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A landscape perspective of bird nest predation in a managed boreal black spruce forest

2000· article· en· W299868637 on OpenAlexaffvenueabout
Marylène Boulet, Marcel Darveau, Louis Bélanger

Bibliographic record

VenueEcoscience · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPredationArboreal locomotionEcologyNest (protein structural motif)Black spruceTaigaPlasticineNest boxBiologyGeographyHabitat

Abstract

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AbstractSeveral landscape level studies have reported that bird nest predation increases as forest cover decreases. These studies have mainly been conducted in agricultural or urban regions. However, few studies have explored relationships between forest cover and nest predation in boreal forests managed for timber harvesting. In 1997 and 1998, we evaluated bird nest predation in a mosaic of clearcuts and forest remnants dominated by black spruce (Picea mariana [Mill.] B.S.P.) and located north of Lake Saint-Jean, Québec. We used a 7 km × 9 km grid of sampling points to determine nest predation at four landscape scales (local vegetation, and 250 m, 500 m, and 1000 m radii around sampling points). Artificial nests (ground and arboreal) containing a common quail (Coturnix coturnix L.) egg and a plasticine egg were used to calculate predation pressure and to identify nest predators. Nest predation was high over the entire study area. Dominant predators were the gray jay (Perisoreus canadensis L.) and the red squirrel (Tamiasciurus hudsonicus Erxleben). Depredation by squirrels was influenced by local variables in 1997 and by landscape variables in 1998. In the latter case, depredation by squirrels increased as spruce cover increased. Depredation by gray jays was positively related to water body area and jack pine (Pinus banksiana Lamb.) cover. Squirrels preyed more on ground nests than on arboreal nests, while gray jays preyed almost exclusively on arboreal nests. We conclude that these predators probably impose different threats to different songbird species in boreal black spruce forests. Our results show that, in the short term, timber harvesting did not seem to increase predation in a boreal black spruce forest.Résumé:Résumé : Plusieurs études réalisées à l’échelle du paysage ont démontré que la prédation des nids d’oiseaux augmente lorsque le couvert forestier diminue. Ces études ont toutefois été surtout réalisées dans des régions agricoles ou urbaines. Par contre, peu d’études ont exploré les relations entre les types de couvert forestier et la prédation dans les forêts boréales. En 1997 et 1998, nous avons évalué la prédation des nids d’oiseaux dans une mosaïque de parterres de coupe et de lambeaux de forêt dominée par l’épinette noire (Picea mariana [Mill.] B.S.P.) au nord du Lac Saint-Jean, Québec. Nous avons établi une grille de points d’échantillonnage de 7 km × 9 km pour déterminer le risque de prédation à quatre échelles différentes (végétation locale et rayons de 250, 500 et 1000 m autour des points). Nous avons utilisé des nids artificiels (0 et 5 m de hauteur) dans lesquels nous avons placé un œuf de caille des blés (Coturnix coturnix L.) et un œuf de plasticine pour faciliter l’identification des prédateurs. La prédation des nids était importante dans l’ensemble de l’aire d’étude. Le mésangeai du Canada (Perisoreus canadensis L.) et l’écureuil roux (Tamiasciurus hudsonicus Erxleben) constituaient les principaux prédateurs. La prédation par l’écureuil était influencée par des variables locales en 1997 et par des variables de paysage en 1998. Cette dernière année, la prédation par l’écureuil était positivement associée à la superficie en épinettes. La prédation par le mésangeai du Canada était positivement corrélée à la présence de plans d’eau et au couvert en pins gris (Pinus banksiana Lamb.). L’écureuil attaquait un peu plus les nids au sol que les nids à 5 m, alors que le mésangeai s’en prenait presque exclusivement aux nids à 5 m. Nous concluons donc que ces prédateurs exercent probablement des pressions différentes sur les différentes espèces de passereaux dans la pessière noire boréale. À court terme, nos résultats indiquent que la récolte forestière ne semble pas augmenter la prédation des nids dans une pessière noire boréale.Keywords:: Bird nest predationLandscape scalesPerisoreus canadensis L.Tamiasciurus hudsonicus Erxleben.Boreal black spruce forestClearcuttingMots-clés:: Prédation de nids d’oiseauxéchelles de paysagePerisoreus canadensis L.Tamiasciurus hudsonicus ErxlebenPessière noire boréaleCoupes forestières

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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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.999

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)0.0020.000

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 head0.009
GPT teacher head0.239
Teacher spread0.231 · 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

Citations26
Published2000
Admission routes3
Has abstractyes

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