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Record W2046521697 · doi:10.1139/x08-172

Effects of climate change, land-use change, and invasive species on the ecology of the Cumberland forests

2009· article· en· W2046521697 on OpenAlexvenueno aff
Virginia H. Dale, Karen O. Lannom, Marie Tharp, Donald G. Hodges, Jonah Fogel

Bibliographic record

VenueCanadian Journal of Forest Research · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsnot available
FundersOak Ridge National LaboratoryUniversity Corporation for Atmospheric ResearchNational Center for Atmospheric ResearchU.S. Department of Energy
KeywordsEcologyClimate changeBiomass (ecology)TsugaLand coverLand useDisturbance (geology)Environmental scienceForest ecologyLand use, land-use change and forestryGeographyHabitatEcosystemAgroforestryBiology

Abstract

fetched live from OpenAlex

Model projections suggest that both climate and land-use changes have large effects on forest biomass and composition in the Cumberland forests of Tennessee and Kentucky. These forests have high levels of diversity, ecological importance, land-use changes, and pressures due to invasive herbivorous insects and climate change. Three general circulation models project warming for all months in 2030 and 2080 and complex patterns of precipitation change. Climate changes from 1980 to 2100 were developed from these projections and used in the forest ecosystem model LINKAGES to estimate transient changes in forest biomass and species composition over time. These projections show that climate changes can instigate a decline in forest stand biomass and then recovery as forest species composition shifts. In addition, a landscape model (LSCAP) estimates changes in land-cover types of the Cumberlands based on projected land-use changes and the demise of eastern hemlock ( Tsuga canadensis (L.) Carrière) due to the spread of the hemlock adelgid ( Adelges tsugae Annand). LSCAP suggests that land-cover changes can be quite large and can cause a decline not only in the area of forested lands but also in the size and number of large contiguous forest patches that are necessary habitat for many forest species characteristic of the Cumberlands.

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)0.001
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 score0.579
Threshold uncertainty score0.848

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.049
GPT teacher head0.272
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

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

Citations21
Published2009
Admission routes1
Has abstractyes

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