Imaging spectroscopy is a burgeoning tool for understanding ecosystem functioning on large spatial scales, yet the application of this technology to assess intra-specific trait variation across environmental gradients has been poorly tested. Selection of specific genotypes via environmental filtering plays an important role in driving trait variation and thus functional diversity across space and time, but the relative contributions of intra-specific trait variation and species turnover are still unclear. To address this issue, we quantified the variation in reflectance spectra within and between six uniform stands of Metrosideros polymorpha across elevation and soil substrate age gradients on Hawai‘i Island. Airborne imaging spectroscopy and light detection and ranging (LiDAR) data were merged to capture and isolate sunlit portions of canopies at the six M. polymorpha-dominated sites. Both intra-site and inter-site spectral variations were quantified using several analyses. A support vector machine (SVM) model revealed that each site was spectrally distinct, while Euclidean distances between site centroids in principal components (PC) space indicated that elevation and soil substrate age drive the separation of canopy spectra between sites. Coefficients of variation among spectra, as well as the intrinsic spectral dimensionality of the data, demonstrated the hierarchical effect of soil substrate age, followed by elevation, in determining intra-site variation. Assessments based on leaf trait data estimated from canopy reflectance resulted in similar patterns of separation among sites in the PC space and distinction among sites in the SVM model. Using a highly polymorphic species, we demonstrated that canopy reflectance follows known ecological principles of community turnover and thus how spectral remote sensing addresses forest community assembly on large spatial scales.
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.
more » « less- Award ID(s):
- 2218932
- PAR ID:
- 10539467
- Publisher / Repository:
- MDPI
- Date Published:
- Journal Name:
- Remote Sensing
- Volume:
- 15
- Issue:
- 19
- ISSN:
- 2072-4292
- Page Range / eLocation ID:
- 4707
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Plant traits are useful for predicting how species may respond to environmental change and/or influence ecosystem properties. Understanding the extent to which traits vary within species and across climatic gradients is particularly important for understanding how species may respond to climate change. We explored whether climate drives spatial patterns of intraspecific trait variation for three traits (specific leaf area (SLA), plant height, and leaf nitrogen content (Nmass)) across 122 grass species (family: Poaceae) with a combined distribution across six continents. We tested the hypothesis that the sensitivity (i.e. slope) of intraspecific trait responses to climate across space would be related to the species' typical form and function (e.g. leaf economics, stature and lifespan). We observed both positive and negative intraspecific trait responses to climate with the distribution of slope coefficients across species straddling zero for precipitation, temperature and climate seasonality. As hypothesized, variation in slope coefficients across species was partially explained by leaf economics and lifespan. For example, acquisitive species with nitrogen-rich leaves grew taller and produced leaves with higher SLA in warmer regions compared to species with low Nmass. Compared to perennials, annual grasses invested in leaves with higher SLA yet decreased height and Nmass in regions with high precipitation seasonality (PS). Thus, while the influence of climate on trait expression may at first appear idiosyncratic, variation in trait–climate slope coefficients is at least partially explained by the species' typical form and function. Overall, our results suggest that a species' mean location along one axis of trait variation (e.g. leaf economics) could influence how traits along a separate axis of variation (e.g. plant size) respond to spatial variation in climate.more » « less
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1. Host plant phenotypic traits affect the structure of the associated consumer community and mediate species interactions. Intraspecific variation in host traits is well documented, although a functional understanding of variable traits that drive herbivore community response is lacking. We address this gap by modelling the trait‐environment relationship using insect traits and host plant traits in a multilevel model.
2. We compare herbivore assemblages from the canopy of the phenotypically variable tree
Metrosideros polymorpha on Hawai‘i Island. Multiple distinct varieties ofM. polymorpha frequently co‐occur, with variation in morphological traits. Using this system, we identify host and insect traits that underlie patterns of herbivore abundance and quantify the strength of host‐insect trait interactions.3. This work examines plant‐insect interactions at a community scale, across 36 herbivore species in three orders. We find that co‐occurring trees of varying phenotype support distinct communities. Leaf traits, including specific leaf area, trichome presence, and leaf nutrients, explain 46% of variation in insect communities. We find that feeding guild and nymphal life history are correlated with host plant traits, and we show that model predictions are improved by including the host and insect trait interaction.
4. This study demonstrates how insect herbivores traits influence community response to morphologically variable hosts. Environmental heterogeneity indirectly affected herbivore community structure via intraspecific variation in host plants, providing an important source of variation for maintaining diversity in the broader community.
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Abstract The utility of plant functional traits for predictive ecology relies on our ability to interpret trait variation across multiple taxonomic and ecological scales. Using extensive data sets of trait variation within species, across species and across communities, we analysed whether and at what scales leaf economics spectrum (
LES ) traits show predicted trait–trait covariation. We found that most variation inLES traits is often, but not universally, at high taxonomic levels (between families or genera in a family). However, we found that trait covariation shows distinct taxonomic scale dependence, with some trait correlations showing opposite signs within vs. across species.LES traits responded independently to environmental gradients within species, with few shared environmental responses across traits or across scales. We conclude that, at small taxonomic scales, plasticity may obscure or reverse the broad evolutionary linkages between leaf traits, meaning that variation inLES traits cannot always be interpreted as differences in resource use strategy. -
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Premise Leaf economic spectrum (LES) theory has historically been employed to inform vegetation models of ecosystem processes, but largely neglects intraspecific variation and biotic interactions. We attempt to integrate across environment–plant trait–herbivore interactions within a species at a range‐wide scale.
Methods We measured traits in 53 populations spanning the range of common milkweed (
Asclepias syriaca ) and used a common garden to determine the role of environment in driving patterns of intraspecific variation. We used a feeding trial to determine the role of plant traits in monarch (Danaus plexippus ) larval development.Results Trait–trait relationships largely followed interspecific patterns in LES theory and persisted in a common garden when individual traits change. Common milkweed showed intraspecific variation and biogeographic clines in traits. Clines did not persist in a common garden. Larvae ate more and grew larger when fed plants with more nitrogen. A longitudinal environmental gradient in precipitation corresponded to a resource gradient in plant nitrogen, which produces a gradient in larval performance.
Conclusions Biogeographic patterns in common milkweed traits can sometimes be predicted from LES, are largely driven by environmental conditions, and have consequences for monarch larval performance. Changes to nutrient dynamics of landscapes with common milkweed could potentially influence monarch population dynamics. We show how biogeographic trends in intraspecific variation can influence key ecological interactions, especially in common species with large distributions.
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/rs15194707
