Subtopic Deep Dive
Model Selection Avian Ecology
Research Guide
What is Model Selection Avian Ecology?
Model selection in avian ecology uses information-theoretic criteria like AIC to compare candidate statistical models for analyzing bird population dynamics, nest survival, and habitat use.
Researchers apply AIC, BIC, and multimodel inference to evaluate competing models in studies of marked bird populations and nest survival (Grant et al., 2005; 242 citations). These methods address time-specific variation and demographic processes (Thomson et al., 2008; 421 citations). Over 10 high-citation papers demonstrate their use in seabird survival and grassland bird declines.
Why It Matters
AIC-based model selection enables robust predictions of nest survival rates, as in passerine studies where time-specific models outperformed constant models (Grant et al., 2005). It supports habitat management for declining species like yellowhammers by ranking environmental covariates (Whittingham et al., 2005). In demographic modeling, it improves inference on weather-driven survival in seabirds (Frederiksen et al., 2008), informing conservation amid climate variability.
Key Research Challenges
Overfitting in Sparse Data
Bird studies often involve small sample sizes from marked individuals, leading to overfitting when many candidate models compete (Thomson et al., 2008). AIC may select overly complex models without cross-validation. Multimodel inference helps average predictions but requires careful model set design.
Time-Varying Covariates
Nest survival varies by age and date, complicating constant-model assumptions (Grant et al., 2005; 242 citations). Incorporating weather extremes demands dynamic model structures (Frederiksen et al., 2008). Balancing model complexity with data availability remains difficult.
Multiscale Habitat Selection
Habitat models must integrate field and landscape scales for species like yellowhammers (Whittingham et al., 2005). AIC rankings may favor local over broad covariates without hierarchical approaches. Linking isotopes or pesticides adds confounding variables (Mineau & Whiteside, 2013).
Essential Papers
Modeling Demographic Processes In Marked Populations
David Thomson, Evan G. Cooch, Michael J. Conroy · 2008 · 421 citations
Seabirds as indicators of marine food supplies: Cairns revisited
JF Piatt, AMA Harding, Michael T. Shultz et al. · 2007 · Marine Ecology Progress Series · 255 citations
MEPS Marine Ecology Progress Series Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections MEPS 35...
The demographic impact of extreme events: stochastic weather drives survival and population dynamics in a long‐lived seabird
Morten Frederiksen, Francis Daunt, M. P. Harris et al. · 2008 · Journal of Animal Ecology · 251 citations
1. Most scenarios for future climate change predict increased variability and thus increased frequency of extreme weather events. To predict impacts of climate change on wild populations, we need t...
TIME-SPECIFIC VARIATION IN PASSERINE NEST SURVIVAL: NEW INSIGHTS INTO OLD QUESTIONS
Todd A. Grant, Terry L. Shaffer, Elizabeth M. Madden et al. · 2005 · The Auk · 242 citations
Abstract Understanding nest survival is critical to bird conservation and to studies of avian life history. Nest survival likely varies with nest age and date, but until recently researchers had on...
Pesticide Acute Toxicity Is a Better Correlate of U.S. Grassland Bird Declines than Agricultural Intensification
Pierre Mineau, Mélanie Whiteside · 2013 · PLoS ONE · 214 citations
Common agricultural birds are in decline, both in Europe and in North America. Evidence from Europe suggests that agricultural intensification and, for some species, the indirect effects of pestici...
Adaptive phenotypic plasticity in an island songbird exposed to a novel predation risk
Susana I. Peluc, T. Scott Sillett, John T. Rotenberry et al. · 2008 · Behavioral Ecology · 197 citations
Avian nest site selection and levels of parental care require assessments of numerous fitness costs and benefits. Nest site selection in open cup–nesting species is considered a relatively conserva...
Habitat selection by yellowhammers <i>Emberiza citrinella</i> on lowland farmland at two spatial scales: implications for conservation management
Mark J. Whittingham, Ruth D. Swetnam, Jeremy D. Wilson et al. · 2005 · Journal of Applied Ecology · 183 citations
Summary Yellowhammer Emberiza citrinella populations have declined rapidly in the UK over recent decades, and a clear understanding of their habitat requirements is important to help inform conserv...
Reading Guide
Foundational Papers
Start with Thomson et al. (2008; 421 citations) for demographic modeling frameworks, then Grant et al. (2005; 242 citations) for nest survival AIC applications.
Recent Advances
Mineau & Whiteside (2013; 214 citations) links pesticides to declines via model selection; Whittingham et al. (2005; 183 citations) ranks habitat covariates.
Core Methods
AIC for model comparison, multimodel averaging, time-dependent logistic regression, Program MARK for mark-recapture (Thomson et al., 2008).
How PapersFlow Helps You Research Model Selection Avian Ecology
Discover & Search
Research Agent uses searchPapers('AIC model selection nest survival birds') to find Grant et al. (2005), then citationGraph reveals 242 citing papers on time-specific models, and findSimilarPapers uncovers Thomson et al. (2008) for demographic extensions.
Analyze & Verify
Analysis Agent applies readPaperContent on Grant et al. (2005) to extract AIC formulas, verifyResponse with CoVe checks model rankings against raw data, and runPythonAnalysis recreates nest survival curves using NumPy/pandas for GRADE A statistical verification.
Synthesize & Write
Synthesis Agent detects gaps in time-varying covariates across papers, flags contradictions in AIC vs. BIC use, then Writing Agent uses latexEditText for model comparison tables, latexSyncCitations for 10-paper bibliography, and latexCompile for publication-ready report with exportMermaid for AIC decision trees.
Use Cases
"Reproduce AIC analysis from Grant et al. 2005 passerine nest survival in Python"
Research Agent → searchPapers → readPaperContent (extract equations) → Analysis Agent → runPythonAnalysis (NumPy fit AIC models to survival data) → matplotlib plot daily rates output.
"Write LaTeX section comparing AIC models in seabird demographics"
Synthesis Agent → gap detection (Frederiksen 2008 + Thomson 2008) → Writing Agent → latexEditText (draft table) → latexSyncCitations (10 papers) → latexCompile → PDF with model selection flowchart.
"Find code for multimodel inference in avian habitat studies"
Research Agent → paperExtractUrls (Whittingham 2005) → paperFindGithubRepo → Code Discovery → githubRepoInspect (R/AICc scripts) → runPythonAnalysis port to sandbox.
Automated Workflows
Deep Research workflow scans 50+ papers via searchPapers on 'AIC avian ecology', structures report with model rankings from Grant (2005) and Thomson (2008). DeepScan's 7-step chain verifies AIC calculations with CoVe on nest data from Frederiksen (2008). Theorizer generates hypotheses on climate-AIC interactions from weather-seabird models.
Frequently Asked Questions
What is model selection in avian ecology?
It compares candidate models using AIC to identify best predictors of bird traits like nest survival and habitat use (Grant et al., 2005).
What are common methods?
AIC, multimodel inference, and time-specific logistic regression for nest survival (Thomson et al., 2008; Grant et al., 2005).
What are key papers?
Foundational: Thomson et al. (2008; 421 citations) on marked populations; Grant et al. (2005; 242 citations) on nest survival.
What are open problems?
Integrating multiscale covariates and avoiding overfitting in sparse mark-recapture data (Whittingham et al., 2005; Thomson et al., 2008).
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Part of the Avian ecology and behavior Research Guide