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Record W2900957722

Tall Timber: Roost Tree Selection of Reproductive Female Silver-Haired Bats (LASIONYCTERIS NOCTIVAGANS)

2017· dissertation· en· W2900957722 on OpenAlexfundno aff
Shelby J. Bohn

Bibliographic record

VenueoURspace (University of Regina) · 2017
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsnot available
FundersParks CanadaUniversity of Regina
KeywordsSelection (genetic algorithm)BiologyZoologyForestryEcologyGeographyComputer scienceArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

Habitat loss is the most significant contributor to the extinction of species worldwide, and yet for many species, habitat requirements remain largely unknown. Identifying habitat is important, especially because the most cost effective strategy for conservation and management is preserving habitat before it is converted or degraded rather than trying to restore it after the fact. Identifying habitat is also important from a scientific perspective because it can help to explain some of the ecological choices made by individuals when potentially conflicting priorities exist. Habitat requirements change for many species, both seasonally and throughout their life cycles, and identifying habitat during key developmental or life history periods will provide further information about priorities of these species. North American bat species show distinct differences in the habitat they use during the summer and winter, which provides us with an opportunity to understand how the selection pressures of reproduction have shaped the habitat use of these species. Silver-haired bats (Lasionycteris noctivagans) are small Vespertilionids that are solitary during their regional seasonal migration, but form small groups or maternity colonies of reproductive females on the summering ground. I captured female silver-haired bats during the reproductive season in Cypress Hills Interprovincial Park, Saskatchewan, Canada and characterized the trees that they roosted in during the day to understand why they chose the roosts that they did. These bats chose trees that were near other dead trees with cavities, presumably to reduce the cost of roost switching, a behaviour commonly undertaken by tree-roosting Vespertilionids. Bats also chose trees that were in plots with higher basal area. Roost choices did not vary over the course of the reproductive season, likely because the priorities of pregnant and lactating bats were similar. I quantified the roost characteristics chosen by silver haired bats while pregnant and lactating. The analysis suggests that the surrounding trees can also be important factors in roosting decisions. Protecting habitat critical for reproduction can be an important conservation step, but understanding why it is critical can yield even more clues for managing both natural resources and bats species.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.560
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.016
GPT teacher head0.207
Teacher spread0.192 · 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 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

Citations5
Published2017
Admission routes1
Has abstractyes

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