Search for: All records

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 Vc_max, 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. 

Abstract Abstract. Using herbarium specimens spanning 133 years and field-collected measurements, we assessed intraspecific trait (leaf structural and stomatal) variability from grass species in the Great Plains of North America. We focused on two widespread, closely related grasses from the tribe Paniceae: Dichanthelium oligosanthes subsp. scribnerianum (C3) and Panicum virgatum (C4). Thirty-one specimens per taxon were sampled from local herbaria from the years 1887 to 2013 to assess trait responses across time to changes in atmospheric [CO2] and growing season precipitation and temperature. In 2021 and 2022, the species were measured from eight grasslands sites to explore how traits vary spatially across natural continental precipitation and temperature gradients. Δ13C increased with atmospheric [CO2] for D. oligosanthes but decreased for P. virgatum, likely linked to increases in precipitation in the study region over the past century. Notably, this is the first record of decreasing Δ13C over time for a C4 species illustrating 13C linkages to climate. As atmospheric [CO2] increased, C:N increased and δ15N decreased for both species and %N decreased for D. oligosanthes. Across a large precipitation gradient, D. oligosanthes leaf traits were more responsive to changes in precipitation than those of P. virgatum. In contrast, only two traits of P. virgatum responded to increases in temperature across a gradient: specific leaf area (increase) and leaf dry matter content (decrease). The only shared significant trend between species was increased C:N with precipitation. Our work demonstrates that these closely related grass species with different photosynthetic pathways exhibited various trait responses across temporal and spatial scales, illustrating the key role of scale of inquiry for forecasting leaf trait responses to future environmental change. 

Abstract Hyperspectral remote sensing has the potential to map numerous attributes of the Earth’s surface, including spatial patterns of biological diversity. Grasslands are one of the largest biomes on Earth. Accurate mapping of grassland biodiversity relies on spectral discrimination of endmembers of species or plant functional types. We focused on spectral separation of grass lineages that dominate global grassy biomes: Andropogoneae (C₄), Chloridoideae (C₄), and Pooideae (C₃). We examined leaf reflectance spectra (350–2,500 nm) from 43 grass species representing these grass lineages from four representative grassland sites in the Great Plains region of North America. We assessed the utility of leaf reflectance data for classification of grass species into three major lineages and by collection site. Classifications had very high accuracy (94%) that were robust to site differences in species and environment. We also show an information loss using multispectral sensors, that is, classification accuracy of grass lineages using spectral bands provided by current multispectral satellites is much lower (accuracy of 85.2% and 61.3% using Sentinel 2 and Landsat 8 bands, respectively). Our results suggest that hyperspectral data have an exciting potential for mapping grass functional types as informed by phylogeny. Leaf‐level hyperspectral separability of grass lineages is consistent with the potential increase in biodiversity and functional information content from the next generation of satellite‐based spectrometers. 

Summary Evolutionary history plays a key role driving patterns of trait variation across plant species. For scaling and modeling purposes, grass species are typically organized into C₃vs C₄plant functional types (PFTs). Plant functional type groupings may obscure important functional differences among species. Rather, grouping grasses by evolutionary lineage may better represent grass functional diversity.We measured 11 structural and physiological traitsin situfrom 75 grass species within the North American tallgrass prairie. We tested whether traits differed significantly among photosynthetic pathways or lineages (tribe) in annual and perennial grass species.Critically, we found evidence that grass traits varied among lineages, including independent origins of C₄photosynthesis. Using a rigorous model selection approach, tribe was included in the top models for five of nine traits for perennial species. Tribes were separable in a multivariate and phylogenetically controlled analysis of traits, owing to coordination of important structural and ecophysiological characteristics.Our findings suggest grouping grass species by photosynthetic pathway overlooks variation in several functional traits, particularly for C₄species. These results indicate that further assessment of lineage‐based differences at other sites and across other grass species distributions may improve representation of C₄species in trait comparison analyses and modeling investigations.