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Record W4391475406 · doi:10.5962/p.363398

Resilience of Foothills Rough Fescue, Festuca campestris, rangeland to wildfire

2002· article· en· W4391475406 on OpenAlexafffundvenueabout
Edward W. Bork, Barry W. Adams, Walter D. Willms

Bibliographic record

VenueThe Canadian Field-Naturalist · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicRangeland and Wildlife Management
Canadian institutionsUniversity of AlbertaAgriculture Food and Rural DevelopmentAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food CanadaUniversity of Alberta
KeywordsFoothillsFestucaRangelandResilience (materials science)GeographyFestuca rubraEnvironmental scienceAgroforestryBiologyEcologyCartographyPhysics

Abstract

fetched live from OpenAlex

A three year monitoring program evaluated the effects of a December 1997 wildfire in southwest Alberta, on Foothills Rough Fescue grassland species composition, ground cover, herbage production, and forage quality.Changes in species abundance included a reduction in grass cover (p<0.10) after burning.Rough Fescue also increased seedhead production during the second year after fire (p =0.08).Relative to the unburned area, graminoid production declined (p< 0.05) by approximately 40% with burning, while forb production was unaffected.By the second growing season, live plant cover and herbage production had recovered on the burned area.The forage quality of individual Foothills Rough Fescue plants was greater on the burned area, with the greatest increase in crude protein in 1998 (p<0.10), and energy and total digestibility in 1999 (p< 0.05).Increased quality may be linked to the level of forage production, as well as a fire-induced delay in plant phenology.Although soil erosion appeared to be minimal, there was an increase in exposed soil and a corresponding decline in litter and mulch cover (p< 0.05).Greater nitrogen levels (p= 0.051) were found in creeks downstream of the burn area during 1998, indicating some nutrient losses may be attributed to the fire.Although the grasslands examined displayed considerable resilience to this severe wildfire, favourable recovery was probably linked to the high precipitation during 1998, when summer rainfall was 48% above average.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.312
Threshold uncertainty score1.000

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.011
GPT teacher head0.208
Teacher spread0.197 · 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 designNot applicable
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

Citations12
Published2002
Admission routes4
Has abstractyes

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