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Survival, breeding probability and reproductive success in relation to population dynamics of Brandt's Cormorants Phalacrocorax penicillatus a

Nadav Nur & William J. Sydeman

a

a

Point Reyes Bird Observatory , 4990 Shoreline Highway, Stinson Beach, CA, 94970, USA Published online: 25 Jun 2009.

To cite this article: Nadav Nur & William J. Sydeman (1999) Survival, breeding probability and reproductive success in relation to population dynamics of Brandt's Cormorants Phalacrocorax penicillatus , Bird Study, 46:S1, S92-S103, DOI: 10.1080/00063659909477236 To link to this article: http://dx.doi.org/10.1080/00063659909477236

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Bird Study (1999) 46 (suppl.), S92-103

Survival, breeding probability and reproductive success in relation to population dynamics of Brandt's Cormorants Phalacrocorax penicillatus NADAV NUR* and WILLIAM J. SYDEMAN Point Reyes Bird

Observatory, 4990 Shoreline Highway, Stinson Beach, CA 94970, USA


The size of the breeding population of Brandt's Cormorants Phalacrocorax penicillatus on Southeast Farallon Island, off the coast of central California, USA, shows large annual fluctuations and has declined by 50% since the 1970s. We investigated patterns of variation in adult survival, breeding probability, resighting probability, juvenile survival and reproductive success, to determine the extent to which variation in demographic processes reflected variation in environmental conditions (e.g. food availability) versus densitydependence, using observations of breeders and non-breeders from 1976 to 1995. Resighting and breeding probabilities varied significantly among years, and both were positively correlated with an annual index of prey availability — the abundance of juvenile rockfish. Adult survival between years was significantly correlated with changes in juvenile rockfish abundance and differed between sexes (0.77, males; 0.71, females). Female, but not male, survival appeared age-specific: older females showed reduced survival, especially during El Nino years. Intermittent breeding appeared common in this population: 54% of males and 49% of females estimated to be alive in a given year were not observed breeding in that year. Reproductive success varied in relation to the juvenile rockfish index but not in relation to population size. The return rate of juveniles, an index of survival during the first three years of life, was negatively related to sea surface temperature, both in the year of hatching and in the third year of life, when individuals first return to the colony to breed. We conclude that this population is strongly susceptible to environmental fluctuation. All parameters of survival and reproduction deteriorate under poor environmental conditions, with no evidence of buffering, and there was no evidence of density-dependence. Thus extrinsic, not intrinsic, forces appear most important in explaining recent population fluctuations. Throughout the world, many seabird popu1 lations have been censused over the course of several decades, yielding exemplary timeseries of fluctuation in abundance. 1-3 Nevertheless, our understanding of what factors (proximal or ultimate) are driving the longterm (decade-scale) or short-term (betweenyear) fluctuations in numbers is meagre. In particular, there has been much controversy *Correspondence author. Email: [email protected] © 1999 British Trust for Ornithology

over the role of intrinsic forces in influencing population number (acting through densitydependence of population processes), compared with the role of extrinsic forces, especially fluctuation in the environment. 45 Density-dependence could act through limitation of nest-sites, or by competition for other resources needed for reproduction or survival. Whereas some seabirds breed in relatively stable environments, many seabird populations are subject to strong temporal fluctuation in resource base. The latter characterizes the

Brandt's Cormorant population dynamics S93 25

METHODS

20

Data collection

15

For a detailed description of the study area and data collection methods see Boekelheide & Ainleylo and Boekelheide et al." In every year since 1971, the total breeding population size of Brandt's Cormorant has been estimated for the South Farallon Islands, two islands (SEFI and West End Island) which are separated by a small surge channel. In addition, since 1971, demographic processes (reproductive success, survival, recruitment, etc.) have been studied at a single colony on SEFI (referred to as 'Cormorant Blind' Colony, also 'Colony II' in Boekelheide et al.; 11 see their Fig. 5.2). This colony comprised up to 500 nests between 1980 and 1982, about 2% of Brandt's Cormorants on the South Farallon Islands nested in this colony. 11 From 1980 on, the number of occupied nest-sites on both islands were counted, from land and by boat, during the peak of the cormorant breeding period. Indices were developed for earlier years on the assumption that population size of the South Farallon Islands was directly proportional to population size of the Cormorant Blind colony. 11,12 From 1971 to 1991, between about 200 and 700 Brandt's Cormorant chicks were ringed annually (mean = 411 chicks, n = 20 years, excluding 1983, a year of reproductive failure). No adults have been ringed, so as to avoid disturbance. From the Cormorant Blind, as many rings as possible were read, both of breeding birds and presumed non-breeders, throughout the March—August breeding season. Non-breeding birds included transient birds, as well as those that built and occupied nests, yet never produced eggs. An individual was considered to be 'sighted' in that year if its ring number was recorded on two or more days. The number of eggs and number of chicks hatched and fledged were recorded; a bird was considered to have bred if it or its mate produced one or more eggs.

10 5 0 71 73 75 77 79 81 83 85 87 89 91 93 95

Year Estifhated breeding population of Brandt's Cormorants on the South Farallon Islands, measured in thousands of individuals.


Figure 1.

environment for seabirds breeding on the Farallon Islands, off the California coast. The Farallon Islands are situated in the California Current, an eastern boundary current system, which is characterized by high variability in productivity in response to intra-annual and inter-annual variation in oceanographic conditions," the El Nirio Southern Oscillation (ENSO) being the most well-known feature of this oceanographic regime. Here we present results from a long-term study of the population dynamics of Brandt's Cormorant Phalacrocorax penicillatus, initiated in 1970 by D.G. Ainley. 9,10 Annual censuses of Brandt's Cormorant on Southeast Farallon Island (SEFI), reveal a complex pattern in abundance over the past quarter-century (Fig. 1). Considerable yearto-year variation in number of breeding pairs superimposed over decadal trends in abundance. We refer to the pattern observed in the 1970s and 1980s as a 'staircase population decline,' i.e. stretches of population stability (more or less), interspersed with sharp drops in population numbers from which the population does not completely recover. Since 1985, the breeding population has maintained a fairly level trend at a lower level. Such patterns have also characterized seabirds breeding in the Peru Current, 9 another eastern boundary system, especially the Guanay Cormorant Phalacrocorax bougainvillei. Current numbers of Brandt's Cormorants are only about half what they were in the mid-1970s (Fig. 1), providing impetus to understand the causes of its population fluctuations in order to manage and conserve this species.

Environmental variation Annual variation in oceanographic conditions, which in turn predicts variation in prey availability, has been indexed by variation in sea surface temperature (SST). 7 Warm-water years (including El Nino years) are years in which

© 1999 British Trust for Ornithology, Bird Study, 46 (suppl.), S92-103


S94 N. Nur and WI. Sydeman upwelling is diminished, and prey availability is reduced. 6,7 Diet composition for Brandt's Cormorant chicks has been described for 1973-77 6,13 and 1993, 14 indicating that, in most years, juvenile rockfish Sebastes spp. is a predominant component of the diet of Brandt's Cormorant chicks. Therefore we use, as one measure of prey availability, abundance of juvenile rockfish from mid-water trawl surveys of the National Marine Fisheries Service, conducted in June of each year since 1983. 15 We considered both the log-transformed mean abundance of juvenile rockfish as published by Adams, 15 and a logarithmic transformation of the log-mean abundance. The measure of rockfish availability used here correlates well with a second, seabird-centred measure of rockfish availability: the proportion of the total diet fed to chicks by Common Guillemots Uria aalge that consists of juvenile rockfish. 7,8 Data analysis We used linear regression analysis to examine whether reproductive success in each year was correlated with several independent variables: rockfish trawl index, sea surface temperature and Brandt's Cormorant breeding population size. For analysis of juvenile survival, capturerecapture analyses would be desirable, but are beyond the scope of this paper (Nur & Sydeman, unpubl. data). Rather, we present analyses of an index of juvenile survival, the return rate of juveniles (the fraction of chicks ringed in each year that were subsequently seen as adults or as breeders), as a preliminary effort. Here we examine the relationship between environmental indices and juvenile return rate, for the cohorts born in 1972-87; note that by 1995, the last year of the study, individuals born in 1987 would have been eight years old. Brandt's Cormorants first return to the colony (as breeders or non-breeders) in their third year of life; therefore any correlation between the return rate of a cohort and an external variable could reflect differences in survival in any of the first three years of life or reflect differences in the tendency to return to the study area, and so be observed. Because cohorts analysed were born between 1972 and 1987 and because the rockfish trawl index only began in 1983, the rockfish trawl index could

not be examined in these analyses. Instead, we examined the return rate in relation to SST, an indicator of general, oceanic conditions. Weighted regression of the return rate was used, 16 where the latter was weighted by the inverse of the variance of the estimate of each cohort's return rate, assuming the number of individuals returning per cohort was binomially distributed. Statistical analyses of reproductive success and juvenile return rate were carried out using the program STATA. 17 Where appropriate, we present results of multiple regression analysis using 'added variable plots' :17 these show the effect of one independent variable on the dependent variable while controlling for additional independent variables. As appropriate, we confirmed that

assumptions of linear regression were met (residuals normally distributed and homoscedastic). Adult survival was estimated using two data sets: first, on the basis of sighting-resighting of individuals that may or may not have been breeding and, second, on the basis of observations of breeding individuals only. Capturerecapture analysis was carried out using SURGE 4.2, for model selection and hypothesis testing as described by Lebreton et al. 18 We used both the Akaike information criterion (Alc) and the likelihood ratio test (LRT, with its statistic, the likelihood ratio statistic, LRs) to discriminate among competing models. 18 We used RELEASE to carry out goodness-of-fit testing following recommendations of Cooch et al. 19 RELEASE allows testing only of the fully time-dependent model for both survival, symbolized cp, and recapture probability, symbolized p; also referred to as the Cormack-Jolly-Seber mode1. 16 In the case of observations on breeding individuals, the 'recapture probability' refers to the probability that an individual is observed breeding in year t +1 given that (1) it survived from year t to t + 1, and (2) it had previously been observed breeding. Thus we also refer to the parameter p, in that case, as estimating

'rebreeding probability'; this has also been called breeding propensity. 19 For the data set consisting of sightings of adult individuals (whether or not they were observed breeding), 'recapture probability' is actually 'resighting probability.' Use of two data sets (one based on sightings,

© 1999 British Trust for Ornithology, Bird Study, 46 (suppl.), S92 - 103


Brandt's Cormorant population dynamics S95 the other on recorded breeding) allows us, first of all, to compare two different estimates of the same parameter, survival, and secondly, allows us to estimate a resighting probability as distinct from a 'rebreeding' probability. In this way we can partition the fate of all individuals into four mutually exclusive categories: (1) died ( = 1 - (p), (2) survived but not resighted, (3) resighted but not observed breeding, (4) resighted and observed breeding. Capture-recapture analyses were carried out only on the 20 most recent 'capture occasions' (years 1976-95), because of limitations of the available SURGE 4.2 and RELEASE programs. The rockfish abundance index, however, was only available for 1983-94. The effect of rockfish index (and other covariates) was modelled using linear constraints, as part of SURGE analyses, as described by Lebreton et al. 18 and Cooch et al. 19 . As in other capture-recapture analyses, 18 we examined age-variation in parameters with reference to entry into the data set, not true chronological age. That is, an individual enters 'age-class 1' the year it is first observed as an adult (sighting-resighting data) or first observed as a breeder (breedingrebreeding data).

RESULTS Survival in relation to sex and age Survival estimated from sighting-resighting data was 77% for males and 71% for females, a significant difference (Table 1). Survival estimated from breeding-rebreeding data was 75% and 66%, a decrease of 2-5%, but for neither sex was the difference in survival estimates significantly different for the two methodologies. The above results were obtained using models which assumed that resighting probability and rebreeding probability differed among years, an assumption that was confirmed (see below). However, survival estimates were nearly identical when resighting or rebreeding probability was assumed to be constant across years (Table lb). Because the sighting-resighting data set had a larger sample size, we prefer to use that data set for deriving survival estimates, rather than the breeding-rebreeding data set. There was no evidence of age variation in male survival; the age-constant survival model was preferred (both by LRT and AO, compared

Table 1. Fate of Brandt's Cormorant adults: resighting and rebreeding probability, survival, by sex. Degrees of freedom = 1 for all statistical tests. In all cases, survival is modelled as constant with time.

Survival (± se)

Resighting (± se)

a. Resighting—rebreeding probability varies with time Sighting—resighting data Male (n = 339) 0.772 ± 0.013 Female (n = 136) 0.711 ± 0.023 Difference LRS = 4.96 between sexes P = 0.026 Breeding—rebreeding data Male (n = 159) 0.752 ± 0.024 0.655 ± 0.039 Female (n = 85) Difference LRS = 4.70 between sexes P = 0.030

b. Resighting—rebreeding probability is constant with time Sighting—resighting data Male (11 = 339) 0.765 ± 0.012 0.708 ± 0.024 Female (n = 136) Difference Las = 4.66 between sexes P = 0.031 Breeding—rebreeding data Male (n = 159) 0.748 ± 0.022 Female (n = 85) 0.649 ± 0.038 Difference LRS = 5.47 between sexes P = 0.019

0.639 ± 0.019 0.522 ± 0.037 LRS =

8.02

P = 0.005

0.459 ± 0.033 0.509 ± 0.058 Las = 0.59 P > 0.5

with models that allowed for two or more age-classes. However, for females there was evidence of significant age-variation (Table 2). Particularly noteworthy, survival was low for the oldest age-class (age-class 5). The confidence interval for this age-class did not include the estimated survival values for age-classes 2, 3 or 4. Especially intriguing, no older females were known to survive the 1983 El Nino; e.g. among seven females, nine years of age or older in 1983, none were subsequently observed, whereas eight older males (age 9 or older in 1983) were known to have survived. During the 1992 El Nifio, also a strong ENSO event, a similar sex-difference was observed: among nine older individuals known to have

© 1999 British Trust for Ornithology, Bird Study,

46 (suppl.), S92-103

S96 N. Nur and VV.J. Sydeman Table 2. Variation in Brandt's Cormorant survival, by sex, in relation to age-class.


Ageclass 1 2 3 4 5 6 7 8 9 Difference between ages

Male 0.754 ± 0.032 0.815 ± 0.040 0.762 ± 0.051 0.694 ± 0.056 0.933 ± 0.072 0.720 ± 0.076 0.675 ± 0.090 0.855 ± 0.115 0.763 ± 0.054

LRS = 7.72 df = 8, P> 0.4 Model accepted 1 No age variation

Ageclass

Female

1 2 3 4 5

0.600 ± 0.048 0.890 ± 0.067 0.754 ± 0.084 0.768 ± 0.106 0.621 ± 0.062

LRS = 10.69 df = 4, P = 0.030

Significant age variation, five age-classes

1 Models accepted were Alc-optimal. Models compared were for males: nine models with 1, 2, 3, ... 9 age-classes (where 2 age-class model is 1, 2+ years, 3 age-class is 1, 2, 3+ years, etc.); for females: five models with 1, 2, ... 5 age-classes.

survived the 1992 El Nino (i.e. at least nine years old in 1992), all but one were male. Annual variation in survival, resighting and rebreeding probabilities To analyse annual variation we combined the sexes; this still resulted in small sample sizes in some years. We had insufficient data to address the question of sex x year interaction. Goodnessof-fit tests were carried out for the fully timedependent model (37 estimable parameters in total for ip and p). The model passed test 3.SR of RELEASE (x 2 = 22.76, df = 17, P = 0.16), but showed significant lack of fit for test 3.Sm and test 2 (P < 0.001 for each; described by Cooch et al. 19 ). There are several possibilities which may account for the lack of fit; e.g. the sexes were pooled, hence sex differences in resighting probability were ignored (Table 1); also, the fully time-dependent model used by RELEASE ignores age effects (for which there was evidence, Table 2). Further examination of sources of heterogeneity is needed as are more flexible goodness-of-fit programs. In the meantime, results of the following analyses should be considered cautiously.

Resighting probability showed considerable and highly significant variation between years, being less than 38% in three years and more than 76% in three years (1_,Rs = 122.2, df = 17, P < 0.001). Rebreeding probability also varied greatly between years (1,Rs = 88.26, df = 17, P < 0.001). The above-cited results were obtained from models in which both survival and recapture probability were fully time-dependent. Adult survival appeared to vary among years, but to a lesser degree: survival was estimated to be 67% or less in four of the years (minimum = 57%), compared to over 80% in four years (maximum = 90%), with nine years being intermediate; standard errors in each year were about 7% (median 0.073, range 0.045-0.138). These results were obtained from a model in which recapture probability was fully time-dependent. The omnibus test of annual variation in adult survival, using 17 df, was not significant (LRs = 10.06, df = 17, P> 0.5). Nevertheless, lack of statistical significance may simply reflect the low power to detect biologically meaningful variation in survival rates, when using 17 degrees of freedom. 18 Therefore, we examined adult survival in relation to prey availability in each year, as indexed by the juvenile rockfish trawl survey. Survival from year x to x + 1 was significantly related to the log-transformed rockfish trawl index in year x + 1 (Fig. 2), but not to the untransformed rockfish trawl index (LRs = 1.65, P> 0.1). In addition, survival from year x to x + 1 was significantly related to the log-transformed rockfish trawl index in year x (LRS = 4.93, df = 1, P = 0.026). In other words, prey availability in a given year was related to survival from the previous year to that year as well as survival from that year to the next year. Because the trawl index in one year was effectively uncorrelated with the trawl index in the following year (r = —0.15, P> 0.6, it = 11 years), we suggest that prey availability affects survival through two distinct mechanisms, acting on different timescales (e.g. through influences on survival during the breeding season and through influences on over-winter survival). There was no evidence for density-dependence in adult survival: there was no significant relationship between adult survival from year x to year x + 1 and breeding population size in year x (P > 0.5, LRT). Rebreeding probability in year x increased significantly as rockfish abundance in year x


Brandt's Cormorant population dynamics S97 0.9

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log (Index of juvenile rockfish abundance) Figure 2. Adult survival (as estimated by SURGE) in relation to prey availability, as indexed by juvenile rockfish trawl surveys of NMFS. The effect of log(juvenile rockfish index) in year x, on survival from year x -1 to year x was significant, LRS = 4.35, df = 1, P = 0.037. Two-digit symbols indicate year x. The least-squares line of best fit is shown, for illustrative purposes, depicting the relationship of annual estimates of survival in relation to the trawl index.

increased (Fig. 3; rockfish index untransformed); the same was true for resighting probability (LRs = 13.06, df = 1, P < 0.001). Intermittent breeding The results of Table 1 indicate that although 77% and 71% of male and female Brandt's Cormorant adults survived to the following year, only 46% and 51%, respectively, were actually observed breeding in that year. A larger fraction of those presumed alive (64% and 52%, respectively) were resighted in the following year, but may or may not have been observed breeding. Table 3 provides a breakdown of the 77% of males and 71% of females that were presumed to have survived from one year to the next, according to whether they

were observed breeding, resighted but not seen breeding, or not resighted at all. These results confirm that intermittent breeding is common in this population. An alternative explanation (which we cannot rule out) is that breeding site fidelity is so low that many individuals move out of the study area in one year and then move back again in a subsequent year. Annual variation in reproductive success As with adult survival and breeding probability, reproductive success (number of chicks fledged per breeding pair) increased significantly with prey availability (Fig. 4). We also examined whether reproductive success was density-dependent but found that it was positively correlated with breeding population

Table 3. Fate of Brandt's Cormorant adults at study colony.

Sex

Fate

Males

77% survive to next year (SURGE estimate), of which 28% not observed 14% observed, but not breeding 35% observed breeding 71% survive to next year (SURGE estimate), of which 34% not observed 1% observed, but not breeding 36% observed breeding

Females

© 1999 British Trust for

Ornithology, Bird Study, 46 (suppl.), S92-103

S98 N. Nur and W.I. Sydeman 0.8

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Figure 3. Rebreeding probability (see text) in year x in relation to prey availability in year x, as indexed by the juvenile rockfish trawl surveys of NMFS (1_,Rs = 7.53, P = 0.006); these results were obtained by allowing survival to be fully time-dependent. Two-digit symbols indicate year. The least-squares line of best fit is shown, illustrating the relationship of annual estimates of rebreeding in relation to the trawl index.

size. Such a positive correlation, however, may have resulted from confounding due to prey availability affecting both reproductive success and breeding population size. Therefore, we attempted to control for the effect of prey availability by statistically adjusting reproductive success for the effect of prey availability in a multiple regression analysis (using the juvenile rockfish trawl abundance index to measure prey availability) and compared that with breeding population size, also adjusted for the

effect of prey availability. The relationship was still positive, although not significant (Fig. 5). Thus, there is no evidence that population size depresses reproductive success. Juvenile survival

For the analysis of return rates of a cohort born in year x, we considered SST measured in years x, x + I, x + 2, x + 3, as well as years x - 1 and x - 2 (recall that individuals first return to the

3 85

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Index of juvenile rockfish abundance Figure 4. Reproductive success in relation to prey availability, as indexed by rockfish trawl surveys of NMFS,

P = 0.002, R 2 = 0.682 (results of linear regression analysis). Two-digit symbols indicate year of data. The leastsquares line of best fit is shown. 0 1999 British Trust for Ornithology, Bird Study, 46 (suppl.), S92 - 103

Brandt's Cormorant population dynamics S99 85

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10 -3 x Standardized population size Figure 5. Standardized reproductive success (chicks fledged per breeding pair) in relation to standardized breeding population size of Brandt's Cormorants (measured in thousands of individuals); both the y-variable and the x-variable have been statistically adjusted (using a multiple regression analysis) to control for the effect of prey availability, as indexed by rockfish trawl surveys of NMFS (see text), and are not correlated (P > 0.1). Standardized y- and x-variables have been adjusted to a mean of zero. Two-digit symbols indicate year of data.

colony in their third year of life). The return rate of a cohort born in year x was significantly correlated with SST in year x and with SST in year x -2 (Fig. 6). In both cases, the warmer the water (implying reduced food availability) the lower is the return rate of that cohort (Fig. 6). These two correlations imply two distinct mechanisms operating, since SST in year x was not correlated with SST in year x +2 (r = 0.147, P> 0.5, n = 23 years). SST in years x - 2, x - 1, x + 1, and x + 3 were not significantly correlated with return rate of juveniles born in year x. There was also no significant correlation between juvenile return rate for a cohort born in year x and breeding population size in years x - 2, x - 1, x, x + 1, x + 2 or x + 3 (P > 0.15 in all cases).

DISCUSSION Temporal variation in reproductive parameters and survival This study found that reproductive success varied greatly between years, a result that has been reported for many seabirds. 2,6 This finding is consistent with theoretical predictions that, for potentially long-lived organisms in a variable environment, a decrease in food availability (i.e. a deterioration of the environment) will lead to reduction in reproductive effort

(hence reduced reproductive success), rather than leading to reduction in adult survival. 20,21 This argument also appears to explain annual variation in breeding propensity: under good feeding conditions Brandt's Cormorants are more likely to attempt breeding (i.e. reproductive effort is higher). It is, therefore, somewhat surprising that adult survival also appeared to vary in relation to environmental conditions, although this conclusion should be somewhat tempered by the finding of significant lack-of-fit of the fully time-dependent model. Specifically, under poor food conditions (as indicated by low rockfish abundance), survival of breeders was reduced, compared with good food conditions. This finding seems to contradict theoretical predictions 20,21 that long-lived individuals should not invest so much in a reproductive episode that they thereby curtail future survival. One explanation is that Brandt's Cormorants are not able to optimize reproductive effort, owing to limited ability to predict future environmental conditions at the time of making a reproductive commitment. Thus, they may only partially respond to environmental variation (e.g. breeding probability is impacted), but not optimally. In contrast, Nur 22 developed a model of optimal reproductive effort which produced predictions different from that of Schaffer 2 ° and

© 1999 British Trust for Ornithology, Bird Study, 46 (suppl.), S92 - 103

S100 N. Nur and W.I. Sydeman 0.32

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Sea surface temperature in third year of life (March) Figure 6. Correlation of juvenile return rate (proportion of ringed young born in year x which were observed at the colony in subsequent years) with sea surface temperature (SST, measured in March), an index of oceanographic condition. (a) Correlation with SST in year of hatching, year x. Results of linear regression are R 2 = 0.570, P = 0.001. Year of birth is shown for each cohort. (b) Correlation with SST in year x + 2. Results of linear regression are R 2 = 0.375, P = 0.015. Year of birth is shown for each cohort. Note log scale of x axis.

Goodman. 21 In Nur's mode1 22 it was assumed that: (1) individuals optimize reproductive effort, and that this effort can vary as environmental conditions vary, (2) increased reproductive effort increases reproductive success but reduces adult survival, and (3) differences in environmental conditions imply that, for a given level of reproductive effort, adult survival will be higher under 'good' conditions than under 'poor' conditions. Note that the observation of low reproductive success does not imply low effort, it could also reflect poor environmental conditions. Nur's optimality mode1 22 predicted that, under good conditions, individuals will increase reproductive effort (just as was observed for Brandt's Cormorants);

the increase in reproductive effort itself would reduce adult survival. Yet at the same time, adult survival under good conditions is greater than it is under poor conditions. In Nur's model, the survival of adults breeding under good conditions and at the optimal reproductive effort was always higher than the survival of adults breeding under poor conditions, assuming that they also optimize reproductive effort. As a result, even when individuals breed at an optimal level of reproductive effort, there would arise a positive correlation between environmental condition and adult survival, as observed in this study. Earlier work on European Shags Phalacrocorax aristotelis on the Isle of May 23-25 considered



Brandt's Cormorant population dynamics S101 that adult survival was fairly constant, or at least not related to environmental conditions. This was in contrast to the situation for European Shags on the Fame Islands, which experienced several episodes of high adult mortality', owing to 'red tide' (paralytic shellfish poisoning). 26' 27 However, even on the Isle of May, high adult mortality was reported in winter 1994, 28 apparently due to poor feeding conditions. Thus, the general pattern for cormorants appears similar to that of other seabirds, where there is increasing evidence that adult siirvival varies from year to year and decade to decade and, furthermore, that changes in adult survival may help explain observed population fluctuations. 28-33 Our study and that of Boekelheide & Ainleyl° provide evidence suggesting that juvenile survival varies among cohorts. It is not possible to untangle the different components of juvenile return rate (survival in the first, second and third years of life, natal philopatry), but because return rate was correlated with sea surface temperature (SST) measured in March of the first year of life, this suggests that first-year survival was affected by oceanographic conditions. The correlation of SST in the third year of life may suggest an effect of the environment on third-year survival or it may indicate that some aspect of the environment enhances return to the study colony in that year. Intercohort variation in juvenile and subadult survival is well-documented in European Shags .23,34-36 Furthermore, Galbraith et al. 37 demonstrated that the critical period of mortality for first-year birds is in the first winter of life rather than the first summer. We have no such indication in the Brandt's Cormorant; clearly, more work on this species is required to understand this important demographic parameter.

indicate that 54% of males and 49% of females that are estimated to be alive in a given year are not observed breeding in that year. This component of the population can be broken down further into (1) those observed that year, but not observed breeding, (2) those not observed at all that year, but which were observed in a subsequent year, and (3) those presumed alive in that year, but which were never observed in any subsequent year. A substantial fraction of Brandt's Cormorants fell into each of these fractions. However, the first subcomponent (those observed but not seen breeding) appeared to differ between the two sexes. We are unable to say whether this reflects a true biological difference (males often attend the colony, even when not breeding) or mainly a methodological difference (non-breeding females are less conspicuous than males when attending the colony). In the European Shag, earlier studies 33,34 had not noted the prevalence or ecological significance of intermittent breeding, but analysis by Aebischer & Wanless 24 (also Aebischer 23 ) indicated that skipping of breeding was implicated in two population 'crashes' of this species on the Isle of May. Studies of the Cape Cormorant Phalacrocorax capensis, 38 Guanay Cormorant 38 and Galapagos Flightless Cormorant Nan nopterum harrisi 4° also found intermittent breeding to be common. In general, the extent of skipping in seabirds is easily underestimated, because skipping birds are absent or inconspicuous. In the Shorttailed Shearwater Puffin us tenuirostris, 41 12% of adults did not attend the colony in a given year (though known to be alive) and 19% maintained burrows but did not lay an egg. In the Manx shearwater Puffin us puffin us, Brooke 42 estimated that 20% of experienced breeders did not attempt breeding in any given year.

Intermittent breeding as part of the cormorant breeding strategy

Life in a variable environment

This study confirmed that intermittent breeding (i.e. individuals that previously have bred skip breeding in one or more years) is an important feature of the Brandt's Cormorant breeding strategy, a point made earlier by Boekelheide & Ainley. 10 However, these authors did not attempt to quantify this phenomenon at the population level. The results of this study

Brandt's Cormorants demonstrate a suite of demographic parameters that appear to correlate positively with prey availability. In years with high prey availability (which tend to be cold-water years), reproductive success, breeding probability, adult survival and, apparently, juvenile survival are high. In contrast, in years with low prey availability, the converse holds: reproductive success, breeding probability and

0 1999 British Trust for Ornithology, Bird Study, 46 (suppl.), S92-103


S102 N. Nur and VV.J. Sydeman survival are all reduced. Boekelheide and Ainleym also argued that age of first breeding is correlated with food availability: years which were categorized by them as years of 'good' food availability were years in which Brandt's Cormorants were more likely to breed for the first time. Yet at the same time, the SEFI population of Brandt's Cormorants demonstrates no ability to compensate for poor environmental conditions. For example, years in which population size was lower were not years in which reproductive success was enhanced. Thus, this population does not appear to be buffered with respect to the marked environmental variation that characterizes the ecosystem of the Farallon Islands. Pelagic Cormorants on SEFI display an even more marked boom-or-bust demographic strategy, at least with regard to reproductive effort and success: in poor food years, reproductive success and! or breeding probability decline to nil (Nur & Sydeman, unpubl. data). The North Sea is not part of an eastern boundary current, and the ecosystem does not show such large temporal changes as the California Current. Yet even here, studies of the European Shag indicate marked demographic response to environmental conditions leading to recurrent population crashes 24,28,34 We conclude that, for cormorants in the California Current ecosystem, extrinsic forces play a predominant role in shaping population trajectories.

ACKNOWLEDGEMENTS Any long-term study relies heavily on a succession of biologists who have dedicated their field seasons to collecting data, year after year. For all their efforts we thank PRBO field and supervisory biologists, including David Ainley, Robert Boekelheide, Harry Carter, Steve Emslie, Michelle Hester, Elizabeth McLaren, and Steve Morrel for collection of long-term data, which has made this study possible. We thank Chris Wernham, Emmanuelle Cam and Kelly Hastings for helpful comments on the manuscript. We are indebted to the US Fish and Wildlife Service — San Francisco Bay National Wildlife Refuge, managers of Farallon Islands National Wildlife Refuge, for encouragement and financial support; additional financial support was provided by the Pacific Seabird

Group, CA Department of Fish & Game (Oil Spill Prevention and Response Program), and Gulf of the Farallones National Marine Sanctuary. This is PRBO Contribution No. 777.

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