Partial migration: growth varies between resident and migratory fish
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Partial migration: growth varies between resident and migratory fish
Downloaded from http://rsbl.royalsocietypublishing.org/ on July 7, 2015 Marine biology rsbl.royalsocietypublishing.org Partial migration: growth varies between resident and migratory fish Bronwyn M. Gillanders1, Christopher Izzo1, Zoe¨ A. Doubleday1 and Qifeng Ye2 1 Research Cite this article: Gillanders BM, Izzo C, Doubleday ZA, Ye Q. 2015 Partial migration: growth varies between resident and migratory fish. Biol. Lett. 11: 20140850. http://dx.doi.org/10.1098/rsbl.2014.0850 Received: 16 October 2014 Accepted: 2 February 2015 Subject Areas: ecology Keywords: migration, residency, partial migration, fish, otolith chemistry, otolith growth Southern Seas Ecology Laboratories, School of Biological Sciences, University of Adelaide, Adelaide, South Australia 5005, Australia 2 South Australian Research Development Institute Aquatic Sciences, Adelaide, West Beach, South Australia 5024, Australia Partial migration occurs in many taxa and ecosystems and may confer survival benefits. Here, we use otolith chemistry data to determine whether fish from a large estuarine system were resident or migratory, and then examine whether contingents display differences in modelled growth based on changes in width of otolith growth increments. Sixty-three per cent of fish were resident based on Ba : Ca of otoliths, with the remainder categorized as migratory, with both contingents distributed across most age/size classes and both sexes, suggesting population-level bet hedging. Migrant fish were in slightly better condition than resident fish based on Fulton’s K condition index. Migration type (resident versus migratory) was 56 times more likely to explain variation in growth than a model just incorporating year- and age-related growth trends. While average growth only varied slightly between resident and migratory fish, year-to-year variation was significant. Such dynamism in growth rates likely drives persistence of both life-history types. The complex relationships in growth between contingents suggest that management of species exhibiting partial migration is challenging, especially in a world subject to a changing climate. 1. Introduction Author for correspondence: Bronwyn M. Gillanders e-mail: [email protected] One contribution to the special feature ‘Frontiers in marine movement ecology’ organized by Lee Fuiman, Benjamin Walther and Pablo Munguia. Electronic supplementary material is available at http://dx.doi.org/10.1098/rsbl.2014.0850 or via http://rsbl.royalsocietypublishing.org. Invited to commemorate 350 years of scientific publishing at the Royal Society. Migration is a powerful force in shaping the distribution and abundance of animals in space and time. It can range from daily vertical migrations of zooplankton and fish [1] to extensive annual migrations of Arctic terns from the high Arctic to the Southern Ocean [2]. Even within marine waters, vast oceanic journeys are undertaken by organisms, such as humpback whales [3] and green turtles [4], which can migrate thousands of kilometres. Although variation in migratory tendency occurs between species and between populations within a species, within population variation has been less well studied [5]. Populations may comprise both resident and migratory individuals, which is known as partial migration. Partial migration occurs in all major vertebrate groups [5] and some invertebrate taxa [1], as well as across all major ecosystems [6]. Bird migration has been most widely researched, and among fish taxa, salmonids and Atlantic cod are the predominant species investigated [7]. Partial migration may influence population dynamics and persistence [8], as it may confer survival benefits through reduced predation risk (e.g. [9]) and/or increased food availability [6]. Although these factors are frequently cited as the ultimate cause of movement, the proximate cause is debated. Effects of partial migration on demographic parameters such as growth have been investigated but usually only for a portion of the life history or as an integrated signature over an individual’s lifespan. Here, we first use otolith Ba : Ca profiles to categorize fish as either resident or migratory, a technique that has been previously validated (e.g. [10,11]). Next, we determine whether the two contingent types lead to differences in growth based on relative changes in widths of otolith growth increments. & 2015 The Author(s) Published by the Royal Society. All rights reserved. Downloaded from http://rsbl.royalsocietypublishing.org/ on July 7, 2015 4 2 rsbl.royalsocietypublishing.org Ba : Ca 3 2 1 0 50 100 150 distance along otolith 200 0 50 100 150 distance along otolith 200 Figure 1. Representative migrant and resident Ba : Ca (mmol mol21) profiles for co-occurring black bream individuals aged 5þ (LHS) and 10þ (RHS); solid line, resident; dashed line, migrant. The distance along the otolith has been standardized to a common value with zero representing the early life and more than 200 representing the collection time. The peaks in Ba : Ca suggest movement of fish. Table 1. Otolith samples examined and number of increments analysed to assess variation in growth. Seven fish were unable to be classified as migrant or resident. movement type no. fish age range total length range (mm) year of capture range no. increment measurements all fish migrant 173 63 5 – 32 5 – 17 283– 470 300– 470 2008– 2012 2008– 2012 1332 630 resident 104 5 – 32 283– 462 2008– 2012 659 2. Material and methods Black bream (Acanthopagrus butcheri) were captured from the Murray River estuary, which is the terminus of Australia’s largest river, the Murray – Darling. Fish were collected from 14 sites throughout the estuary between October 2008 and September 2013 (table 1). The salinity of each collection site was estimated from the WaterConnect website or measured directly while in the field. All fish were measured (total length, mm), weighed (body weight, g) and sexed (electronic supplementary material, table S1). Gonads were removed and weighed (gonad weight, g) and sagittal otoliths extracted, cleaned and stored. Fulton’s K condition factor was estimated by dividing body weight minus gonad weight by length3 and multiplying by a constant. Otoliths were prepared for elemental analysis and analysed using a laser ablation inductively coupled plasma-mass spectrometer (Resonetics). Sectioned otoliths were examined under a compound microscope (Leica DMLB), photographed and growth increment widths measured across the otolith. Thus, a temporally resolved proxy of somatic growth was obtained [12] (see the electronic supplementary material for more details on otolith preparation and elemental analysis, as well as growth analyses). A series of mixed effects models were used to investigate differences in annual growth among resident and migratory fish based on increment widths. A two-stage process was adopted where first the random effect structure was optimized, followed by the fixed effects structure (see the electronic supplementary material for more details on growth modelling). The relative support for each model was assessed using Akaike’s information criterion corrected for small sample sizes [13]. Analyses were performed in R [14]. 3. Results All locations comprised both resident and migrant fish where more than two fish were collected (with the exception of a single location) (figures 1 and 2a). In addition, residents and migrants were caught from freshwater to hypersaline waters (0.3–74 ppt), although the majority of fish were collected from marine salinities. Age at first migration ranged from 0 to 5þ, with the majority of fish (94%) moving before they were 2þ. Of the fish analysed, 62% were resident and 38% were migratory, with both sexes showing similar patterns. In addition, migrants and residents were found for most size and age classes, but migrant fish tended to be larger and older than resident fish (electronic supplementary material, figure S1). Condition of fish as estimated by Fulton’s K was marginally greater in migrant fish than in resident fish, but was not significantly different (electronic supplementary material, table S2). Inclusion of migration type in the fixed model structure was the highest ranked model and was 56 times more likely to explain variation in growth among all fish than a model just incorporating age (electronic supplementary material, table S3). Resident and migrant fish did not share a common age–growth relationship and adding a contingent-specific directional growth term did not improve the model (electronic supplementary material, table S4). When modelled independently, the best explanatory mixed effects model structure differed slightly between resident and migrant fish (table 2). The random year effects show different growth trajectories for resident and migrant fish (figure 2b). Biol. Lett. 11: 20140850 0 Downloaded from http://rsbl.royalsocietypublishing.org/ on July 7, 2015 For both resident and migrant fish, predicted growth decreased with increasing age; however, the rate of decrease was greater in migrant fish than resident fish (figure 2c). For migrant fish, age at capture had a positive influence on growth, which suggests that older samples represent faster growing fish. For resident fish, the growth trend was representative of the entire sample. 120 80 40 0 1900 predicted growth (mm) (b) predicted growth (mm) 2000 2005 growth year 2010 1995 2000 2005 growth year 2010 0.8 0.4 0 –0.4 –0.8 1900 (c) 1995 0.4 0.3 0.2 0.1 0 0 5 10 15 20 age (years) 25 30 Figure 2. (a) Numbers of increments representing each growth year. (b) Predicted growth based on year random effect estimates (þs.e.). Only years with more than or equal to five increment measurements are shown (see dashed line in (a)). Dashed line represents the mean growth of the time series (model intercept). (c) Predicted growth based on age fixed effect estimates (+95% CI). Year and age effects are derived from a base model including age, random intercept for year and random age slopes for each random fishID intercept for each contingent type. Black columns and lines, migrant fish; grey columns and lines, resident fish. Throughout the late 1990s and early 2000s resident fish had increased growth compared with migrant fish, but this changed around 2005 when growth of migrant fish increased. There was clear evidence for resident and migratory contingents within the black bream population. Such flexibility in life history has now been identified in many fish taxa and reflects a balance between the costs and benefits of migration in terms of fitness. Fish that migrate may have access to increased food availability, leading to greater growth and increased fitness. Fish may also move to avoid adverse environmental conditions. Indeed, conditions within the River Murray estuary deteriorated as the drought intensified and salinities of up to 120 ppt were recorded [15]. Although there was variation in salinity throughout the estuary, the whole estuary experienced some impact from drying conditions; therefore growth of both migrant and resident fish was likely affected. Deteriorating conditions may explain the reduction in growth of resident black bream through time. At the same time, otolith growth of migratory fish increased slightly, presumably reflecting the greater ability of migratory fish to find more favourable conditions and source food. Our study suggested small differences in average growth of fish over the chronological time series, but large differences in year-to-year variation, as well as age-specific variation, especially after the first few years of life. Mixed results have been found in relation to growth variation among resident and migratory fish of other species. Migratory white perch had higher juvenile and adult growth rates than resident fish [16,17], but a study on southern flounder found no advantage of specific residency periods based on several growth proxies [18]. The latter study only focused on first year growth. Minimal overall variation in growth between contingents may also be expected from a biological and evolutionary point of view. Dynamism in year-to-year growth variation probably drives persistence of both contingent types and the ratio of migrants to residents may be the outcome of population-level bet hedging. Growth variation may also be important for understanding resilience of populations to natural and anthropogenic change. One strategy may be more favourable under some conditions (e.g. migrants in drought conditions), whereas an alternative strategy may be more favourable under a different regime (e.g. [16,19]). Analysis of growth increments allowed continuous annually resolved growth histories of the two migratory contingents to be reconstructed. As otolith growth reflects fish growth, the otolith chronologies are accurate proxies of population-level fluctuations in somatic growth. Further work is required to determine how growth may influence population viability, including reproductive output and survival [20]. Our study highlights complex relationships in growth between resident and migratory contingents, making management of species exhibiting partial migration challenging, especially in a world subject to a changing climate. Biol. Lett. 11: 20140850 4. Discussion 3 rsbl.royalsocietypublishing.org no. increments (a) Downloaded from http://rsbl.royalsocietypublishing.org/ on July 7, 2015 (i) fixed covariate (ii) random t-value covariate variance (s.d.) corr intercept age 22.675 (0.073) 20.216 (0.009) 236.860 223.070 fishID agejfishID 0.038 (0.194) 0.005 (0.073) 0.830 movement type 20.058 (0.030) 21.920 year year class 0.065 (0.254) 0.022 (0.148) residual 0.047 (0.216) (a) all fish (b) resident fish intercept 22.609 (0.043) 260.97 fishID 0.030 (0.173) age 20.211 (0.011) 219.18 agejfishID year 0.006 (0.076) 0.018 (0.135) year class residual 0.002 (0.045) 0.055 (0.235) fishID agejfishID 0.010 (0.098) 0.001 (0.033) year residual 0.026 (0.162) 0.043 (0.208) 0.804 (c) migrant fish intercept age age at capture 22.580 (0.043) 20.159 (0.009) 260.66 217.94 0.026 (0.010) 2.68 Ethics statement. Otoliths were available from archived collections which had been previously collected via SARDI Aquatic Sciences and adhered to South Australian state laws. Data accessibility. Data can be found at Dryad: http://dx.doi.org/10. 5061/dryad.885sn. Acknowledgements. We thank SARDI Aquatic Sciences staff and Vidya Kare for preparing otoliths and Aoife McFadden at Adelaide Microscopy for assistance with LA ICP-MS. We thank Ben Walther, 20.558 John Morrongiello and two anonymous reviewers for their constructive comments. Author contributions. B.M.G. designed the study, Q.Y., C.I. and Z.A.D. collected and analysed data, B.M.G., C.I., Z.A.D. and Q.Y. wrote the paper. Funding statement. This work was financially supported by an Australian Research Council (ARC) Discovery Project and an ARC Future Fellowship, both to B.M.G. Conflict of interests. We have no competing interests. References 1. 2. 3. 4. Hansson L-A, Hylander S. 2009 Size-structured risk assessments govern Daphnia migration. Proc. 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