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Record W2167142494

Growth Response of Eight Hardwood Species to Current and Past Climatic Variations Using Regression Models

2001· article· en· W2167142494 on OpenAlex
Hamid Jalilvand, S. Jalali, Mohammad Reza Akbarian, Masoud Tabari, S. M. Hosseini

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Agricultural Science and Technology · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsnot available
Fundersnot available
KeywordsBasal areaBeechForestryEvapotranspirationFraxinusMapleMathematicsBotanyHorticultureGeographyBiologyEcology
DOInot available

Abstract

fetched live from OpenAlex

The impact of climatic variations on basal area growth of basswood (BA) (Tilia americana L.), American beech (BE) (Fagus grandi/olia Enrh.), bitternut hickory (BH) (Caria cordi/ormis (Wang.) K. Koch), largetooth aspen (LA) (Populus grandidentata Michx.), red maple (RM) (Acer rubrum L.), red oak (RO) (Quercus rubra L.), sugar maple (SM) (Acer saccharum Marsh.), and white ash (WA) (Fraxinus american aL.) was studied in a southern province of Quebec, Canada (45025 ' N, 73 0 57 ' W). In total, forty-eight climatic variations of precipitation (P) (13 variables), temperature (T) (13 variables), heat index (H), (11 variables), and evapotranspiration (11 variables) from the current (C) and past three years (PI, P2, & P3) were tested in regression models to find the best model of the relationship between those independent variables and the last ten years (1985-1994) of basal area growth of the species. Simple individual linear and second degree, mixed, and combination of multiple regression models were used to develop the best regression model for each tree species, separately. The best models explained 79% , 80% , 99% , 91% , 71%, 99% , 49% , and 98% of the total variance of the growth in BA, BE, BH, LA, RM, RO, SM and WA, respectively. The growth in BH, LA, RM, 1(0, SM, and WA were more associated with the previous year's climatic variations rather than the current year's. Bitternut hickory, LA, RM, SM, and WA growth were more related to the first year rather than the second or third preceding year variables. The June heat index of the third previous year of variables explained only 7% of the growth of white ash. It was concluded that the impact of climatic variables on tree growth may vary and may depend on the species and other unknown variables. Also, the results suggested that the first and second previous climatic variables have an important role on the growth of some species. American beech, BH, RO, and WA seem to be a good species to use for the study in dendrochronological and dendroclimatological studies.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.788
Threshold uncertainty score0.205

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 studies0.0000.001
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 head0.014
GPT teacher head0.237
Teacher spread0.223 · 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