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Record W2768020423 · doi:10.58809/votq8559

Flooding tolerance of native and nonnative grasses: Variation in photosynthesis, transpiration, respiration, and carbon isotope discrimination

2010· dissertation· en· W2768020423 on OpenAlexfundno aff
Elizabeth F. Waring

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicPlant responses to water stress
Canadian institutionsnot available
FundersU.S. Fish and Wildlife ServiceDirectorate for Biological SciencesLeading Edge Endowment Fund
KeywordsPhragmitesPhalaris arundinaceaTranspirationAgronomySorghumPhotosynthesisEnvironmental scienceStomatal conductanceSpartinaBiologyBotanyWetlandMarshEcology

Abstract

fetched live from OpenAlex

Invasion by nonnative plants is particularly prevalent in wetlands. While the ecological patterns in wetland plants are well known, it is less well known how flooding-related soil conditions influence the physiological success of introduced species in wetlands. In chapter 1, effects of flooding were measured in invasive common reed (Phragmites australis), reed canary grass (Phalaris arundinacea), Johnson grass (Sorghum halepense), and native prairie cordgrass (Spartina pectinata). The four species were kept at four levels of flooding (deep flooding, medium flooding, low flooding, and dry conditions), and their responses were measured after 7 and 28 days of treatment using by a Li-Cor LI-6400 photosynthesis and fluorescence system. Measurements included light harvesting abilities, CO2 fixation rates, leaf carbon isotope ratios, and root anaerobic enzyme activities. CO2 fixation and light harvesting abilities in Phragmites were maximized at deep flooding conditions whereas they were maximized in Phalaris at medium flooding conditions. Light harvesting abilities in Sorghum were maximized at deep flooding conditions after 7 days. However, at 28 days most of the Sorghum had died. Native Spartina had the lowest light harvesting and CO2 fixation abilities after 7 days of flooding. After 28 days of flooding, light harvesting abilities of Spartina were maximized at deep flooding levels, but the rates were lower than Phragmites. In chapter 2, flooding-sensitive Sorghum halepense and flooding-tolerant Phragmites australis (n=5) were flooded to 8 cm depth or kept dry for 7 days. Transpiration, stomatal conductance, boundary layer conductance, and vapor conductance were measured for each. Transpiration was significantly higher in drained treatments compared to flooded treatments for Sorghum. However, transpiration was significantly higher in flooded treatments compared to drained treatments for Phragmites. Thus, there was a significant species x treatment interaction in transpiration. A similar interaction was detected in both stomatal and vapor conductances. Phragmites had increased stomatal conductance when flooded, which indicated a high physiological tolerance to waterlogged soils. This allowed Phragmites to photosynthesize under waterlogged conditions and to be successful as wetland invaders. Further information on the conditions that maximize stomatal opening for Phragmites can help management efforts. By contrast, stomatal conductance in Sorghum was decreased under flooding, indicating a greater sensitivity to flooding. The sampled population of Sorghum is therefore not a threat to invade chronically flooded soils based on these results. Additional work will be needed to test the ability of Sorghum to acclimate to wet environments. Increased photosynthesis rates under flooded conditions, especially in short-term flooding, might help invasive grasses to invade wetland settings.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

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 head0.012
GPT teacher head0.226
Teacher spread0.214 · 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".

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Citations0
Published2010
Admission routes1
Has abstractyes

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