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Record W2889889310 · doi:10.1111/rec.12890

Incomplete recovery of plant diversity in restored prairie wetlands on agricultural landscapes

2018· article· en· W2889889310 on OpenAlexafffundabout
Saloni Salaria, R.D. Howard, Shari Clare, Irena F. Creed

Bibliographic record

VenueRestoration Ecology · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsUniversity of SaskatchewanWestern University
FundersAlberta Land Institute, University of AlbertaAlberta Innovates Bio SolutionsAlberta Conservation Association
KeywordsWetlandSpecies richnessVegetation (pathology)Native plantEcologyChronosequenceRestoration ecologyPlant communityHabitatBiological dispersalBiodiversitySpecies diversityIntroduced speciesEnvironmental scienceGeographyAgroforestryEcological successionBiologyPopulation

Abstract

fetched live from OpenAlex

Restoration efforts are being implemented globally to mitigate the degradation and loss of wetland habitat; however, the rate and success of wetland vegetation recovery post‐restoration is highly variable across wetland classes and geographies. Here, we measured the recovery of plant diversity along a chronosequence of restored temporary and seasonal prairie wetlands ranging from 0 to 23 years since restoration, including drained and natural wetlands embedded in agricultural and natural reserve landscapes in central Alberta, Canada. We assessed plant diversity using the following structural indicators: percent cover of hydrophytes, native and non‐native species, species richness, and community composition. Our findings indicate that plant diversity recovered to resemble reference wetlands in agricultural landscapes within 3–5 years of restoration; however, restored wetlands maintained significantly lower species richness and a distinct community composition compared to reference wetlands located within natural reserves. Early establishment of non‐native species during recovery, dispersal limitation, and depauperated native seed bank were probable barriers to complete recovery. Determining the success of vegetation recovery provides important knowledge that can be used to improve restoration strategies, especially considering projected future changes in land use and climate.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.081
Threshold uncertainty score0.936

Codex and Gemma teacher scores by category

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 head0.016
GPT teacher head0.226
Teacher spread0.211 · 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 teacher head, 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

Citations16
Published2018
Admission routes3
Has abstractyes

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