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Record W2282063747 · doi:10.1080/11956860.2015.1079409

Long-term decline in a salt marsh hare population largely driven by bottom-up factors

2015· article· en· W2282063747 on OpenAlexvenueno aff
Maarten Schrama, Dries P. J. Kuijper, Roos M. Veeneklaas, Jan P. Bakker

Bibliographic record

VenueEcoscience · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsnot available
FundersNarodowym Centrum NaukiNederlandse Organisatie voor Wetenschappelijk Onderzoek
KeywordsVegetation (pathology)Population densityPopulationEcologyAbiotic componentSalt marshPredationForageDensity dependenceGeographyPopulation declineEnvironmental scienceBiologyHabitatDemography

Abstract

fetched live from OpenAlex

The widespread decline of the European brown hare (Lepus europaeus) in Europe has been attributed to both bottom-up and top-down factors, as well as climate change. Few studies have attempted to study the relative importance of these factors considered simultaneously. In this study we tested the hypotheses that hare population density is regulated by bottom-up (food), top-down (predation) or abiotic factors including tidal floods and climatic conditions. We related data on hare population density on a relatively isolated island to changes in surface area of suitable vs. unsuitable vegetation for forage, predator densities, flooding parameters and climatic variables. During the study period (1996–2012), hare numbers decreased from 580 to 219. Estimated population density was positively correlated with the cover of short, intermediate successional vegetation types and was negatively correlated with the cover of tall, late successional vegetation types. These findings corroborate results from earlier experimental studies that reported a strong aversion of hares to tall vegetation. Additionally, we found indications that raptor population density and unusually high floods also exerted negative effects on hare population density. We conclude that bottom-up factors (the availability of suitable forage) are the main regulators of the studied hare population. This suggests that the importance of bottom-up effects has been underestimated and could explain leporid population decline in areas that have experienced a similar increase in tall, unsuitable vegetation.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.629

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 communication0.0000.001
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 head0.023
GPT teacher head0.256
Teacher spread0.233 · 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

Citations16
Published2015
Admission routes1
Has abstractyes

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