TIMING OF CURRENT REPRODUCTION DIRECTLY AFFECTS FUTURE REPRODUCTIVE OUTPUT IN EUROPEAN COOTS pdf

Evolution, 56(2), 2002, pp 400–411 TIMING OF CURRENT REPRODUCTION DIRECTLY AFFECTS FUTURE REPRODUCTIVE OUTPUT IN EUROPEAN COOTS ´ MARTIN W G BRINKHOF,1,2 ANTON J CAVE,1 SERGE DAAN,3 Netherlands AND ALBERT C PERDECK1 Institute of Ecology, Center for Terrestrial Ecology, P.O Box 40, NL-6666 ZG Heteren, The Netherlands Laboratory, University of Groningen, P.O Box 14, NL-9750 AA Haren, The Netherlands Zoological Abstract Life-history theory suggests that the variation in the seasonal timing of reproduction within populations may be explained on the basis of individual optimization Optimal breeding times would vary between individuals as a result of trade-offs between fitness components The existence of such trade-offs has seldom been tested empirically We experimentally investigated the consequences of altered timing of current reproduction for future reproductive output in the European coot (Fulica atra) First clutches of different laying date were cross-fostered between nests, and parents thereby experienced a delay or an advance in the hatching date The probability and success of a second brood, adult survival until and reproduction in the next season were then compared to the natural variation among control pairs Among control pairs the probability of a second brood declined with the progress of season Delayed pairs were less likely and advanced pairs were more likely to produce a second brood These changes were quantitatively as predicted from the natural seasonal decline The number of eggs in the second clutch was positively related to egg number in the first clutch and negatively related to laying date Compared to the natural variation, delayed females had more and advanced females had fewer eggs in their second clutch The size of the second brood declined with season, but there was no significant effect of delay or advance Local adult survival was higher following a delay and reduced following an advance The effect of the experiment on adult survival was independent of sex Laying date and clutch size of females breeding in the next year were not affected by treatment The study demonstrates the existence of a trade-off between increased probability of a second brood and decreased parental survival for early breeding Timing-dependent effects of current reproduction on future reproductive output may thus play an important role in the evolution of the seasonal timing of reproduction Key words Adult survival, Fulica atra, future reproduction, life-history evolution, multiple breeding, timing of reproduction Received July 31, 2000 Accepted October 22, 2001 Models of life-history evolution assume that the variation in reproductive traits within populations may be explained on the basis of trade-offs between fitness components A major trade-off is between investment in current reproduction and future reproductive output (Williams 1966; Lessells 1991; Roff 1992; Stearns 1992) This trade-off incorporates the concept of a cost of reproduction: An increase in current reproductive effort can only be at the expense of a reduction in residual reproductive value Costs of reproduction are principally expressed in survival and future fecundity (Bell 1980) and should be investigated by experimental manipulation within the natural range of variation of the trait concerned (Linden and Møller 1989) The experimental evaluation of ´ trade-offs between current and future reproduction is a major goal for understanding the evolution of life-history patterns, such as the variation in timing of reproduction within animal populations (Daan and Tinbergen 1997) The seasonal timing of reproduction is a reproductive trait that often has a large impact on fitness (Clutton-Brock 1988), as has been shown in insects (e.g., Ohgushi 1991; Landa 1992; Cushman et al 1994), fish (e.g., Schultz 1993), reptiles (e.g., Olsson and Shine 1997), and mammals (e.g., FestaBianchet 1988) Most descriptive and nearly all experimental research on the topic has focused on birds (Nilsson 1999) In most avian populations, early breeding individuals produce larger clutches, more fledglings, and eventually more recruits from their first clutch than late breeders (Klomp 1970; Perrins Present address: University of Bern, Zoological Institute, Division of Evolutionary Ecology, Wohlenstrasse 50 A, CH-3032 Hinterkappelen, Switzerland; E-mail: martin.brinkhof@esh.unibe.ch 1970; Daan et al 1989; Rohwer 1992) Early breeders are also more likely to raise an additional brood in the same breeding season (e.g., Kluyver et al 1977; Smith et al 1987; Geupel and DeSante 1990; Hepp and Kennamer 1993; Verboven and Verhulst 1996) They also may molt earlier (Leafloor and Batt 1990) and use a longer post-breeding period to recover, which may enhance their survival until next breeding (Nilsson and Svensson 1996) Thus, the overall picture is one of early breeders having a higher fitness than late breeders The apparent natural seasonal decline in fitness does not imply that there is directional selection for earlier breeding dates (Cave 1968; Price et al 1988) Two mechanisms have ´ been proposed to explain seasonal variation in single fitness components: the parental quality hypothesis and the date hypothesis (Brinkhof et al 1993; Nilsson 1999) The parental quality hypothesis predicts that variation in the value of fitness components with date reflects differences in phenotype (e.g., age or breeding experience, Sæther 1990; Perdeck and Cave 1992) or environmental quality (e.g., territory quality, ´ Alatalo et al 1986) between early and late breeders Differences in reproductive output between early and late individuals would then not reveal the consequences of an alternative timing of breeding for the individual The date hypothesis predicts that earlier or later timing of breeding affects the value of a fitness component for all pairs alike However, variation in the trade-offs between individuals might result in unforeseen effects on other fitness components and thereby on total fitness (Daan et al 1990) Ultimately, the optimal breeding date may be determined by a trade-off between current and future reproduction, the outcome of which depends 400 ᭧ 2002 The Society for the Study of Evolution All rights reserved 401 TIMING OF BREEDING IN COOTS on parental and territory quality (Daan et al 1990; Daan and Tinbergen 1997; Nilsson 1999) Individuals may thus adopt different strategies to maximize fitness (individual optimal date hypothesis) Individual optimization may explain the absence of a relationship between breeding time and parental survival in several species (e.g., Newton and Marquiss 1984; Daan et al 1990; Winkler and Allen 1996) despite quality differences between early and late breeders (Nilsson 1999) Thus, the consequences of timing of breeding for an individual can only be assessed experimentally Reproductive costs have been experimentally demonstrated as a reduction in survival or future fecundity following brood size enlargements (reviewed by Linden and Møller ´ 1989; Dijkstra et al 1990) Experimental date manipulations mostly indicate timing per se as the most important factor for seasonal variation in reproductive success during the prefledging and postfledging period, supporting the date hypothesis (Nilsson 1999) Thus, an experimental change in breeding time generally alters the probability of nestling survival (e.g., Brinkhof et al 1993; Norris 1993; Wiggins et al 1994; Brouwer et al 1995) Even if an experimentally altered timing has no direct effect on fledging success (e.g., Hatchwell 1991; Verhulst et al 1995; De Forrest and Gaston 1996), future reproductive output may change through the effects of breeding date on other stages of the life cycle, such as molt (Nilsson and Svensson 1996) Few studies have examined the effects of date manipulations beyond survival and growth of first brood offspring (Nilsson 1994; Verhulst et al 1995; Verboven and Verhulst 1996; Nilsson and Svensson 1996; reviewed by Nilsson 1999) Most of these studies employed artificial delays in breeding only, although experimental advances are crucial in the distinction between some models of optimal timing (Daan and Tinbergen 1997) No study has investigated the effect of an experimental delay as well as advance on major components of future reproduction, including the probability of producing a second brood as well as adult survival In this study, we examine how timing of reproduction affects the incidence of second broods and parent survival of European coots, Fulica atra We manipulated the timing by exchanging first clutches of equal size, but differing in laying date between nests, thereby creating delayed and advanced pairs over most of the season (Brinkhof et al 1993) The date hypothesis predicts that an experimental delay should lead to a decline in the production of second broods, whereas an advance should lead to an increase Under the parental quality hypothesis we expect no effect of our manipulation on the production of second broods Adult survival in coots is independent of season, which may be the result of individual date optimization, if parents refrain from breeding earlier because survival costs outweigh the benefits for current reproductive output Thus, experimentally delayed and advanced pairs are predicted to show enhanced and reduced adult survival, respectively MATERIALS AND METHODS General and Experimental Procedures Fieldwork was conducted from 1988 to 1993 at the lake Westeinderplassen (57Њ18ЈN, 4Њ42ЈE), 17 km southwest of Amsterdam, The Netherlands For a description of the study area, see Cave and Visser (1985) The annual number of ´ breeding pairs ranged from 135 to 157 Most adults were marked with steel leg bands and numbered plastic neck collars Throughout the breeding season (mid-March through mid-July) the area was searched at least once a week to locate nest sites, determine laying date and clutch size, and identify marked parents Laying date (of the first egg) was determined by backdating, assuming a laying frequency of one egg per day Incubation starts before the clutch is completed, and eggs hatch asynchronously The mean hatching date of the nestlings in each brood was used in the analyses (Brinkhof et al 1993) Successful clutches were defined as those that hatched at least one young The number of young surviving in successful broods was determined weekly until at least weeks of age Components of subsequent reproduction studied included the probability and success of a second brood in the same breeding season, adult survival until the following breeding season, and laying date and clutch size of females breeding the next season Calendar dates were expressed as the day of the year (e.g., May ϭ day 121) The study uses both natural and experimentally induced variation in the timing of first broods To investigate the natural relationship between timing of the first brood and the probability and success of a second brood, we used data from all breeding pairs that successfully hatched a first brood in the years 1988–1993 (Table 1) In 1988, 1989, and 1991 we manipulated the timing of the brood care period for individual pairs by exchanging first clutches of equal size, differing by 10 days in laying date, between nests For further details on the experimental design, see Brinkhof et al (1993) The experiment confronted individual pairs with a delayed or an advanced hatching date of young, and thus induced them to start parental care for the foster brood at a later or earlier date than anticipated By comparing seasonal variation in fitness components between control and experimental pairs, we can discriminate between the date and quality hypotheses Moreover, the experiment allowed us to investigate the costs or benefits of an advanced or delayed breeding date in terms of future reproduction at the individual level Within years, control and experimental pairs showed similar variation in clutch size and hatching date of the first brood (Table 1) Second Broods Second broods are those initiated after successful hatching of a first brood within the same breeding season, irrespective of the number of first-brood young eventually surviving The observed incidence of second broods is the result of initiation rate and finding probability Coots may switch nests between breeding attempts, and not all second broods initiated are found In particular, some nests may be predated prior to detection The observed incidence of second broods therefore underestimates the actual initiation rate We have no means to estimate the finding probability of initiated second broods in our population and assume that this probability was independent of year, timing, success, and experimental manipulation of the first brood (see below) Second broods are readily discovered once the eggs have hatched, either visually or acoustically by the vocalization of small chicks Thus, 402 MARTIN W G BRINKHOF ET AL TABLE Mean clutch size and original hatching date of the first clutch for control, delayed, and advanced pairs in 1988 – 1993 Within years, there were no significant differences in clutch size between control and experimental groups The number of individuals wearing a neck collar indicates the number used in survival analyses Clutch size Original hatching date No with neck collar Year Group n Mean SD Mean SD Females Males 1988 advanced control delayed advanced control delayed control advanced control delayed control control 116 10 17 101 17 112 26 89 25 104 122 7.9 7.5 8.0 7.0 7.1 7.0 7.2 6.9 7.3 7.0 7.2 7.1 0.8 1.6 1.0 1.4 1.6 1.2 1.4 1.2 1.7 1.3 1.6 1.2 128.5 124.9 118.1 131.8 127.6 120.1 132.0 138.8 134.6 129.5 137.4 131.7 7.4 12.3 6.7 10.5 16.2 12.0 12.1 11.4 12.1 11.5 14.3 12.1 73 14 60 11 49 18 57 15 51 83 15 68 13 45 21 47 20 51 1989 1990 1991 1992 1993 whether a breeding pair reared second-brood young until at least weeks of age was reliably determined in scheduled weekly visits to each territory The assessment of brood size was blind to treatment and accurate, because counts in subsequent weeks rarely exceeded those of the previous one The number of young surviving up to weeks of age largely determines the number of young raised to independence (Brinkhof et al 1993) and was used in the analysis Analysis of Breeding Parameters Data analysis was performed using Statistix (Analytical Software 1992) or GLIM (Francis et al 1993) by fitting generalized linear models using a stepwise backward-elimination procedure (Crawley 1993) These models include multiple regression models with continuous explanatory variables (variates), analysis of variance (ANOVA) with categorical variables (factors), as well as models with any mixture of factors and (co)variates (ANCOVA) and their interactions Logistic regression (binomial error) was used when analyzing proportions, Poisson regression (Poisson error) for analyzing count data, and significance was tested using the chi-square test Linear regression (normal error) with F-tests was used in other analyses All statistical tests are two-tailed Basic explanatory variables in the analysis of breeding parameters were year (as a factor), hatching date of the first brood, and brood size weeks after hatching In the analysis of clutch or brood size of second broods, we also used the laying date of the second clutch as a predictor variable The maximal model (starting point for analysis) also included two-way interactions and quadratic terms The size of the first brood at weeks after hatching was used to investigate the effect of the success of the first brood on the probability and success of second broods, because renesting normally takes at least weeks (i.e., the mean interbrood interval, defined as the number of days between the hatching date of the first brood and the laying date of the second clutch, was 21.7 days, SE ϭ 1.3, n ϭ 70) The earliest coots of the year tend to be the largest females, who breed with the oldest males in the population (Perdeck and Cave 1992; A.C Perdeck, unpubl data) on the largest ´ territories with abundant natural vegetation (Cave et al 1989; ´ A C Perdeck, unpubl data) These parameters of territory or bird quality were not included in the analyses of breeding parameters and adult survival (next section) because we randomly assigned pairs to the experimental treatments, irrespective of territory and bird quality The natural variation in breeding parameters was taken as the starting point for the analysis of experimental variation The variation among experimental groups was initially examined using manipulation as a factor In case a breeding parameter varied with hatching date among controls, we tested manipulation as a variate (i.e., the number of days manipulated), first, relative to the natural variation of the hatching date of the experimental pair’s original clutch (original hatching date, OHD) and, second, relative to the actual hatching date (AHD) of the fostered clutch This procedure allowed us to discriminate between the date hypothesis and the parental quality hypothesis (Brinkhof et al 1993; Verboven and Verhulst 1996) Adult Survival Survival estimates of adult birds were determined on the basis of capture-recapture data using the program MARK (Cooch and White 1998; White 1998; White and Burnham 1999) We excluded nests outside the main study area and nests with a failed first clutch, unknown hatching date, or extra food provisioning (Brinkhof and Cave 1997) Recapture ´ was based on the visual observation of neck-collared individuals Survival estimation is thus local and underestimates real survival, because some individuals may emigrate permanently from the study area Overall mean real adult survival, estimated from ringing recoveries of dead adult birds ringed in our study area from 1966 to 1978, was 0.70 (95% confidence interval: 0.65–0.75; Perdeck 1998) The overall estimate in the present study (data 1989–1993) was 0.59 (95% confidence interval: 0.54–0.63; data 1989–1993, control birds of model ␾[m]P[s], see below) Thus, the ratio of local to real survival is about 0.86, indicating that the most adults not locally recaptured in the study area are dead We therefore used local recaptures only, and, in discussing the results, we will assume that variation in local survival probability reflects genuine variation in survival In 1988, the number of experimental manipulations involving neck-collared individuals was too few to obtain survival estimates (Table 1) We therefore restricted the survival 403 TIMING OF BREEDING IN COOTS analysis to observations from 1989 through 1993, comparing the survival of individuals with experimentally delayed or advanced breeding in 1989 or 1991 with that of unmanipulated controls in these years (Table 1) In the initial analysis we considered three factors: time (t, year), sex (s), and manipulation (m; with three levels: control [c], delayed [d], advanced [a]) We applied the Cormack-Jolly-Seber (CJS) method to model time dependency in both recapture and survival probability CJS models are denoted (⌽t, Pt), where ⌽t is the survival probability from year t Ϫ to year t (including possible permanent emigration) and Pt is the probability of recapture of birds alive in year t To avoid sparse data problems, we considered the data as two three-encounter sets, that is, the first set contained the capture data for 1989, 1990, and 1991 and the second set those for 1991, 1992, and 1993 For each of the two sets of encounters histories (referred to as replicates, r) six groups were formed: (1) control females; (2) delayed females; (3) advanced females; (4) control males; (5) delayed males; and (6) advanced males A consequence of a three-encounter analysis is that survival and capture rate of the second year t ϩ cannot be estimated independently Note that an individual can be present in both sets and is thus counted twice We assumed that the manipulations had an effect on survival until the year after the manipulation only Traditionally, the analysis is carried out by a series of likelihood-ratio tests (LRTs), starting with a model containing all factors of interest (the maximal model in GLIM terminology) and removing one by one the nonsignificant terms until a minimal adequate model is obtained This method works for nested models only, and the Aikaike information criterion (AIC) has been proposed as an alternative tool to select the most parsimonious model (Cooch and White 1998) Two main reasons for considering AIC as a general model selection tool instead of LRT include: (1) the equal or better performance of AIC when data meet or violate standard markrecapture assumptions, respectively; and (2) that AIC provides a criterion that is not affected by the number of tests performed (i.e., no need for adjustment of ␣-values to the number of tests performed, e.g., using Bonferroni method) The use of AIC requires an a priori set of models from which the one with the lowest AIC value is chosen as the best model Comparisons with next-lowest models cannot be evaluated by a statistical test Instead, the degree of support is given using an index of relative plausibility known as AIC-weight We used both LRTs and AIC criteria in our analysis In defining the maximal model we made the following considerations The main aim was to investigate the effect of manipulation (m) on adult survival from the experimental year (1989, 1991) to the following year Survival for the experimental years may also differ between the sexes (s) and the effects of m on survival rate could differ between the sexes (interaction s.m) Capture probability may vary with sex, manipulation, or both; therefore, s, m, and s.m were included in the capture rate part of the model The survival and capture rate for the second year cannot be estimated independently in a three-encounter dataset We assumed that the capture rate within replicates (r) was independent of year (t), and obtained survival estimates for the two years of each replicate separately To test for differences in survival rate or capture rate between replicates, we included t, r, and the interaction t.r in the survival part of the model and r in the capture part (t and t.r are nonexistent for capture rate) Finally, because the effects of manipulation on survival and capture rates may differ between replicates, the interaction m.r was included in both parts of the model Summarizing, the maximal model we considered in the analysis was [␾(t/ r ϩ s/m ϩ m*r) P(s/m ϩ m*r)], in which t/r stands for t ϩ t.r, s/m for s ϩ s.m, and m*r for m ϩ r ϩ m.r To evaluate the goodness-of-fit of this model, we used the parametric bootstrap procedure provided in MARK (Cooch and White 1998) A P-value for the goodness-of-fit test of 0.97 was obtained from 100 simulations The model showed no overdispersion (c ϭ 0.973) ˆ RESULTS Detecting a Second Brood Of all second broods recorded in the years 1988–1993 (n ϭ 94), 83% (n ϭ 78) were detected prior to hatching Over successive years (1988–1993) the proportion of second broods found prehatching was 0.72 (n ϭ 18), 0.65 (n ϭ 23), 1.00 (n ϭ 6), 0.95 (n ϭ 20), 0.93 (n ϭ 14), and 0.92 (n ϭ 13), respectively The probability of detecting a second brood before hatching (eggs found ϭ 1, no eggs found ϭ 0) differed significantly between years (logistic regression, (␹2 ϭ 12.58, df ϭ 5, P ϭ 0.028), but was independent of hatching date of the first brood (␹2 ϭ 0.91, df ϭ 1, P ϭ 0.34), size of the first brood (␹2 ϭ 0.46, df ϭ 1, P ϭ 0.50), and experimental manipulation (tested as factor, i.e., control, delayed, advance: (␹2 ϭ 3.25, df ϭ 2, P ϭ 0.20) We therefore assume that within-year variation in the observed rate of second broods reflects the actual variation in initiation rate Probability of a Second Brood The natural variation in the probability of a second brood was analyzed among 644 unmanipulated pairs that successfully hatched a first clutch in 1988–1993 The incidence of second broods varied significantly between years (tested as factor) and with hatching date and size of the first brood (Table 2A) The size of the first clutch did not affect the probability of a second brood (␹2 ϭ 2.56, df ϭ 1, P ϭ 0.11) The probability of a second brood progressively declined with season (Fig 1A), and the slope of this decline was similar between years (for interaction year ϫ hatching date, (␹2 ϭ 9.45, df ϭ 5, P ϭ 0.092) In addition, the incidence of a second brood gradually declined with the size of the first brood (Fig 1B) The probability of a second brood among experimentally delayed (n ϭ 51) and advanced (n ϭ 50) pairs was compared with the expectation on the basis of the natural seasonal trend found among controls in 1988, 1989, and 1991 (n ϭ 306) In agreement with the general trends (i.e., 1988–1993), the incidence of second broods among control pairs declined significantly with hatching date and size of the first brood, whereas the variation between years was not significant (␹2 ϭ 5.35, df ϭ 2, P ϭ 0.07; cf Table 2A) The model containing hatching date and size of the first brood was taken as basis for the analysis of the experimental variation 404 MARTIN W G BRINKHOF ET AL TABLE Logistic regression analysis of the natural (A) and experimental (B, C) variation in the occurrence of second broods Model A is based on all unmanipulated broods (n ϭ 644, data 1988 – 1993); for year, the mean constant over the five years is given Models B and C give the result of the analysis among control (n ϭ 306) and experimental (delayed, n ϭ 52; advanced, n ϭ 51) pairs in 1988, 1989, or 1991 Model B gives the effect of manipulation relative to the hatching date of the parent’s original first clutch; model C gives it relative to the actual hatching date of the adopted clutch Manipulation was tested as a variate, that is, the number of days delayed (ϩ values) or advanced (Ϫ values) (Increase in) Model A B, C B C Parameter Null model Final model Constant Year Hatching date of first brood Brood size of first brood Null model Final model Constant Original hatching date Brood size of first brood Manipulation Final model Constant Actual hatching date Brood size of first brood Manipulation† Deviance df 479.41 276.71 643 636 1 408 405 1 1 406 1 1 11.03 141.64 98.03 344.56 182.59 100.02 73.64 7.18 184.64 109.45 77.76 2.05 P 0.051 Ͻ0.001 Ͻ0.001 Ͻ0.001 Ͻ0.001 0.007 Ͻ0.001 Ͻ0.001 0.152 Coefficients estimate Ϯ SE 17.3 Ϯ 2.01 Ϫ0.151 Ϯ 0.0175 Ϫ0.934 Ϯ 0.120 19.06 Ϫ0.1496 Ϫ1.153 Ϫ0.0979 Ϯ Ϯ Ϯ Ϯ 2.558 0.0198 0.170 0.0372 18.36 Ϯ 2.475 Ϫ0.1445 Ϯ 0.0190 Ϫ1.123 Ϯ 0.1661 † Excluded from the model First, the experimental variation in the occurrence of second broods was compared to the level expected on the basis of original timing The probability of a second brood was significantly related to OHD, brood size and manipulation (Table 2B) The coefficients for OHD and brood size indicate the established natural decline in the probability of a second brood with hatching date (Figs 1C, D; solid line) and with offspring number of the first brood The significance of manipulation indicates that the probability of a second brood among experimental pairs differed significantly from that expected from the natural seasonal trend on OHD For a given OHD, delayed pairs showed a lower frequency of second broods and advanced pairs a higher frequency of second broods (Table 2B, see coefficient) Thus, the experiment affected the occurrence of second broods, which contradicts the parental quality hypothesis Second, to test the date hypothesis we compared the experimental variation in the incidence of second broods to the level expected on the basis of the AHD Given the established decline in the probability of a second brood with hatching date (note that AHD equals OHD for controls) and size of the first brood, the effect of the manipulation was not significant (Table 2C) Thus, quality differences between early and late breeders had no additional effect beyond the effect of breeding time itself The incidence of second broods among experimental pairs was explained by the AHD of the first clutch: A delay in the hatching date of the first clutch led to a decline, whereas an advance led to an increase in the incidence of second broods (Figs 1C, D) This result is consistent with the date hypothesis Interbrood Interval The length of the interbrood interval was determined in 70 of 79 control pairs that started a second brood in 1988–1993 In the remaining nine cases, the laying date of the second clutch was unknown The interbrood interval varied between and 69 days, with a mean of 21.7 days (SE ϭ 1.3) The interbrood interval was positively related to the size of the first brood (linear regression; F1,68 ϭ 15.17, P Ͻ 0.001; R2 ϭ 0.19) and independent of year (F5,63 ϭ 1.23, P ϭ 0.31) and hatching date of the first brood (F1,67 ϭ 2.26, P ϭ 0.14) In particular, pairs that raised only one or no first-brood chick renested sooner than more successful pairs To investigate the effect of the experiment on interbrood interval, data from 38 control, three delayed, and 10 advanced pairs were available (data 1989, 1991, 1991) The interbrood interval increased significantly with size of the first brood (F1,49 ϭ 16.71, P Ͻ 0.001) Manipulation was not significant when tested as variate (F1,48 ϭ 0.051, P ϭ 0.82) nor as factor (control, delayed, advanced; F2,47 ϭ 0.43, P ϭ 0.65) Thus, the increase in the interbrood interval with success of the first brood among experimental pairs was similar to that among controls, suggesting that the relationship was independent of the timing of breeding Clutch Size of the Second Brood The second clutch (mean ϭ 6.1 Ϯ 0.2 eggs) from unmanipulated pairs (data 1988–1993) was significantly smaller than that of the first clutch (mean ϭ 7.2 Ϯ 0.2 eggs; paired t-test, t ϭ Ϫ4.64, df ϭ 52, P Ͻ 0.0001) Size of the second clutch differed significantly between years, and within years there was a progressive decline in clutch size with laying date Females with a large first clutch also produced a large second clutch (Table 3A, see sign of coefficients) The effect of hatching date of the first clutch was not significant (F1,44 ϭ 0.51, P ϭ 0.48) Sample sizes for analyzing the effect of the experiment on the egg number in the second clutch were small (data 1988, 405 TIMING OF BREEDING IN COOTS FIG (A, B) Natural variation in the occurrence of second broods (data 1988–1993) with hatching date and second-week size of the first brood (C, D) Seasonal variation in the occurrence of second broods for experimentally delayed and advanced pairs The solid line gives the natural seasonal decline in the probability of a second brood as based on control pairs only Dots represent the mean initiation rate of second broods for experimental pairs, grouped according to the actual hatching date of the first brood For sample sizes, see the top of each graph The arrows give the effect of the manipulation Arrow tails give the probability of a second brood on the hatching date of experimental pair’s original first clutch; arrow heads point toward the mean probability found after delay or advance Under the date hypothesis, the probability of a second brood following delay or advance should be as predicted from the natural seasonal trend (solid line) The parental quality hypothesis predicts no effect of a 10-day delay or advance on the probability of a second brood The broken line indicates this prediction 1989, 1991; delayed n ϭ 3, advanced n ϭ 9, controls n ϭ 27) Second clutches did not differ significantly in size between years in this dataset (F2,33 ϭ 1.15, P ϭ 0.33), whereas the decline in clutch size with laying date and the increase in egg number with the size of the first clutch (P ϭ 0.06) were confirmed (cf Tables 3A, B) Delayed and advanced pairs produced, on average, 0.67 eggs more or less, respectively, than expected on basis of laying date of the second clutch and size of the first clutch (Table 3B) Brood Size of the Second Brood The number of young surviving two weeks after hatching was analyzed using Poisson regression Among unmanipulated pairs (data 1988–1993, n ϭ 79), the size of the second brood progressively declined with hatching date of the first brood (␹2 ϭ 37.43, df ϭ 1, P Ͻ 0.0001; Fig 2) Effects of year (␹2 ϭ 7.05, df ϭ 5, P ϭ 0.22) and size of the first brood (␹2 ϭ 2.40, df ϭ 1, P ϭ 0.12) were not significant In addition, the effect of second brood hatching date was not significant (␹2 ϭ 0.39, df ϭ 1, P ϭ 0.53), indicating that the number of second brood young was better explained by the timing of the first brood than by that of the second brood In agreement with the general pattern (data 1988–1993), brood size declined progressively with hatching date of the first brood among controls (␹2 ϭ 15.00, df ϭ 1, P Ͻ 0.001; n ϭ 46; data from 1988, 1989, 1991) As predicted by the parental quality hypothesis, the number of second brood young of delayed (n ϭ 5) or advanced pairs (n ϭ 10) did not deviate significantly from the number expected on the basis of their original timing (manipulation tested as variate: (␹2 ϭ 0.02, df ϭ 1, P ϭ 0.89; tested as factor: (␹2 ϭ 0.02, df ϭ 2, P ϭ 0.99) However, brood size was also not significantly different from the size expected for the actual hatching date (tested as variate: (␹2 ϭ 2.27, df ϭ 1, P ϭ 0.13; tested as factor: (␹2 ϭ 2.27, df ϭ 2, P ϭ 0.32) Thus, the data not distinguish between date and parental quality differences as the cause for the natural seasonal decline in size of the second brood, which may be due to the small sample sizes Adult Survival We started the analysis of adult survival by modeling recapture probability The AIC-based selection indicated the recapture-model with sex only as the best model (Table 4A, 406 MARTIN W G BRINKHOF ET AL TABLE Linear regression models describing (A) the natural variation (data 1988 – 1993) and (B) the experimental variation (data 1988, 1989, 1991) in size of the second clutch Significance was tested using F-tests (Increase in) Model A B Parameter Null model Final model Constant Year Laying date of second clutch Clutch size of first clutch Null model Final model Constant Laying date of second clutch Clutch size of first clutch Manipulation Deviance df 80.53 41.26 52 45 1 38 35 1 1 12.90 11.43 8.56 49.59 37.65 6.77 4.13 4.57 model 4) Of the five preconceived models, it had the lowest AIC and 2.8 times the support of the nearest best model (Table 4A, model 3) Recapture probability (p) was higher in males (p ϭ 0.97, SE ϭ 0.02) than in females (p ϭ 0.76, SE ϭ 0.06) The lower recapture probability in females was not due to an overall lower probability of identifying (i) the female parent in relation to a recorded first brood in the study area (data 1989–1993, range 162–178 broods; i ϭ 0.96, SE ϭ 0.01, both for males and females) The difference in recapture probability thus suggests that females are more likely to skip a breeding season or to breed outside the study area than males It is important to note that manipulation had no effect on recapture probability In addition, p was independent of r, indicating that recapture probability did not differ between the two experimental years Next we modeled survival by taking model 4, which controlled for variation in recapture probability with sex, as a starting point (Table 4B) The interactions s*m, m*r, and t*r were not relevant to survival (Table 4B, see AIC-weight and LRTs to model 4) Thus, the effect of manipulation on survival did not differ between the sexes or between replicates, whereas among replicates there was no difference in survival between the first and the second year In addition, the main FIG Natural seasonal variation in the number of second brood young (data 1988–1993) P Coefficients estimate Ϯ SE 0.027 0.001 0.004 Ϫ0.0418 Ϯ 0.0118 0.249 Ϯ 0.0815 0.017 0.058 0.047 9.48 Ϫ0.0335 0.185 0.0669 Ϯ Ϯ Ϯ Ϯ 1.92 0.0133 0.0943 0.0325 factors s and t were not relevant to survival (Table 4B, models and 7, respectively) Thus, males and females had similar survival rates, and first-year survival was similar to the second-year survival within replicates The AIC-based selection indicated model 8, which contained manipulation (m) and replicate (r), as the best model This model has nearly 1.5 times the support than the nearest best model (i.e., model 9), which contained manipulation only (Table 4B) Replicate accounts for the overall higher first-year survival shown by the 1991 group (Fig 3, best shown by controls) Removing manipulation from the best model reduces the support by nearly five times (Table 4B, cf AIC-weights to models and 10) We therefore conclude that manipulation was the main factor explaining variation in survival rate among adults To assess whether the effect of manipulation was due to the advance, the delay, or both treatments, we tested their effects separately Thus, we compared the current best model (model 8) with two distinct models, one with advanced pairs removed (Table 4C, model 12) and one with delayed pairs removed (Table 4C, model 11) AIC-based selection indicated model as the best and minimal adequate model, with a nearly two-fold support over the two alternative models Therefore, we conclude that individuals with experimentally delayed breeding dates showed a higher survival, whereas those with experimentally advanced breeding showed lower survival than controls of the same year (Fig 3) We assumed that delayed and advanced parents did not differ in quality and that the effect of manipulation is limited to the year following manipulation As a consequence of the experimental design, which requires early-laid clutches to be swapped with late-laid ones, on average, delayed pairs had earlier original hatching dates than controls, whereas advanced pairs had later original hatching dates than controls (see Table 1) Thus, the possibility exists that delayed birds were of a higher quality than advanced birds, and this could in principle also explain the effect of the manipulation on survival (an indirect or chronic effect; see Burnham et al 1987) To check this, we modeled survival with the inclusion of the original hatching date of the first brood (h) as an individual covariate In a set of models ␾(r ϩ m)P(s), ␾(r ϩ m ϩ h)P(s) and ␾(r ϩ m ϩ h ϩ h2)P(s) the AIC-weights were 0.52, 0.35, and 0.13, respectively The LRTs also showed 407 TIMING OF BREEDING IN COOTS TABLE Capture-recapture models for coot parents For each model the Aikaike information criterion (AIC), the AIC weight (calculated separately within each a priori set of models A, B, or C), the number of parameters (np) and the deviance (Dev) are given All models include an intercept, both for survival (␾ ) and recapture probability (P) Linear predictors are year (t), replicate (r; datasets 1989, 1990, 1991 and 1991, 1992, 1993), and sex (s) The factor manipulation (m) has three levels: control (c), advanced (a), and delayed (d) Model algebra specification is according to GLIM (Crawley 1993) and m*r stands for m ϩ r ϩ m.r, t/r for t ϩ t.r, and s/m for s ϩ s.m Within each set of analyses, models are numbered according to decreasing complexity, but ordered according to AIC The selected model in each set of analysis as well as the key comparisons between models are presented in bold type Model Models compared, hypothesis tested, likelihood-ratio test AIC AIC weight np Dev A Modeling recapture probability (P): ␾(t/r؉s/m؉m*r)P(s) ␾(t/rϩs/mϩm*r)P(sϩr) ␾(t/rϩs/mϩm*r)P(s/mϩm*r) ␾(t/rϩs/mϩm*r)P(mϩsϩr) ␾(t/rϩs/mϩm*r)P(.) 1119.94 1121.99 1123.55 1124.57 1129.07 0.613 0.219 0.101 0.060 0.006 13 14 17 16 12 14.46 14.44 9.73 12.84 25.67 B Modeling survival rate (␾ ): ␾(m؉r)P(s) ␾(m)P(s) ␾(tϩmϩr)P(s) 10 ␾(r)P(s) ␾(tϩmϩsϩr)P(s) ␾(t/rϩs/mϩm*r)P(s) 1112.07 1112.86 1114.07 1115.21 1115.40 1119.94 0.406 0.275 0.149 0.085 0.077 0.008 13 20.98 23.80 20.95 28.18 20.23 14.46 – 9, r, P ‫90.0 ؍‬ – 8, t, P ϭ 0.85 – 10, m, P ‫30.0 ؍‬ – 7, s, P ϭ 0.40 – 6, interactions, P ϭ 0.33 C Checking delayed and advanced separately: ␾(m؉r)P(s) 12 ␾(dϩr)P(s) 11 ␾(aϩr)P(s) 1112.07 1113.09 1113.42 0.474 0.285 0.241 5 20.98 24.03 24.37 – 12, a ‫ ؍‬c, P ‫80.0 ؍‬ – 11, d ‫ ؍‬c, P ‫70.0 ؍‬ that h (P ϭ 0.27) and h2 (P ϭ 0.52) did not contribute significantly to the survival probability Therefore, the natural timing of breeding was not associated with adult survival and the difference in original hatching date between control and experimental pairs was apparently not responsible for their different survival rates The previous analyses included birds that were manipulated in 1988 and thereafter used as controls or experimentals Manipulation in 1988 may theoretically affect survival in later years and the same may hold for individuals manipulated both in 1989 and 1991 We therefore repeated the analyses with individuals not manipulated previously (n ϭ 409, 53, and 63 for control, delayed, and advanced birds, respectively, as compared to 428, 59, and 68 birds in the main analysis) The result was similar to that of the analyses previously – 4, r, P ϭ 0.88 – 3, m, P ϭ 0.45 – 2, interactions, P ϭ 0.08 – 5, s, P ‫8000.0 ؍‬ shown: Survival estimates for advanced, control, and delayed birds, respectively, were 0.40, 0.55, and 0.69 for 1989 and 0.47, 0.62, and 0.74 for 1992 This confirms our initial assumption that there is no indirect or chronic effect of manipulation on survival We also checked whether the difference in the initiation rate of second broods could explain the difference in survival probability between experimental groups We therefore modeled survival with the inclusion of an individual covariate indicating the initiation of a second brood (br2) The AICweights in this set of models ␾(r ϩ m)P(s) and ␾(r ϩ m ϩ br2)P(s) were 0.62 and 0.25, respectively The LRTs for the contribution of br2 was not significant (P ϭ 0.62) Thus, differences in initiation rate of second broods did not explain the variation in survival among advanced, control, and delayed birds Reproduction in the Next Year We investigated the effect of the experiment on laying date and size of the first clutch produced by females breeding in the next year To control for variation in breeding parameters between years, we calculated for each individual female the deviation in laying date and clutch size from the population mean for first clutches in each year Manipulation (delayed, n ϭ 15; advanced, n ϭ 12) did not affect the change in relative laying date (F2,98 ϭ 0.39, P ϭ 0.68) or relative clutch size (F2,98 ϭ 0.51, P ϭ 0.48) between successive breeding seasons as compared to control birds (n ϭ 74) Thus, there were no indications of long-lasting effects of date manipulations on reproductive performance of surviving females DISCUSSION FIG Mean local survival of advanced, control, and delayed adult coots Survival estimates (with SE) are for female and male combined and based on the best model (Table 4B, model 8) Life-history theory suggests that variation in the seasonal timing of reproduction within populations may be explained 408 MARTIN W G BRINKHOF ET AL on the basis of trade-offs between fitness components (Daan and Tinbergen 1997) Our experimental study provides strong evidence for the existence of such trade-offs, because the timing of current reproduction directly affected the future reproductive output of adult coots The probability of starting a second brood in the same breeding season declined following an experimental delay of the hatching date of the first brood, whereas an experimental advance raised the likelihood of second broods The effect of the experiment was exactly as predicted on the basis of the natural seasonal decline in the probability of a second brood in the population, and we therefore conclude that the result was consistent with the date hypothesis Furthermore, the survival probability of adult females and males with an experimentally advanced hatching date of the first brood was significantly reduced compared to that of control pairs, whereas delayed breeding pairs had a significantly higher survival An experimental change in timing of breeding thus had opposing effects on second broods and adult survival, the two major components of future reproduction in coots Experimental Bias or Genuine Effects of Altered Timing? The experimental design does not allow us to distinguish between effects due to altered reproductive timing and consequences of the prolonged or shortened incubation period used to delay or advance the hatching date of the first brood, respectively One might argue that delayed pairs are forced to allocate more energy to incubation, whereas advanced pairs enjoy reduced incubation costs, and that this affects their future reproductive potential relative to that of control birds Nevertheless, it is unlikely that manipulation of the length of the incubation period severely affected the condition of the adult coots and thereby determined the outcome of the present experiment In European coots (Horsfall 1984) as well as American coots (Ryan and Dinsmore 1979) male and female take about equal parts of the incubation load, leaving each parent ample time to forage and to maintain energy balance during the incubation (Alisauskas and Ankney 1985) In Brunnich’s guillemots (Uria lomvia), another species with shared incubation, body mass was not affected by an experimentally prolonged incubation period (Gaston and Perin 1993) The change in reproductive performance observed among experimental pairs also argues against a major role for the experimental bias First, it is unclear why the increased number of second broods by advanced pairs should be more pronounced in the first than in the second half of the breeding season (Fig 1D) In great tits (Parus major), with higher initiation rates of second broods throughout the season, the seasonal effect of delay on the incidence of second broods similarly contradicted the uniform outcome predicted from an experimental bias (Verboven and Verhulst 1996) Second, local survival of experimentally delayed pairs, which experienced a longer incubation period, was higher than that of experimentally advanced pairs It is important to note that the difference in survival between control and experimental pairs was not associated with the production of a second brood Therefore, we cannot attribute the altered survival of delayed or advanced pairs to a retarded effect of an experi- mental bias on the production of second broods Thus, it is unlikely that the manipulation of the length of the incubation period played a role in the future reproductive performance of coots Link between Timing of the First Brood and the Probability of a Second Brood Consistent with the general pattern in birds (e.g., Smith et al 1987; Geupel and DeSante 1990; Stouffer 1991; Hepp and Kennamer 1993; Verboven and Verhulst 1996), the incidence of second broods in coots declined progressively with season In addition, the probability of a second brood was negatively related to the number of first-brood young surviving the first two critical weeks after hatching A possible mechanism is indicated by the increase in the interbrood interval with size of the first brood If the opportunities or benefits of raising a second brood decline with the progress of season, whereas large first broods require a longer period of parental care, then pairs with many first-brood young might be selected to refrain from starting a second brood (Tinbergen and Van Balen 1988) This proposition is supported by experimental studies, which generally found a decline in the probability of a second broods and an increase in interbrood interval following enlargement of the first brood, whereas the opposite is found following brood reduction (Smith et al 1987; Tinbergen 1987; Linden 1988) ´ In the present study we manipulated the hatching date of the first brood and revealed a causal relationship between the timing of the first brood and the probability of a second brood (date hypothesis) Because we statistically controlled for the effect of the experiment on size of the first brood, this relationship most likely reflects a direct effect of altered timing on the incidence of second broods Three experimental studies are available for comparison, all in Parus species Nilsson (2000) found that female blue tits (P caeruleus) producing their first clutch early in the season were most likely to initiate a repeat clutch following removal of the first clutch Verhulst et al (1995) also induced female great tits to produce a replacement clutch and considered the replacement as a delayed brood None of the experimental pairs initiated an additional brood, in agreement with the natural seasonal decline in second broods in the population Verboven and Verhulst (1996) used a similar experimental approach as used in coots and obtained an identical result: As predicted on the basis of the natural seasonal variation, delay of the hatching date of the first brood caused a decline, whereas advance increased the incidence of second broods Thus, all four experimental studies indicate that the seasonal decline in the probability of starting a second (or repeat) brood was causally related to the timing of the first brood The seasonal decline in the probability of a second brood is most likely related to the progressive decline in the availability of insect food for raising young in the second half of the breeding season (Brinkhof 1997) and to the decline in the first-year survival of independent offspring with hatching date (Brinkhof et al 1997) Thus, the reproductive value of a second brood in coots will decline with its initiation date Such a seasonal decline in brood reproductive value is common in birds (Daan et al 1989; Rohwer 1992) Given that 409 TIMING OF BREEDING IN COOTS rearing a second brood may causally reduce reproductive output of the female parent in subsequent years (Verhulst 1998), the seasonal decline in the likelihood of a second brood most likely reflects a general decision rule that optimizes the trade-off between successive attempts of future reproduction (Verhulst 1998; Nilsson 2000) Clutch Size of the Second Brood Given the size of the first clutch and the laying date of the second clutch, advanced females produced fewer eggs and delayed females produced more eggs in the second clutch than controls (Table 3B) Individual female European coots differ consistently in laying date (Perdeck and Cave 1992) ´ These intrinsic quality differences also affect clutch size: Consistently early-breeding females produced large clutches for the laying date, whereas the consistently late-breeding ones produced small clutches, independent of female age (A.C Perdeck, unpubl data) Consistent individual differences in laying date and clutch size are common in birds (reviewed by Klomp 1970; Findlay and Cooke 1983; Loman 1984; Hochachka 1993) In the European coot such differences are related to body size, with large females breeding early and producing large first and second clutches Adult Survival Survival of adult coots of both sexes was independent of timing of breeding An experimental delay of the hatching date of the first brood by 10 days enhanced both female and male survival In tits, effects of experimental delays on survival are either absent (Verhulst et al 1995) or inconsistent between years (Nilsson and Svensson 1996), whereas experimental advances led to reduced female survival in blue tits (Nilsson 1994) In coots, most pairs for which hatching date was advanced eventually raised more young, whereas fewer young were raised following delay as compared to the number predicted from original timing This is the combined result of the causal effect of hatching date on the success of the first brood (Brinkhof et al 1993) and the production of second broods (present study) Brood care is provided by both sexes and mainly involves food provisioning as well as brooding during periods of rain or low ambient temperature (Brinkhof 1997) The mortality of the parents is increased by advancing and reduced by delaying the date, which suggests that the accompanying change in the number of young places a toll on the parents Another possibility is that parental care is prolonged or shortened by advancing or delaying the date of hatching, respectively One might surmise that both the change in the number of young or in the length of the parental care period result in a change in daily work rate, which could explain the enhanced or reduced mortality following advance or delay, respectively (Dijkstra et al 1990; Daan et al 1996) However, we have no data to substantiate such a relationship in the coot, which would require the direct comparison of time and energy budgets during brood care between pairs with natural and experimentally altered timing of breeding The individual optimization hypothesis, which states that variation in the timing of reproduction reflects fitness-maximizing strategies of individuals that differ in breeding qual- ity, might give a comprehensive explanation for the observed natural and experimental variation in adult survival That advanced and delayed breeding resulted in reduced and enhanced adult survival, respectively, whereas survival was independent of season among controls, indicates that pairs with a different laying date adjusted their timing to pay moderate survival-mediated costs to future reproduction Parents might thus maximize their lifetime fitness by trading off, with the advancement of laying date, the benefits of enhanced current reproduction (Brinkhof et al 1993, 1997) and future reproduction on the basis of second broods (present study), against the reduction in future reproductive output Such a trade-off, based on a cost of early reproduction, might be especially important to fitness in long-lived species such as the European coot To assess whether the variation in breeding date can be explained on the basis of individual optimization, the opposite effects of timing on different components of the current and future reproduction need to be integrated into one measure of fitness, for instance, using reproductive value (Daan et al 1990; Lessells 1991) The implementation of such integrative studies is essential to fully understand the evolution 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Ecology 77:922–932 Corresponding Editor: B Crespi ... existence of such trade-offs, because the timing of current reproduction directly affected the future reproductive output of adult coots The probability of starting a second brood in the same breeding... components of future reproduction, including the probability of producing a second brood as well as adult survival In this study, we examine how timing of reproduction affects the incidence of second... second half of the breeding season (Brinkhof 1997) and to the decline in the first-year survival of independent offspring with hatching date (Brinkhof et al 1997) Thus, the reproductive value of a second