Climate variability supersedes grazing to determine the anatomy and physiology of a dominant grassland species

Bachle, Seton; Nippert, Jesse B.

doi:10.1007/s00442-022-05106-x

Cited by 3 publications

(4 citation statements)

References 77 publications

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“…Phylogeny‐based approaches have enabled the partitioning of sources of spectral variability in regional floras (Griffith, Byrd, Anderegg, et al., 2023) and the mapping of dominant plant lineages (Griffith et al., 2023a, 2023b). Most studies showing phylogenetic conservatism in leaf spectra, however, are limited to single sites and few sampling periods despite recognition that leaf traits are highly plastic within a given species and change under varying resource limitations (Bachle & Nippert, 2022). Thus, a key question is which leaf spectra wavelengths vary with phylogeny, and are changes in these wavelengths discernible under different environmental contexts?…”

Section: Introductionmentioning

confidence: 99%

Grass Evolutionary Lineages Can Be Identified Using Hyperspectral Leaf Reflectance

Slapikas,

Pau,

Donnelly

et al. 2024

JGR Biogeosciences

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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.

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Section: Introductionmentioning

confidence: 99%

Grass Evolutionary Lineages Can Be Identified Using Hyperspectral Leaf Reflectance

Slapikas,

Pau,

Donnelly

et al. 2024

JGR Biogeosciences

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“…Relationships between species distributions and landscape attributes shed light on factors shaping current distributions, characterize use within those distributions, and better predict changes in future distributions (Matthiopoulos et al, 2020). Organisms in dynamic systems, such as many mid‐continental grasslands, exhibit phenotypic plasticity in their phenology (Wagle et al, 2019), physiology (Bachle & Nippert, 2022), and behavior (McMillan et al, 2021; McNew et al, 2013) in response to environmental variability over space and time. Mobile species (e.g., grassland birds) may also alter their dispersal and settlement decisions, tracking conditions that presumably increase their survival and reproduction (Kentie et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

The long shadow of woody encroachment: An integrated approach to modeling grassland songbird habitat

Silber,

Hefley,

Castro‐Miller

et al. 2024

Ecological Applications

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Animals must track resources over relatively fine spatial and temporal scales, particularly in disturbance‐mediated systems like grasslands. Grassland birds respond to habitat heterogeneity by dispersing among sites within and between years, yet we know little about how they make post‐dispersal settlement decisions. Many methods exist to quantify the resource selection of mobile taxa, but the habitat data used in these models are frequently not collected at the same location or time that individuals were present. This spatiotemporal misalignment may lead to incorrect interpretations and adverse conservation outcomes, particularly in dynamic systems. To investigate the extent to which spatially and temporally dynamic vegetation conditions and topography drive grassland bird settlement decisions, we integrated multiple data sources from our study site to predict slope, vegetation height, and multiple metrics of vegetation cover at any point in space and time within the temporal and spatial scope of our study. We paired these predictions with avian mark‐resight data for 8 years at the Konza Prairie Biological Station in NE Kansas to evaluate territory selection for Grasshopper Sparrows (Ammodramus savannarum), Dickcissels (Spiza americana), and Eastern Meadowlarks (Sturnella magna). Each species selected different types and amounts of herbaceous vegetation cover, but all three species preferred relatively flat areas with less than 6% shrub cover and less than 1% tree cover. We evaluated several scenarios of woody vegetation removal and found that, with a targeted approach, the simulated removal of just one isolated tree in the uplands created up to 14 ha of grassland bird habitat. This study supports growing evidence that small amounts of woody encroachment can fragment landscapes, augmenting conservation threats to grassland systems. Conversely, these results demonstrate that drastic increases in bird habitat area could be achieved through relatively efficient management interventions. The results and approaches reported pave the way for more efficient conservation efforts in grasslands and other systems through spatiotemporal alignment of habitat with animal behaviors and simulated impacts of management interventions.

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“…More specifically, these morphological traits are framed by underlying structures at the anatomical level in leaf and root tissues [57]. Anatomical leaf traits within and across families in Poaceae also have been observed to influence physiological responses most often associated with hydraulics (xylem lumen area/diameter; resistance to cavitation) [58–61]. However, the aforementioned physiological, morphological, and anatomical traits may not convey equal benefits in drought response or recovery across and within Poaceae lineages.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Physiological responses to drought stress and recovery reflect differences in leaf function and anatomy among grass lineages

Bachle

Zaricor

Griffith

et al. 2022

Preprint

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Grasses are cosmopolitan, existing in many biome and climate types from xeric to tropical. Traits that control physiological responses to drought vary strongly among grass lineages, suggesting that tolerance strategies may differ with evolutionary history. Here, we withheld water from 12 species representing six tribes of grasses to compare how species respond to drought in different grass lineages. We measured physiological, morphological, and anatomical traits. Dominant lineages from tropical savannas, like Andropogoneae, tolerated drought due to above and belowground morphological traits (specific leaf area and root length, SLA and SRL), while temperate grasses in this study utilized conservative leaf physiology (gas exchange) and anatomy traits. Increased intrinsic water-use efficiency coincided with a larger number of stomata, resulting in greater water loss (with inherently greater carbon gain) and increased drought sensitivity. Inherent leaf and root economic strategies impacting drought response were observed in all species, resulting in either high SLA or SRL, but not both. Our results indicate that grasses subjected to severe drought were influenced by anatomical traits (e.g., number of stomata and xylem area) and similar within lineages. In addition, grasses recovered at least 50% of physiological functioning across all lineages and 92% within Andropogoneae species, illustrating how drought can influence functional responses across diverse grass lineages.

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Climate variability supersedes grazing to determine the anatomy and physiology of a dominant grassland species

Cited by 3 publications

References 77 publications

Grass Evolutionary Lineages Can Be Identified Using Hyperspectral Leaf Reflectance

Grass Evolutionary Lineages Can Be Identified Using Hyperspectral Leaf Reflectance

The long shadow of woody encroachment: An integrated approach to modeling grassland songbird habitat

Physiological responses to drought stress and recovery reflect differences in leaf function and anatomy among grass lineages

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