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1 Electronic Supplementary Materials of the paper 2 Reproductive costs in terrestrial male vertebrates: insights from bird studies 3 4 Josefa Bleu†, Marlène Gamelon† and Bernt-Erik Sæther 5 6 † Co-first authors 1 7 ESM 1. General framework. 8 The goal of this review is to give a synthetic view of the importance of direct fitness 9 costs of reproduction in males in wild vertebrate populations. We did not aim at clarifying the 10 definition of a reproductive cost, or providing statistical tools to test direct costs of 11 reproduction accurately as definition and statistical advices are the same for both males and 12 females and have been previously described in details [see 1]. This means that we 13 summarized the results of studies investigating the effects of reproduction (time t) on survival 14 and/or reproduction the next breeding season (time t+1) [two consecutive breeding seasons] 15 through the co-variations between life history traits (also called direct fitness traits sensu Roff 16 [2]). There are direct costs of reproduction in the reviewed studies when these co-variations 17 were negative and there is no direct cost of reproduction in the opposite case. As shown in 18 Figure S1, the following types of studies were not included: 19 (1) Mechanistic studies. These studies investigate the effect of reproductive effort on 20 different individual characteristics, such as physiological parameters, but they do not provide 21 direct measures of fitness cost. For example, the growing literature on the putative role of 22 oxidative stress as a mediator of reproductive costs is not included in this review [e.g. 3]. 23 Other examples are the studies on breeding dispersal in birds. It is known that reproductive 24 success may affect the distance of dispersal the following year, such that unsuccessful 25 breeders will be able to find a better territory. However, it is not clear how breeding dispersal 26 affects future reproduction and survival and how it can be interpreted in the context of costs 27 of reproduction. Thus, we did not include studies that looked at the effect of reproduction on 28 breeding dispersal without providing evidence of an effect of breeding dispersal on 29 reproductive output or survival [e.g. 4]. 2 30 (2) Studies with indirect measure of reproductive effort. We kept only studies 31 providing direct measure of the investment in reproduction to focus our review on life history 32 trade-offs. Moreover, we did not want to overlap with the large literature on the costs of the 33 investment in sexually selected characters [5]. However, if it was shown in the same study 34 that a male characteristic was correlated to reproduction and also to future survival or 35 reproduction, then it was included (e.g. the dominance trait in the jackdaw study [e.g. 6]). 36 (3) Delayed costs of reproduction. Finally, studies investigating the cumulative costs 37 of reproduction, the long-term costs of reproduction (late performance) in line with the 38 disposable soma theory of aging [7] or the effect of reproduction on following generations 39 were not included in this review. Indeed, we aimed at assessing the overall support of costs of 40 reproduction in males and its potential consequences in terms of population dynamics. Thus, 41 we focused on parameters that are relevant in population models, namely we studied only 42 direct reproductive costs. Indeed, in stochastic models, demographic parameters (i.e. survival 43 and reproductive rates) fluctuate from year to year [8]. These fluctuations from year t to year 44 t+1 may be in part explained by the existence of direct costs of reproduction. 45 46 Figure S1. The scope of this review (red/bold boxes) is presented in the broader context of 47 all the type of studies on reproductive trade-offs (not included in this review), which include 48 the studies on delayed reproductive costs (long-term or inter-generational costs), and studies 49 using indirect measures of reproductive effort or of costs (white boxes). The main life history 50 traits used in the reviewed studies to investigate the trade-offs between current reproduction 51 and subsequent reproduction and/or survival are summarized within the bold/red boxes. The 52 reviewed studies support the hypothesis of a direct costs of reproduction in males when 53 reproduction a given year reduces survival (i.e., survival costs of reproduction) and/or 54 reduces fecundity the following year (i.e., fecundity costs of reproduction) (red arrows). 3 55 56 4 57 ESM 2. Search protocol. 58 To summarize all the empirical tests of direct reproductive costs in males of 59 unmanipulated wild vertebrate populations, we performed a literature search using the ISI 60 Web of Knowledge database (SCI-expanded). More specifically, we used the keywords 61 “cost/costs” and “reproduction/reproductive/mating” and “male/males” (see [1] for a similar 62 approach on male mammals and [9] for a similar approach on male Arthropods). We did not 63 restrict the taxonomic range of the search in the key words but we rather excluded journals 64 focusing on specific taxa that were clearly out of our range (e.g. journals specialized on 65 plants, entomology…). Then, we screened the abstract of the articles to select only those 66 testing the existence of direct costs of reproduction in wild unmanipulated populations of 67 terrestrial seasonally reproducing birds, mammals, squamates and amphibians. We focused 68 only on studies testing for direct costs of reproduction that included direct measures of fitness 69 (see details in ESM1 and Fig. S1). This literature search included studies published until 70 August 2015. We also checked the studies presented in the books or book chapter that 71 reviewed the subject [i.e., 2,10–13]. For mammals, we used the list of studies published in the 72 review of Hamel et al. [1], screened the recent literature and also the papers citing this 73 review. If we found several studies on the same population, with the same conclusions on 74 reproductive costs, we kept only the most recent one. Relevant references cited in the selected 75 papers were also screened. Finally, all the retained papers were read by two co-authors to 76 report (i) the life history traits used to quantify current reproductive effort (at time t), (ii) 77 those used to quantify subsequent performance (at time t+1) and (iii) their co-variations to 78 assess the support for direct reproductive costs. 5 79 Table S1. Summary of all the studies investigating direct reproductive costs in male birds, mammals, squamates and amphibians. For 80 each study, we provide the name of the species studied, the bibliographic reference, the localization of the studied population, reproductive traits 81 considered at time t (trait at t) (summarized in a type of trait at t), traits affected by reproduction at time t+1 (trait at t+1), and co-variation 82 (positive “+”, negative “-” or no co-variation “=”) between trait at t and trait at t+1 (in the column “Results”). The abbreviations in the column 83 “Results” are explained below the table. We concluded that the reviewed studies highlighted direct costs of reproduction in males (“Y” in the 84 column “Cost of reproduction?”) when reproduction a given year reduces survival and/or fecundity the following year and do not highlight 85 direct costs of reproduction (“N” in the column “Cost of reproduction?”) in other cases. 6 Species Ref. Location Trait at t Type of trait at t Trait at t+1 Results Cost of reproduction? HS > MS > NS N* Birds Barn swallow Barnacle goose [14] [15] Switzerland (several Number of fledglings (0 [No Success NS] vs.1-6 populations) [Medium Success MS] vs. >6 [High Success HS]) island of Gotland, Sweden Number of young Number of fledglings (NS vs. MS vs. HS) Number of fledglings (NS vs. MS vs. HS) Number of young Survival = N Clutch size Number of young Survival = N Hatching date Timing Survival = N Number of hatchlings Number of young Survival = N Number of fledglings Number of young Survival = N Hatching success Number of young Survival = N Rearing success Number of young Survival = N Fledged young per egg Number of young Survival = N Black grouse [16] Central Finland Number of matings Mating Survival + N* Blue tit [17] Antwerp, Belgium Polygynous vs. monogamous Breeding status Survival = N Female partner laying date Timing Survival = N Number of clutches Number of breeding Survival = N Number of fledglings Number of young Survival = N EPC vs. Non-EPC Mating Survival EPC < Non-EPC Y Clutch size Number of young Survival = N Brood size Number of young Survival = N Clutch size Number of young Survival = N Gothenburg, B vs. NB Breeding status Survival = N Sweden Number of nestlings Number of young Survival = N Timing of nest desertion (early vs. late) Paternal care Survival = N Early < Late Y = N Brown Thornbill Cliff swallow Collared flycatcher Crested tit Great reed warbler Great tit [18] [19] [20] [21] [22] [23] Canberra, Australia Nebraska, USA Island of Gotland, Sweden Central Japan Eastern Netherlands Timing of nest desertion (early vs. late) Paternal care Single brood vs. Double brood Number of breeding 7 Timing of settlement (early vs. late) Survival [24] Oxford, UK [25] Kansas, USA Clutch size Number of young Survival = N Number of fledglings Number of young Survival = N Number of matings Mating Survival = N B vs. NB Breeding status Survival B>NB N* B vs. NB Breeding status Breeding probability B>NB N* Clutch size Number of young Survival + N* SB vs. FB Breeding status Survival SB>FB N* Number of fledglings Number of young Survival + N* Greater prairiechickens Green-rumped Parrotlet Hawai‘I [26] Hato Masaguaral, Venezuela [27] Island of Hawai‘i B vs. NB Breeding status Survival = N House martin [28] Perthshire, Scotland Single brood vs. Double brood Number of breeding Survival = N Indigo bunting [29] Michigan, USA SB vs. FB Breeding status Survival SB>FB N* (several Number of fledglings Number of young Survival + N* populations) Number of fledglings Number of young Number of fledglings = N Number of young Survival = N B vs. NB Breeding status Survival = N B vs. NB Breeding status Breeding probability B<NB Y SB<FB<NB Y Survival SB>NB>FB N* ‘Elepaio Jackdaw King penguin [6] [30] Haren, Netherlands Crozet Archipelago Dominant vs. Subdominant (indirect measure of number of fledglings) SB vs. FB vs. NB Breeding status SB vs. FB vs. NB Kittiwake gull [31] [32] Laysan [33] Brittany, France Tyne and Wear, England Oahu, Hawaii Breeding status Breeding successfully probability B vs. NB Breeding status Survival B>NB N* B vs. NB Breeding status Breeding probability B>NB N* Number of fledglings (0,1,2 or 3) Number of young 3>2>1>0 N* SB vs. FB Breeding status SB<FB Y 8 Number of fledglings (0,1,2 or 3) Survival albatross archipelago SB vs. FB SB (helped) vs. SB (not-helped) vs. FB (helper) vs. Long-tailed tit [34] Sheffield, UK FB (non-helper) SB (helped) vs. SB (not-helped) vs. FB (helper) vs. FB (non-helper) [35] [36] Sheffield, UK Monteiro’s storm-Petrel [38] crowned [39] Petrel Oystercatcher Savannah sparrow [41] [42] [43] Survival SBH=SBNH=FBH >FBNH N* SBH=SBNH>FBNH>FBH N* Breeding status Breeding successfully probability N Bialowieza forest, FB vs. SB (both partner) Breeding status Survival = N Poland SB (partner lost) vs. SB (both partner) Breeding status Survival = N Female partner laying date Timing Survival = N Clutch size Number of young Survival = N B vs. NB vs. Immature Breeding status Survival ? ? SB vs. FB Breeding status Survival SB>FB N* SB vs. FB Breeding status Breeding probability SB>FB N* Lund, Sweden Praia Islet Number of fledglings (1,2,3,4,5) Number of young Survival = N Number of nesting attempts (1, 2, 3+) Number of breeding Survival = N Clutch size (3,4,5-6,7,8,9-10,11+) Number of young Survival = N Single brood vs. Double brood Number of breeding Survival = N Paternal care Survival Early < Late Y NB vs. FB (Egg) vs. FB (chick) vs. SB Breeding status Survival SB>other or other<NB Both2 NB vs. FB (Egg) vs. FB (chick) vs. SB Breeding status SB>FB>NB N* Bird island, South SB vs. FB Breeding status Breeding probability = N Georgia SB vs. FB Breeding status Survival = N Skokholm island, UK Clutch size Number of young Survival + N* Number of hatchlings Number of young Survival = N Number of fledglings Number of young Survival = N Survival - Y3 California, USA completion (early vs. late)1 Northern giant Breeding status = Duration of care assessed by timing of breeding [40] N Survival sparrow Nazca booby = Paternal care Mountain white- Breeding probability Parental effort (feeding rate) Marsh tit [37] Breeding status Galapagos Islands, Ecuador New Brunswick, Interaction of number of fledglings and duration Paternal care X Canada of care Number of young 9 Breeding successfully probability Number of fledglings (1st breeding) [44] Snowy Plover Southern giant Petrel Spotted owl Tengmalm’s owl [45] [41] [46] [47] Tree swallow [48] Wheatear [49] [50] Willow ptarmigan Willow tit [51] [52] Survival = N Number of young Survival = N Timing Survival + N* Timing of breeding completion (2nd breeding) Timing Survival = N Clutch size Number of young Survival = N Number of hatchlings Number of young Survival = N Number of fledglings Number of young Survival = N Time spent incubating Paternal care Survival + N* Time spent brooding Paternal care Survival = N Bird island, South SB vs. FB Breeding status Breeding probability SB < FB Y Georgia SB vs. FB Breeding status Survival = N Central Sierra B vs. NB Breeding status Breeding probability B < NB Y Nevada, USA B vs. NB Breeding status Survival = N Clutch size Number of young Clutch size = N Number of fledglings Number of young Number of fledglings = N Clutch size Number of young Survival = N Number of fledglings Number of young Survival = N Clutch size (1-5 vs. 6-8) Number of young Survival 1-5 > or < 6-8 Both2 Early breeder vs. late breeder Timing Survival = N FB vs. SB Breeding status Survival = N Canada California, USA Western Finland New Brunswick, Canada RhinelandPalatinate, Germany Southern central Sweden British Columbia, Canada Oulu, Finland breeding) Number of young Timing of breeding completion (1st breeding) New Brunswick, Number of fledglings (2nd paired vs. unpaired Breeding status Breeding probability paired > unpaired N* Polygynous vs. monogamous vs. unpaired Breeding status Clutch size = N Polygynous vs. monogamous vs. unpaired Breeding status Hatching success = N Polygynous vs. monogamous vs. unpaired Breeding status Number of fledglings = N Polygynous vs. monogamous vs. unpaired Breeding status Survival = N B vs. NB Breeding status Survival = N 10 B vs. NB [21] Breeding status Breeding probability B > NB N* Gothenburg, B vs. NB Breeding status Survival B < NB Y Sweden Number of nestlings Number of young Survival - Y Mating Tenure of a territory = N Mating effort (duration of tenure of a territory) Mating Tenure of a territory + N* Mating effort Mating Survival = N Mating effort Mating Mating effort + N* = N SB > FB N* SB > FB N* Mammals Antartic fur [53] South Georgia seal Bighorn sheep Bison [54] [55] Alberta, USA Nebraska, USA Mating success (relative copulation index, oestrous female availability) Rank (positively correlated to number of matings) SB vs. FB Black-tailed prairie dog Fallow deer Northern elephant seal Yellow-bellied marmots [56] South Dakota, USA Mating Breeding status Rank (number of matings) Survival Breeding succesfully SB vs. FB Breeding status SB vs. FB Breeding status Number of young SB = FB N B vs. NB Breeding status Survival = N(*)4 Mating Survival - Y5 probability [57] Dublin, Ireland [58] California, USA [59] Colorado, USA Mating effort (number of females defended) Mating Survival + N* [60] Central Spain Number of offspring Number of young Survival + N* Total number of copulations Mating - Y6 B vs. NB Breeding status Breeding probability = N B vs. NB Breeding status Survival B > NB N* Mating success Number of young Survival + N* Mating success (number of females inseminated) Squamate reptiles Carpetane rock lizard Marine iguana Northern water snake Striped plateau lizard [61] [62] [63] Galapagos Islands, Ecuador Ontario, Canada Arizona, USA Amphibians 11 Total number of copulations European treefrog Yellow-bellied toad 86 87 88 89 90 91 92 93 94 95 96 97 98 99 [64] [65] Southern Germany North-eastern France Chorus attendance (positively correlated to the number of matings) B vs. NB * Results that support the individual quality hypothesis 1 Late males give less care than early males 2 Results depend on the year 3 Negative correlation for large brood only 4 B > NB for 5-year old males (for other males B = NB) 5 Negative correlation for 7-8 year old males (no correlation for other males) 6 Negative correlation for males with high reproductive success only (mean number of matings per year > 1) B = Breeder NB = Non-breeder SB = Successful breeder FB = Failed breeder EPC = Extra-pair copulation ? = No information available 12 Mating Survival + N* Breeding status Breeding probability B < NB Y 100 Table S2. Summary of the empirical tests of direct reproductive costs in males in 101 vertebrates. The first column corresponds to the reproductive traits considered at time t 102 (summarized in a type of traits at t), the second column corresponds to the reproductive traits 103 considered the subsequent breeding season (summarized in a type of traits at t+1, i.e. survival 104 or fecundity), the third column indicates the number of negative co-variations between trait at 105 t and trait at t+1 among the tested co-variations collected in the literature, and the last column 106 shows the number of species for which negative co-variations between trait at t and trait at 107 t+1 have been detected among all the species for which co-variations have been investigated. Type of traits at t Type of traits at t+1 N. negative co-variations / N. species with negative co- N. co-variations tested variations / N. species tested Number of young Survival 2/35 2/20 Number of young Fecundity 0/5 0/4 Breeding status Survival 3/25 3/21 Breeding status Fecundity 5/20 4/15 Matings Survival 2/7 2/7 Matings Fecundity 1/5 1/4 Paternal care Survival 2/6 2/5 Paternal care Fecundity 1/1 1/1 Timing Survival 0/6 0/5 Number of breeding Survival 0/5 0/4 108 109 13 110 Table S3. Effect of the taxa analysed on the probability to detect a cost of reproduction (i.e. a 111 trade-off between reproduction at time t and reproduction or survival at time t+1). We fitted a 112 generalized linear model with: a binomial distribution, the presence/absence of costs as the 113 response variable, the variable “taxa” as an explanatory variable (using the taxon “bird” as a 114 reference). Due to the very low number of studies on amphibians (n = 2), we removed these 115 studies from this analysis. A generalized linear mixed model with the factor “species” as a 116 random effect gives similar results (we considered separately the 7 species analyzed in 2 117 different studies). Fixed effect Intercept Taxa Mammals Taxa Squamates Estimate -1.04 -0.76 -0.06 SE 0.35 1.14 1.21 z -2.95 -0.67 0.05 p 0.003 0.51 0.96 118 119 Table S4. Effect of the type of trait considered at t in a given study on the probability to 120 detect a cost of reproduction (i.e. a trade-off between reproduction at time t and reproduction 121 or survival at time t+1). We fitted a generalized linear mixed model with: a binomial 122 distribution, the presence/absence of costs as the response variable, the variable “type of trait 123 at t” as an explanatory variable (using the trait “number of young” as a reference) and the 124 factor “species” as a random effect. The traits “Number of breeding”, “Paternal care” and 125 “Timing” were grouped as “Others” due to low number of studies with these traits. Fixed effect Intercept Trait Breeding status Trait Mating Trait Others Estimate -3.02 1.40 1.88 1.34 126 127 14 SE 0.81 0.85 1.03 0.98 z -3.75 1.66 1.83 1.36 p 0.0002 0.10 0.07 0.17 128 Table S5. Effect of the number of relationships considered in a given study on the probability 129 to detect a cost of reproduction (i.e. a trade-off between reproduction at time t and 130 reproduction or survival at time t+1). We fitted a generalized linear model with: a binomial 131 distribution, the presence/absence of costs as the response variable, the variable “number of 132 correlations tested” as an explanatory variable. A generalized linear mixed model with the 133 factor “species” as a random effect gives similar results (we considered separately the 7 134 species analyzed in 2 different studies). Fixed effect Intercept Number of correlations tested Estimate -1.04 -0.01 SE 0.57 0.23 z -1.83 -0.06 p 0.07 0.95 135 136 Table S6. Effect of the number of different types of traits considered in a given study on the 137 probability to detect a cost of reproduction (i.e. a trade-off between reproduction at time t and 138 reproduction or survival at time t+1). We fitted a generalized linear model with: a binomial 139 distribution, the presence/absence of costs as the response variable, the variable “number of 140 type of trait” as an explanatory variable. A generalized linear mixed model with the factor 141 “species” as a random effect gives similar results (we considered separately the 7 species 142 analyzed in 2 different studies). Fixed effect Intercept Number of type of trait Estimate -1.27 0.15 143 15 SE 0.81 0.58 z -1.57 0.26 p 0.12 0.79 144 Table S7. 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