When and why do smallmouth bass abandon their broods? The effects of brood and parental characteristics
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Fisheries Management and Ecology Fisheries Management and Ecology, 2011, 18, 1–11 When and why do smallmouth bass abandon their broods? The effects of brood and parental characteristics G. B. STEINHART & B. D. LUNN* School of Biological Sciences, Lake Superior State University, Sault Sainte Marie, MI, USA Abstract Variation in brood abandonment was explored by conducting partial brood removals from small- mouth bass, Micropterus dolomieu Lacepède, nests in two north temperate lakes. In both lakes, percent of the brood removed had no eﬀect on nest failure rates. Nest failure prior to oﬀspring swim-up was more common, but unrelated to brood size after removal, in the lake with higher post-spawning mortality and lower growth and fecundity. Brood size after removal was negatively related to nest failure in the lake with high survival, growth and fecundity. Nests guarded by young males failed more frequently than those of old males, and young broods failed more frequently than old broods. Dynamic programming and logistic regression models developed to predict nest fate worked better for the lake with selective pressures that theoretically favoured abandonment (e.g. high post-spawning mortality). Both models identiﬁed male age and brood age as important factors in predicting nest fates. Because nest success is related to the age of the parent, this could have consequences for overall nest success for populations with diﬀerent demographics. KEYWORDS: brood abandonment, brood predation, Micropterus dolomieu, nest success, parental care. dity, as well as juvenile survival and growth (Clutton- Introduction Brock 1991; Stearns 1992; Hutchings 1993). For Parental care can be energetically costly for a parent species that care for their oﬀspring, current brood size but is required for many species or the offspring will is an important factor determining the amount of care perish. Providing care can reduce parental survival, provided (Armstrong & Robertson 1988). growth and breeding interval, thus reducing future There is considerable variation in the amount of breeding attempts and their expected future ﬁtness parental care provided among different species. Brood (Sabat 1994; Balshine-Earn 1995; Székely & Cuthill abandonment following changes to the current brood 2000). Therefore, species that provide parental care varies. The most common pattern in birds has been an face a trade-oﬀ between current and future ﬁtness increase in brood abandonment with a reduction in (Williams 1966; Trivers 1972). If the beneﬁts to future clutch size (Armstrong & Robertson 1988; Székely & ﬁtness by abandoning the current brood exceed the Cuthill 2000), but there are exceptions. Nests para- expected return of continuing to provide care, aban- sitised (i.e. loss of at least some of the original brood) donment would be the optimal behaviour. Although by brown-headed cowbirds, Molothrus ater Boddaert, individuals might not be continuously assessing the have been reported to have both higher abandonment costs and beneﬁts of guarding or abandoning their rates (Clotfelter & Yasukawa 1999) and little change in brood, natural selection should favour those that abandonment (Whitehead et al. 2000). Eurasian kes- choose the behaviour that increases lifetime ﬁtness. trel, Falco tinnunculus L., parental effort has been In this theoretical context, reproductive eﬀort, includ- reported to remain relatively constant across manipu- ing providing care, should be predictable and probably lated brood sizes (Tolonen & Korpimäki 1996) and to depends on factors such as adult survival and fecun- be positively related to brood size (Dijkstra et al. Correspondence: Geoﬀrey B. Steinhart, School of Biological Sciences, Lake Superior State University, 650 W. Easterday Avenue, Sault Sainte Marie, MI 49783, USA (e-mail: email@example.com) *Present address: Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada T6G 2E9. 2010 Blackwell Publishing Ltd. doi: 10.1111/j.1365-2400.2010.00758.x 1
2 G. B. STEINHART & B. D. LUNN 1990). In addition, red-backed salamanders, Plethodon Canada. Lake Opeongo (58.6 km2) contains various cinereus Green, also tend to abandon small broods ﬁshes, including yellow perch, Perca ﬂavescens more than large broods (Yurewicz & Wilbur 2004). (Mitchill), pumpkinseed, Lepomis gibbosus (L.), lake Fishes also demonstrate increased abandonment or trout, Salvelinus namayacush (Walbaum), several cor- ﬁlial cannibalism of small broods (Petersen 1990; Suski egonids and many cyprinids (Martin & Fry 1973). et al. 2003; Hanson et al. 2007). Finally, cuckoldry Provoking Lake is only 11 km2 and supports only (extra-pair fertilisations) often result in cannibalism or smallmouth bass, splake, S. namaycush · Salvelinus abandonment in ﬁshes and birds (Mauck et al. 1999; fontinalis (Mitchill), and yellow perch. Both lakes have Neﬀ 2003). populations of smallmouth bass that were introduced Although one might think parental care is predict- in the early 1900s. The smallmouth bass populations able, it is apparent that there is considerable vari- are quite different, however, with the Provoking Lake ability that may be caused by environmental or population characterised by higher densities, slower demographic differences among populations. The growth rates, earlier maturation and higher post- goal of this research was to assess variability in spawning mortality than smallmouth bass in Lake parental care in a nest-guarding ﬁsh, the smallmouth Opeongo (Dunlop et al. 2005). bass, Micropterus dolomieu Lacepède, in lakes with Snorkel surveys were conducted during 31 May to different selective pressures. Male smallmouth bass 12 June 2007 in Opeongo and 3 June to 29 June 2008 in provide sole parental care for their offspring, some- Opeongo and Provoking to locate smallmouth bass times for more than 1 month (Ridgway 1988). As nests and monitor their success following experimental with other organisms, this care is costly, resulting in brood removals. Different stretches of shoreline were increased mortality (Ridgway 1986; Dunlop et al. sampled each year in Lake Opeongo to avoid any 2005) and a loss of energetic content (Gillooly & resampling or cumulative effects of the brood remo- Baylis 1999; Mackereth et al. 1999; Steinhart et al. vals. Nests were marked with numbered rocks to 2005b), the latter of which may reduce the number of ensure proper identiﬁcation on subsequent visits that eggs a male receives in the future (Wiegmann et al. occurred typically every 2 days (range 1–4 days). Male 1992; Mackereth et al. 1999). Angling of nest-guard- presence or absence and offspring developmental stage ing males can substantially increase brood abandon- were recorded on each visit. Developmental stages ment in some systems (Suski et al. 2003; Hanson were deﬁned as unhatched embryos (eggs), hatched et al. 2007), but in other lakes the eﬀects are minor embryos (clear fry or pigmented fry), larvae (swim-up (Steinhart et al. 2005a). fry) or juveniles (green fry still associated with a nest The speciﬁc objectives of this study were to: (1) and guarding male). Nests containing free-swimming assess if experimentally reduced broods were more larvae were deemed successful while nests that did not likely to fail than unmanipulated broods; (2) explore reach the larval stage were considered failures. Because how male age, and brood age and size affected nest angling for smallmouth bass was not allowed during failures; and (3) evaluate two modelling techniques for the survey period and there are few predators of adult predicting nest abandonment. From parental care smallmouth bass in the lakes, nest failures were theory, it was hypothesised that nest failure (i.e. considered abandoned nests, although unobserved abandonment) would increase as the percent brood sources of adult or offspring mortality could have led removed increased and as male age, brood size and to some nest failures. brood age decreased. If brood abandonment is pre- Brood-removal treatments were systematically as- dictable, then it may be possible to forecast the signed to nests starting with 0% brood removal and potential effects of perturbations, such as angling, that continuing to 25%, 50%, or 75% brood removal. affect parental behaviour and even predict resulting However, because treatment assignments varied in impacts on offspring production or recruitment suc- space (i.e. where nests were found or treated on a cess. given day) and time (i.e. the day nests were found or treated), the treatment assignments were essentially random. Some newly discovered nests had treatment Methods assignments reserved for a later date to allow for manipulation of older broods. For all treatments, Field surveys nest-guarding smallmouth bass were removed from Smallmouth bass nests were located via snorkelling their nests via angling with a single-hook jig. Total surveys in known spawning areas in Lakes Opeongo length (TL, mm) and wet weight (nearest 5 g) were and Provoking, Algonquin Provincial Park, Ontario, measured, scale samples were collected to estimate 2010 Blackwell Publishing Ltd.
VARIABILITY IN SMALLMOUTH BASS PARENTAL CARE 3 age and then the ﬁsh was released. This procedure Predictive modelling was performed as quickly as possible (typically
4 G. B. STEINHART & B. D. LUNN Table 1. Age-dependent parameter values for male smallmouth bass most parsimonious model(s), those with the best included in the stochastic dynamic programming model. Smallmouth combination of the best ﬁt and the fewest parameters. bass in Lakes Opeongo and Provoking had diﬀerent total length at Models were ranked based on the model likelihoods. age (TL, in mm), initial brood size (B), adult annual survival rate (ASR) and cost of parental care (DASR; daily reduction in ASR The ratio of likelihoods, or evidence ratio, shows how when guarding). See the Methods for explanations of parameters much more likely one model is compared with another. values Normalised Akaike model weights, often treated as the probability of a model being the best-supported model Lake Opeongo Provoking Lake among all candidates, were calculated. Individual Age TL B ASR DASR TL B ASR DASR variables were ranked by summing all Akaike weights for models containing that particular variable 4 259 940 0.7 0.025 255 927 0.7 0.038 (Burnham & Anderson 2002). 5 285 1474 0.6 0.015 284 1175 0.6 0.028 6 323 2256 0.5 0.008 306 1360 0.5 0.021 7 355 2914 0.45 0.0015 322 1498 0.45 0.015 Results 8 382 3469 0.4 0.001 334 1602 0.4 0.014 9 406 3963 0.4 0.001 343 1679 0.4 0.014 10 428 4415 0.4 0.001 350 1736 0.4 0.014 Field surveys 11 448 4827 0.3 0.001 355 1779 0.3 0.014 A total of 138 nests, 105 in Lake Opeongo and 33 in 12 466 5197 0.2 0.001 359 1812 0.2 0.014 Provoking Lake, were monitored until they were 13 482 5526 0.1 0.001 362 1836 0.1 0.014 14 497 5835 0.05 0.001 365 1863 0.05 0.014 deemed successful or failures (Table 2). In general, 15 512 6143 0.01 0.001 368 1888 0.01 0.014 guarding male smallmouth bass were older, larger and 16+ 512 6410 0.01 0.001 370 1905 0.01 0.014 had larger broods in Lake Opeongo than in Provoking Lake. However, within each lake male age, brood age at treatment or estimated brood size before treatment same as Lake Opeongo. Because providing care is did not diﬀer among brood-removal treatments energetically costly, annual survival rates and lost (Table 2). growth potential were modiﬁed based on the duration Nest failure rates generally were lower in Lake of parental care. Annual survival for nesting vs non- Opeongo (22 of 105 nests, 21% failed; Fig. 1) than in nesting males is known to decline at diﬀerent rates in Provoking Lake (13 of 33 nests, 39% failed). Neither each lake, so daily declines in annual survival for nest- year (WaldÕs statistic = 2.68, P = 0.10), treatment guarding males were higher in Provoking Lake than level (WaldÕs statistic = 0.86, P = 0.35) nor the Lake Opeongo and were based on observed post- model with treatment and year (Likelihood ratio nesting mortality rates (Table 1; Dunlop et al. 2005). v2 = 3.63, P = 0.16) affected nest failure rate in Lake Change in length was estimated in Lake Opeongo Opeongo. In Provoking Lake, nest failure rate was not ()0.5 mm day)1 of care; Steinhart et al. 2008) and affected by treatment (Likelihood ratio v2 = 0.08, assumed similar for Provoking because similar preda- P = 0.77). Although the brood-removal treatment tor burdens are likely to lead to similar energetic costs had no effect on nest fate, brood size after treatment of care (Steinhart et al. 2005b). In summary, model was signiﬁcantly lower for failed nests (1554 ± 262 parameters were assumed similar in the two lakes offspring; mean ± SE) than successful nests except for change in annual survival from providing (2150 ± 229) in Opeongo (t = 1.71, d.f. = 57, care, length at age and initial brood size. Full details P = 0.046; Fig. 2a). In Provoking, however, there on construction and exploration of the DP model are was no diﬀerence in brood size after treatment between available in Steinhart et al. (2008). successful (837 ± 118 oﬀspring) and failed For the logistic regression analysis, the a priori set of (663 ± 141) nests (t = 0.94, d.f. = 31, P = 0.18). candidate models included all possible models using Nest fate was related to male length, age and brood one or more of the following variables: male age, age in both lakes. In Lake Opeongo, failed nests were brood age, brood-removal treatment and brood size guarded by males that were on average 34-mm shorter after treatment to predict nest fate as a binary variable (t = 2.76, d.f. = 48, P = 0.004; Fig. 2b) and 1.3-year (i.e. success = 0 or failure = 1). Year was not younger (t = 3.66, d.f. = 66, P < 0.001; Fig. 2c) included as a variable in any model as year affects than males with successful broods. Failed nests were are likely driven by unpredictable weather. AkaikeÕs 1.9-day younger on the day of brood removal than age Information Criterion adjusted for small sample size of successful nests in Lake Opeongo (t = 4.37, (AICc; Burnham & Anderson 2002) was used to d.f. = 73, P < 0.001; Fig. 2d). Nests that failed in evaluate competing models. AICc scores identiﬁed the Provoking Lake also were guarded by smaller (274 vs 2010 Blackwell Publishing Ltd.
VARIABILITY IN SMALLMOUTH BASS PARENTAL CARE 5 Table 2. Mean (±standard error) age, total length, brood size and nest age at treatment of nests treated in Lake Opeongo (2007 and 2008) and Provoking Lake (2008) Brood-removal treatment Lake Variable 0% 25% 50% 75% All ANOVA Opeongo Sample size 25 27 26 27 105 Male age (years) 7.6 ± 0.4 7.6 ± 0.4 8.2 ± 0.5 7.7 ± 0.4 7.8 ± 0.2 F3,101 = 0.42 P = 0.74 Total length (mm) 362 ± 12 363 ± 13 375 ± 13 368 ± 13 367 ± 6 F3,101 = 0.22 P = 0.89 Brood size 3229 ± 218 3554 ± 693 3379 ± 650 2579 ± 443 3182 ± 269 F3,101 = 1.03 P = 0.38 Brood age (days) 3.7 ± 0.4 4.1 ± 0.6 4.3 ± 0.6 4.4 ± 0.6 4.1 ± 0.3 F3,101 = 0.31 P = 0.82 Provoking Sample size 8 8 8 9 33 Male age (years) 6.6 ± 0.4 6.8 ± 0.7 7.3 ± 0.8 7.0 ± 0.4 6.9 ± 0.3 F3,29 = 0.22 P = 0.88 Total length (mm) 282 ± 12 303 ± 20 299 ± 13 290 ± 8 294 ± 7 F3,29 = 0.45 P = 0.72 Brood size 1143 ± 101 1524 ± 272 1082 ± 246 1217 ± 243 1241 ± 112 F3,29 = 0.72 P = 0.55 Brood age (days) 4.1 ± 0.7 4.4 ± 0.7 4.1 ± 0.5 4.6 ± 0.7 4.3 ± 0.3 F3,29 < 0.001 P = 0.99 Predictive modelling The most parsimonious logistic regression model in both lakes included only male age and brood age at treatment (Table 3). In both lakes, the best-supported models were more than twice as likely to be the best models as the second-most parsimonious models. For Lake Opeongo, the model containing male age and brood age at treatment was a signiﬁcant predictor of nest failure (Likelihood ratio v2 = 16.42, P < 0.001). The second-best model in Lake Opeongo contained both brood age and brood remaining after treatment, and the third-best model contained only brood age. In Provoking Lake, the model containing brood age and male age was also the best model and a signiﬁcant predictor of nest fate (Likelihood ratio v2 = 12.22, P = 0.002); the second-best model contained only Figure 1. Percent nest failure for smallmouth bass nests after catch- brood age, and the third-best-supported model con- and-release angling and partial brood removal in Lake Opeongo in 2007 tained only male age. (black circles) and 2008 (white circles) and in Provoking Lake (grey Additional support for the importance of male age squares). See Table 2 for sample sizes. and brood age at treatment was seen after summing Akaike weights for each model containing a particular variable. Models containing brood age at treatment 306 mm; t = 2.48, d.f. = 31, P = 0.009; Fig. 2b) and had the greatest sum (0.96 for Opeongo and 0.79 for younger (6.1 vs 7.4 years; t = 2.32, d.f. = 31, Provoking), and models with male age had the second P = 0.01; Fig. 2c) males than successful nests. Failed highest (Opeongo = 0.65, Provoking 0.72). Models nests in Provoking Lake also contained younger containing brood remaining (Opeongo = 0.32, Pro- oﬀspring when brood removal occurred than success- voking 0.18) or percent of brood removed ful nests (3.5 vs 4.9 days; t = 2.46, d.f. = 31, (Opeongo = 0.20, Provoking 0.12) had much lower P = 0.01; Fig. 2d). summed Akaike weights. Male age and brood age had 2010 Blackwell Publishing Ltd.
6 G. B. STEINHART & B. D. LUNN (a) (b) (c) (d) Figure 2. Nest-guarding male and brood characteristics for successful (grey bars) and failed (white bars) nests in Lakes Opeongo and Provoking. All characteristics were diﬀerent (P < 0.05) between successful and failed nests except for brood size in Provoking Lake. Table 3. Logistic regression models for predicting smallmouth bass nest failure and their associated values for AkaikeÕs Information Criteria (corrected for small sample sizes, AICc), model likelihoods and normalised Akaike model weights. Models are shown in order of decreasing likelihood for Lake Opeongo Lake Opeongo Provoking Lake Model AICc Model likelihood Model weight AICc Model likelihood Model weight Brood age, male age 103.4 1.00 0.37 44.9 1.00 0.40 Brood age, brood remaining 105.0 0.45 0.17 48.7 0.15 0.06 Brood age 105.6 0.32 0.12 46.5 0.43 0.17 Brood age, male age, treatment 105.6 0.32 0.12 48.8 0.14 0.06 Brood age, brood remaining, male age 105.9 0.28 0.10 48.2 0.18 0.07 Brood age, treatment 108.4 0.08 0.03 50.7 0.05 0.02 Male age 108.6 0.07 0.03 46.9 0.37 0.15 Brood age, brood remaining, treatment 109.1 0.06 0.02 52.8 0.02 0.01 Brood age, brood remaining, male age, treatment 109.5 0.05 0.02 53.0 0.02 0.01 Male age, treatment 111.5 0.02 0.01 50.9 0.05 0.02 Brood remaining, male age 112.6 0.01 0.00 51.1 0.05 0.02 Brood remaining 114.0 0.00 0.00 51.7 0.03 0.01 Treatment 115.0 0.00 0.00 52.6 0.02 0.01 Brood remaining, male age, treatment 115.5 0.00 0.00 55.5 0.00 0.00 Brood remaining, treatment 118.0 0.00 0.00 55.9 0.00 0.00 negative coefﬁcients indicating that older males and broods and nests with a lower percent of offspring older broods were more likely to be successful than removed to be more successful. young males or young broods. Although the results Despite the relative statistical superiority of the best- suggest that the brood remaining after treatment and ﬁtting logistic models, the models had mixed results for percent of brood removed were not strong predictors predicting brood failure (Table 4). The most parsimo- of nest fate, the coefﬁcients suggested a trend for larger nious logistic model correctly predicted 75% of nest 2010 Blackwell Publishing Ltd.
VARIABILITY IN SMALLMOUTH BASS PARENTAL CARE 7 Table 4. Classiﬁcation matrix for the logistic regression models and logistic models. This supports the idea that parental dynamic programming (DP) models for actual smallmouth bass nest investment is tied to factors other than number of fates (failed or successful) and model predicted fates. Bold numbers offspring (Tolonen & Korpimäki 1996). Indeed, an indicate correct classiﬁcations analysis of 20 years of nesting data from Lake Ope- Opeongo Provoking ongo revealed that male body size, which was strongly related to male age, was an important predictor of nest Failed Successful Failed Successful success, especially later in the parental care period Logistic model when the energetic costs of care may lead small males Predicted failure 0 4 10 4 to abandon (Suski & Ridgway 2007). In addition, Predicted success 22 79 3 16 Steinhart et al. (2008) provided evidence from simula- DP model tion models that annual adult survival was the most Predicted failure 3 8 5 5 Predicted success 19 75 8 15 important factor aﬀecting brood abandonment of nesting smallmouth bass. Functionally, adult survival and male age may have a similar eﬀect on parental behaviour because they both relate to the expected fates in Lake Opeongo and 79% of fates in Provoking. number of future breeding attempts: old males or Predicting nest failures was problematic in Lake males with low annual survival have fewer expected Opeongo: no failed nests were classiﬁed as such. The future breeding attempts and, therefore, should be best-supported logistic model performed better in more likely to guard their current brood. A growing Provoking Lake, correctly predicting 71% of nest body of literature suggests that size-selective ﬁshing failures. The DP model correctly classiﬁed 74% of all mortality aﬀects many life-history and behavioural nest fates in Lake Opeongo, but only 14% of failed traits, sometimes in only a few generations (e.g. Olsen nests were predicted to be abandoned. For Provoking et al. 2004; Walsh et al. 2006). For ﬁsh that provide Lake, the DP model correctly classiﬁed 61% of the care when faced with high adult mortality (i.e. few nest fates and 38% of the nests that failed. breeding attempts), the most successful ﬁsh would likely be those that guard their broods even when the ﬁtness value of the oﬀspring is relatively low. Con- Discussion versely, ﬁsh that were prone to abandoning would be Brood size and percent brood reduction had little effect less likely to produce a successful brood during their on nest failure in this study. Speciﬁcally, percent of few reproductive attempts and their genotype would be brood removed did not signiﬁcantly affect nest failure less likely to persist. Alternatively, if high annual in either study lake, and brood size affected nest failure mortality reduces smallmouth bass density and in- only in Lake Opeongo but was not an important creases their growth rates, individuals may be able to variable in the logistic regressions for either lake. These allocate more time and energy to parental care, again results may have been inﬂuenced by the great variabil- resulting in an increased willingness to guard small ity in the number of eggs received by male smallmouth broods. bass. Multiple linear regressions using male length and Because annual survival, growth and cost of care spawning date to predict brood size had low coefﬁ- vary among systems (Dunlop et al. 2005; Steinhart cients of determination (
8 G. B. STEINHART & B. D. LUNN of brood size not being important in determining nest failure in Provoking, while brood age and male age were, supports that notion that population demo- graphics may be important to parental care behaviour. In systems where brood size is not an important factor in nest failure, brood predation should not lead to increased nest failures, as was demonstrated in Lake Erie (Steinhart et al. 2005a). It is unclear why both modelling techniques were better at predicting abandonment in Provoking Lake than in Lake Opeongo. One possibility is that the demographics in Provoking, which were characterised by slow growth, high post-spawning mortality and low fecundity, select for ﬁsh that have a better-deﬁned and higher brood-size abandonment threshold because providing care more strongly affects future ﬁtness via poor growth and survival in Provoking Lake. In the Figure 3. Change in nest failure rate following brood reduction, more benign Lake Opeongo, higher expected ﬁtness compared to control treatments, in four diﬀerent studies. All nest- guarding males were angled for both control and removal treatments. and lower consequences for providing care (i.e. costs Data from Opeongo (white bars) and Provoking (black bars) are from are ameliorated by better growth during the non- this study. Steinhart et al. (2005a) estimated brood reduction from nesting season) may allow males to be more ﬂexible in natural predation to be 25–50% of the brood size in Lake Erie, Ohio providing care. An alternative hypothesis is that some (grey bars; n = 131 controls and 65 removals). Suski et al. (2003) males may have abandoned in Lake Opeongo because manipulated broods in Charleston Lake, Ontario (stippled bars; n = 11 of storms that created waves and may have cause rapid controls and 10 removals). Hanson et al. (2007) studied Devil and temperature changes as a result of seiches (MacLean Wolfe Lakes, Ontario (cross-hatched bars; n = 12 controls and 12 removals). et al. 1981). Such storm events would likely be more common in larger Lake Opeongo than in Provoking and would not be predicted in the models. Finally, Other studies have examined the effect of brood several DP model parameter values were assumed, removals on smallmouth bass nest success with vari- especially for Provoking Lake ﬁsh, which may have led able conclusions (Fig. 3). In Lake Erie, Ohio, where to poor prediction of nest abandonment. The variables nest predators [i.e. round gobies, Neogobius melano- deemed most important to the DP model by Steinhart stomus (Pallas)] are extremely abundant, brood preda- et al. (2008) were adult annual survival and cost of tion during catch-and-release angling typically resulted providing care. For this study, it was assumed that the in a loss of 25–50% of the offspring in a nest (Steinhart base annual survival rates were identical in both lakes. et al. 2004a), but this predation resulted in no diﬀer- If poor growth rates, or some other factor, in Provok- ence in nest success from control nests (Steinhart et al. ing Lake led to lower annual survival than what was 2005a). Smallmouth bass in Lake Erie have high used in the DP simulation, it would lead to an growth rates compared with many other populations underestimation of brood abandonment (i.e. high (Doan 1940; Steinhart et al. 2004b), likely ameliorating adult survival in the model would favour nest aban- the cost of providing care (Steinhart et al. 2005b). donment). Despite this shortcoming, the results sug- Relatively high angling pressure should increase mor- gest that the model worked better in Provoking Lake tality and lead to a shorter expected life span in Lake than in Lake Opeongo, so the assumed base survival Erie than in lakes in this study and, possibly, a Ôgrow rates might not have been as important as the and reproduce quicklyÕ life history (Shuter et al. 2005). adjustments to annual survival based on duration of These factors should favour a guard strategy even at parental care which were based on known values small brood sizes. In limited experimental brood (Dunlop et al. 2005). Therefore, although not all manipulations (25%–75% of oﬀspring removed) in model parameters were explicitly measured in the ﬁeld, Lake Erie, 10 of 11 males continued to guard their the results still point towards a stronger eﬀect of brood broods after brood reduction, at least until a storm age, male age and adult annual survival (including the occurred (mean 6 days, range 0–19 days; Steinhart eﬀects of parental care on adult survival) on nest et al. 2005a). success than the eﬀects of brood size and brood By contrast, removing 50% of broods in Charleston reduction. Lake, Ontario, led to a 61% increase in abandonment 2010 Blackwell Publishing Ltd.
VARIABILITY IN SMALLMOUTH BASS PARENTAL CARE 9 compared with an angled control (Suski et al. 2003). In prone to abandonment and, therefore, might beneﬁt the Suski et al. (2003) study, manipulated nests were from more protective regulations. For example, estab- limited to average-sized broods guarded by average- lishing no-take zones or minimising disturbances may sized males (presumably these were not the youngest produce a greater increase in oﬀspring production in individuals to spawn). Because the current study systems where males are more likely to abandon (e.g. suggests that young males are more prone to aban- lakes with high mortality, low growth or fecundity, or donment, the brood removals in Charleston Lake may high parental care cost) than in systems where males have been biased towards males that were less likely to tend to guard. Therefore, ﬁsheries managers may be abandon, which means that across the whole popula- able to improve their ability to manage populations tion the increase in nest abandonment could have been when they can predict the eﬀects of angling on the nest higher. Furthermore, only nests older than 4 days were success based on relatively simple-to-collect demo- manipulated by Suski et al. (2003), again biasing the graphic parameters (e.g. annual survival, age struc- sample towards broods that, based on the results of the ture). While the model simulations did not do a good current study, may have been less likely to be aban- job in predicting abandonment, characteristics of the doned. Another manipulation study removed 90% of nest and the guarding male did vary among successful the brood from smallmouth bass nests in Devil and and failed nests. Future eﬀorts can reﬁne these models Wolfe Lakes, Ontario (Hanson et al. 2007). For the and consider other variables to improve the ability to Hanson et al. (2007) study, there was no male size- predict brood abandonment for smallmouth bass and selection and only young nests (
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