Historical Dynamics of the Australian Fur Seal Population: Evidence of Regulation by Man?

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Historical dynamics of the Australian fur seal population: evidence of regulation by man?

J.P.Y. Arnould, I.L. Boyd, and R.M. Warneke

Abstract: The Australian fur seal (Arctocephalus pusillus doriferus) was severely over-exploited in the 18th and 19th centuries and until relatively recently its population had remained steady at well below estimated presealing levels. However, the population is now increasing rapidly (6%–20% per annum) throughout its range and there is a need to understand its dynamics in order to assess the potential extent and impact of interactions with fisheries. Age distribution (n = 156) and pregnancy rate (n = 110) were determined for adult females collected at a breeding colony on Seal Rocks, southeast Australia, in 1971–1972. Mean ± SE and maximum observed ages were 9.37 ± 0.41 and 20 years (n = 1), respectively. A stochastic modelling approach was used to fit an age distribution to the observed age-structure data and calculate rates of recruitment and adult survival. Annual adult female survival and recruitment rates between 1954 and 1971 were 0.478 ± 0.029 (mean ± SE) and 0.121 ± 0.007, respectively, suggesting that the population was experiencing a decline during the 1960s. The pregnancy rate increased from 78% at 3 years of age to an average of 85% between 4–13 years of age before significantly decreasing in older females (the oldest was 19 years of age). There was no significant effect of body mass or condition on the probability of a female being pregnant (P >0.5in both cases) and the nutritional burden of lactation did not appear to affect pregnancy rates or gestational performance. These findings suggest that the low survivorship was due to density-independent effects such as mortality resulting from interactions with fishers, which are known to have been common at the time. The recent increase in the population is consistent with anecdotal evidence that such interactions have decreased as fishing practices have changed. Résumé : L’otarie à fourrure d’Australie (Arctocephalus pusillus doriferus) a été fortement surexploitée au cours des 18e et 19e siècles et, jusqu’à récemment, sa population était demeurée stable à des densités bien inférieures à celles qui prévalaient avant la chasse commerciale. Cependant, la population est actuellement en croissance rapide (6%–20% par an) sur toute son aire de répartition; il est donc nécessaire de comprendre cette dynamique pour évaluer le potentiel de l’expansion et l’impact des interactions avec les pêches commerciales. Nous avons déterminé la structure en âge (n = 156) et le taux de grossesse (n = 110) chez les femelles adultes d’une colonie reproductrice à Seal Rocks dans le sud-est de l’Australie en 1971–1972. L’âge moyen ± erreur type observé était de 9,37 ± 0,41 ans et l’âge maximal de 20 ans (n = 1). Un modèle de type stochastique a permis d’ajuster une distribution d’âges aux données de structure d’âge et de calculer les taux de recrutement et de survie des adultes. Les taux annuels moyens (± erreur type) de survie des femelles adultes de 1954 à 1971 étaient de 0,478 ± 0,029 et les taux de recrutement, de 0,121 ± 0,007, ce qui laisse croire que la population a subi un déclin au cours des années 1960. Le taux de grossesse a augmenté de 78 % à l’âge de 3 ans à une moyenne de 85 % aux âges 4–13, avant de décliner significativement chez les femelles plus âgées (la plus vielle de 19 ans). Il n’y avait pas d’effet significatif de la masse ou de la condition sur la probabi- lité qu’une femelle soit enceinte (P > 0,5 dans les deux cas) et le fardeau alimentaire de l’allaitement ne semblait pas affecter les taux de grossesse ou le succès de la gestation. Ces résultats laissent croire que la faible survie était due à des facteurs indépendants de la densité, tels que la mortalité due aux interactions avec les pêcheurs, un phénomène commun à l’époque. L’accroissement récent de la population est en accord avec des indications anecdotiques que de telles interactions ont diminué, alors que les pratiques de pêche ont changé. [Traduit par la Rédaction] Arnould et al. 1436

Introduction (Bonner 1994). However, most species have since recovered to some degree or are in the process of doing so (Bonner During the commercial-sealing era of the 18th and 19th 1985; Wickens and York 1997). These population increases centuries, fur seals throughout the world were severely over- have occurred while the worldwide human exploitation of exploited and, in some cases, hunted to near extinction marine living resources has expanded rapidly (Alverson

Received 21 January 2003. Accepted 14 July 2003. Published on the NRC Research Press Web site at http://cjz.nrc.ca on 22 September 2003. J.P.Y. Arnould.1 Department of Zoology, University of Melbourne, Melbourne, Victoria 3010, Australia. I.L. Boyd. Sea Mammal Research Unit, Gatty Marine Laboratory, University of St. Andrews, St. Andrews, Fife KY16 8LB, Scotland, United Kingdom. R.M. Warneke. Blackwood Lodge, 1511 Mount Hicks Road, Yolla, Tasmania 7325, Australia. 1Corresponding author (email: [email protected]).

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Arnould et al. 1429

1992; Shannon et al. 1992; Klaer 2001). A consequence of and Mitchell 2002; Shaughnessy et al. 2002), is still substan- this has been an increase in interactions between fur seals tially less than the estimated presealing levels (Warneke and and commercial fisheries (DeMaster et al. 1985; Wickens et Shaughnessy 1985; Pemberton and Kirkwood 1994), con- al. 1992; Pemberton and Shaughnessy 1993; Arnould and cerns have been raised about the current and future levels of Croxall 1995; Punt and Butterworth 1995; Shaughnessy and interaction between Australian fur seals and commercial Davenport 1996; Klaer 2001). This has led to concerns be- fisheries (Pemberton et al. 1992; Pemberton and Shaughnessy ing raised about the impact of commercial fishing on prey 1993; Hindell et al. 1998; Goldsworthy et al. 2003). There is availability for fur seals and incidental mortality in fishing a pressing need, therefore, to understand the population dy- gear (Everson and Goss 1991; Wickens et al. 1992) and, namics of Australian fur seals in order to assess the potential conversely, to calls from the fishing industry for the imple- extent and impact of these interactions. mentation of measures to manage the fur seal population Crucial information necessary for modelling population (Butterworth 1992; Pemberton and Shaughnessy 1993; dynamics in large, long-lived mammals include data on adult Balmelli and Wickens 1994; Wickens 1996; Thomson et al. female survivorship and the factors influencing pregnancy 2000). There has been considerable interest, therefore, in the rates (Harwood and Prime 1978; Eberhardt 1988; Brown and population dynamics of fur seals and the modelling of their Rothery 1993). No information is currently available for prey consumption for the purpose of developing adequate these variables in Australian fur seals and previous predic- policies for managing the fisheries and the fur seal populations of population trends have been based on information tions (Eberhardt 1990; Butterworth et al. 1995; Wickens and obtained in other species (Pemberton and Kirkwood 1994; York 1997). Goldsworthy et al. 2003), particularly the extensive data The Australian fur seal (Arctocephalus pusillus doriferus) collected for the conspecific Cape fur seal (Rand 1955; is a temperate-latitude species with a breeding distribution Butterworth et al. 1995; Punt and Butterworth 1995). How- restricted to Bass Strait between the southeastern tip of the ever, because of the markedly higher productivity of their Australian mainland and Tasmania, which is recognised as marine environment, demographic data for Cape fur seals being of low oceanic productivity (Warneke and Shaughnessy may not be adequate for modelling the population dynamics 1985). Natal colonies are currently located on just nine is- of Australian fur seals (Wickens and York 1997). lands but there is historical evidence to suggest that several The aims of this study, therefore, were to (i) determine the other islands within Bass Strait also once hosted breeding age distribution; (ii) assess the influence of age, body condi- colonies (Warneke and Shaughnessy 1985; Pemberton and tion, and lactation status on pregnancy rates; and (iii) model Kirkwood 1994). Commercial sealing ceased in ca. 1825 survivorship and recruitment in a historical sample of adult and, while there have been several minor regulated culls and female Australian fur seals. killings by fishers (both legal and illegal), the species has been largely protected since the 1890s (Warneke 1975). Re- Materials and methods covery of the population was initially slow, with Warneke and Shaughnessy (1985) concluding that there had been no The study was conducted at Seal Rocks (38°31′S, measurable increase between 1945 and 1975 and that the 145°06′E) in northern Bass Strait from February to October population had stabilized at well below its estimated in 1971 and 1972. Australian fur seals give birth between presealing annual production level of 50 000 pups. Warneke mid-November and mid-December (pupping peaks on (1988) recorded an annual production of ca. 8000 pups in 1 December) and the lactation period normally lasts 10– 1986 and concurred with this conclusion. In stark contrast, 11 months (Warneke and Shaughnessy 1985; Arnould and the population of the conspecific Cape fur seal (Arctocepha- Hindell 2001). Because the species is extremely wary of hu- lus pusillus pusillus) has recovered rapidly from postsealing mans, sampling required crawling upwind into the colony lows of < 100 000 animals at the end of the 19th century and and making use of the terrain for cover. Selected individuals presently numbers over 1.7 million individuals (Butterworth were killed with a 0.22 rifle shot to the head from close et al. 1995). The Cape fur seal, however, inhabits the range using a quiet, very low velocity cartridge. Animals nutrient-rich waters of the Benguela Current, and Warneke constantly move around the colony and the wind direction and Shaughnessy (1985) suggested that the lower marine changes frequently at the study site, so weaned females productivity of the waters inhabited by the Australian fur (>1 year old, identifiable from pelage characteristics) were seal may have influenced its slow population recovery and selected at random by collecting the first individual encoun- will impose a much lower limit on its ultimate size. Compe- tered within range. Sampling was conducted over several tition with commercial fisheries, direct interactions with days at monthly intervals. fishing operations, and entanglement in man-made debris Body mass (±0.1 kg) was measured on a spring scale have also been suggested as factors that may have contrib- (Salter No. 85T, Salter Pty Ltd., Melbourne, Victoria, Aus- uted to the continuing low population levels (Shaughnessy tralia) and standard length (STDL; straight-line nose to tail, and Warneke 1987; Pemberton et al. 1992; Pemberton and body supine) was determined with large stainless-steel slide Kirkwood 1994). callipers (±0.5 cm). As body mass covaries to a large degree The Australian fur seal population is currently increasing with body length and, hence, may not accurately reflect at 6.1%–19.7% per annum throughout its range (Arnould body lipid reserves, residual values from the mass–length and Littnan 2000; Littnan and Mitchell 2002; Shaughnessy relationship were used as a body-condition index (BCI) et al. 2002). The reasons for the recent increases are not (Guinet et al. 1998; Arnould and Warneke 2002). For preg- known. While annual pup production, presently estimated at nant females, body mass was corrected by subtracting the approximately 19 000 (Arnould and Littnan 2000; Littnan mass of the foetus and placenta, with placental mass as-

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1430 Can. J. Zool. Vol. 81, 2003

sumed to be 10% of foetal mass (Boyd and McCann 1989). vival rate was 8, estimated by fitting an exponential regres- For logistical reasons, not all measurements (body mass, sion model to the age structure of adult females. Only fe- length) were made on every individual sampled. males ≥3 years of age were included in the analysis (these Pregnancy was determined by visual inspection of the age groups are sexually mature and are therefore most likely uterus for the presence of a foetus in females collected be- to be an unbiased sample of the population age structure of tween April and October (during the period of active gesta- adults; Arnould and Warneke 2002), but the regression also tion; Rand 1955; Boyd 1991). The sex of small foetuses was provided an estimate of the initial cohort size required to determined where possible and their STDL and body mass produce this age structure. These variables were then used as were measured by vernier callipers (±1 mm) and a top- the starting values within a stochastic model of the popula- loading balance (±1 g), respectively; larger foetuses were tion. During each simulation, the population was projected measured with a tape (±1 mm). Lactation status was deter- forward using a Leslie matrix. We assumed that there was mined by visual observation of a suckling pup prior to sam- no age-specific component to the survival rate because we pling, external inspection of the teats for evidence of recent reasoned that, on average, all adult females were likely to be suckling, manual expression of milk, and (or) inspection of exposed to the same extrinsic factors affecting their survival dissected mammary glands for the presence of milk. in any calendar year. In this case, the matrix used at each An upper canine tooth was collected from each animal time step was structured by selecting potential values for the and longitudinal thin sections (0.2 mm) were cut using a adult female survival rate by assuming that it was normally low-speed saw with a 0.4 mm diamond wafering blade. The distributed, with a mean equal to the slope of the exponen- thin sections were stored in a mixture of glycerol and 70% tial regression. The same method was used to provide values ethanol until analysis in 2001 (for details see Arnould and for the rate of recruitment to the adult female population, but Warneke 2002). Age was determined by counting annual this was centred around recruitment at 3 years of age esti- growth lines in the cementum layer under a stereomicro- mated from the exponential model. This stochastic approach scope with transmitted polarized light (Payne 1978; Arnbom allowed us to investigate the parameter space that could et al. 1992). The age determined from counting annual have produced the observed age structure while relaxing the growth lines in the cementum was adjusted for date of col- assumption of a stable age structure that accompanies classi- lection assuming a mean birth date of 1 December (Warneke cal cohort analysis. The pregnancy rate in the model was and Shaughnessy 1985). fixed at 0.78 (see below). Model simulations in which the The age structure of the population was modelled to ex- pregnancy rate was allowed to vary, however, did not signif- amine the underlying vital rates that could have given the icantly alter the population age structure or the projected re- observed age distribution and to examine the evidence for cruitment and adult survival rates. any historical rate of change in the size of the population. Each modelled population was projected forward for Assuming that a population has no immigration or emigra- 10 000 time steps, and the population age structure, ex- tion, age structure represents the combination of two pro- pressed in terms of the proportion of adult females in each cesses: the initial size of each cohort and the cumulative cohort ≥3 years of age, was compared with the observed age mortality experienced by that cohort since birth. If each co- structure using minimum least squares weighted for sample hort in an age-structured population is considered independ- size in each age class. This was repeated 100 times to obtain ently, it would be impossible to distinguish between the an estimate of the variance associated with the results. effects of initial cohort size and cumulative mortality. How- Statistical analyses were performed using Statistica® (Ver- ever, initial cohort size is a function of the number of adult sion 5.1, Statsoft Inc.) and the 9-population model was de- females in the population and is therefore constrained by the veloped in C++. The Kolmogorov–Smirnov test was used to fecundity rate. Similarly, it is likely that the mortality experi- determine whether the data were normally distributed and a enced by a cohort will be correlated with the mortality expe- F test to confirm homogeneity of variances. Unless other- rienced by all cohorts represented in the population during wise stated, data are presented as the mean ± SE and results any time step. Therefore, the cumulative mortality experi- considered significant at the P < 0.05 level. enced by a cohort will be correlated with the cumulative mortality experienced by neighbouring cohorts. Conse- Results quently, information exists within an age structure that could be used to estimate survival and reproductive rates. In this Female age distribution and survivorship analysis we have not attempted to solve this problem analyt- A total of 156 weaned females were collected. There was ically but have adopted a stochastic modelling approach. no correlation between sampling date (Julian) and female For this analysis, we have combined the samples from age (r = 0.07, n = 156, P > 0.3). Nine individuals were 1971 and 1972. Our objective was to search for trends in the younger than the earliest age of first pregnancy (3 years; see survival rates through time, rather than survival rates in spe- below) and were excluded from further analyses. The age cific years, and the advantages gained from the increase in distribution of breeding-age females is presented in Fig. 1 sample sizes resulting from combining samples from the together with the mean age structure derived from the popu- 2 years offset any increase in the temporal precision of the lation model. The most common age class was 4 years estimates obtained by carrying out simulations for each year (15%) but a large proportion of animals were ≥10 years of separately. age (42%), with secondary peaks in frequency evident at The initial conditions for the simulation assumed that the 14 years and, to a lesser extent, 8 years of age. The model observed age structure was stable, but this was not an as- was able to simulate these features of the observed age sumption of the simulations. The initial mean annual sur- structure.

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Table 1. Observed and modelled age structures of female Australian fur seals (Arctocephalus pusillus doriferus) from Seal Rocks, 1971–1972, and calculated recruitment and adult survival rates. Frequency (%) Age (years) Observed Modelled Year Recruitment rate Adult survival rate 39.5210.01±1.87 1970–1971 0.159±0.034 0.630±0.137 4 15.65 15.41±1.75 1969–1970 0.158±0.033 0.630±0.130 5 8.84 9.13±1.51 1968–1969 0.106±0.026 0.420±0.105 6 5.44 6.87±1.21 1967–1968 0.106±0.024 0.423±0.093 7 4.08 5.80±1.01 1966–1967 0.123±0.031 0.491±0.120 8 6.80 6.97±1.22 1965–1966 0.110±0.036 0.435±0.140 9 5.44 5.68±1.0 1964–1965 0.082±0.029 0.322±0.114 10 2.72 4.16±1.0 1963–1964 0.079±0.027 0.312±0.105 11 3.40 3.66±1.04 1962–1963 0.064±0.022 0.251±0.084 12 5.44 4.88±1.14 1961–1962 0.143±0.037 0.567±0.146 13 5.44 4.61±1.24 1960–1961 0.082±0.028 0.317±0.109 14 7.48 5.88±1.14 1959–1960 0.146±0.037 0.576±0.150 15 3.40 3.01±0.75 1958–1959 0.128±0.037 0.507±0.149 16 6.80 4.85±1.13 1957–1958 0.170±0.040 0.674±0.155 17 3.40 2.85±0.69 1956–1957 0.146±0.039 0.578±0.152 18 4.08 2.76±0.70 1955–1956 0.133±0.045 0.526±0.180 19 1.36 1.79±0.45 1954–1955 0.117±0.048 0.464±0.191 20 0.68 1.68±0.41 1953–1954 0.121±0.048 0.479±0.189 Note: Values are presented as the mean ± SE. The years involved in each estimate are given as split years because the samples from 1971 to 1972 were combined, so the estimated recruitment and survival rates will be mean values for the split years.

Fig. 1. Observed (shaded bars) and modelled (᭹) age distribu- Fig. 2. Age-specific pregnancy rates for Australian fur seals from tions of breeding-age female Australian fur seals (Arctocephalus Seal Rocks, 1971–1972. To reduce variability, sample sizes were pusillus doriferus) from Seal Rocks, 1971–1972. increased by grouping animals into 2-year age classes (regression equation: y = –0.53x2 + 8.65x + 53.93; r2 = 0.90).

Mean ± SE and maximum observed ages were 9.37 ± 0.41 and 20 years (n = 1), respectively. The calculated annual rates of adult female survival and recruitment between 1954 from 78% at 3 years to an average of 85% between 4 and and 1971 (Table 1) were 0.478 ± 0.029 (mean ± SE) and 13 years of age before decreasing in older females, this rela- 0.121 ± 0.007, respectively. tionship being best described by a second-order polynomial (Fig. 2). The probability that a female was pregnant de- Pregnancy rates creased from 86 ± 7% in early gestation (May–April, n = Pregnancy status was determined in a total of 110 fe- 28) to 55 ± 9% in late gestation (September–October, n = males. The youngest and oldest pregnant females were 3 and 28). Stepwise logistic regression analyses also indicated that 19 years of age, respectively, the overall pregnancy rate in there was no significant effect of body mass or BCI (or age breeding-age females being 78%. Stepwise logistic regres- or STDL) on the probability of a female being pregnant sion analysis using date, body mass, STDL, BCI, and age as when the analysis was carried out just within early and late continuous variables and pregnancy as the binomial response gestation (P > 0.06 in all cases) or within lactating and showed significant negative and positive relationships for nonlactating females (P > 0.1 in all cases). However, the date and age (P < 0.001 in both cases) and STDL (P < 0.02), proportions of seals that were pregnant and lactating and respectively. The pregnancy rate varied with age, increasing seals not pregnant and nonlactating were both higher than

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Table 2. Chi-square contingency table with observed and ex- declining at a rate of about 8% per annum. These results pected (in parentheses) frequencies of adult female Australian fur suggest that both adult survival and recruitment were gener- seals from Seal Rocks, 1971–1972 (n = 107). ally well below the level required to sustain the population during the 1950s and 1960s and that there was a particular Lactating Nonlactating dip during the early–mid 1960s. Pregnant 60 (54) 23 (29) Following a range-wide aerial census of pup production in Nonpregnant 10 (16) 14 (8) 1986 (14 years after the present study), Warneke (1988) con- Note: χ 2 = 7.72, df = 1, P < 0.01. cluded that there had been no measurable increase in the Australian fur seal population since a census carried out in 1945, which is consistent with the results of the present χ2 χ2 expected ( test, = 7.72, df = 1, P < 0.01; Table 2), sug- study. Results of mark–recapture estimates, however, indi- gesting that females were reproductively either “very good” cate that annual pup production at the study colony has in- or “very poor”. In addition, the results suggest that the ener- creased substantially since the present sample was obtained getic cost of lactation did not affect pregnancy rates. (from 2100–2200 in 1966–1974 to ca. 4024 in 1997). Be- A total of 70 individuals were recorded as lactating when tween 1968 and 1991, pup production increased 2.4% per sampled during the gestation period. There was no relation- annum (Shaughnessy et al. 1995) and then 6.1% per annum ship between sampling date and the probability that a female until 1997, when the most recent census was conducted was lactating (logistic regression, χ2 = 0.41, df = 1, P > 0.5). χ2 (Shaughnessy et al. 2000). Pup production has also been in- A significant positive relationship (logistic regression, = creasing at several other large colonies and total production 14.72, df = 1, P < 0.0001), however, was found between the for the population is estimated to have doubled since the probability that a female was lactating and her BCI. Lac- present study (Arnould and Littnan 2000; Littnan and tating animals had a higher BCI than nonlactating ones Arnould 2002; Shaughnessy et al. 2002). These observations within both the pregnant (t79 = 4.87, P < 0.0001) and suggest increases in fecundity or adult survival, or a combi- nonpregnant groups of females (t22 = 2.35, P < 0.03). Fur- nation of these, since the present sample was obtained. thermore, foetal BCI (derived from residuals of the sex- specific foetal STDL and body mass relationship, n = 65) Changes in prey availability could theoretically be respon- did not differ significantly between lactating and nonlacta- sible for the calculated rates of population decline during the 1960s and the observed increases since the present study. ting females (t21 = 0.165, P > 0.33), indicating that the nutritional burden of lactation did not affect gestational per- There is little evidence, however, for major shifts in the ma- formance in those seals that were pregnant. Maternal age, rine productivity in Bass Strait and surrounding waters over body mass, and BCI had no effect on foetal sex (stepwise lo- the last century (Klaer 2001; N.L. Klaer, unpublished data). gistic regression, P > 0.2 in all cases). Foetal BCI was also Records from steam trawlers in southeastern Australia dur- not correlated with maternal age, length, body mass, or BCI ing 1915–1961 indicate decreases in total fish catches, but (P > 0.1 in all cases). these appear to be more likely due to overfishing than to environmental fluctuations (Klaer 2001; N.L. Klaer, unpublished data). Competition with commercial fisheries, Discussion therefore, could have had an impact on the Australian fur Female survivorship seal population. However, while Australian fur seals are The mean age (9.4 years) and modal age (4 years) ob- known to consume some commercial target species (Gales served in the present study are similar to those reported for and Pemberton 1994; Goldsworthy et al. 2003), the degree other fur seal and sea lion species (Boyd et al. 1990; Rosas of competition with fisheries is difficult to assess because of et al. 1993; Butterworth et al. 1995; Wickens and York a lack of detailed information regarding the level of tempo- 1997). The annual survival rates estimated using the popula- ral and spatial overlap between their foraging areas and the tion model fitted to the age structure, however, are lower activities of the fishing fleet. than those reported for most fur seal species (Wickens and An alternative explanation for the age structure observed York 1997). in the present sample and the subsequent population growth The results of the modelled age structure suggest that age is that through the 1960s there was a relatively high level classes 5–11 years had previously experienced survival rates of harvest of this population, which has since subsided. considerably lower than those experienced by the older age Between 1923 and 1983, fishers in Victoria could legally classes. The reasons for this are not known but the results shoot “nuisance seals” interfering with fishing operations suggest either that the sample was biased toward older age (Warneke 1966; R.M. Warneke, unpublished data) and anec- classes or that this population experienced a change in con- dotal evidence suggests that this was common practice, with ditions during the decade before this sample was obtained. If at least 8% (17% where the cause of death was known) of the adult age structure in the sample was unbiased, then the tagged individuals retrieved showing signs of having died estimated recruitment and survival rates suggest that, at the from gunshot wounds (Warneke 1975). Furthermore, mortal- time of sampling, this population was experiencing a rapid ity due to operational interactions with fisheries (e.g., decline. Based on the mean estimated recruitment and sur- drowning in nets and lobster pots and entanglement in man- vival rates between 1954 and 1971, the population growth made debris) at the time the present sample was collected rate was 0.763 (i.e., the population was declining at a rate of accounted for an additional 23% (49% where the cause of about 24% per annum). Using the estimated adult female death was known) of tag retrievals. survival rate and the recruitment rate in 1971, the rate of The attitudes and practices of fishers, their perception of population growth would be 0.924 and the population was seals as competitors, and the size of the fishing fleet have

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Arnould et al. 1433

Table 3. Relationship between the adult survival rate foetuses are observed around Australian fur seal natal colo- and the rate of population increase derived from nies in September (personal observation), which coincides model predictions based on the age structure ob- with the onset of the third (and most nutritionally expensive) served in the present study and a constant rate of trimester (Widdowson 1981; Bronson and Manning 1991). recruitment (0.159). Similar observations of abortions and declining pregnancy Annual rate of population rates during gestation have been reported for Steller sea Adult survival rate increase lions (Eumetopias jubatus) and Cape fur seals (Guinet et al. 1998; Pitcher et al. 1998). In view of this decline in preg- 0.63 0.925 nancy rates, a potential bias in the present study could result 0.65 0.942 from no samples having been collected in the month prior to 0.69 0.977 the breeding season (November). However, as most females 0.73 1.012 wean their pup during October and are able to forage exten- 0.77 1.048 sively thereafter (Cane 19993; Arnould and Hindell 2001), 0.81 1.084 the further incidence of abortion due to nutritional stress 0.85 1.119 during this period is likely to have been low. Conversely, as females who abort may continue to suckle their pup through changed over the last 20 years (Kailola et al. 1993; Hickman to a second year (Arnould and Hindell 2001; Hume et al. 19992; Hume 2000; Norman 2000) and this is likely to have 2001), and therefore may be more likely to be ashore during substantially reduced the non-natural mortality of Australian October, the observed pregnancy rate in late gestation could fur seals and contributed to the population growth. Indeed, be negatively biased. using the observed age structure and recruitment rates from Whereas Boyd (1991) suggested that implantation is the the early 1970s and varying the adult survival rate in the point where nutritional factors have their greatest influence model predictions indicate that a 20% increase in adult sur- on pinniped reproduction, Pitcher et al. (1998) postulated vival would result in a 12% per annum increase in popula- that otariid species with extended lactation may abandon tion (Table 3). Furthermore, as there is likely to be a pregnancy later in gestation when the energetic costs in- positive correlation between adult and juvenile survival, the crease and future reproductive success can be better as- real change in adult survival required to account for the pop- sessed. Indeed, the rate of abortion in Steller sea lions and ulation increase is likely to be considerably smaller. A rate Cape fur seals was found to be negatively related to body of increase in the population of between 1.2% and 4.8% condition, suggesting a need for adequate lipid stores to would be sufficient to account for the observed change in maintain pregnancy (Guinet et al. 1998; Pitcher et al. 1998). population size between the present study and 1997. If the In the present study, however, the pregnancy rate was not re- estimated mortality rate due to shooting and (or) operational lated to BCI at any stage of gestation. interaction with fisheries is considered to be a minimum (be- The overall pregnancy rate (78%) in Australian fur seals is cause of under-reporting by fishers and low recovery of the same as that reported in Cape fur seals (78%–79%; tags), the relaxation of this source of mortality could account Butterworth et al. 1995; Guinet et al. 1998) and within the for the recent history of the population. range found in other otariid species (Wickens and York 1997). It is also consistent with reports of some female Aus- Pregnancy rates tralian fur seals not producing a pup every year and suckling Age at first pregnancy (3 years) was the same as that re- offspring for a second or even third year (Hume et al. 2001). ported for Cape fur seals (Butterworth et al. 1995) and simi- Recent studies (Coulson et al. 2000, 2001) have shown that lar to that in other otariids (Wickens and York 1997). The density-dependent effects on large mammals tend to lower pregnancy rate at the age at first pregnancy in Cape fur seals fecundity rates before influencing adult survival. The com- (37%), however, was less than half that in Australian fur paratively normal pregnancy rates observed in the present seals (78%), with comparable rates not being reached until study, therefore, support the notion that the apparently low females were 2–3 years older. In the present study, maximal survival rates were due to a density-independent process pregnancy rates were observed at 4–13 years of age before (e.g., shooting, drowning in nets) rather than to any effect of decreasing significantly in older females, which suggests the the food supply. Comparisons between species, however, existence of reproductive senescence in these animals. Simi- must be interpreted with caution, as sampling times in rela- lar declines in the reproductive performance of older females tion to stage of gestation differed markedly between studies. have been documented in South American (Arctocephalus In addition, the present study encompassed only 2 years, australis), Cape, Antarctic (Arctocephalus gazella), and whereas longer term studies have documented significant northern (Callorhinus ursinus) fur seals (Trites 1991; Boyd interannual differences in pregnancy rate due to environmen- et al. 1995; Butterworth et al. 1995; Lima and Paez 1995). tal variability (Boyd et al. 1995; Lima and Paez 1995; The decline in the proportion of females that were preg- Guinet et al. 1998; Pitcher et al. 1998). nant throughout the course of gestation suggested that some In the present study, there was no difference in pregnancy foetuses were aborted as pregnancy progressed, potentially rate or foetal BCI between lactating and nonlactating fe- in response to nutritional stress. Indeed, numerous aborted males, suggesting that lactation did not impinge on gesta-

2 L.J. Hickman. 1999. Effects of fur seals on fishing operations along the New South Wales south coast. B.Sc.(Hons.) thesis, University of New South Wales, Sydney, N.S.W., Australia. 3 K. Cane. 1999. Aspects of the behaviour of male Australian fur seals Arctocephalus pusillus doriferus during the breeding season. B.Sc.(Hons.) thesis, University of Melbourne, Melbourne, Victoria, Australia.

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tional performance. In contrast, Pitcher et al. (1998) found Acknowledgments that lactation had a negative impact on pregnancy rates in Steller sea lions, especially in younger animals, and Lima The assistance of the many fieldworkers in collecting the and Paez (1995) found foetal mass to be significantly lower data is gratefully acknowledged. The teeth were sectioned in lactating than in nonlactating South American fur seals. In by Barbara Baxter (Arthur Rylah Institute for Environmental the present study, there was also a positive relationship be- Research, Heidelberg). The help of Mark Darragh and Joan tween BCI and the probability that a female was lactating, as Dixon (Museum Victoria) in maintaining the database and has been observed in Cape fur seals and Steller sea lions providing access to the teeth for aging is greatly appreciated. (Guinet et al. 1998; Pitcher et al. 1998). This is not surpris- The collection of seals for this study was part of a wider ing, as most of the milk delivered to pups is produced on project on the biology of the Australian fur seal conducted land from stored body reserves (Arnould and Boyd 1995), so by R.M. Warneke (Fisheries and Wildlife Department, Vic- lactating females might be expected a priori to have larger toria) and supported by grants from the M.A. Ingram Trust, adipose stores than nonlactating ones, as a result of milk- Victoria. production patterns rather than superior foraging abilities in lactating females. Consequently, the differences in BCI be- References tween lactating and nonlactating females are likely to have been the consequence rather than the cause of lactation. Alverson, D.L. 1992. A review of commercial fisheries and the Steller sea lion (Eumetopias jubatus) — the conflict arena. Rev. Compared with the conspecific Cape fur seal population, Aquat. Sci. 6: 203–256. which inhabits the nutrient-rich productive waters of the Arnbom, T.A., Lunn, N.J., Boyd, I.L., and Barton, T. 1992. Aging Benguela Current and has experienced a rapid increase live antarctic fur seals and southern elephant seals. Mar. Mamm. (Warneke and Shaughnessy 1985; Butterworth et al. 1995), Sci. 8: 37–43. the Australian fur seal population has experienced compara- Arnould, J.P.Y., and Boyd, I.L. 1995. Temporal patterns of milk tively slow growth since the end of commercial harvesting production in Antarctic fur seals (Arctocephalus gazella). J. (Warneke and Shaughnessy 1985; Warneke 1988). Warneke Zool. (Lond.), 237: 1–12. and Shaughnessy (1985) proposed that the low marine pro- Arnould, J.P.Y., and Croxall, J.P. 1995. Trends in entanglement of ductivity of Bass Strait might be limiting the rate of recov- Antarctic fur seals (Arctocephalus gazella) in man-made debris ery of the Australian fur seal population through effects on at South Georgia. Mar. Pollut. Bull. 30: 707–713. female fecundity. Contrary to what might be expected if this Arnould, J.P.Y., and Hindell, M.A. 2001. Dive behaviour, foraging was the case (Caughley 1980; Fowler 1990), however, the locations and maternal-attendance patterns of Australian fur age at first pregnancy and overall pregnancy rates in the seals (Arctocephalus pusillus doriferus). Can. J. Zool. 79: 35– present study were comparable to those found in Cape fur 48. seals. Indeed, the proportion of 3-year-old female Australian Arnould, J.P.Y., and Littnan, C.L. 2000. Pup production and breed- fur seals that were pregnant was double that of Cape fur ing areas of Australian fur seals (Arctocephalus pusillus seals. Furthermore, the apparent lack of influence of body doriferus) at Kanowna Island and The Skerries in northeastern condition and lactation on pregnancy rates suggests that nu- Bass Strait. Aust. Mamm. 22: 51–55. Arnould, J.P.Y., and Warneke, R.M. 2002. Growth and condition in tritional resources were not limiting for Australian fur seals Australian fur seals (Arctocephalus pusillus doriferus) (Carni- at the time of the present study. However, if the population vora: Pinnipedia). Aust. J. Zool. 50: 53–66. was experiencing a substantial level of harvesting (as sug- Balmelli, M., and Wickens, P.A. 1994. Estimates of daily ration for gested above), it is possible that any potential effects of the the South-African (Cape) fur seal. S. Afr. J. Mar. Sci. 14: 151– nutrient-poor nature of Bass Strait on fecundity may have 157. been masked by a reduction in density-dependent effects. In- Bonner, W.N. 1985. Impact of fur seals on the terrestrial environ- deed, Arnould and Warneke (2002) found that the body con- ment at South Georgia. In Antarctic nutrient cycles and food dition of Australian fur seal females decreased between the webs. Springer-Verlag, Berlin. pp. 641–646. present sample and the late 1990s and suggested that this Bonner, W.N. 1994. Seals and sea lions of the world. Blandford, may be indicative of increased competition for resources as London. the population has recovered. It will be of interest to monitor Boyd, I.L. 1991. Environmental and physiological factors control- changes in pregnancy rates of Australian fur seals as the ling the reproductive cycles of pinnipeds. Can. J. Zool. 69: population continues to grow and approach historical levels. 1135–1148. In summary, the model predictions based on the age struc- Boyd, I.L., and McCann, T.S. 1989. Pre-natal investment in repro- ture of Australian fur seals at Seal Rocks in 1971–1972 sug- duction by female Antarctic fur seals. Behav. Ecol. Sociobiol. gest that survivorship was sufficiently low for the population 24: 377–385. Boyd, I.L., Lunn, N.J., Rothery, P., and Croxall, J.P. 1990. Age dis- to be experiencing a decline. However, the relatively high tribution of breeding female Antarctic fur seals in relation to pregnancy rate, especially in younger females, and the ap- changes in population growth rate. Can. J. Zool. 68: 2209–2213. parent lack of any effect of body mass or condition on preg- Boyd, I.L., Croxall, J.P., Lunn, N.J., and Reid, K. 1995. Population nancy suggest that food was not limiting and that the low demography of Antarctic fur seals: costs of reproduction and survivorship was due to density-independent effects. Mortal- implications for life-histories. J. Anim. Ecol. 64: 505–519. ity resulting from interactions with fishers is known to have Bronson, F.H., and Manning, J.M. 1991. The energetic regulation been common at this time and could account for the low of ovulation; a realistic role for body fat. Biol. Reprod. 44: 945– survivorship. The recent increase in the population is consis- 950. tent with anecdotal evidence that fatal interactions with fish- Brown, D., and Rothery, P. 1993. Models in biology: mathematics, ers have decreased as fishing practices have changed. statistics and computing. John Wiley and Sons, Chichester, U.K.

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