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Hierarchical Organization of Ecosystems at Multiple Spatial Scales on the Yukon-Kuskokwim Delta, Alaska, U.S.A.

2000· article· en· W4231509052 on OpenAlexaboutno aff
M. Torre Jorgenson

Bibliographic record

VenueArctic Antarctic and Alpine Research · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal wetland ecosystem dynamics
Canadian institutionsnot available
FundersU.S. Geological SurveyNational Science Foundation
KeywordsEcotypeFloodplainEcologyEcosystemEnvironmental sciencePermafrostRiparian zoneBiology

Abstract

fetched live from OpenAlex

I conducted an ecological land survey near Hazen Bay, on the Yukon-Kuskokwim Delta of Alaska during 1994–1998 in order to assess potential effects of sea-level rise on coastal ecosystems in this region. Independent classification of three landscape components grouped ecological characteristics of the area into 10 geomorphic units (e.g., tidal flats, abandoned floodplain cover deposits), 9 surface forms (e.g., levees, basins), and 18 plant associations (e.g., Carex rariflora–Salix fuscescens). I then used hierarchical associations among these landscape components to derive an ecosystem classification at three levels of organization that included 10 ecosections (based on geomorphology), 11 ecoseries (based on surface forms and geomorphology), and 27 ecotypes (primarily based on vegetation).The nature and distribution of ecosystems at all levels showed a strong influence from geomorphic processes. The active floodplain, with frequent flooding and sedimentation, had brackish ecotypes that were dominated by graminoids and forbs. The inactive floodplain, where flooding and sedimentation were infrequent, had slightly brackish ecotypes with a wide diversity of species and growth forms. In contrast, the abandoned floodplain, which lacked flooding and sediment deposition, but was strongly affected by permafrost aggradation, had ecotypes that were dominated by evergreen shrubs, mosses, and lichens that were intolerant to salts, but tolerated acidic, nutrient-poor conditions. Ecotypes with similar vegetation generally had similar environmental properties, including surface elevation, soil morphology, sedimentation, organic matter accumulation, thaw depths, water depths, pH, and electrical conductivity. When similar ecotypes were aggregated into ecosections based on geomorphic similarities, differences in ecological properties increased.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.122
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.001

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 head0.015
GPT teacher head0.246
Teacher spread0.231 · 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; both teacher heads agree on what is shown here.

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

Citations38
Published2000
Admission routes1
Has abstractyes

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