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Record W2774412369 · doi:10.58809/wxjf8098

Gas Exchange And Leaf Anatomy Of Andropogon Gerardii Ecotypes Over A Climatic Gradient Of The Great Plains

2012· dissertation· en· W2774412369 on OpenAlexfundno aff
Jacob Olsen

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicBioenergy crop production and management
Canadian institutionsnot available
FundersNational Institute of Food and AgricultureLeading Edge Endowment FundDirectorate for Biological SciencesU.S. Department of Agriculture
KeywordsEcotypeDeserts and xeric shrublandsTranspirationStomatal conductanceAndropogonBiologyWater-use efficiencyPopulationBotanyAgronomyPhotosynthesisEcology

Abstract

fetched live from OpenAlex

The phenotype of two Andropogon gerardii subspecies, big bluestem and sand bluestem, varies broadly throughout the Great Plains of North America, giving rise to ecotypes within the species. This study sought to discriminate between genetic and environmental variation of big bluestem and sand bluestem by examining gas exchange and leaf anatomy in common gardens across a climatic gradient of the Great Plains. Thirteen populations of big bluestem and one population of sand bluestem, constituting five ecotypes, were planted in community plots and a single plant plots in a common garden at each of four sites ranging from western Kansas to southern Illinois. Photosynthesis, stomatal conductance, intercellular CO2, transpiration, and intrinsic water use efficiency were measured three times in the 2010 growing season. In addition, leaf thickness, midrib thickness, bulliform cells, interveinal distance, and vein size were assessed by light microscopy. Abundant phenotypic variation exists among ecotypes within community plots. At all planting sites, big bluestem ecotypes from xeric environments had higher photosynthesis, stomatal conductance, and transpiration compared to mesic ecotypes. Single plant plots also had abundant phenotypic variation; ecotypes native to xeric environments also had higher photosynthesis, stomatal conductance, and transpiration, but differences were more distinct. In addition, sand bluestem, which was only planted in single plant plots, had similar photosynthesis, stomatal conductance, and transpiration to the big bluestem ecotype native to the most xeric environment. Sand bluestem also had higher water use efficiency and lower intercellular CO2 than any big bluestem ecotype. Leaf anatomy assessments indicated xeric ecotypes of A. gerardii had thicker leaves and fewer bulliform cells. Environmental variation was as important as genetic variation for gas exchange and leaf anatomy in both community and single plant plots. Compared to xeric sites, mesic sites had higher photosynthesis, stomatal conductance, and water use efficiency and lower intercellular CO2 and transpiration in community and single plant plots. Leaves from mesic sites also had thicker midribs, larger veins, and a greater proportion of bulliform cells. Ecotypes of A. gerardii across the Great Plains are adapted to water availability. Drought-adapted ecotypes of A. gerardii were shorter in stature and had smaller, thicker, narrower leaves, which reduced the evaporative surface area of these plants. Evidently, A. gerardii controls water loss by reducing evaporative surface area more than it does by increasing the proportion of bulliform cells. This allows drought-adapted ecotypes to have higher photosynthetic rates, stomatal conductances, and transpiration rates in both mesic and xeric environments compared to ecotypes native to mesic environments. This study brings to light potential responses of big bluestem ecotypes to climate change. This study also indicates the phenotypic variation among big bluestem could prove useful in the restoration of native prairies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.235
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2012
Admission routes1
Has abstractyes

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