Abstract To predict ecological responses at broad environmental scales, grass species are commonly grouped into two broad functional types based on photosynthetic pathway. However, closely related species may have distinctive anatomical and physiological attributes that influence ecological responses, beyond those related to photosynthetic pathway alone. Hyperspectral leaf reflectance can provide an integrated measure of covarying leaf traits that may result from phylogenetic trait conservatism and/or environmental conditions. Understanding whether spectra‐trait relationships are lineage specific or reflect environmental variation across sites is necessary for using hyperspectral reflectance to predict plant responses to environmental changes across spatial scales. We measured hyperspectral leaf reflectance (400–2400 nm) and 12 structural, biochemical, and physiological leaf traits from five grass‐dominated sites spanning the Great Plains of North America. We assessed if variation in leaf reflectance spectra among grass species is explained more by evolutionary lineage (as captured by tribes or subfamilies), photosynthetic pathway (C3or C4), or site differences. We then determined whether leaf spectra can be used to predict leaf traits within and across lineages. Our results using redundancy analysis ordination (RDA) show that grass tribe identity explained more variation in leaf spectra (adjustedR2 = 0.12) than photosynthetic pathway, which explained little variation in leaf spectra (adjustedR2 = 0.00). Furthermore, leaf reflectance from the same tribe across multiple sites was more similar than leaf reflectance from the same site across tribes (adjustedR2 = 0.12 and 0.08, respectively). Across all sites and species, trait predictions based on spectra ranged considerably in predictive accuracies (R2 = 0.65 to <0.01), butR2was >0.80 for certain lineages and sites. The relationship between Vcmax, a measure of photosynthetic capacity, and spectra was particularly promising. Chloridoideae, a lineage more common at drier sites, appears to have distinct spectra‐trait relationships compared with other lineages. Overall, our results show that evolutionary relatedness explains more variation in grass leaf spectra than photosynthetic pathway or site, but consideration of lineage‐ and site‐specific trait relationships is needed to interpret spectral variation across large environmental gradients.
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Idiosyncrasy and predictability in intraspecific trait–climate relationships of grasses
Abstract Many plant species can exhibit remarkable variation in leaf characteristics, depending on their abiotic and biotic environment. Environmental changes therefore have the potential to alter leaf traits, which in turn scale up to influence ecosystem processes including net primary productivity, susceptibility to fire, and palatability to herbivores. It is not well understood how consistent trait–environment relationships are among species, across sites and over time. This presents a fundamental challenge for functional ecology, because no study can measure all relevant species in all places at all times. Thus, understanding the limits of transferability is critical. We collected leaf trait measurements on 13 species of grass (family: Poaceae) across 11 sites and five years (n = 3091 individuals). Sites were arrayed along a spatial precipitation gradient in coastal northern California (annual precipitation of 590–1350 mm) with substantial interannual precipitation variability (from 60% below the 30‐year average to 100% above average). Temporal and spatial linear relationships between precipitation and specific leaf area (SLA) appear at first idiosyncratic, with each species sometimes displaying positive and sometimes negative responses. However, this variation arises from sampling different portions of an underlying hump‐shaped relationship, which was shared across most species. This hump‐shaped relationship was driven primarily by changes in leaf tissue density. These results suggest the potential for transferability among species, as well as between space and time, as long as the gradients are sufficiently long to capture the nonlinear response. Future work could explore the physiological basis of the nonlinear SLA response, including the possibility that distinct physiological mechanisms are operating at the two extremes of the gradient.
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- Award ID(s):
- 2046733
- PAR ID:
- 10522649
- Publisher / Repository:
- ESA
- Date Published:
- Journal Name:
- Ecosphere
- Volume:
- 15
- Issue:
- 4
- ISSN:
- 2150-8925
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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