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Record W2032281464 · doi:10.5558/tfc85235-2

Forest management and stick-nesting birds: New direction for mitigation in Ontario

2009· article· en· W2032281464 on OpenAlexaffvenueabout
Brian J. Naylor

Bibliographic record

VenueThe Forestry Chronicle · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife-Road Interactions and Conservation
Canadian institutionsMinistry of Natural Resources and Forestry
Fundersnot available
KeywordsHabitatOccupancyDisturbance (geology)Nest (protein structural motif)Nesting (process)Forest managementGeographyAdaptive managementEnvironmental resource managementProductivityChristian ministryEcologyEnvironmental scienceForestryEngineeringBiology

Abstract

fetched live from OpenAlex

Forest management operations (harvest, renewal, tending, road construction and use) may affect the occupancy or productivity of nest sites used by stick-nesting birds (eagles, ospreys, herons, hawks, owls, corvids) either by directly disrupting breeding activities, altering habitat suitability, or creating new access that may lead to subsequent disturbance of nest sites by other forest users. On public land in Ontario, potential effects are mitigated through an area-of-concern planning approach that involves placement of buffers around nests that restrict the timing of forest management operations, habitat alteration, and the construction of new roads. Early direction developed in the 1980s was based largely on expert opinion. The Ontario Ministry of Natural Resources (OMNR) has reviewed and revised this direction to incorporate new understanding of habitat requirements and the effects of forest management operations. Case studies are provided to show how published literature, directed studies, and the precautionary principle were used to revise direction for ospreys and great blue herons. For many species, this review led to a reduction in the size of buffers deemed necessary to mitigate the effects of forest management operations. Despite the increased use of scientific evidence, there is still uncertainty about the effects of forest management operations on stick-nesting birds and the effectiveness of proposed direction. OMNR is developing a monitoring plan to evaluate the effectiveness of revised direction as part of its cycle of adaptive policy development. Key words: buffers, stick-nesting birds, eagles, ospreys, herons, hawks, owls, disturbance, habitat alteration, access

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 score0.132
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.013
GPT teacher head0.228
Teacher spread0.215 · 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

Citations5
Published2009
Admission routes3
Has abstractyes

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