranted for some trait-based analyses provided traits were measured under similar light levels and climate conditions.
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- Award ID(s):
- 1759724
- PAR ID:
- 10323411
- Date Published:
- Journal Name:
- Frontiers in Forests and Global Change
- Volume:
- 4
- ISSN:
- 2624-893X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3389/ffgc.2021.754063
