Proximate causes and fitness consequences of double brooding in female barn owls

Acknowledgements We are grateful to all people having helped with the fieldwork over the years and to people having accepted to host nest boxes. C. Riols took part of the pellet analysis. P. Frederick, D. LaFlamme and S.M.R. Orzechowski provided a critical read of the manuscript. J.F. Therrien and two anonymous reviewers provided valuable comments that greatly improved a previous version of the ms. The organisation ‘La Choue’ has partially supported this study. JZ benefited from grant 659648, BetMon, of the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement. Permission to handle and ring birds was granted by the Centre de Recherche sur la Biologie des Populations d’Oiseaux (MNHN Paris).Peer reviewedPostprin

Standard deviation of the random factor.

<p>We show the standard deviation of the best model in each set (in all cases this was the model including either individual or breeding pair identities, see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0090254#pone-0090254-t003" target="_blank">Tables 3</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0090254#pone-0090254-t004" target="_blank">4</a>), and that of the same model set but with a random factor specification based on territory.</p

Monitoring summary, considering only cases with complete information and two or more consecutive years of monitoring.

<p>Breeding pairs refers to the couples in which the identity of both members was known, whereas Females and Males refer to data sets considering only one member of the breeding pair. Territories represents the different territories included in the analyses and Pairs/Individuals the breeding pairs or individuals. <i>n</i> indicates the number of territories/pairs/individuals included in the analyses. Average is the average number of years for which each territory/pair/individual was successfully monitored and St. Dev. its standard deviation.</p

Models with different random structures compared with a GLS Model.

<p>The response variable used was number of fledglings. Data set indicates whether the data refer to the breeding success of pairs, females or males. Random term indicates the random structure depicting the model (all models had the same fixed term structure). AIC is the Akaike Information Criterion and AIC<i>c</i> is the same corrected for small sample sizes. <i>n</i> stands for the number of data included and K for the number of parameters of the model. ΔAIC<i>c</i> is the increase in AICc units respective to the best model, and <i>w_i</i> the Akaike weight, or the weight of evidence in favour of that model being the best model in the set. The best model in every set is marked in bold.</p

Serial partial autocorrelation correlation plot of average fledglings produced per year.

<p>Lag is expressed in years.</p

Serial correlation plot of average fledglings produced per year. Lag is expressed in years.

<p>Serial correlation plot of average fledglings produced per year. Lag is expressed in years.</p

Results of multi-model evaluation of different random structures and GLS models using BQI as the response variable. Same key as in Table 2.

<p>Results of multi-model evaluation of different random structures and GLS models using BQI as the response variable. Same key as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0090254#pone-0090254-t002" target="_blank">Table 2</a>.</p

Individual Quality Explains Variation in Reproductive Success Better than Territory Quality in a Long-Lived Territorial Raptor

<div><p>Evolution by natural selection depends on the relationship between individual traits and fitness. Variation in individual fitness can result from habitat (territory) quality and individual variation. Individual quality and specialization can have a deep impact on fitness, yet in most studies on territorial species the quality of territory and individuals are confused. We aimed to determine if variation in breeding success is better explained by territories, individual quality or a combination of both. We analysed the number of fledglings and the breeding quality index (the difference between the number of fledglings of an individual/breeding pair and the average number of fledglings of the monitored territories in the same year) as part of a long term (16 years) peregrine falcon (<i>Falco peregrinus</i>) monitoring program with identification of individuals. Using individual and territory identities as correlates of quality, we built Generalised Linear Models with Mixed effects, in which random factors depicted different hypotheses for sources of variation (territory/individual quality) in the reproductive success of unique breeding pairs, males and females, and assessed their performance. Most evidence supported the hypothesis that variation in breeding success is explained by individual identity, particularly male identity, rather than territory. There is also some evidence for inter year variations in the breeding success of females and a territory effect in the case of males. We argue that, in territorial species, individual quality is a major source of variation in breeding success, often masked by territory. Future ecological and conservation studies on habitat use should consider and include the effect of individuals, in order to avoid misleading results.</p></div

Brief results of the fixed factors in the best model in each set (see Tables 3 and 4).

<p>In the BQI section we show the <i>p</i>-value of the t statistic, while in the Fledglings section it is the <i>p</i>-value of the z. <i>p</i> values beyond 0.05 are marked in bold.</p