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Record W2095284049 · doi:10.1890/14-0239.1

Ecological recovery in an Arctic delta following widespread saline incursion

2014· article· en· W2095284049 on OpenAlexafffund
Trevor C. Lantz, Steve V. Kokelj, Robert Fraser

Bibliographic record

VenueEcological Applications · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsNatural Resources CanadaGovernment of Northwest TerritoriesUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEnvironmental scienceTundraVegetation (pathology)EcosystemEcologyWetlandStorm surgeChronosequenceClimate changeRiparian zoneHabitatStormOceanographyGeology

Abstract

fetched live from OpenAlex

Arctic ecosystems are vulnerable to the combined effects of climate change and a range of other anthropogenic perturbations. Predicting the cumulative impact of these stressors requires an improved understanding of the factors affecting ecological resilience. In September of 1999, a severe storm surge in the Mackenzie Delta flooded alluvial surfaces up to 30 km inland from the coast with saline waters, driving environmental impacts unprecedented in the last millennium. In this study we combined field monitoring of permanent sampling plots with an analysis of the Landsat archive (1986-2011) to explore the factors affecting the recovery of ecosystems to this disturbance. Soil salinization following the 1999 storm caused the abrupt dieback of more than 30,000 ha of tundra vegetation. Vegetation cover and soil chemistry show that recovery is occurring, but the rate and spatial extent are strongly dependent on vegetation type, with graminoid- and upright shrub-dominated areas showing recovery after a decade, but dwarf shrub tundra exhibiting little to no recovery over this period. Our analyses suggest that recovery from salinization has been strongly influenced by vegetation type and the frequency of freshwater flooding following the storm. With increased ocean storm activity, rising sea levels, and reduced sea ice cover, Arctic coastal ecosystems will be more likely to experience similar disturbances in the future, highlighting the importance of combining field sampling with regional-scale remote sensing in efforts to detect, understand, and anticipate environmental change.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.996

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)0.0050.001

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 head0.037
GPT teacher head0.270
Teacher spread0.233 · 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.

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

Citations39
Published2014
Admission routes2
Has abstractyes

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