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Low energy reserves and energy allocation decisions affect reproduction by Mountain Pine Beetles,<i>Dendroctonus ponderosae</i>

2005· article· en· W2148711060 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFunctional Ecology · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversity of Calgary
FundersU.S. Forest Service
KeywordsBiologyReproductionBiological dispersalEcologyMountain pine beetleDendroctonusForagingLife history theoryReproductive successContext (archaeology)Energy budgetHabitatLife historyDemographyBark beetleCurculionidae

Abstract

fetched live from OpenAlex

Summary Low internal energy reserves at the beginning of the breeding season may impose physiological constraints on an animal's reproductive investment and may alter the optimal trade‐off between investment in reproduction and somatic condition. Here we examine how the energetic condition of female Mountain Pine Beetles ( Dendroctonus ponderosae ) affects their reproductive investment. We starved beetles to simulate the decrease in energy that accompanies dispersal and tested whether starved beetles had decreased egg number and decreased egg size, or both. We further distinguished whether changes are due to physiological constraints or shifts in allocation between reproduction and somatic condition. We found that starved beetles produced smaller eggs than non‐starved beetles, but females were able to partially offset the energetic deficit by feeding at their breeding habitat. Starvation did not decrease the number of eggs beetles produced. The number and size of eggs produced depended on whether females allocated energy to reproduction or to somatic condition. However, this life‐history allocation decision was independent of the amount of energy beetles had at the beginning of reproduction. Our results demonstrate the importance of assessing reproductive investment in the context of other life‐history trade‐offs. Specifically, since egg size in Mountain Pine Beetles was highly dependent on both the amount of energy remaining after dispersal and whether energy was allocated to reproduction or somatic maintenance, we expect both of these trade‐offs to be under strong selection.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.772
Threshold uncertainty score0.672

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.222
Teacher spread0.204 · 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