Interaction of Climate Change with Effects of Conspecific and Heterospecific Density on Reproduction

This is a self-archived version of an original article. This version may differ from the original in pagination and typographic details. Author(s): Title: Year: Version: Copyright: Rights: Rights url: Please cite the original version: In Copyright http://rightsstatements.org/page/InC/1.0/?language=en Interaction of climate change with effects of conspecific and heterospecific density on reproduction © 2020 Nordic Society Oikos. Published by John Wiley & Sons Ltd Accepted version (Final draft) Møller, Anders Pape; Balbontín, Javier; Dhondt, André A.; Adriaensen, Frank; Artemyev, Alexandr; Bańbura, Jerzy; Barba, Emilio; Biard, Clotilde; Blondel, Jacques; Bouvier, Jean-Charles; Camprodon, Jordi; Cecere, Francesco; Charter, Motti; Cichoń, Mariusz; Cusimano, Camillo; Dubiec, Anna; Eens, Marcel; Eeva, Tapio; Ferns, Peter N.; Forsman, Jukka T.; Goldshtein, Aya; Goodenough, Anne E.; Gosler, Andrew G.; Gustafsson, Lars; Harnist, Iga; Hartley, Ian R.; Heeb, Philipp; Hinsley, Shelley A.; Jacob, Staffan; Järvinen, Antero; Juškaitis, Rimvydas; Korpimäki, Erkki; Krams, Indrikis; Laaksonen, Toni; Leclercq, Bernard; Lehikoinen, Esa; Loukola, Olli; Mainwaring, Mark C.; Mänd, Raivo; Massa, Bruno; Matthysen, Erik; Mazgajski, Tomasz D.; Merino, Santiago; Mitrus, Cezary; Mönkkönen, Mikko; Nager, Ruedi G.; Nilsson, Jan-Åke; Nilsson, Sven G.; Norte, Ana C.; von Numers, Mikael; Orell, Markku; Pimentel, Carla S.; Pinxten, Rianne; Priedniece, Ilze; Remeš, Vladimir; Richner, Heinz; Robles, Hugo; Rytkönen, Seppo; Senar, Juan Carlos; Seppänen, Janne T.; da Silva, Luís P.; Slagsvold, Tore; Solonen, Tapio; Sorace, Alberto; Stenning, Martyn J.; Török, János; Tryjanowski, Piotr; van Noordwijk, Arie J.; Walankiewicz, Wiesław; Lambrechts, Marcel M. Møller, A. P., Balbontín, J., Dhondt, A. A., Adriaensen, F., Artemyev, A., Bańbura, J., Barba, E., Biard, C., Blondel, J., Bouvier, J.-C., Camprodon, J., Cecere, F., Charter, M., Cichoń, M., Cusimano, C., Dubiec, A., Eens, M., Eeva, T., Ferns, P. N., . . . Lambrechts, M. M. (2020). Interaction of climate change with effects of conspecific and heterospecific density on reproduction. Oikos, 129(12), 1807-1819. https://doi.org/10.1111/oik.07305 2020 ‘This article is protected by copyright. All rights reserved.’ Interaction of climate change with effects of conspecific and heterospecific density on reproduction Anders Pape Møller1,2 | Javier Balbontín3 | André A. Dhondt4 | Frank Adriaensen5 | Alexandr Artemyev6 | Jerzy Bańbura7 | Emilio Barba8 | Clotilde Biard9 | Jacques Blondel10 | Jean-Charles Bouvier11 | Jordi Camprodon12 | Francesco Cecere13 | Motti Charter14 | Mariusz Cichoń15 | Camillo Cusimano16 | Anna Dubiec17 | Marcel Eens18 | Tapio Eeva19 | Peter N. Ferns20 | Jukka T. Forsman21 | Aya Goldshtein22 | Anne E. Goodenough23 | Andrew G. Gosler24 | Lars Gustafsson25 | Iga Harnist26 | Ian R. Hartley27 | Philipp Heeb28 | Shelley A. Hinsley29 | Staffan Jacob30 | Antero Järvinen31 | Rimvydas Juškaitis32 | Erkki Korpimäki33 | Indrikis Krams34 | Toni Laaksonen35 | Bernard Leclercq36 | Esa Lehikoinen37 | Olli Loukola38 | Mark C. Mainwaring39 | Raivo Mänd40 | Bruno Massa41 | Erik Matthysen42 | Tomasz D. Mazgajski43 | Santiago Merino44 | Cezary Mitrus45 | Mikko Mönkkönen46 | Ruedi G. Nager47 | Jan-Åke Nilsson48 | Sven G. Nilsson49 | Ana C. Norte50 | Mikael von Numers51 | Markku Orell52 | Carla S. Pimentel53 | Rianne Pinxten54 | Ilze Priedniece55 | Vladimir Remeš56 | Heinz Richner57 | Hugo Robles58 | Seppo Rytkönen59 | Juan Carlos Senar60 | Janne T. Seppänen61 | Luís P. da Silva62 | Tore Slagsvold63 | Tapio Solonen64 | Alberto Sorace65 | Martyn J. Stenning66 | János Török67 | Piotr Tryjanowski68 | Arie J. van Noordwijk69 | Wiesław Walankiewicz70 | Marcel M. Lambrechts71 1Anders Pape Møller, Ecologie Systematique Evolution, CNRS, AgroParisTech, Université Paris-Saclay, F-91405 Orsay Cedex, France 2Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, College of Life Sciences, Beijing Normal University, Beijing 100875, China 3Departamento de Zoología, Facultad de Biología, Edificio Verde, Avda. de Reina Mercedes s/n, E-41012 Sevilla, Spain 4Laboratory of Ornithology, Cornell University, 159 Sapsucker Woods Road, Ithaca, NY 14850, USA 5Evolutionary Ecology Group, University of Antwerp, Department of Biology, Campus CGB, B-2020 Antwerp, Belgium 6Institute of Biology of the Karelian Research Centre, Russian Academy of Sciences (IB KRC RAS), Petrozavodsk 185610, Russia 7Department of Experimental Zoology & Evolutionary Biology, University of Łodź, Banacha 12/16, 90-237 Łodź, Poland 8Terrestrial Vertebrates Research Unit "Cavanilles", Institute of Biodiversity and Evolutionary Biology, University of Valencia, C/ Catedrático José Beltran 2, E-46980 Paterna, Spain 9Sorbonne Université, UPEC, Paris 7, CNRS, INRA, IRD, Institut d'Écologie et des Sciences de l'Environnement de Paris, iEES Paris, F-75005 Paris, France 10Centre d’Ecologie Fonctionnelle et Evolutive, CEFE UMR 5175, Campus CNRS, 1919 route de Mende, F-34293 Montpellier Cedex 5, France 11INRA, UR 1115, Plantes et Systèmes de culture Horticoles, F-84000 Avignon, France 12Àrea de Biodiversitat, Grup de Biologia de la Conservació, Centre Tecnològic Forestal de Catalunya, Carretera de St. Llorenç de Morunys, km. 2, E-25280 Solsona, Spain 13Strada Bine, 1424, I-46011 Acquanegra sul Chiese (MM), Italy 14Shamir Research Institute, University of Haifa, Katzrin 1290000 Israel 15Jagiellonian Univ., Inst. Environm. Sci., Krakow, Poland 16Department of Agricultural and Forest Sciences, Università di Palermo, Italy 17Museum and Institute of Zoology, Polish Academy of Sciences, Wilcza 64, PL-00-679 Warsaw, Poland 18Department of Biology, B-2610 Antwerp (Wilrijk), Belgium 19Department of Biology, University of Turku, FI-20014 Turku, Finland 20Cardiff Univ, Sch Biosci, Cardiff CF10 3AX, S Glam, Wales 21Natural Resources Institute Finland, Oulu, FIN-90014 University of Oulu, Finland 22University of Haifa, Israel 23Department of Natural and Social Sciences, University of Gloucestershire, Glos GL50 4AZ, UK 24Department of Zoology, Edward Grey Institute of Field Ornithology & Institute of Human Sciences, Oxford, South Parks Road, Oxford OX1 3PS, UK 25Uppsala Univ., Department of Animal Ecology, Evolutionary Biology Centre, SE-75236 Uppsala, Sweden 26Museum and Institute of Zoology, Polish Academy of Sciences, Wilcza 64, PL-00-679, Warszawa, Poland 27Lancaster Environment Centre, Lancaster University, Lancaster LA1 4YQ, UK 28Laboratoire Évolution & Diversité Biologique, UPS Toulouse III, Bât 4R1, salle 122, 118 route de Narbonne, F-31062 Toulouse, France 29CEH Wallingford, Maclean Building, Crowmarsh Gifford, Wallingford, OX10 8BB, UK 30Station d’Ecologie Théorique et Expérimentale, UMR 5321, 2 route du CNRS, F-09200 Moulis, France 31Kilpisjarvi Biological Station, P. O. Box 17, FIN-00014 University of Helsinki, Finland 32Institute of Ecology of Nature Research Centre, Akademijos 2, LT-08412 Vilnius, Lithuania 33Section of Ecology, Department of Biology, University of Turku, FI-20014 Turku, Finland 34Univ Tartu, Institute of Ecology & Earth Sciences, EE-51014 Tartu, Estonia 35Section of Ecology, Department of Biology, University of Turku, FI-20014 Turku, Finland 36Crx. St. Pierre, 6 rue Morcueil, F-21410 Fleurey Sur Ouche, France 37Section of Ecology, Department of Biology, University of Turku, FI-20014 Turku, Finland 38Department of Ecology and Genetics, University of Oulu, FI-90014 University of Oulu, Finland 39Division of Biological Sciences, University of Montana, Missoula, MT 59812, USA 40Department of Zoology, Institute of Ecology and Earth Sciences, University of Tartu, 46 Vanemuise Str., EE-51014 Tartu, Estonia Accepted Article ‘This article is protected by copyright. All rights reserved.’ 41Stazione Ornitologica, Palermo, Italy 42Department of Biology, University of Antwerp, B-2020 Antwerp, Belgium 43Museum and Institute of Zoology, Polish Academy of Sciences, Wilcza 64, PL-00-679, Warszawa, Poland 44CSIC, Departamento de Ecología Evolutiva Museo Nacional de Ciencias Naturales, Agencia Estatal Consejo Superior de Investigaciones Científicas CSIC, C/ José Gutiérrez Abascal 2, E-28002 Madrid, Spain 45Department of Vertebrate Ecology and Palaeontology, Wrocław University of Environmental and Life Sciences, Wrocław, Poland 46University of Jyväskylä, Department of Biological and Environmental Sciences, POB 35, FIN-40014 University of Jyväskylä, Finland 47Institute of Biodiversity, Animal Health & Comparative Medicine, Graham Kerr Building, University of Glasgow, Glasgow G12 8QQ, UK 48Department of Biology, Evolutionary Ecology, Lund University, SE-223 62 Lund, Sweden 49Dept. of Biology, Biodiversity, Lund University, Ecology Building, SE-223 62 Lund, Sweden 50MARE - Marine and Environmental Sciences Centre, Department of Life Sciences, Largo Marquês de Pombal, Faculty of Sciences and Technology, University of Coimbra, PT-3004-517 Coimbra, Portugal 51Environmental and Marine Biology, Åbo Akademi University Artillerigatan 6, Biocity, FI-20520 Åbo, Finland 52Department of Ecology and Genetics, University of Oulu, P.O. Box 3000, FIN-90014 University of Oulu, Finland 53Centro de Estudos Florestais, Instituto Superior de Agronomia, University of Lisbon, 1349-017 Lisbon, Portugal 54Behavioural Ecology & Ecophysiology Research Group, Department of Biology, B-2610 Wilrijk, and Faculty of Social Sciences, Research Unit Didactica, University of Antwerp, Antwerp, Belgium 55Latvian Fund for Nature, Vilanders Street 3-7, Riga, LV-1010, Latvia 56Laboratory of Ornithology, Department of Zoology, Palacky University, CZ-77146 Olomouc, Czech Republic 57University of Bern, Institute of Ecology & Evolution (IEE), CH-3012 Bern, Switzerland 58Evolutionary Ecology Group (GIBE), Falculty of Sciences, University of A Coruña, Campus Zapateira, E-15008 A Coruña, Spain, and Evolutionary Ecology Group (EVECO), Department of Biology, University of Antwerp, Middelheimcampus, Groenenborgerlaan 171, B-2020 Antwerp, Belgium 59Department of Ecology and Genetics, University of Oulu, P. O. Box 3000, FIN-90014, Finland 60Unidad de Ecología Evolutiva y de la Conducta, Museu de Ciències Naturals de Barcelona, Barcelona, Spain 61University of Jyväskylä, Department of Biological and Environmental Sciences, POB 35, FIN-40014 University of Jyväskylä, Finland 62CIBIO-InBIO, Research Center in Biodiversity and Genetic Resources, University of Porto, 4485-661 Vairão, Portugal 63Department of Biosciences, University of Oslo, Oslo, Norway 64Luontotutkimus Solonen Oy, Neitsytsaarentie 7b B 147, FI-00960 Helsinki, Finland 65SROPU, Via R. Crippa 60, Rome, Italy 66School of Life Sciences, University of Sussex, Falmer, Brighton, Sussex BN1 9QG, UK 67Eötvös Lorand Univ., Behav. Ecol. Grp., Dept. Systemat. Zool. & Ecol., H-1117 Budapest, Hungary 68Institute of Zoology, Poznan University of Life Sciences, Wojska Polskiego 71 C, PL-60-625 Poznań, Poland 69Netherlands Institute of Ecology (NIOO-KNAW), Doevendaalsesteg, 10, NL-6708 BP Wageningen, The Netherlands 70Siedlce University of Natural Sciences and Humanities, Faculty of Natural Science, Department of Zoology, Prusa 12, PL-08-110 Siedlce, Poland 71Centre d’Ecologie Fonctionnelle et Evolutive, CEFE UMR 5175, Campus CNRS, 1919 route de Mende, F-34293 Montpellier Cedex 5, France Corresponding author: Javier Balbontín, Departamento de Zoología, Facultad de Biología, Edificio Verde, Avda. de Reina Mercedes s/n, E-41012 Sevilla, Spain. E-mail: [email protected] Decision date: 08-Aug-2020 This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: [10.1111/oik.07305]. Accepted Article ‘This article is protected by copyright. All rights reserved.’ Abstract We studied the relationship between temperature and the coexistence of great tit Parus major and blue tit Cyanistes caeruleus, breeding in 75 study plots across Europe and North Africa. We expected an advance in laying date and a reduction in clutch size during warmer springs as a general response to climate warming and a delay in laying date and a reduction in clutch size during warmer winters due to density-dependent effects. As expected, as spring temperature increases laying date advances and as winter temperature increases clutch size is reduced in both species. Density of great tit affected the relationship between winter temperature and laying date in great and blue tit. Specifically, as density of great tit increased and temperature in winter increased both species started to reproduce later. Density of blue tit affected the relationship between spring temperature and blue and great tit laying date. Thus, both species start to reproduce earlier with increasing spring temperature as density of blue tit increases, which was not an expected outcome, since we expected that increasing spring temperature should advance laying date, while increasing density should delay it cancelling each other out. Climate warming and its interaction with density affects clutch size of great tits but not of blue tits. As predicted, great tit clutch size is reduced more with density of blue tits as temperature in winter increases. The relationship between spring temperature and density on clutch size of great tits depends on whether the increase is in density of great tit or blue tit. Therefore, an increase in temperature negatively affected the coexistence of blue and great tits differently in both species. Thus, blue tit clutch size was unaffected by the interaction effect of density with temperature, while great tit clutch size was affected in multiple ways by these interactions terms. Keywords: Blue tit, clutch size, Cyanistes caeruleus, great tit, interspecific competition, intraspecific competition, laying date, Parus major, temperature anomaly Accepted Article ‘This article is protected by copyright. All rights reserved.’ Introduction Climate change has been predicted to affect both intra- and interspecific competition either through effects on the abundance of limiting resources, through changes in the abundance of interacting species or through changes in species distribution (Møller et al. 2010, 2019). It is well known that density-dependent effects on fecundity or other demographic traits can regulate populations as a result of intra- and/or interspecific competition. There are two mechanisms that explain density-dependence in fecundity. First, as density increases breeding habitats are occupied in sequential order of quality. High quality sites are occupied firsts and poor quality sites later (i.e. those that yield lower than average fecundity) resulting in a decrease of reproductive parameters at the population level (i.e. Habitat Heterogeneity Hypothesis) (e.g. Dhondt et al. 1992). This hypothesis can be extended to the individual level whereby high quality or older individuals settle first and hence occupy the high quality sites while low quality individuals appear later and occupy low quality sites. This also would enhance the decrease in reproductive parameters at the population level (e.g. Balbontín and Ferrer 2008). Second, increased density can also reduce reproductive parameters due to antagonistic encounters amongst individuals (i.e. Interference Hypothesis) (e.g. Dhondt and Schillemans 1983) or through competition for food. In birds, advanced phenology is correlated with increased fecundity (Kluijver 1951, Winkler and Allen 1996, Smith and Moore 2004). Thus, it is expected that competition caused by increased density would result in delayed breeding at the population level and hence reduce fecundity (e.g. clutch size). Intra- and interspecific competition are known to affect laying date and clutch size in hole-nesting birds (Dhondt 2010, 2012, Stenseth et al. 2015, Møller et al. 2018). However, some studies suggest that such effects of competition are significant only in specific plots or specific periods, raising questions about the generality of these phenomena, but also about their underlying causes (Alatalo and Lundberg 1984, Török and Tóth 1988, Dhondt et al.1992). Birds advance the timing of migration or breeding in response to climate warming (Parmesan and Yohe 2003). This response has been attributed to improve the synchronization of the timing of reproduction with the timing of prey emergence at lower trophic levels. Thus, the peak in food abundance (e.g. caterpillar) would match with the peak of maximum demand of chicks during the nestling stage. However, this possible mismatch could vary across Europe (e.g., Visser et al. 1998, 2009).. Although the relationship between laying date and climate warming is well known, we know little about the relationship between clutch size and temperature. For instance, a warmer spring could provide a more Accepted Article ‘This article is protected by copyright. All rights reserved.’ favourable ambient environment for females that might result in an increase in reproductive investment. However, it has been suggested that a reduction in clutch size could be an alternative strategy to improve reproductive adjustment with lower trophic levels (e.g. Bleu et al. 2017). Female great and blue tits lay a clutch of 7-9 eggs and 7-13 eggs, respectively (e.g., Perrins 1991). The species differ in life-history strategies in that the probability to lay a second brood is lower in blue compared to great tit (e.g. Gibb and Betts 1963, Visser et al. 2003). As double-brooded species have more difficulty to cope with climate change than single-brood species (e.g. Husby et al. 2009) we expected a difference in response to climate change of blue tits compared to great tits. Blue tit should respond more strongly to increasing temperatures since it is a mainly single-brood species. During the breeding season interspecific competition for food occurs when the smaller blue tit consumes smaller instar of the same caterpillar species as eaten by the larger great tit. This results in preemptive food consumption that differentially impairs the great tit, which is therefore the inferior competitor (Dhondt 2012). On the other hand, competition for access to nest boxes favours great tits when large-holed nest boxes are available (Dhondt and Eyckerman 1980). Great tits outcompete blue tits by excluding blue tits from boxes used as roosting or breeding sites, even when boxes are super-abundant (Dhondt 2012). During the non-breeding season great and blue tit adult survival rate is affected by winter severity (e.g. Robinson et al. 2007, Pearce-Higgins and Green 2014). Winters with abundant and extended snow cover decrease survival rate of adult and one-year old birds and consequently population size is reduced during the next breeding season. These effects of winter weather on survival have been attributed to reduced food supply in snowy winters (e.g., beech mast) (Pearce-Higgins and Green 2014 and reference herein). Thus, we expected an increase in population size (i.e. density) after warmer winters. Specifically, as density increased, the proportion of one-year old individuals being part of the populations this effect should specifically affect short-lived species. This could constitute part of the mechanism that could delay laying date and reduce clutch size due to density-dependent effects (e.g. Dhondt et al. 1992, Balbontín and Ferrer 2008). Recently, Møller et al. (2018) published extensive analyses of effects of competition on laying date and clutch size in great and blue tit across Europe and North Africa. Here we expand these analyses by testing for the first time whether the effects of climate change during the last 50 years significantly influenced intra- and interspecific competition by measuring their presumed effect on lay date and clutch Accepted Article ‘This article is protected by copyright. All rights reserved.’ size while controlling statistically for a number of variables that are known to predict lay date and clutch size in blue and great tit (Møller et al. 2014a). We did so by analysing a long-term dataset of 75 studies of two species of secondary hole nesting birds across Europe and North Africa. We used density (number of occupied nestboxes per ha) as a proxy for intensity of competition (Dhondt 2012). Intensity of competition could be measured as the slope of density on a demographic parameter (e.g. laying date or clutch size). Therefore, we included density as an independent variable in statistical models were the dependent variable was laying date or clutch size to measure intensity of competition (Welden and Slauson 1986). We used temperature anomalies during winter and spring as a proxy of climate change. The objectives of this study are to test whether laying date advanced and clutch size change with increasing temperature, whether this effect was modified by density; and whether the intensity of intra- and interspecific competition was impacted by increasing temperature anomalies. We predicted that (1) in warmer winters survival rates should increase, particularly for yearling birds (i.e. those that lay smaller clutches and lay later) in both great and blue tits. Hence inter- and intraspecific density should increase resulting in a delayed laying date and a reduced clutch size. The relationships between temperature anomalies in winter and laying date and clutch size are predicted to increase with density. Thus, we expected a greater delay in laying date and a greater reduction in clutch size with increased winter temperature anomalies (for details see Table 1). (2) In warmer springs (i.e. with increased spring temperature anomalies) a more proximal cue for seasonally breeding species, we expected laying date to advance in both great and blue tit, with a stronger response in blue tits. If this results in a mismatch with lower trophic levels, tits should adaptively reduce clutch size to cope with the reduced food availability when feeding nestlings. We thus expect that positive spring temperature anomalies will lead to a reduced clutch size with a stronger effect in great tits. We did not predict an effect for the outcome of the interaction between temperature anomalies in spring and density on laying date. Because warming should advance laying, and competition should delay laying, both effects could cancel each other out. Likewise, competition and its interaction with temperature anomalies in spring should reduce clutch size in great tits more than blue tits. This is expected because the latter outcompetes the former for food, and also because blue tits should respond more rapidly to temperatures in spring since it is mainly a single-brood species (for details see Table 1). Methods Accepted Article ‘This article is protected by copyright. All rights reserved.’ Study sites and data sets We obtained information on density of occupied nest boxes per ha, nest box size, clutch size, laying date and ecological variables from all studies considered in this paper for two common species of secondary hole-nesters, the great tit and the blue tit, across Europe and North Africa, as described in detail elsewhere (Møller et al. 2014a, b). Density of great or blue tits was estimated as the number of occupied nest boxes per ha. Nest boxes have entrance holes that could be large enough for great tits (32 mm diameter) and in some plots have additional small-holed nest boxes available for blue tits (26 mm diameter). Nest boxes usually are available in all plots at high densities (e.g., >6.6.ha-1) and did not limit population size. In total, we calculated 919 yearly mean laying dates and 916 yearly mean clutch sizes across 75 study plots with both great and blue tits breeding during the period 1957-2012 (Møller et al. 2014a, b). Study years started in 1957 in Vlieland and ended in 2012 in several study plots. The mean (SD) numbers of years monitored was 11.49 (14.66) (range: 1-55 years). The mean (SD) Nearest Neighbour Distance was 173.6 (115.4) km. The abundance of great and blue tits changes across years within study plots. The average abundance of great tits was 18 (range: 1-137) occupied nest boxes and for blue tits 17 (range: 1-99) occupied nest boxes. The average density was 0.68 breeding pairs / ha for great tit and 0.65 breeding pairs / ha for blue tit. We included only study plots in which both great and blue tits had been recorded breeding at least once in order to ensure that all study plots contained suitable habitats, breeding sites and nest boxes for both species. Although the taxonomy of tits is currently under revision (Stenning 2018), we used two taxa of tits (great tit and blue tit) with comparable ecologies without considering that some populations in the Canary Islands and North Africa may constitute the separate species Cyanistes teneriffae (Stenning 2018). We restricted the analyses to first clutches, or early clutches known to be initiated less than 30 days after the first egg was laid in a given year in a study area to standardize sampling procedures (cf. Nager and van Noordwijk 1995). We assumed that the very small number of unidentified early repeat clutches that usually result from perturbations (e.g. Haywood 1993), or lay-dates calculated from information obtained from different breeding stages (e.g. Lambrechts et al. 1997), did not substantially alter the overall average clutch size and average lay date per study plot. Second or late clutches were excluded from analyses because they are usually smaller than first or early clutches and their frequency varies between years and habitats (e.g. Kluijver 1951, Lambrechts et al. 2008). Accepted Article ‘This article is protected by copyright. All rights reserved.’ All data are available at DOI: doi:10.5061/dryad.p763611. Life-history traits and environmental factors Information on latitude, longitude and altitude was provided by the authors of earlier studies or found in publications (for details, see Vaugoyeau et al. 2016, Møller et al. 2014a, b, 2018). Tree species vary significantly in timing and amount of invertebrates available for raising offspring in tits (e.g. Kennedy and Southwood 1984, Lambrechts et al. 2008). We classified vegetation as ‘deciduous’ habitat dominated by non-evergreen broad-leaved deciduous trees (Alnus, Betula, Carpinus, Citrus, Fagus, Fraxinus, Malus, Quercus, including Q. faginea), ‘evergreen’ habitat dominated by non-coniferous broad-leaved evergreen trees (Q. ilex, Q. suber), ‘coniferous’ habitat dominated by coniferous trees (Abies, Cedrus, Picea, Pinus), or ‘mixed’ habitats formed by a combination of the former tree vegetation classes (e.g. deciduous mixed with evergreen). Study plots were classified as either rural or urban, using the classifications provided by the original studies. Urban areas were characterized by city parks, gardens and similar habitats in close proximity to humans, while forests, plantations and similar habitats were classified as rural. Only nest box studies were included. We calculated the internal floor area (in cm²) of nest boxes, using publications (e.g. Lambrechts et al. 2010) or additional information provided by participants. The material constituting the nest box was divided into two broad binary classes that are readily distinguishable: wood scored as 1, which includes tree trunks, plywood, board-masonite, or board (e.g. Gustafsson and Nilsson 1985) and concrete scored as 0 (a mixture of cement and other materials; Lambrechts et al. 2010). We included all these input variables in the statistical models because previous studies have indicated that each of these variables are significant predictors of laying date and clutch size (Lambrechts et al. 2010; Møller et al. 2014a, b; Vaugoyeau et al. 2016). Major life history traits are known to vary among years. For instance, in local study plots biotic (e.g. resource availability, intra- or interspecific interactions) and abiotic factors (e.g. weather) can vary substantially among years perhaps explaining within-plot variation in average clutch size (e.g. Kluijver 1951, Perrins 1965, Both 2000). We thus used study year as a random factor in all analyses. Temperature We used temperature anomalies rather than temperatures themselves to characterize climate across the very large geographic area of the study because we were interested in the effect of temperature Accepted Article ‘This article is protected by copyright. All rights reserved.’ which is in line with results of Dhondt (2010) in which he reports a stronger effect of density on clutch size of great tit than blue tit (Prediction 8: supported). Density-dependence could result in a delay in laying date and a reduction in clutch size (Stenseth et al. 2015). An increase in intra- or interspecific competition (resulting from higher densities) could affect the response to climate warming (Stenseth et al. 2015). If that was the case, we would expect a significant interaction between density and temperature anomaly on laying date and clutch size. Indeed, an increase in winter temperature interacted with density of great tit by delaying laying date of both great and blue tit (Prediction 3: supported). An increase in winter temperature anomaly could increase adult survival in both species, specifically in blue tits, and this could affect the intensity of competition the subsequent spring, which in turn could reduce clutch size and delay laying at the population level due to density-dependent processes including an increase in the proportion of young inexperienced breeders (e.g. Dhondt et al. 1992, Ferrer and Donazar 1996). Importantly, that is what we found for the interactions between winter temperature and density for laying date of great and blue tit and for clutch size of great tit. Alternatively, energetic constraints imposed during winter may also have physiological consequences that may affect laying date. Warm winters may select for metabolic genotypes with a reduced rate of living resulting in smaller clutches (Nilsson and Nilsson 2016). However, our statistical analyses still showed a relationship between temperature anomaly and life history traits after adjustment for density, implying that there are genuine temperature anomaly effects. Warm springs imply faster caterpillar development, and birds have to speed up to keep up with the caterpillars. One way of doing so is by laying fewer eggs, or by starting incubation earlier (Matthysen et al. 2011). Therefore, it would be possible that the advance in laying date would not suffice to match the emergence of caterpillars, the main food for nestling tits (Perrins 1965, Both et al. 2009). Reduced clutch size may constitute an additional reproductive strategy to decrease the mismatch by advancing incubation, as experimentally shown in the great tit (Bleu et al. 2017). Therefore, a mismatch between emergence of food and timing of reproduction could also occur at large spatial and temporal scales across the breeding season, as already shown for specific European populations of birds (e.g. Visser et al. 1998, Both et al. 2009). In contrast, there is only little evidence of mismatch between blue and great tits and their food resources except for summers with warmer spring (Burgess et al. 2018). Therefore, there are different explanations for the observed reduction in clutch size with increasing temperatures in winter, and this should be explored further in future studies. Accepted Article ‘This article is protected by copyright. All rights reserved.’ Since increasing temperature anomaly in winter reduced clutch size of both species, the abundance of both species should be affected equally by climate warming. However, winter temperature anomaly has a stronger effect on clutch size in great tit (estimate (SE) =-0.506 (0.079), Table 4) than in blue tit (estimate (SE)=-0.159 (0.067), Table 5). However, clutch size is only a component of fitness and we need future studies to try to find out how these contrasting effects translate into differences in population sizes between these tits species. The interacting effect of climate warming with density affected clutch size of great tit while it did not affect clutch size of blue tits. For instance, an increase in spring temperature interacted differently with density of blue tit compared to the effect of density of great tits on their clutch size. Specifically, increasing spring temperature interacted with density of blue tits increasing clutch size of great tit (i.e. rejecting prediction 7), while increasing spring temperatures interacted with density of great tits to decrease clutch size of great tits (i.e. supporting prediction 7). In contrast, the interaction between spring temperature anomaly and density of great or blue tits on clutch size of blue tits was not significant. That is in accordance with prediction 7 since we predicted stronger effects on great compared with blue tits. Therefore, a rapid advance in laying date with density and temperature anomaly did not provide a reproductive advantage for great tits, while that could be the case for blue tits since clutch size was not reduced in blue tits when temperature anomaly and density interacted to affect clutch size. The difference in response to clutch size in great compared to blue tits could be related that either blue tits consume earlier instars of caterpillar larvae that emerge earlier or to that the two species may forage in different micro-habitats, such as different heights in trees with great tits consuming more food on the ground (Slagsvold and Wiebe 2007). The phenology of invertebrate prey may differ between such micro-habitats (Tremblay et al. 2005, Visser et al. 2003), and, therefore, the difference in prey response to climate change by the two species could explain small differences in timing of breeding. Therefore, if these trends in climate warming continue at similar rates, these interspecific differences could translate into differences in abundance or population size favouring blue tit since this species seems to be less affected by climate warming than great tit. In conclusion, when studying the effects of increasing temperature anomalies on timing of reproduction and clutch size at large spatial and temporal scales, we found that great and blue tits responded to climate warming by advancing timing of reproduction. However, this advance in breeding date with increasing temperature anomaly did not prevent a reduction in clutch size due to increasing temperature anomalies and increasing densities. In addition, the response to increasing temperature Accepted Article ‘This article is protected by copyright. All rights reserved.’ anomaly interacted with density by advancing laying date even more at higher densities. This interaction reduced clutch size in great, but not in blue tits. Further studies are needed to examine how intra- and interspecific relationships interact with temperature anomalies, on timing of breeding and breeding success, which may ultimately affect fitness and population size. Acknowledgements We would like to warmly thank the hundreds of collaborators and contributors who helped with study plot management, data collection, data management, administration, financial support, and scientific discussion. Listing their names individually would most probably provide a biased picture of all of their contributions. Fundings A. Artemyev acknowledges funding by IB KRC RAS No. 0221-2017-0046 and T. Eeva acknowledges funding by the Academy of Finland (project 265859). This study was funded by research project CGL- 2016-79568-C3-3-P (to J.C. Senar), from the Ministry of Economy and Competitivity, Spanish Research Council. Author contributions A.P.M. and J.B. conceived the idea. A.P.M. and J.B. analysed data and A.P.M. J.B. and A.A.D. wrote the manuscript. A.P.M., A.A.D., F.A., A.A., J.Ba., E.B., C.B., JcB.,J.C.B., J.C., F.C., M.C., M.Ch.,C.C., A.D., M.E., T.E., P.N.F., J.T.F., A.G., A.E.G., A.G.G., L.G., I.H., I.R.H., P.H., S.A.H., S.J., A.J., R.J.,E.K., I.K., T.L., B.L., E.L.,O.L, M.C.M., R.M., B.M., E.M.,T.D.M., S.M., C.M., M.M., R.G.N., J.- Å.N., S.G.N., A.C.N., M.V.N., M.O.,C.S.P., R.P., I.P., V.R., H.R.,Hu.R., S.R.,J.C.S.,J.T.S.,L.P.S, T.S.,T.So. A.S., M.J.S., J.T.,P.T., A.J.v.N., W.W., and M.M.L. collected data and approved final manuscript. Conflicts of interest The authors declare not conflicts of interest Permits Accepted Article ‘This article is protected by copyright. All rights reserved.’ The data used in every study plot have the appropriated permits issued for each country or region government. Data accessibility Data are available from the Dryad Digital Repository upon acceptance. Accepted Article ‘This article is protected by copyright. All rights reserved.’ References Aplin, L. M. et al. 2015. Experimentally induced innovations lead to persistent culture via conformity in wild birds. - Nature 518: 538–541. Alatalo, R. V. and Lundberg, A. 1984. Density dependence in breeding success of the pied flycatcher (Ficedula hypoleuca). – J. Anim. Ecol. 53: 969-977. Balbontín, J. and Ferrer, M. 2008. Density-dependence by habitat heterogeneity: individual quality versus territory quality. – Oikos 117: 1111-1114, 2008 Bartón, K. 2009. MuMIn: multi-model inference. R package, version 0.12.2. Available at: http://r-forge.r-project.org/projects/mumin/. Bates, D. and Maechler, M. 2009. lme4: Linear mixed-effects models using S4 classes. R package, version 0.999375-31. Available at: http://CRAN.R-project.org/package=lme4. Bleu, J. et al. 2017. Nest box temperature affects clutch size, incubation initiation and nestling health in great tits. – Behav. Ecol. 48: 489-501. Both, C. 2000. Density dependence of avian clutch size in resident and migrant species: Is there a constraint on the predictability of competitor density? – J. Avian Biol. 31, 412–417. Both, C. et al. 2009. Climate change and unequal phenological changes across four trophic levels: constraints or adaptations. – J. Anim. Ecol. 78, 73–83. Burgess, M.D. et al. 2018. Tritrophic phenological match-mismatch in space and time. Nat. Ecol. Evol. 2(6):970-975. Burnham, K. P. and Anderson, D. R. 2002. Model selection and multimodel inference: A practical information-theoretic approach. 2nd Edition. Springer-Verlag, New York, NY. CMB and Crouch, J. (17 September 2012). Global surface temperature anomalies: Background information. NOAA NCDC. Dhondt, A. A. 2010. Effects of competition on great and blue tit reproduction: Accepted Article ‘This article is protected by copyright. All rights reserved.’ intensity and importance in relation to habitat quality. – J. Anim. Ecol. 79:257- 265. doi: 10.1111/j.1365-2656.2009.01624.x Dhondt, A. A. 2012. Interspecific competition in birds. Oxford University Press, Oxford, UK. Dhondt, A. A. and Eyckerman, R. 1980. Competition Between the Great Tit and the Blue Tit Outside the Breeding Season in Field Experiments. – Ecology 61:1291–1296. doi: 10.2307/1939036. Dhondt, A. A. and Schillemans J. 1983. Reproductive success of the great tit in relation to its territorial status. – Anim. Behav. 31: 902-912. Dhondt, A. A. et al. 1992. Density-dependent clutch size caused by habitat heterogeneity. – J. Appl. Ecol. 61: 643-648. Ferrer, M. and Donázar, J.A. 1996. Density-dependent fecundity by habitat heterogeneity in an increasing population of Spanish imperial eagles. – Ecology 77: 69-77. Freund, R.J., Littell, R.C., and Creighton, L. 2003. Regression Using JMP. Cary, NC: SAS Institute, Inc. Gelman, A. 2008. Scaling regression inputs by dividing by two standard deviations. –Statis. Med. 27: 2865–2873. Gibb, J. A. and Betts, M. M. 1963. Food and food supply of nestling tits (Paridae) in Breckland pine. – J. Anim. Ecol. 32: 489–533 Grueber, C. E. et al. 2011. Multimodel inference in ecology and evolution: challenges and solutions. – J. Evol. Biol. 24: 699-711. Gustafsson, L. and Nilsson, S. G. 1985. Clutch size and breeding success of pied and collared flycatchers Ficedula spp. – Ibis 127: 380-385. Hansen, J. and Lebedeff, S. 1987. Global trends of measured surface air temperature. – J. Geophys. Res. 92:13,345-13,372. Haywood, S. 1993. Sensory and hormonal control of clutch size in birds. – Q. Rev. Biol. 68:33-60. Husby, A. et al. 2009. Decline in the frequency and benefits of multiple brooding in great tits as a consequence of a changing environment. Proc. R. Soc. Lond. B: Biol. Sci. 276 (1663): 1845– 1854. Kennedy, C. E. J. and Southwood, T. R. E. 1984. The Number of Species of Insects Associated with British Trees: A Re-Analysis. – J. Anim. Ecol. 53(2):455-478. Accepted Article ‘This article is protected by copyright. All rights reserved.’ Kluijver, H. N. 1951. The population ecology of the great tit Parus m. major L. – Ardea 39:1–135. Lambrechts, M. M. et al. 1997. A single response mechanism is responsible for evolutionary adaptive variation in a bird’s laying date. – Proc. Nat. Acad. Sci. USA 94:5153-5155. Lambrechts, M. M. et al. 2008. Double-brooded great tits (Parus major) in Mediterranean oak habitats: Do first broods always perform better than second broods? – Russian J. Ecol. 39:516. Lambrechts, M. M. et al. 2010. The design of artificial nest boxes for the study of secondary hole-nesting birds: A review of methodological inconsistencies and potential biases. – Acta Ornithol. 45:1- 26. Matthysen, E. M. et al. 2011. Multiple responses to increasing spring temperatures in the breeding cycle of blue and great tits (Cyanistes caeruleus, Parus major. – Global Change Biol. 17:1-16, doi: 10.1111/j.1365-2486.2010.02213.x Møller, A. P. et al. 2014a. Clutch size in European secondary hole-nesting passerines in relation to nest-box floor area, habitat, geographic location and study year. – Methods Ecol. Evol. 5:353-362. Møller, A. P. et al. 2014b. Variation in clutch size in relation to nest size in birds. – Ecol. Evol. 4:3583-3595. Møller, A. P. et al. 2010. Effects of climate change on birds. - Oxford University Press, Oxford, UK. Møller, A. P. et al. 2018. Effects of interspecific coexistence on laying date and clutch size in two closely related species of hole-nesting birds. – J. Anim. Ecol. 87:1738-1748. Møller, A. P. et al. 2019. Effects of climate change on birds. - Oxford University Press, Oxford, UK. Nager, R. G. and van Noordwijk, A. J. 1995. Proximate and ultimate aspects of phenotypic plasticity in timing of great tit breeding in a heterogeneous environment. – Am. Nat. 146:454–474. Accepted Article ‘This article is protected by copyright. All rights reserved.’ Nilsson, J.-F and Nilsson, J.-Å. 2016. Fluctuating selection on basal metabolic rate. – Ecol. Evol. 6:1197-1202. Parmesan, C. and Yohe, G. 2003. A globally coherent fingerprint of climate change impacts across natural systems. – Nature 421: 37–42. Perrins, C. M. 1965. Population fluctuations and clutch-size in the great tit, Parus major. – J. Anim. Ecol. 34: 601–647. Perrins, C. M. 1991. Tits and their caterpillar food supply. – Ibis 133: 49–54. Pearce-Higgins, J. W. and Green, R. E. 2014. Birds and Climate Change: Impacts and Conservation Solutions. Cambridge University Press, Cambridge. R Core Team (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/. Richards, S. A. 2008. Dealing with overdispersed count data in applied ecology. – J. Appl. Ecol. 45:218– 227. Robinson, R. A. et al. 2007. Weather-dependent survival: implications of climate change for passerine population processes. – Ibis 149: 357–364. Samplonius, J. M. and Both, C. 2017. Competitor phenology as a social cue in breeding site selection. – J. Anim. Ecol. 86: 615–23. Samplonius, J. M. et al. 2017. Nest site preference depends on the relative density of conspecifics and heterospecifics in wild birds. – Frontiers Zool. 14:56. DOI 10.1186/s12983-017-0246-5 Slagsvold, T. and Wiebe, K. L. 2007. Learning the ecological niche. – Proc. R. Soc. B 274:19–23. Smith, R. J. and Moore, F. R. 2004. Arrival timing and seasonal reproductive performance in a long-distance migratory landbird. – Behav. Ecol. Sociobiol. 57:231–239. Stenning, M. 2018. The blue tit. T. and A. D. Poyser, London, UK. Stenseth, N. C. et al. 2015. Testing for effects of climate change on competitive relationships and coexistence between two bird species. – Proc. R. Soc. B 282:20142929. Accepted Article ‘This article is protected by copyright. All rights reserved.’ Tremblay, I. et al. 2005. The effect of habitat quality on foraging patterns, provisioning rate and nestling growth in Corsican Blue Tits Parus caeruleus. – Ibis 147 :17– 24. Török, J. and Tóth, L. 1988. Density dependence in reproduction in the collared flycatcher (Ficedula albicollis) at high population levels. – J. Anim. Ecol. 57: 251-258 Vaugoyeau, M. et al. 2016. Interspecific variation in the relationship between clutch size, laying date and intensity of urbanisation in four species of hole-nesting birds. – Ecol. Evol. 6: 16. Welden, C. W. and Slauson, W. L. 1986. The intensity of competition versus its importance – an overlooked distinction and some implications. - Q. Rev. Biol. 61: 23–44. Visser, M. E. et al. 1998. Warmer springs lead to mistimed reproduction in great tits (Parus major). – Proc. R. Soc. B 265: 1867–1870. Visser, M. E. et al. 2003. Variable responses to large scale climate change in European Parus populations.– Proc. R. Soc. B 270:367–372. https://doi.org 10.1098/rspb.2002.2244. Visser M. E. et al. 2009. Temperature has a causal effect on avian timing of reproduction. - Proc R. Soc. B 276: 2323–2331. Winkler, D. W. and Allen, P. E. 1996. The seasonal decline in tree swallow clutch size: physiological constraint or strategic adjustment? – Ecology 77: 922–932. Wittwer, T. et al. 2015. Long‐term population dynamics of a migrant bird suggests interaction of climate change and competition with resident species. Oikos 124 (9): 1151–1159. Accepted Article ‘This article is protected by copyright. All rights reserved.’ Figure legends Figure 1 Effects of temperature anomaly (ºC) in spring and winter on laying date of great and blue tits where 1 = January 1st. The lines (± 95% CI) are the predicted values obtained from a linear mixed-effect model where latitude, longitude and altitude and nest floor surface are maintained at their mean values and habitat, urbanization and nest box material at their reference values (i.e., conifer, rural habitat and box material concrete). Black lines represent effect size and did not include zero in 95% CI and grey lines represent effect size and did include zero in 95% CI (see Tables 3 and 4 for details) Accepted Article ‘This article is protected by copyright. All rights reserved.’ Table 2 Summary results after model averaging of the effects of temperature anomaly in spring and winter and density of great and blue tits on laying date of great tits across Europe and North Africa. Estimates (SE) and 95% CI are reported. The model also included other potential predictors of laying date of great tit. Sample size is 919 observations on yearly average laying date taken across 75 sites across Europe. Effects in bold font are statistically significant ______________________________________________________________________ Parameter Estimate SE CI (95%) ______________________________________________________________________ Intercept 58.910 2.130 (54.729, 63.091) Density of Blue tit (BT) 1.497 0.766 (-0.006, 3.002) Density of Great tit (GT) -1.730 0.611 (-2.928, -0.530) Latitude 8.766 2.738 (3.392, 14.139) Longitude 5.295 1.918 (1.531, 9.060) Floor surface (nest) 0.069 1.145 (-2.177, 2.317) Tª Spring -5.100 0.626 (-6.330, -3.870) Tª winter -0.977 0.559 (-2.075, 0.121) Tª Spring x BT -2.452 0.849 (-4.199, -0.875) Tª Spring x GT -1.267 0.760 (-2.759, 0.224) Tª Winter x BT -0.521 0.913 (-2.313, 1.270) Tª Winter x GT 1.535 0.702 (0.157, 2.914) Altitude 0.389 2.577 (-4.668, 5.448) Material 2.027 1.837 (-1.577, 5.632) Urbanization -2.553 1.259 (-5.026, -0.081) Habitat (Deciduous) -4.858 2.461 (-9.689, -0.027) Habitat (Evergreen) 1.395 3.603 (-5.677, 8.467) Habitat (Mixed) -3.432 1.039 (-5.471, -1.392) ______________________________________________________________________ *Effect sizes have been standardized to two SD following Gelman (2008). Reference levels were (no) urbanized for urbanization and (conifer) for habitat. Parameter estimates for predictors with confidence intervals not including zero are highlighted in bold. CI is confidence interval Accepted Article ‘This article is protected by copyright. All rights reserved.’ Table 3 Summary results after model averaging of the effects of temperature anomaly in spring and winter and density of great and blue tit on laying date of blue tit across Europe and North Africa. Estimates (SE) and 95% CI are reported. The model also included other potential predictors of laying date of great tit. Sample size is 919 observations on yearly average laying date taken across 75 sites across Europe. Effects in bold font are statistically significant ______________________________________________________________________ Parameter Estimate SE CI (95%) ______________________________________________________________________ Intercept 58.836 2.273 (54.374, 63.299) Density of Blue tit (BT) 1.946 0.651 (0.667, 3.224) Density of Great tit (GT) -1.713 0.519 (-2.732, -0.693) Latitude 22.628 2.738 (16.475, 28.782) Longitude 0.079 2.155 (-4.150, 4.309) Floor surface (nest) -2.191 1.038 (-4.229, -0.153) Tª Spring -4.925 0.526 (-5.959, -3.891) Tª winter -0.469 0.471 (-1.394, 0.454) Tª Spring x BT -2.794 0.732 (-4.232, -1.357) Tª Spring x GT -1.512 0.654 (-2.796, -0.227) Tª Winter x BT -0.652 0.731 (-2.087, 0.872) Tª Winter x GT 1.472 0.571 (0.350, 2.594) Altitude 15.362 2.620 (10.219, 20.506) Material 1.307 1.907 (-2.436, 5.051) Urbanization -2.592 1.080 (-4.713, -0.472) Habitat (Deciduous) -5.985 2.626 (-11.139, -0.831) Habitat (Evergreen) 6.846 3.793 (-0.598, 14.290) Habitat (Mixed) -3.684 0.883 (-5.418, -1.951) ______________________________________________________________________ *Effect sizes have been standardized to two SD following Gelman (2008). Reference levels were (no) urbanized for urbanization and (conifer) for habitat. Parameter estimates for predictors with confidence intervals not including zero are highlighted in bold. CI is confidence interval Accepted Article ‘This article is protected by copyright. All rights reserved.’ Table 4 Summary results after model averaging of the effects of temperature anomaly in spring and winter and density of great and blue tit on clutch size of great tit across Europe and North Africa. Estimates (SE) and 95% CI are reported. The model also included other potential predictors of clutch size of great tit. Sample size is 916 observations on yearly average laying date taken across 75 sites across Europe. Effects in bold font are statistically significant ______________________________________________________________________ Parameter Estimate SE CI (95%) ______________________________________________________________________ Intercept 8.642 0.200 (8.247, 9.036) Laying date of Great tit -0.839 0.094 (-1.024, -0.653) Density of Blue tit (BT) -0.150 0.102 (-0.351, 0.050) Density of Great tit (GT) -0.203 0.080 (-0.362, -0.044) Latitude 0.145 0.404 (-0.648, 0.939) Longitude 1.110 0.180 (0.759, 1.464) Floor surface (nest) 0.101 0.143 (-0.179, 0.382) Tª Spring 0.040 0.092 (-0.140, 0.222) Tª Winter -0.506 0.079 (-0.662, -0.349) Tª Spring x BT 0.322 0.122 (0.083, 0.562) Tª Spring x GT -0.277 0.098 (-0.470, -0.084) Tª Winter x BT -0.445 0.120 (-0.682, -0.208) Tª Winter x GT 0.128 0.096 (-0.060, 0.318) Altitude -0.480 0.213 (-0.899, -0.060) Material 0.494 0.208 (0.084, 0.903) Urbanization -0.655 0.163 (-0.976, -0.334) Habitat (Deciduous) 0.339 0.246 (-0.144, -0.824) Habitat (Evergreen) -0.211 0.383 (-0.964, 0.541) Habitat (Mixed) 0.196 0.142 (-0.082, 0.475) ______________________________________________________________________ *Effect sizes have been standardized to two SD following Gelman (2008). Reference levels were (no) urbanized for urbanization and (conifer) for habitat. Parameter estimates for predictors with confidence intervals not including zero are highlighted in bold. CI is confidence interval Accepted Article ‘This article is protected by copyright. All rights reserved.’ Table 5 Summary results after model averaging of the effects of temperature anomaly in spring and winter and density of great and blue tit on clutch size of blue tit across Europe and North Africa. Estimates (SE) and 95% CI are reported. The model also included other potential predictors of clutch size of great tit. Sample size is 916 observations on yearly average laying date taken across 75 sites across Europe ______________________________________________________________________ Parameter Estimate SE CI (95%) ______________________________________________________________________ Intercept 9.705 0.254 (9.205, 10.205) Laying date of blue tit -0.954 0.107 (-1.165, -0.743) Density of blue tit (BT) -0.143 0.097 (-0.335, 0.047) Density of great tit (GT) -0.109 0.080 (-0.267, -0.047) Latitude 1.560 0.467 (0.643, 2.478) Longitude 0.491 0.234 (0.030, 0.951) Floor surface (nest) -0.282 0.153 (-0.583, 0.017) Tª Spring -0.146 0.079 (-0.301, 0.008) Tª Winter -0.159 0.067 (-0.291, -0.026) Tª Spring x BT 0.032 0.111 (-0.185, 0.250) Tª Spring x GT -0.136 0.086 (-0.306, 0.034) Tª Winter x BT 0.027 0.100 (-0.169, 0.224) Tª Winter x GT 0.106 0.093 (-0.077, 0.290) Altitude -1.021 0.339 (-1.687, -0.355) Material 0.608 0.261 (0.096, 1.121) Urbanization -0.020 0.168 (-0.350, 0.309) Habitat (Deciduous) 0.272 0.296 (-0.309, 0.854) Habitat (Evergreen) -0.926 0.467 (-1.843, -0.010) Habitat (Mixed) 0.232 0.142 (-0.047, 0.513) ______________________________________________________________________ *Effect sizes have been standardized to two SD following Gelman (2008). Reference levels were (no) urbanized for urbanization and (conifer) for habitat. Parameter estimates for predictors with confidence intervals not including zero are highlighted in bold. CI is confidence interval Accepted Article