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Record W2469165505

The relationships between forest structure and red squirrel midden density in Mud Lake study area, Cooke City Basin, Montana.

2011· dissertation· en· W2469165505 on OpenAlexaboutno aff
Mina Haaverstad

Bibliographic record

VenueDuo Research Archive (University of Oslo) · 2011
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicBotany and Plant Ecology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMiddenStructural basinArchaeologyGeographyFisheryForestryEcologyGeologyHydrology (agriculture)GeomorphologyBiologyGeotechnical engineering
DOInot available

Abstract

fetched live from OpenAlex

Whitebark pine (Pinus albicaulis) seeds are a very important food source for grizzly bears (Ursus arctos horribilis) and other species in the Greater Yellowstone Ecosystem. Whitebark pine is a long-lived stone pine of high-elevation forests in southwestern Canada and the western United States, with large nutrition-rich seeds. The cones do not abscise or release their seeds in fall, so bears have to raid red squirrel (Tamiasciurus hudsonicus) middens; a large site on the forest floor where squirrels open gathered cones and hide seeds.\nIn fall 2009 I documented forest structure, midden density and bear sign density on four transect lines near Mud Lake, Cooke City Basin, south-central Montana. These transect lines were originally part of a larger bear study with 27 transect lines, where data on bear sign were collected between June-October in 1990-1991 and between July-October in 1996, 1997, 2003, 2004, and 2007-2009.\nMy predictions where; (i) a higher density of middens in mixed forest; (ii) a positive relationship between bear sign and midden density; and (iii) a high density of trees with beetle infection in the Mud Lake study area. I found that the density of red squirrel middens were highest in mixed forest with a high content of whitebark pine trees. Midden density, both number of separate middens and midden area, increased with more cone-producing trees. Red squirrels are dependent on other conifers when the highly variable whitebark pine cone crops are low. I also found more bear sign in association with high densities of red squirrel middens, which shows that whitebark pine is an important habitat for bears. The amounts of dying and newly dead trees I found in my study can infer a coming epidemic of mountain pine beetle and blister rust. This can have enormous consequences for the animals that are so dependent on the food supply that whitebark pine offers. Whitebark pine as a keystone species supports a wide range of different species and a decrease of whitebark pine trees most likely will lead to less biodiversity.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.902
Threshold uncertainty score0.999

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 studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.072
GPT teacher head0.254
Teacher spread0.182 · 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.

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

Citations0
Published2011
Admission routes1
Has abstractyes

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