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AIC model selection and multimodel inference in behavioral ecology: some background, observations, and comparisons

Burnham, Kenneth P., Anderson, David R., Huyvaert, Kathryn P.·2011·Behavioral Ecology and Sociobiology

DOI 10.1007/s00265-010-1029-6

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Subedi, N., Lamichhane, B. R., Amin, R., Jnawali, S. R., & Jhala, Y. V. (2017) · Global Ecology and Conservation · doi:10.1016/j.gecco.2017.11.008 · Cited by 39
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García, N. C., & Tubaro, P. L. (2018) · The Auk · doi:10.1642/auk-17-146.1 · Cited by 35
“Following Burnham et al. (2011), we also calculated the differences of each compared model with the one with lowest AICc value (DAICc) and considered the ones with DAICc , 6 as competing models.”
Method
Microbial Modulators and Mechanisms of Soil Carbon Storage
Trivedi, P., Wallenstein, M. D., Delgado‐Baquerizo, M., & Singh, B. K. (2018) · Elsevier eBooks · doi:10.1016/b978-0-12-812766-7.00003-2 · Cited by 35
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“ranking models to find the best fit, and thus helps to prevent overfitting of models with multiple fixed effects (Burnham et al., 2011; Aho et al., 2014).”
Background
Responses of plants to polybrominated diphenyl ethers (PBDEs) induced phytotoxicity: A hierarchical meta-analysis
Sun, Y., Wang, C., Xu, X., & Ruan, H. (2019) · Chemosphere · doi:10.1016/j.chemosphere.2019.124865 · Cited by 34
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Crop Resilience to Drought With and Without Response Diversity
Elsalahy, H. H., Bellingrath‐Kimura, S. D., Roß, C., Kautz, T., & Döring, T. F. (2020) · Frontiers in Plant Science · doi:10.3389/fpls.2020.00721 · Cited by 35
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Limited heat tolerance in an Arctic passerine: Thermoregulatory implications for cold‐specialized birds in a rapidly warming world
O’Connor, R. S., Pogam, A. L., Young, K. G., Robitaille, F., Choy, E. S., Love, O. P., Elliott, K. H., Hargreaves, A. L., Berteaux, D., Tam, A., et al. (2021) · Ecology and Evolution · doi:10.1002/ece3.7141 · Cited by 32
“Models with an Akaike information criterion adjusted for small sample sizes (AICc) less than 8 (i.e., ∆AICc 8) were considered to fit the data equally well (Burnham et al., 2011).”
Method
Long-term ecological trends of small secondary forests of the atlantic forest hotspot: A 30-year study case
de Souza, C. R., Maia, V. A., de Aguiar‐Campos, N., Santos, A. B. M., Rodrigues, A. F., Farrapo, C. L., Gianasi, F. M., de Paula, G. G. P., Fagundes, N. C. A., Silva, W. B., et al. (2021) · Forest Ecology and Management · doi:10.1016/j.foreco.2021.119043 · Cited by 35
Contrasting response of native and non‐native plants to disturbance and herbivory in mountain environments
Geppert, C., Boscutti, F., Bella, G. L., Marchi, V. D., Corcos, D., Filippi, A., & Marini, L. (2021) · Journal of Biogeography · doi:10.1111/jbi.14097 · Cited by 35
“Multi- model inference analyses were performed with the MuMIn package (Barton & Barton, 2015; Burnham et al., 2011).”
Method
Higher temperatures are associated with reduced nestling body condition in a range‐restricted mountain bird
Oswald, K. N., Smit, B., Lee, A. T., Peng, C. L., Brock, C., & Cunningham, S. J. (2021) · Journal of Avian Biology · doi:10.1111/jav.02756 · Cited by 37
“These sublethal costs can include the additive and interactive effects of daily adult body mass (Mb) loss (du Plessis et al. 2012), interannual adult Mb loss (Lee et al. 2020) and reduced nestling growth rates (Catry et al. 2015, van de Ven et al. 2020).”
Background
Trade-offs between foraging reward and mortality risk drive sex-specific foraging strategies in sexually dimorphic northern elephant seals
Kienle, S. S., Friedlaender, A. S., Crocker, D. E., Mehta, R. S., & da Costa, D. P. (2022) · Royal Society Open Science · doi:10.1098/rsos.210522 · Cited by 35
Evaluating Hair as a Predictor of Blood Mercury: The Influence of Ontogenetic Phase and Life History in Pinnipeds
Peterson, S. H., McHuron, E. A., Kennedy, S. N., Ackerman, J. T., Rea, L. D., Castellini, J. M., O’Hara, T. M., & da Costa, D. P. (2015) · Archives of Environmental Contamination and Toxicology · doi:10.1007/s00244-015-0174-3 · Cited by 35
Temporal Epidemiology of Sudden Oak Death in Oregon
Peterson, E. K., Hansen, E. M., & Kanaskie, A. (2015) · Phytopathology · doi:10.1094/phyto-12-14-0348-fi · Cited by 35
Climate impact on Italian fisheries (Mediterranean Sea)
Fortibuoni, T., Aldighieri, F., Giovanardi, O., Pranovi, F., & Zucchetta, M. (2015) · Regional Environmental Change · doi:10.1007/s10113-015-0781-6 · Cited by 35
“…were carried out on an averaged model, built computing the weighted averages parameters for each independent variable, using AICc weights (WAICc) (Burnham and Anderson 2002, Burnham et al. 2011) and considering the set of models whose cumulative weights (WAICc) represent 95 % of the total ensemble.”
Method
Carryover effects in amphibians: Are characteristics of the larval habitat needed to predict juvenile survival?
Earl, J. E., & Semlitsch, R. D. (2013) · Ecological Applications · doi:10.1890/12-1235.1 · Cited by 35
“models may be useful (Burnham et al. 2011).”
The impact of changing climate and abundance on reproduction in an ice-dependent species, the Northwest Atlantic harp seal,Pagophilus groenlandicus
Stenson, G. B., Buren, A. D., & Koen‐Alonso, M. (2015) · ICES Journal of Marine Science · doi:10.1093/icesjms/fsv202 · Cited by 35
An empirical test of the relative and combined effects of land‐cover and climate change on local colonization and extinction
Yalcin, S., & Leroux, S. (2018) · Global Change Biology · doi:10.1111/gcb.14169 · Cited by 34
Free housing for declining populations: Optimizing the provision of artificial breeding structures
D’Amico, M., Tablado, Z., Revilla, E., & Palomares, F. (2014) · Journal for Nature Conservation · doi:10.1016/j.jnc.2014.03.006 · Cited by 34
Size and Retention of Breeding Territories of Yellow-Billed Loons (Gavia adamsii) in Alaska and Canada
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The patterns and modes of the evolution of disparity in Mesozoic birds
Wang, M., Lloyd, G. T., Zhang, C., & Zhou, Z. (2021) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2020.3105 · Cited by 32
“The five models—stasis (a null model describing time-invariant change in disparity), Brownian motion, trend, Ornstein–Uhlenbeck with one optimum, and the early burst models [36]—are compared using the sample-size-corrected Akaike information criterion (AICc) and Akaike weights [37].”
Method
Motives driving gaze and walking decisions
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An intentional cohesion call in male chimpanzees of Budongo Forest
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Pokharel, K., Ludwig, T., & Storch, I. (2015) · PLoS ONE · doi:10.1371/journal.pone.0117917 · Cited by 28
“The AIC-IT approach compares different models that are based on a-priori formulated hypotheses about the focal species [38].”
Method
Information to Act: Household Characteristics are Predictors of Domestic Infestation with the Chagas Vector Triatoma dimidiata in Central America
Zamora, D. M. B., Menes, M., Torres, N., Zúñiga, C., Sosa, W., de Abrego, V. C., & Monroy, M. C. (2015) · American Journal of Tropical Medicine and Hygiene · doi:10.4269/ajtmh.14-0596 · Cited by 34
“the data; a model with a weight close to one can be considered the “best” model among those considered.(39) When high uncertainty was detected (no model with weight = 1), weighted model parameter estimates were calculated using”
Method
Shared risk factors for multiple livestock diseases: A case study of bovine tuberculosis and brucellosis
Cowie, C. E., Marreos, N., Gortázar, C., Jaroso, R., White, P. C. L., & Balseiro, A. (2014) · Research in Veterinary Science · doi:10.1016/j.rvsc.2014.09.002 · Cited by 34
“Information theoretic analysis generates a set of models made from different combinations of the terms in a ‘global model’, containing all the variables of interest (Burnham et al., 2010).”
Background
Housing induced mood modulates reactions to emotional stimuli in sheep
Reefmann, N., Muehlemann, T., Wechsler, B., & Gygax, L. (2012) · Applied Animal Behaviour Science · doi:10.1016/j.applanim.2011.12.007 · Cited by 36
“We used AICc values to compare the model with the interaction between test situation and mood group with the main effects model, with the model including mood group only, the model including test situation only and the model including a constant (intercept) only (Burnham et al., 2011; Dochtermann and Jenkins, 2011).”
Method
Measurement and Correlation of the Solubility for Camptothecine in Different Organic Solvents
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A molecular phylogeny of the Pacific clade of Cyrtandra (Gesneriaceae) reveals a Fijian origin, recent diversification, and the importance of founder events
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Depth to the apparent redox potential discontinuity (aRPD) as a parameter of interest in marine benthic habitat quality models
Gerwing, T. G., Cox, K., Gerwing, A. M. A., Carr‐Harris, C., Dudas, S. E., & Juanes, F. (2017) · International Journal of Sediment Research · doi:10.1016/j.ijsrc.2017.09.001 · Cited by 34
“DO and Eh conditions were analyzed separately, and for each response variable seven models, selected a priori, were evaluated using the Information Theoretic Model Selection Approach (Burnham & Anderson, 2001; Burnham et al., 2011).”
Method
The Impact of Workaholism on Nurses’ Burnout and Disillusion
Nonnis, M., Massidda, D., Cuccu, S., & Cortese, C. G. (2018) · The Open Psychology Journal · doi:10.2174/1874350101811010077 · Cited by 36
“[51, 52], and Vrieze [53] for further details).”
Substrate identity and amount overwhelm temperature effects on soil carbon formation
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Microcystin concentrations can be predicted with phytoplankton biomass and watershed morphology
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“In this case, the simpler model (fewer variables) was selected as the best fit model (Burnham et al. 2010).”
Method
Soil drivers of local‐scale tree growth in a lowland tropical forest
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Nest box selection and reproduction of European Rollers in Central Italy: a 7-year study
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Dietary Plasticity in a Specialist Predator, the Gyrfalcon (Falco rusticolus): New Insights into Diet During Brood Rearing
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“We used an information-theoretic approach to evaluate models and to test parameter support against the intercept-only model (Burnham et al. 2011).”
MethodSelf-citation
Solubility Determination and Model Correlation of Pymetrozine and Evaluation of the Effect of Solvent Properties and Composition
Zhu, A., Hong, K., Zhu, F., Dai, B., Ji-ming, X., & Zhao, W. (2019) · Journal of Chemical & Engineering Data · doi:10.1021/acs.jced.9b00229 · Cited by 34
Sea wrack delivery and accumulation on islands: factors that mediate marine nutrient permeability
Wickham, S. B., Shackelford, N., Darimont, C. T., Nijland, W., Reshitnyk, L., Reynolds, J., & Starzomski, B. M. (2019) · Marine Ecology Progress Series · doi:10.3354/meps13197 · Cited by 34
Characterizing the temperature and precipitation covariability over Canada
Singh, H., Pirani, F. J., & Najafi, M. R. (2019) · Theoretical and Applied Climatology · doi:10.1007/s00704-019-03062-w · Cited by 35
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Vitantonio‐Mazzini, L. N., Gómez, D. R., Gambín, B. L., Mauro, G. D., Iglesias, R., Costanzi, J., Jobbagy, E. G., & Borrás, L. (2020) · Crop Science · doi:10.1002/csc2.20315 · Cited by 34
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The role of Weber’s law in human time perception
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“The magnitude of the AICc differences between these two models for both the mean PSF and the individual PSFs are high enough to conclude that the hypothesis that the Bizo et al. model would give a better fit to the data has no empirical support (Burnham et al., 2011).”
BackgroundInfluential
Impact of individual demographic and social factors on human–wildlife interactions: a comparative study of three macaque species
Balasubramaniam, K. N., Marty, P. R., Samartino, S., Sobrino, A., Gill, T., Ismail, M., Saha, R., Beisner, B. A., Kaburu, S., Bliss‐Moreau, E., et al. (2020) · Scientific Reports · doi:10.1038/s41598-020-78881-3 · Cited by 33
Understanding Food Web Mercury Accumulation Through Trophic Transfer and Carbon Processing along a River Affected by Recent Run-of-river Dams
Ponton, D. E., Lavoie, R. A., Leclerc, M., Bilodeau, F., Planas, D., & Amyot, M. (2021) · Environmental Science & Technology · doi:10.1021/acs.est.0c07015 · Cited by 34
Female blue tits sing frequently: a sex comparison of occurrence, context, and structure of song
Sierro, J., de Kort, S. D., Riebel, K., & Hartley, I. (2022) · Behavioral Ecology · doi:10.1093/beheco/arac044 · Cited by 25
“We used the relative importance of each factor in the final model together with the coefficients and estimated confidence intervals (CIs) with a threshold of 95% (Nakagawa and Cuthill 2007; Burnham et al. 2011), concluding there was a significant effect if the CI did not overlap with zero.”
Octodon degus kin and social structure
Davis, G. T., Vásquez, R. A., Poulin, É., Oda, E., Bazán-León, E. A., Ebensperger, L. A., & Hayes, L. D. (2015) · Journal of Mammalogy · doi:10.1093/jmammal/gyv182 · Cited by 34
“Each possible combination of factors and interactions was tested and models with ∆AIC < 7 were considered to be well supported (Burnham et al. 2011).”
Method
Importance of wave and current exposure to fauna communities in Laminaria hyperborea kelp forests
Norderhaug, K. M., Christie, H., Rinde, E., Gundersen, H., & Bekkby, T. (2014) · Marine Ecology Progress Series · doi:10.3354/meps10754 · Cited by 34
Pay the farmer, or buy the land?—Cost-effectiveness of payments for ecosystem services versus land purchases or easements in Central Kenya
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Wind energy production in forests conflicts with tree-roosting bats
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Drought initialised bark beetle outbreak in Central Europe: Meteorological factors and infestation dynamic
Pirtskhalava-Karpova, N., Trubin, A., Karpov, A., & Jakuš, R. (2024) · Forest Ecology and Management · doi:10.1016/j.foreco.2023.121666 · Cited by 33
Assessing ecological habitat structure from local to landscape scales using synthetic aperture radar
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“W performed a model selection based on the comparison of the values of the corrected Akaike information criterion (AICc) (Burnham et al. 2011) and adjusted r-squared to test the effcts of hedgerow network structure and internal hedgerow structure at different scales on carabid beetle abundance.”
Method
Environmental control of community organisation on ocean-exposed sandy beaches
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“The primary criterion to evaluate the ‘performance’ of models was the corrected Akaike information criterion (AICc) based on all possible combinations of environmental variables used in model building (Burnham et al. 2011; Symonds and Moussalli 2011).”
Method
Determinants of yearling male lekking effort and mating success in black grouse (Tetrao tetrix)
Kervinen, M., Alatalo, R. V., Lebigre, C., Siitari, H., & Soulsbury, C. D. (2012) · Behavioral Ecology · doi:10.1093/beheco/ars104 · Cited by 33
“Currently, there is no consensus about the optimal cutoff point for model rejection (Burnham and Anderson 2002; Richards 2005, 2008; Bolker et al. 2009; Burnham et al. 2011; Richards et al. 2011).”
Background
Plant functional diversity increases grassland productivity‐related water vapor fluxes: an Ecotron and modeling approach
Milcu, A., Eugster, W., Bachmann, D., Guderle, M., Roscher, C., Gockele, A., Landais, D., Ravel, O., Geßler, A., Lange, M., et al. (2016) · Ecology · doi:10.1890/15-1110.1 · Cited by 33
Shifts in historical streamflow extremes in the Colorado River Basin
Solander, K. C., Bennett, K. E., & Middleton, R. S. (2017) · Journal of Hydrology Regional Studies · doi:10.1016/j.ejrh.2017.05.004 · Cited by 33
Continental‐extent patterns in amphibian malformations linked to parasites, chemical contaminants, and their interactions
Haas, S. E., Reeves, M. K., Pinkney, A. E., & Johnson, P. T. J. (2017) · Global Change Biology · doi:10.1111/gcb.13908 · Cited by 33
Living on the edge: characteristics of human–wildlife conflict in a traditional livestock community in Botswana
McNutt, J. W., Stein, A. B., Boggs, L. P., & Jordan, N. R. (2017) · Wildlife Research · doi:10.1071/wr16160 · Cited by 33
“9 and somemodels had deviance in theAIC of <7 units (Burnham et al. 2011; Grueber et al. 2011).”
BackgroundMethodInfluential
Environmental drivers of harbour porpoise fine-scale movements
van Beest, F. M., Teilmann, J., Dietz, R., Galatius, A., Mikkelsen, L., Stalder, D., Sveegaard, S., & Nabe‐Nielsen, J. (2018) · Marine Biology · doi:10.1007/s00227-018-3346-7 · Cited by 33
Do avian blood parasites influence hypoxia physiology in a high elevation environment?
Ishtiaq, F., & Barve, S. (2018) · BMC Ecology · doi:10.1186/s12898-018-0171-2 · Cited by 33
“We used a model-averaging approach to check the validity of the top-ranking model in each case, only including models with ΔAICc 2 [49].”
Influential
Large river habitat complexity and productivity of Puget Sound Chinook salmon
Hall, J. E., Greene, C. M., Stefankiv, O., Anderson, J. H., Timpane-Padgham, B., Beechie, T. J., & Pess, G. R. (2018) · PLOS ONE · doi:10.1371/journal.pone.0205127 · Cited by 33
Persistence of fire-killed conifer snags in California, USA
Grayson, L. M., Cluck, D. R., & Hood, S. M. (2019) · Fire Ecology · doi:10.1186/s42408-018-0007-7 · Cited by 33
“Terms were thus selected from these full equations using both a backward and a stepwise AIC procedure until the difference in AIC of the simpler model and the full model fell to less than 7 (Anderson and Burnham 2002; Burnham et al. 2011).”
Method
Environmental drivers of humpback whale foraging behavior in the remote Southern Ocean
Riekkola, L., Andrews-Goff, V. L., Friedlaender, A. S., Constantine, R., & Zerbini, A. N. (2019) · Journal of Experimental Marine Biology and Ecology · doi:10.1016/j.jembe.2019.05.008 · Cited by 33
A novel variable selection algorithm for multi-layer perceptron with elastic net
Zhang, F., Sun, K., & Wu, X. (2019) · Neurocomputing · doi:10.1016/j.neucom.2019.04.091 · Cited by 33
High-intensity endurance capacity assessment as a tool for talent identification in elite youth female soccer
Datson, N., Weston, M., Drust, B., Gregson, W. A., & Lolli, L. (2019) · Journal of Sports Sciences · doi:10.1080/02640414.2019.1656323 · Cited by 33
Causes and consequences of inverse density‐dependent territorial behaviour and aggression in a monogamous mammal
Mayer, M., Frank, S. C., Zedrosser, A., & Rosell, F. (2019) · Journal of Animal Ecology · doi:10.1111/1365-2656.13100 · Cited by 33
Development of a new multi-layer perceptron based soft sensor for SO2 emissions in power plant
Sun, K., Wu, X., Xue, J., & Ma, F. (2019) · Journal of Process Control · doi:10.1016/j.jprocont.2019.10.007 · Cited by 33
Solubility Determination and Thermodynamic Modeling of Edaravone in Different Solvent Systems and the Solvent Effect in Pure Solvents
Qiu, J., Huang, H., He, H. Z., Liu, H., Hu, S., Han, J., Yi, D., An, M., Guo, Y., & Wang, P. (2020) · Journal of Chemical & Engineering Data · doi:10.1021/acs.jced.0c00290 · Cited by 33
Prey availability and ambient temperature influence carrion persistence in the boreal forest
Peers, M. J. L., Konkolics, S. M., Lamb, C. T., Majchrzak, Y. N., Menzies, A. K., Studd, E. K., Boonstra, R., Kenney, A. J., Krebs, C. J., Martinig, A. R., et al. (2020) · Journal of Animal Ecology · doi:10.1111/1365-2656.13275 · Cited by 33
Seasonal and Geographical Differences in Total and Pathogenic Vibrio parahaemolyticus and Vibrio vulnificus Levels in Seawater and Oysters from the Delaware and Chesapeake Bays Determined Using Several Methods
Parveen, S., Jacobs, J. M., Ozbay, G., Chintapenta, L. K., Almuhaideb, E., Meredith, J., Ossai, S., Abbott, A., Grant, A., Brohawn, K., et al. (2020) · Applied and Environmental Microbiology · doi:10.1128/aem.01581-20 · Cited by 33
“information criterion corrected for small sample size (AICc) (21), as described in”
MethodInfluential
Combining Satellite Remote Sensing and Climate Data in Species Distribution Models to Improve the Conservation of Iberian White Oaks (Quercus L.)
Vila-Viçosa, C. M., Arenas‐Castro, S., Marcos, B., Honrado, J. P., García, C., Pardo, F. M. V., Almeida, R., & Gonçalves, J. (2020) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi9120735 · Cited by 33
“combined), we also calculated the Akaike information criterion (with finite sample size correction; AICc) for GLM’s allowing to rank models [72,73] while accounting for a different number of variables in each set (i.”
Method
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Cong, Y., Du, C., Wang, M., Jiang, Z., Xing, K., Bian, Y., & Wang, M. (2021) · Journal of Molecular Liquids · doi:10.1016/j.molliq.2021.116489 · Cited by 33
The interaction of land-use history and tree species diversity in driving variation in the aboveground biomass of urban versus non-urban tropical forests
Borges, É. R., Dexter, K. G., Pyles, M. V., Bueno, M. L., dos Santos, R. M., Fontes, M. A. L., & Carvalho, F. A. (2021) · Ecological Indicators · doi:10.1016/j.ecolind.2021.107915 · Cited by 35
“We evaluated model performance based on AICc and considered as equally supported the set of models with Δ AICc ≤ 2 via multimodel inference (Burnham et al., 2011; Burnham and Anderson, 2002).”
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Lei, W., Masero, J. A., Dingle, C., Liu, Y., Chai, Z., Zhu, B., Peng, H., Zhang, Z., & Piersma, T. (2021) · Animal Conservation · doi:10.1111/acv.12717 · Cited by 33
Landscape composition drives the impacts of artificial light at night on insectivorous bats
Barré, K., Vernet, A., Azam, C., Viol, I. L., Dumont, A., Deana, T., Vincent, S., Challéat, S., & Kerbiriou, C. (2021) · Environmental Pollution · doi:10.1016/j.envpol.2021.118394 · Cited by 33
Invasive alien acacias rapidly stock carbon, but threaten biodiversity recovery in young second-growth forests
Matos, F. A. R., Edwards, D. P., Magnago, L. F. S., Heringer, G., Neri, A. V., Buttschardt, T. K., Zenni, R. D., de Menezes, L. F. T., Saiter, F. Z., Schaefer, C. E. G. R., et al. (2022) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2021.0072 · Cited by 33
“We used multi-model inference and an information-theoretic approach to assess the effect of exploratory variables on carbon stock [69].”
Method
Individual variability of wild juvenile Atlantic salmon activity patterns: effect of flow stage, temperature, and habitat use
Roy, M. L., Roy, A. G., Grant, J. W. A., & Bergeron, N. É. (2013) · Canadian Journal of Fisheries and Aquatic Sciences · doi:10.1139/cjfas-2012-0274 · Cited by 33
Management Forcing Increased Specialization in a Fishery System
Hentati‐Sundberg, J., Hjelm, J., Boonstra, W. J., & Österblom, H. (2014) · Ecosystems · doi:10.1007/s10021-014-9811-3 · Cited by 33
Binocular fusion, suppression and diplopia for blurred edges
Georgeson, M. A., & Wallis, S. A. (2014) · Ophthalmic and Physiological Optics · doi:10.1111/opo.12108 · Cited by 33
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“The sum of weights from single variable models and multiple variable models were also compared (Burnham and Anderson 2002; Arnold 2010; Burnham et al. 2011).”
Method
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“avg function to average models within a 95% confidence interval (CI) (Burnham et al. 2011) in MuMIn package (Bartón 2016) and confint function to calculate the CI of each parameter.”
Method
Influence of grazing management on resource selection by a small mammal in a temperate desert of South America
Spirito, F., Rowland, M. M., Nielson, R. M., Wisdom, M. J., & Tabeni, S. (2017) · Journal of Mammalogy · doi:10.1093/jmammal/gyx106 · Cited by 32
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Revisiting the nonlinear relationship between ENSO and winter extreme station precipitation in North America
Cannon, A. J. (2015) · International Journal of Climatology · doi:10.1002/joc.4263 · Cited by 32
“Finally, because of the additional nonlinear models evaluated in this study, as well as the non-nested nature of some of the comparisons, the strength of evidence approach recommended by Burnham et al. (2011) is used to assess the relative performance of the different candidate models.”
BackgroundMethodInfluential
Performance evaluation of recent information criteria for selecting multilevel models in Behavioral and Social Sciences
Vallejo, G., Herrero, E. T., Núñez, J. C., & Rosário, P. J. S. L. F. (2013) · International Journal of Clinical and Health Psychology · doi:10.1016/s1697-2600(14)70036-5 · Cited by 32
Short-term effects of tagging on activity and movement patterns of Eurasian beavers (Castor fiber)
Graf, P. M., Hochreiter, J., Hackländer, K., Wilson, R. P., & Rosell, F. (2016) · European Journal of Wildlife Research · doi:10.1007/s10344-016-1051-8 · Cited by 32
Extra-territorial movements differ between territory holders and subordinates in a large, monogamous rodent
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“5/ΔAICc)) and Akaike weight (relative likelihood/sum of all relative likelihoods) were computed [49].”
Method
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“Models 5’–8’ had relatively little empirical support (∆AICc > 11) [49] and were dismissed.”
BackgroundMethodInfluential
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Wood, K. A., Brown, M. J., Cromie, R., Hilton, G. M., Mackenzie, C., Newth, J. L., Pain, D. J., Perrins, C. M., & Rees, E. C. (2018) · Biological Conservation · doi:10.1016/j.biocon.2018.12.010 · Cited by 32
Altitudinal gradients fail to predict fungal symbiont responses to warming
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Regional scientific research benefits threatened-species conservation
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H.E.S.S. and MAGIC observations of a sudden cessation of a very-high-energy γ -ray flare in PKS 1510−089 in May 2016
Abdalla, H., Adam, R., Aharonian, F., Benkhali, F. A., Angüner, E. O., Arcaro, C., Armand, C., Armstrong, T. P., Ashkar, H., Backes, M., et al. (2021) · Astronomy and Astrophysics · doi:10.1051/0004-6361/202038949 · Cited by 32
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Liu, X., Zhang, L., Huang, M., & Zhou, S. (2020) · Journal of Plant Ecology · doi:10.1093/jpe/rtaa099 · Cited by 32

Authors: Burnham, K. P., Anderson, D. R., & Huyvaert, K. P.
Affiliations: Colorado State University (US)
Corresponding author: Burnham, Kenneth P.
ORCID: Huyvaert, Kathryn P.
Venue: Behavioral Ecology and Sociobiology
Publisher: Springer Science and Business Media LLC
Published: 2010-08-18
Volume: 65
Issue: 1
Pages: 23-35
ISSN: 0340-5443 (ISSN-L)
1432-0762
DOI: 10.1007/s00265-010-1029-6
OpenAlex: W2096650374
Semantic Scholar: 33e08c84858e01d75d94592e03272dd4073316ff
Cited by: 4,104
References: 95
Citations by year: 2026: 228 · 2025: 300 · 2024: 327 · 2023: 365 · 2022: 358 · 2021: 434 · 2020: 404 · 2019: 335 · 2018: 340 · 2017: 251 · 2016: 239 · 2015: 192 · 2014: 154 · 2013: 98 · 2012: 53
FWCI: 44.95
Type: journal article
Language: en
Open access: closed
Licence: www.springer.com/tdm (tdm)
Locations: Behavioral Ecology and Sociobiology (publishedVersion)
Funders: Colorado State University
Innovative Research Group Project of the National Natural Science Foundation of China
Topics: Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Inference
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
Keywords: AIC model selection, multi-model inference, alternative hypothesis, hypothesis testing, behavioral ecology, statistical inference, probability models

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AIC model selection and multimodel inference in behavioral ecology: some background, observations, and comparisons

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