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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. Plain Language Summary: Understanding and identifying changes in plant diversity along broad environmental gradients requires scalable and reliable data. Spectroscopy has been shown to provide data across scales with the ability to measure plant reflectance at various extents (e.g., leaf, plot, and landscapes) with high spectral resolution and broad coverage of the electromagnetic spectrum (350–2,500 nm). In grasses, evolutionary lineage captures major axes in plant biodiversity and functional variation. We show that identifying grass evolutionary lineages from spectroscopy is possible based on common characteristics in their leaf‐level spectra. We classified 43 grass species from four sites in North America into their respective evolutionary lineages with very high accuracy (>90%) based on similarities in their leaf spectra. Classifying grass species into lineages using coarser spectral resolution data, similar to existing multispectral satellites, Sentinel 2 and Landsat 8, resulted in lower accuracy due to a loss of information from decreasing the spectral resolution. Grass lineages likely have similar spectra because of common leaf traits that evolved under similar ecological contexts. The importance of these distinctions found in the spectral reflectance of dominant grass lineages, should help our efforts in mapping and understanding grassland ecosystem function and patterns of biodiversity. Key Points: Globally dominant grass lineages are identifiable using hyperspectral leaf signaturesKey wavelengths for separating grass lineages were visible, red‐edge and shortwave infrared regions, rarely measured by multispectral sensorsHyperspectral sensors have the potential to improve remote sensing identification of grass functional types over multispectral sensors [ABSTRACT FROM AUTHOR]

Grassland ecosystems are historically shaped by climate, fire, and grazing which are essential ecological drivers. These grassland drivers influence morphology and productivity of grasses via physiological processes, resulting in unique water and carbon-use strategies among species and populations. Leaf-level physiological responses in plants are constrained by the underlying anatomy, previously shown to reflect patterns of carbon assimilation and water-use in leaf tissues. However, the magnitude to which anatomy and physiology are impacted by grassland drivers remains unstudied. To address this knowledge gap, we sampled from three locations along a latitudinal gradient in the mesic grassland region of the central Great Plains, USA during the 2018 (drier) and 2019 (wetter) growing seasons. We measured annual biomass and forage quality at the plot level, while collecting physiological and anatomical traits at the leaf-level in cattle grazed and ungrazed locations at each site. Effects of ambient drought conditions superseded local grazing treatments and reduced carbon assimilation and total productivity in A. gerardii. Leaf-level anatomical traits, particularly those associated with water-use, varied within and across locations and between years. Specifically, xylem area increased when water was more available (2019), while xylem resistance to cavitation was observed to increase in the drier growing season (2018). Our results highlight the importance of multi-year studies in natural systems and how trait plasticity can serve as vital tool and offer insight to understanding future grassland responses from climate change as climate played a stronger role than grazing in shaping leaf physiology and anatomy. [ABSTRACT FROM AUTHOR]

The expansion of woody species into grasslands has altered community structure and ecosystem function of grasslands worldwide. In tallgrass prairie of the Central Great Plains, USA, decreased fire frequency and intensity have increased the cover and abundance of woody species. In particular, clonal shrub cover has increased at accelerated rates due to vegetative reproduction and resprouting after disturbance. We measured the intra-clonal stem demography and relative growth rates (estimated change in woody biomass) of the shrub Cornus drummondii in response to fire frequency (4 vs 20 year burn intervals) and simulated browsing during the 2018 and 2019 growing seasons at Konza Prairie Biological Station (Manhattan, Kansas). Overall, infrequent fire (4 year burn interval) increased intra-clonal stem relative growth rates and shrub relative growth rates. Intra-clonal stem relative growth rates were reduced in unbrowsed clones in 2018 due to drought and simulated browsing reduced intra-clonal stem relative growth rates in 2019. Additionally, simulated browsing nearly eliminated flower production within clones but did not affect intra-clonal stem mortality or recruitment within a growing season. Fire in conjunction with simulated browsing reduced estimated relative growth rates for entire shrub clones. Browsed shrubs that experienced prescribed fire in 2017 had reduced intra-clonal stem densities compared to unbrowsed shrubs and stem densities of browsed shrubs did not recover in 2018 or 2019. These results illustrate that infrequent fire alone promotes the expansion of clonal shrubs in tallgrass prairie and multiple interacting disturbances (e.g., fire and browsing) are required to control the spread of clonal shrubs into grasslands. [ABSTRACT FROM AUTHOR]

Background and Aims Andropogon gerardii is a highly productive C4 grass species with a large geographic range throughout the North American Great Plains, a biome characterized by a variable temperate climate. Plant traits are often invoked to explain growth rates and competitive abilities within broad climate gradients. For example, plant competition models typically predict that species with large geographic ranges benefit from variation in traits underlying high growth potential. Here, we examined the relationship between climate variability and leaf-level traits in A. gerardii , emphasizing how leaf-level microanatomical traits serve as a mechanism that may underlie variation in commonly measured traits, such as specific leaf area (SLA). Methods Andropogon gerardii leaves were collected in August 2017 from Cedar Creek Ecosystem Science Reserve (MN), Konza Prairie Biological Station (KS), Platte River Prairie (NE) and Rocky Mountain Research Station (SD). Leaves from ten individuals from each site were trimmed, stained and prepared for fluorescent confocal microscopy to analyse internal leaf anatomy. Leaf microanatomical data were compared with historical and growing season climate data extracted from PRISM spatial climate models. Key Results Microanatomical traits displayed large variation within and across sites. According to AICc (Akaike's information criterion adjusted for small sample sizes) selection scores, the interaction of mean precipitation and temperature for the 2017 growing season was the best predictor of variability for the anatomical and morphological traits measured here. Mesophyll area and bundle sheath thickness were directly correlated with mean temperature (annual and growing season). Tissues related to water-use strategies, such as bulliform cell and xylem area, were significantly correlated with one another. Conclusions The results indicate that (1) microanatomical trait variation exists within this broadly distributed grass species, (2) microanatomical trait variability appears likely to impact leaf-level carbon and water use strategies, and (3) microanatomical trait values vary across climate gradients, and may underlie variation in traits measured at larger ecological scales. [ABSTRACT FROM AUTHOR]

Grassland ecosystems globally are being negatively impacted by changes in climate, disturbance regimes, nutrient flux, and consumer guilds. Changes in the trophic ecology of consumers can substantially influence local resources, contributing to shifting diversity, community turnover, and other processes of ecosystem change. Small mammals are diverse and abundant within grasslands and yet the impact of changing ecosystems on small mammals and the role of these mammals as consumers are still both under‐studied. We assessed small mammal resource use within grassland and woodland vegetation types that have resulted from landscape‐scale experimental disturbance through fire treatments within the tallgrass prairie ecoregion of the North American Great Plains. We predicted that resource use would vary significantly among grassland vs. woodland communities, in turn reducing the role of small mammals in contributing to future maintenance of native prairies. We sampled five dominant species of rodents across three years and multiple habitats. Using stable isotope analysis, we investigated isotopic niche area and overlap to infer variation in diet, both within and among species. Resource use shifted in bivariate isotopic space seasonally but not across years when combining all species and habitats. Inferred spring diet (based on fur samples) was highly diverse and overlapping. Summer isotopic values (based on liver tissue) in woody habitat treatments were narrower and overlapped less than within grassland habitats. Consumers generally shifted from C4 herbivory to C3 herbivory, or greater omnivory, when analyzing grassland, shrubland, and woodland habitats respectively. Within the tallgrass prairie ecosystem, small mammal populations in herbaceous‐dominated habitats use a broader variety of resources than small mammals in proximate woody‐dominated habitats. As native grasslands experience woody encroachment, small mammal assemblages experience turnover of dominant species and associated changes in diet. Ecosystem changes such as cessation of frequent fire resulting in more woody habitats may include reduced roles by native small mammals as consumers/dispersers/propagators of native grassland plants. [ABSTRACT FROM AUTHOR]