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Record W6989563431

Barn owl breeding in agricultural landscapes of Great Britain

2023· dissertation· en· W6989563431 on OpenAlexfundno aff

Bibliographic record

VenueNottingham Trent University's Institutional Repository (Nottingham Trent Repository) · 2023
Typedissertation
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsnot available
FundersTrent UniversityNottingham Trent University
KeywordsPopulationAgricultureHabitatEctothermExclosure
DOInot available

Abstract

fetched live from OpenAlex

Habitat loss and fragmentation associated with agricultural intensification have affected farmland biodiversity worldwide. Large tracts of heterogeneous natural habitats are transformed into homogenous agricultural lands thereby resulting in a decline in farmland bird populations. The resultant decline in farmland bird populations can be associated with unsuitable foraging habitats, a decline in prey resources and an increase in chemical pollutants such as pesticides associated with agriculture. In this thesis, I use the widely studied and monitored farmland raptor species, the barn owl (Tyto alba) to examine the effects of agricultural landscape composition of different crop types, and the pesticides used in the cultivation of cereal crops, the most dominant crop type in Great Britain, on barn owl brood size (a proxy for barn owl productivity) and nestling body mass (a proxy for nestling body condition). In addition, I also explore the impact of the most dominant crop type, cereal crops, on the diet of the barn owl in Great Britain. 
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\nPrevious studies on barn owl breeding success in relation to land use in the South Midlands and South East of Great Britain have shown that barn owl breeding is independent of land use. However, these studies are local and use broad habitat types. In this novel study (Chapter 2), the effects of agricultural landscape composition of different crop types on barn owl brood size and nestling body mass across a national level and a regional level between three regions of Great Britain, namely the Midlands, the South East and the South West, with varying degrees of agricultural intensification, are examined. Among all crop types, fruit/forage crops have a positive impact on barn owl brood size, whereas, cereal crops have a negative impact on barn owl productivity, with a greater total area of cereal crops predicting smaller brood sizes. I build on using the landscape composition of cereal crops to further explore the impacts on aspects of barn owl reproduction in Chapter 3, where the effects of the landscape composition of cereal crops on maternal barn owl body condition and consequently the impact on barn owl brood size and nestling body mass is determined. Here I show that the perimeter:area ratio (a proxy for habitat complexity) of cereal crop fields has a positive impact on the maternal body condition of barn owls with a greater perimeter:area ratio of cereal crops predicting larger brood sizes. Building on the results of both Chapter 2 and Chapter 3, the impact of four commonly used pesticides by weight, in the cultivation of cereal crops namely, fungicides (chlorothalonil and diflufenican) and herbicides (glyphosate and flufenacet), on barn owl brood size and nestling body mass is investigated. An increase in the use of the herbicide flufenacet has a negative impact on barn owl brood size in Great Britain. Finally, in Chapter 5, the impact of the landscape composition of cereal crops on the diet of the barn owl in the Midlands and South East, the two regions that showed differential responses in the impact of cereal crops on brood sizes in Chapter 2 and Chapter 4, is determined. The number of prey items recovered in the diet of the barn owl decreased with an increase in the total area of cereal crops. 
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\nThe findings of this study demonstrate that barn owl reproduction is not influenced by agricultural landscape alone, but by a series of knock-on effects of agricultural landscape composition and management practices on life-history traits such as maternal body condition of breeding barn owls, and on prey availability around barn owl nest boxes. Finally, Chapter 6 offers recommendations to improve the quality of life for barn owls, with implications for the conservation of all farmland 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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.008
GPT teacher head0.207
Teacher spread0.199 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

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