When and why do smallmouth bass abandon their broods? The effects of brood and parental characteristics

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
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-
                                                                       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: gsteinhart@lssu.edu)
*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

    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
                                                                 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.

age and then the fish was released. This procedure
                                                           Predictive modelling
was performed as quickly as possible (typically

    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

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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

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                                         (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.

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-
                                                                        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 (

    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
    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.

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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