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Responses to Riparian Restoration in the Spring Creek Watershed, Central Pennsylvania

2007· article· en· W2056332531 on OpenAlexfundno aff
Robert F. Carline, Mary C. Walsh

Bibliographic record

VenueRestoration Ecology · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsnot available
FundersU.S. Fish and Wildlife ServiceGraymontU.S. Department of AgricultureU.S. Environmental Protection Agency
KeywordsRiparian zoneSTREAMSEnvironmental scienceHydrology (agriculture)Stream restorationBankRiparian bufferErosionWatershedChannel (broadcasting)Water qualitySedimentStream bedBank erosionGeologyEcologyGeomorphologyHabitat

Abstract

fetched live from OpenAlex

Abstract Riparian treatments, consisting of 3‐ to 4‐m buffer strips, stream bank stabilization, and rock‐lined stream crossings, were installed in two streams with livestock grazing to reduce sediment loading and stream bank erosion. Cedar Run and Slab Cabin Run, the treatment streams, and Spring Creek, an adjacent reference stream without riparian grazing, were monitored prior to (1991–1992) and 3–5 years after (2001–2003) riparian buffer installation to assess channel morphology, stream substrate composition, suspended sediments, and macroinvertebrate communities. Few changes were found in channel widths and depths, but channel‐structuring flow events were rare in the drought period after restoration. Stream bank vegetation increased from 50% or less to 100% in nearly all formerly grazed riparian buffers. The proportion of fine sediments in stream substrates decreased in Cedar Run but not in Slab Cabin Run. After riparian treatments, suspended sediments during base flow and storm flow decreased 47–87% in both streams. Macroinvertebrate diversity did not improve after restoration in either treated stream. Relative to Spring Creek, macroinvertebrate densities increased in both treated streams by the end of the posttreatment sampling period. Despite drought conditions that may have altered physical and biological effects of riparian treatments, goals of the riparian restoration to minimize erosion and sedimentation were met. A relatively narrow grass buffer along 2.4 km of each stream was effective in improving water quality, stream substrates, and some biological metrics.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.125
Threshold uncertainty score0.890

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.251
Teacher spread0.236 · 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

Citations48
Published2007
Admission routes1
Has abstractyes

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