Ontogenetic milestones of chemotactic behaviour reflect innate species-specific response to habitat cues in larval fish

Animal Behaviour 132 (2017) 61e71

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Ontogenetic milestones of chemotactic behaviour reflect innate species-specific response to habitat cues in larval fish J. Jack O'Connor a, b, *, David J. Booth a, Stephen E. Swearer c, D. Stewart Fielder d, Jeffrey M. Leis b, e a

School of Life Sciences, University of Technology Sydney, Sydney, Australia Ichthyology, Australian Museum Research Institute, Sydney, Australia School of BioSciences, University of Melbourne, Melbourne, Australia d Port Stephens Fisheries Institute, NSW Department of Primary Industries, Orange, Australia e Institute for Marine and Antarctic Studies, University of Tasmania, Hobart, Australia b c

a r t i c l e i n f o Article history: Received 3 November 2016 Initial acceptance 5 January 2017 Final acceptance 28 June 2017 MS. number: 16-00957R Keywords: larval behaviour olfaction ontogenetic milestone seagrass sensory ecology

The distribution and connectivity of marine populations are largely dependent on biophysical factors affecting pelagic larval dispersal between spawning at adult spawning sites and settlement to juvenile nursery habitats. Behaviour and swimming ability of pelagic larvae are increasingly understood to influence patterns of dispersal, but it is unclear which sensory cues are involved and when during ontogeny these abilities first develop. Here we studied the early ontogenetic development of responses to olfactory cues from coastal and estuarine waters in larvae of two temperate estuarine-associated fish species, Australian bass, Macquaria novemaculeata, and mulloway, Argyrosomus japonicus, to determine when olfaction begins to influence dispersal. Olfactory responses to habitat-associated cues were not present when larvae first transitioned from nonswimming to swimming (indicated by flexion of the notochord), but emerged after ca. 7 days in a species-specific manner that was consistent across different cohorts. Based on general additive models (GAMs), age (in days posthatch) best explained the ontogenetic pattern in both species. The emergence of chemotactic responses coincides with an exponential increase in swimming endurance reported for these species. This suggests the existence of ontogenetic milestones during larval development that, once reached, trigger active influence on dispersal. Salinity and pH did not influence choice behaviour after these ontogenetic milestones; however, the presence of cues generated by seagrass harvested from the estuary habitat elicited strong responses in fish larvae consistent with species-specific habitat preferences, indicating an important role for aquatic vegetation in driving these behaviours. © 2017 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.

The pelagic larval stage of many demersal marine organisms is a critical period in their life history, which has a profound influence on the distribution and magnitude of population replenishment, yet empirical data on larval behaviour remains limited (Kendall, Poti, Wynne, Kinlan, & Bauer, 2013). Obtaining such data on the role of larval behaviour in population connectivity remains a challenge for effective management of marine ecosystems (Cowen, Gawarkiewicz, Pineda, Thorrold, & Werner, 2007; Siegel et al., 2008). Recent research into larval capabilities has resulted in a paradigm shift in our understanding of dispersal from a purely physical process, relying solely on physical oceanography (Stobutzki, 2001), towards a

* Correspondence: J. J. O'Connor, Biosciences 4, University of Melbourne, Royal Parade, Parkville VIC 3052, Australia. E-mail address: [email protected] (J. J. O'Connor).

biophysical model incorporating the influence of larval behaviour (Leis, 2015). How and when this influence develops, however, remains an important gap to fill in our understanding of how larval behaviour affects dispersal and survival (Saenz-Agudelo, Jones, Thorrold, & Planes, 2011; Staaterman & Paris, 2014). By the time larvae of many marine species are developmentally competent to make the transition from a pelagic larval stage to a demersal juvenile stage (referred to hereafter as ‘settlement’) they have well-developed visual, auditory and olfactory abilities allowing them to detect and respond to habitat-relevant cues at a range of spatial scales (Atema, Gerlach, & Paris, 2015; Huijbers et al., 2012). These abilities can provide orientation to complement the formidable locomotory capabilities of many species at this life history stage, allowing larvae to influence their dispersal by ocean currents (Kashef, Sogard, Fisher, & Largier, 2014; Leis, 2010). Indeed, biophysical dispersal

http://dx.doi.org/10.1016/j.anbehav.2017.07.026 0003-3472/© 2017 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.

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models that have incorporated larval behaviour and sensory abilities are often better correlated with patterns of settlement observed in the field than models that assume passive dispersal (Fiksen, Jørgensen, Kristiansen, Vikebø, & Huse, 2007; Kough, Paris, & Butler, 2013). Biophysical dispersal modelling, however, is hampered by a lack of species-specific, empirical data on presettlement behaviours of larvae that may influence dispersal trajectories, and these parameters are often estimated or included as simply present or absent (Leis, 2007; Treml et al., 2012). Furthermore, studies show that behaviour is often not static during the pelagic larval stage but may change with ontogeny (Clark, Leis, Hay, & Trnski, 2005; Leis, 2010). To effectively incorporate these dynamics into dispersal models we must first describe ontogenetic patterns of behaviour and understand their underlying causes. This remains a challenge as most studies focus on larvae that have already developed to the settlement stage (Pollux et al., 2007; Simpson, Meekan, Jeffs, Montgomery, & McCauley, 2008; Stobutzki & Bellwood, 1998), and do not investigate the potentially important processes occurring earlier in larval development. Estuarine habitats are important nursery grounds for many fishes and invertebrates. However, fish larvae approaching such settlement habitats from coastal areas must first locate and enter them in order to take advantage of their benefits. Spatial patterns of fish larvae settling in estuaries and embayments show higher levels of settlement to locations with favourable habitat conditions for postsettlement success, suggesting that an ability to detect and respond to habitat-associated olfactory cues would be advantageous (Hale, Downes, & Swearer, 2008; Radford, Sim-Smith, & Jeffs, 2012). Dissolved odour cues from estuarine habitats have been implicated in larval settlement for various species (Boehlert & Mundy, 1988; James, Cowley, Whitfield, & Kaiser, 2008), and the development of the ability to discern between water from marine and estuarine areas may be important for orientation towards and within estuaries, or selection between stratified sections of the water column. We tested olfactory responses in larvae of two temperate, estuarine-associated fish species throughout the pelagic larval phase to address the following questions: (1) when do responses to habitat-relevant olfactory cues develop, (2) are olfactory responses to these cues consistent throughout ontogeny both within and between years, and (3) which characteristics of these contrasting cues (e.g. salinity, pH and seagrass odour) may underlie any observed behavioural responses? METHODS Study Species Important for recreational fishers and aquaculture, the Australian bass, Macquaria novemaculeata (Family: Percichthyidae) is found in streams and estuaries on the eastern coast of Australia (Trnski, Hay, & Fielder, 2005). A catadromous euryhaline fish, this species spends most of its life in fresh water, migrating down into estuaries during the winter months to spawn. During periods of heavy rainfall and flooding events less saline plumes of water can skirt the coastline, allowing adults and larvae to move out of the estuaries and into the coastal environment (Wolanski & Jones, 1981). The presence of M. novemaculeata larvae, tolerant to marine salinities, moving on incoming tides into estuaries indicates the potential for oceanic dispersal between estuaries in this species (Trnski et al., 2005). This movement of adults and larvae between catchments allows for the development and maintenance of genetic population structure in this species (Jerry, 1997), and makes this an interesting species for investigating the ontogenetic development of olfactory cue use in larvae. Percichthyid larvae are known to have well-developed olfactory pits at a young age which may be used in some species to orient towards habitat cues (Gehrke, 1990).

Mulloway, Argyrosomus japonicus (Family: Sciaenidae), is another key species for recreational and commercial fishing and is also associated with estuaries throughout its life history. Small juveniles can be found in estuaries and adults often associate with the estuaryecoastal boundary, again particularly during spawning. However, the timing, age and length at which mulloway recruit as new settlers to estuaries after hatching in coastal waters are not well known (Fielder & Heasman, 2011). As dissolved odour cues from estuarine habitats have been implicated in larval recruitment for various species (Boehlert & Mundy, 1988; James et al., 2008), we hypothesized that responses to olfactory cues from coastal and estuary habitats would vary ontogenetically. The development of the ability to discern between water from coastal and estuarine areas may be important for orientation towards and within estuaries. Larval Rearing We obtained larvae from Port Stephens Fisheries Institute (PSFI) reared as part of aquaculture research projects by the New South Wales Department of Primary Industries. Methods used to collect broodstock and to culture larvae are described in detail by Fielder and Heasman (2011). Briefly, Australian bass (AB) broodstock were captured by monofilament seine net, removed within minutes of being snared and transferred to a 600-litre transporter tank which had been prefilled with water from the collection site. This procedure minimized physical trauma of capture and subsequent handling stress. No more than 30 fish, each of approximately 500 g, were carried in the tank. Compressed oxygen was supplied via a ceramic airstone to maintain saturated dissolved oxygen concentration. Fish arrived at the PSFI hatchery within 6 h of capture, and were then anaesthetized in a 100-litre bin containing oxygenated sea water and Aqui-S (Lower Hutt, New Zealand; 20 ppm; active ingredient ca. 10 ppm isoeugenol) for approximately 10 min. After this time, fish had lost equilibrium of swimming and were then measured, sexed, checked for breeding status and injected with hCG (Chorulon, Intervet International B.V., Boxmeer-Holland; 500 I.U./kg) to induce spawning (Fielder & Heasman, 2011). One to three males and one female fish were then transferred to 500-litre conical-bottomed plastic tanks filled with aerated sea water and maintained at 18 ± 1
C. Once fish had regained equilibrium of swimming, within 5e10 min, lids were placed onto the tanks and the fish were left in darkness for up to 40 h during which time spontaneous spawning occurred. Mulloway (M) larvae were obtained from broodstock that had been maintained for 10 years in purpose-built 22 000-litre recirculating tank systems at the PSFI. A total of 12 broodfish (ca. 15 kg/ fish) at 1:1 male:female were held under controlled temperature conditions. Every 2 h, 100% of the tank sea water was recirculated through mechanical and biological filters to remove solid and dissolved waste, respectively. In addition, 2000 litres of new, filtered (10 mm) sea water was added to the tank system each day. Fish were fed a diet of high-quality squid and pilchards to satiation every second day. Spontaneous spawning was induced by manipulating water temperature from 16
C to 22
C within 24 h. Fertilized eggs of each species were collected, disinfected with ozone (1 ppm for 60 s) and placed into 200-litre conical-bottomed tanks filled with disinfected seawater (33 ppt; 18 ± 1
C (AB), 22 ± 1
C (M); pH 8.0e8.2) at a density of approximately 500 eggs/litre and incubated in darkness until hatching, which occurred after approximately 45 h. Hatched larvae were then transferred by bucket from the incubating tanks into six 2000-litre conical-bottomed hatchery tanks with black sides and a white bottom. Larvae were stocked at approximately 50 larvae/litre. The tanks were housed in a photoperiod- and temperature-controlled room. Each tank was filled

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with disinfected sea water (30e33 ppt; 20 ± 1
C; pH 8.0e8.2) and lightly aerated (200 ml air/min) from a central air ring to maintain oxygen concentration at saturation. Tanks were siphoned daily to remove dead larvae and detritus. Approximately 100% of the sea water volume was replaced daily with new disinfected sea water. Larvae were kept in the dark until 3 days posthatch (dph) and 2 dph (AB and M, respectively). After this time, fluorescent light (Philips white TLA 40W 33QS) was provided at 100 lx on a 14:10 h light:dark cycle. Surface skimmers were supplied to remove surface films and thus encourage swimbladder inflation (Battaglene & Talbot, 1994). A standard feeding regime was used while larvae were maintained in the hatchery. The feeding regime was as follows. Rotifers, Brachionus plicatilis, were fed to larvae from 4 dph and 3 dph for AB and M, respectively, at a density of 10/ml. Uneaten rotifers were removed from the tank each morning by flushing new exchange water, before rotifer density was returned to 10/ml by adding newly harvested rotifers. Rotifers were nutritionally enriched using S.presso (Inve (Thailand) Ltd., Phichit 66220, Thailand) for 12 h before harvest. When larvae were 15 dph, rotifers were replaced by 24 h posthatch Artemia. The Artemia were enriched for 12 h with Algamac 3050 (Bio-Marine Inc., Hawthorne, CA, U.S.A.) prior to feeding. Feeding regime had important relevance to larval growth, as lapses in the rotifer feeding regime of mulloway larvae in 2013 resulted in slower development before the experimental period and a different age at notochord flexion (and therefore the start of the experimental period) in 2014. All life stages of Australian bass and mulloway including fertilized eggs, larvae, live feeds and juvenile fish were cultured in sea water that had been disinfected with ozone and then filtered through activated carbon. Ozone not only reduces the microbial biomass of sea water but also stimulates microflocculation of organic matter, which leads to improved filtration. Ozone also removes colour and taste of sea water by oxidizing dissolved or
& Bader, 1983; Otte, Hilge, & Rosenthal, 1977; ganics (Hoigne Siddiqui, Amy, & Murphy, 1997). Activated carbon is known to adsorb and remove from water a wide range of dissolved organic compounds including chloroform and trihalomethanes, and pollutants including aromatic compounds, hydrocarbons, detergents, soluble dyes, chlorinated solvents, phenols and also unpleasant tastes and odours (Rattier, Reungoat, Gernjak, & Keller, 2012). We began behavioural trials once larvae were competent to swim in our test apparatus, using flexion of the notochord and the coinciding formation of the caudal fin as a developmental marker (ca. 6 mm length from nose to caudal fin, or standard length (SL), for M. novemaculeata and ca. 6.5 mm SL for A. japonicus). Every 3 days we haphazardly selected a subset of individuals from hatchery stock for olfactory choice experiments over a period of 21 days. This period was selected to encompass most of the presettlement stage from when larvae first reach swimming competency to when they reach settlement competency (Fielder & Heasman, 2011). We directed selected individuals (without contact) by net into a plastic container and moved them to the laboratory to recover from the catching procedure and behaviourally acclimate to the novel surroundings for a minimum of 1 h. If after this time larvae displayed persisting behavioural signs of stress (e.g. darting movement, affinity for the bottom) they were given a maximum of 1 h longer to acclimate, which was sufficient for all individuals. Each fish larva was randomly selected for testing by catching it in a 50 ml beaker during a gentle pour of the group from one holding container to another to minimize direct contact. Behaviour of 20 larvae was recorded on each experimental day during a period from 0800 hours to 1800 hours, with each larva tested only once.

Broodstock were obtained and housed following ethical guidelines approved by NSW DPI Animal Research Authority, ACEC Projects 93/3 & 93/1. Larvae not used in our experiment were used for restocking programmes in New South Wales waterways. Following testing, we euthanized larvae with 0.1% benzocaine solution buffered with sodium bicarbonate (Leary et al., 2013). Larvae remained immersed for a minimum of 10 min after operculum movements ceased to ensure death. We then recorded their size before preserving them in 70% ethanol. All experiments were approved by University of Technology Sydney Animal Care and Ethics Committee (2012-254A).

Choice Experiments

Olfactory Cue Preparation

We tested behavioural responses to olfactory cues in temperature-controlled laboratories on site at PSFI, NSW. A

As these species show movement within and between estuaries at different life history stages, we sourced water in situ from Port

two-channel Perspex choice flume and observational procedure similar to that described by Gerlach, Atema, Kingsford, Black, and Miller-Sims (2007) were used to test preferences between olfactory cues in water sourced from different areas (Appendix Fig. A1). We placed individual fish in the centre of the downstream end of the flume where they were free to explore the chamber and swim between the two adjacent flows for an acclimation period of 2 min. We removed from the trials larvae that did not swim actively or explore both sides of the chamber during these 2 min (mean 4.2% of larvae per cohort were removed). After the acclimation period, we recorded the side of the chamber in which the larva was located at 5 s intervals for a period of 2 min. To control for any side bias due to the experimental set-up, we used valves to switch water sources to the opposite side of the chamber, allowing a further 3 min (1 min for the chamber to flush completely, 2 min acclimation) before observing the larva for a second 2 min period. This provided two sets of 25 time points of choice behaviour for each larva. We calculated the percentage of time spent in each cue by dividing the number of observations in each cue by the overall number of observations (50). We applied this procedure twice to each fish during a single trial, first with a control treatment (where incoming water on both sides of the chamber was from the same source) and second with inflow switched to treatment conditions (testing preferences between water from two different sources). Although a pilot study indicated that the water source selected for the control treatment had no influence on the following choice behaviour during the experimental trial, the cue we used for control water (i.e. coastal or estuary water) was alternated for each experimental day. Flow rate was maintained using variable area flow meters (Dwyer Instruments, Unanderra, NSW, Australia) at 200 ml/min, giving a depth of ca. 10 mm in the test chamber. This flow of ca. 3.4 cm/s made possible by the small chamber size encouraged the larvae to swim without having to struggle against the current, ensuring movement was likely to be due to active choice (Dixson, Munday, Pratchett, & Jones, 2011). Dye tests were conducted in the chamber each day before testing to ensure a laminar flow on each side without eddies or mixing. This was particularly important during trials with water sources of different salinities. Through fine adjustments of the outflow aperture and chamber slope, the amount of stratified mixing crossing the centreline was kept to a minimum (Appendix Fig. A2). In addition, the shallow water depth in the chamber made the possibility of a larva crossing the sides of the chamber without detecting any olfactory change unlikely. Experiments were conducted in both 2013 (Cohort 1) and 2014 (Cohort 2) to test the consistency of observed behaviours between cohorts. Ethical Note

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Stephens estuary to provide larvae with a choice between ‘coastal water’ (taken on an incoming tide at the estuary mouth, 32
420 34.700 S, 152
11004.100 E) and ‘estuary water’ (taken from the upper estuary at PSFI, ca. 20 km from the mouth, 32
440 41.800 S, 152
03015.800 E; Appendix Fig. A3). Collected cue water was run through a 1 mm filter to remove particulate matter but allow their related dissolved materials detectable by a larva's olfactory organs to be retained before testing, as differences in turbidity and particulate matter between the two water sources had to be minimized to reduce visual bias affecting choice behaviour. Cue water was kept overnight in tanks, mixed and oxygenated by airstones, to match temperatures with that of larval rearing tanks. Monitoring of water quality parameters revealed the main differences between coastal water (COA) and estuary water (EST) were in salinity (mean ± SE ¼ 35.1 ppt ± 0.23 and 29.8 ppt ± 0.43, respectively) and pH (mean ± SE ¼ 8.15 ± 0.019 and 8.02 ± 0.015, respectively). Therefore, for the second cohort of larvae we prepared artificial sea water (Ocean Nature Sea Salt, Aquasonic, Wauchope, NSW, Australia) to test behavioural responses between water sources with different salinity (low, 28 ppt, versus high, 35 ppt) or pH (low, 7.8, versus high, 8.2). To test behavioural response to the presence of cues from organic matter associated with seagrasses, we prepared batches of coastal water by soaking seagrass, Zostera muelleri subsp. Capricorni, collected from Bagnall's Beach, 6 km within Port Stephens estuary (32
430 08.600 S, 152
070 37.000 E; Fig. A3). We rinsed the seagrass (300 g wet weight) with freshwater to remove traces of epibionts and soil and soaked it for 2 h in a 200-litre tank of coastal water to create seagrass-treated coastal water (SCOA). We then tested larvae for preference behaviour to the seagrass cue against unmanipulated coastal water (i.e. SCOA versus COA). We tested the effect of these water properties on larval choice behaviour at the start of the experimental period (1 day postflexion, N ¼ 20 per treatment) and 2 weeks later (15 days postflexion, N ¼ 20 per treatment). Data Analysis We used the Wilcoxon signed-rank test (a nonparametric paired test suitable for count data) to test for olfactory responses of larvae to different chemical cues and different levels of salinity, pH and seagrass cue at the start of the experimental period (N ¼ 20 per species for each treatment condition). We then used factorial general linear models (GLMs) to assess changes in olfactory choice behaviour across different size classes (0.5 mm increments for M. novemaculeata, 1.5 mm increments for A. japonicus) and across age classes (3-day increments) compared to the response at the start of the experimental period. We used ANOVA with Tukey's post hoc tests to investigate differences in the proportion of time larvae spent in the high pH, salinity and seagrass treatments between the start (tail flexion stage: ca. 6 mm SL for M. novemaculeata and ca. 6.5 mm SL for A. japonicus) and end (start of settlement stage: ca. 9.5 mm SL for M. novemaculeata and ca. 15 mm SL for A. japonicus) of the experimental period. To assess which factors were the strongest drivers of ontogenetic patterns we used general additive models (GAMs) with a binomial distribution to evaluate the development of choice behaviour in response to different olfactory cues as a function of age and size (continuous variables), and year (categorical variable). Because they are useful for examining nonlinear patterns in continuous variables, we considered the smoothing functions that GAMs utilize as a more biologically relevant approach to modelling ontogenetic patterns than traditional linear models. Smoothing matrices with k ¼ 4 provided the best fit to observed ontogenetic patterns. We investigated olfactory ontogeny by modelling the proportion of time M. novemaculeata spent in EST water or A. japonicus spent in COA water as the dependent variable, as initial plotting of data indicated

species-specific cue preferences. To assess the relative importance of age and size to ontogenetic patterns we examined eight models of increasing complexity with separate smoothers fitted by grouping variables. We kept age and size separate in each model to deal with the collinearity of the correlated predictor variables (age and size), which could lead to biased effects (Smith, Koper, Francis, & Fahrig, 2009). We selected the most parsimonious model using Akaike's information criterion corrected for small sample size (AICc), with models compared using DAICc (Anderson & Burnham, 2002), and plotted the shapes of the functional forms for the selected predictors. RESULTS Consistent, Species-Specific Olfactory Ontogeny Ontogeny of olfactory responses was consistent between cohorts for both species. No evidence of choice behaviour was detected for M. novemaculeata larvae at the stage at which the first tail flexion had taken place (ca. 6 mm SL) in Cohort 1 (Wilcoxon signed-rank test: Z ¼ 1.22, P ¼ 0.31, r ¼ 0.55) or Cohort 2 (Wilcoxon signed-rank test: Z ¼ 1.78, P ¼ 0.076, r ¼ 0.40). Olfactory preference for COA in M. novemaculeata developed from 30 dph in Cohort 1 (GLM: b ¼ 0.41, SE ¼ 0.09, P  0.01) and 34 dph in Cohort 2 (GLM: b ¼ 0.47, SE ¼ 0.09, P < 0.001; Fig. 1). Choice behaviour remained for the duration of the experimental period; however, cue preference switched from COA to EST after 36 dph in Cohort 1 (GLM: b ¼ 0.26, SE ¼ 0.09, P < 0.01) and after 37 dph in Cohort 2 (GLM: b ¼ 0.83, SE ¼ 0.09, P < 0.01). Likewise, no evidence of choice behaviour was detected for A. japonicus larvae immediately postflexion in Cohort 1 (Wilcoxon signed-rank test: Z ¼ 1.01, P ¼ 0.33, r ¼ 0.23) or Cohort 2 (Wilcoxon signed-rank test: Z ¼ 0.35, P ¼ 0.74, r ¼ 0.08). We found significant responses to olfactory cues in A. japonicus larvae from 41 dph in Cohort 1 (GLM: b ¼ 1.08, SE ¼ 0.09, P < 0.01) and 28 dph in Cohort 2 (GLM: b ¼ 0.88, SE ¼ 0.09, P < 0.01). Larvae of A. japonicus spent significantly more time in the COA cue after this preference developed in both cohorts (Fig. 2). Larvae at the key developmental stages (notochord flexion, chemotactic emergence and settlement) are illustrated in Fig. 3. Modelling Predictors of Sensory Ontogeny Models that best explained the ontogeny of choice behaviour in both species contained age rather than size, while cohort alone explained the least amount of deviance (Table 1). In M. novemaculeata, the most parsimonious model contained age alone as the predictor, which explained 32.7% of deviance. Our age-based model shows no significant preference by M. novemaculeata larvae for habitat cues during the first 6 days after the caudal fin forms. After this initial period an initial preference for COA cues emerged, before switching towards EST cues (GAM: edf ¼ 3.91, P < 0.01; Fig. 4). Agebased models of the ontogeny of choice behaviour were also the best fit for A. japonicus olfactory ontogeny, with the large effect of cohort by age probably due to the 10-day difference in size-at-age between the two A. japonicus cohorts. The model for age by cohort shows no significant preference by A. japonicus larvae for the first 6e8 days after flexion before a preference for COA emerged and was maintained in each cohort year (GAM: edf ¼ 3.93, P < 0.01; Fig. 5). Seagrass as a Key Driver of Cue Response We detected no choice behaviour by M. novemaculeata larvae at the start of the experiment in response to different levels of salinity (Wilcoxon signed-rank test: Z ¼ 0.84, P ¼ 0.42, r ¼ 0.2), pH (Wilcoxon signed-rank test: Z ¼ 1.07, P ¼ 0.3, r ¼ 0.24) or seagrass cue

Mean % time in cue (cohort 1)

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100 (a)

(c)

*

* 75 COA

50

EST 25 0 24

Mean % time in cue (cohort 2)

M. novemaculeata

65

27

30

33

36

6

3940

100 (b)

6.5

7.5

7

8

8.5

9

9.5

(d) * *

75 50 25 0 25

28

31

34

37

40

43

5.5

6

Age (dph)

7

6.5

7.5

8

8.5

Standard length (mm)

Mean % time in cue (cohort 1)

100 (a)

Mean % time in cue (cohort 2)

Figure 1. Mean % of time ± SE spent in coastal water (COA) or estuary water (EST) (a), (b) for different ages (days posthatch, dph) and (c), (d) for different size classes (mm SL) by Macquaria novemaculeata larvae for (a, c) Cohort 1 reared in 2013 and (b, d) Cohort 2 in 2014. Arrows indicate developmental stage at which significant choice emerged and asterisks ()) indicate switch in cue preference (P < 0.001, N ¼ 20 per experimental day).

100 (b)

(c)

A. japonicus *

*

75 COA

50

*

EST

25 0 29

32

35

38

41

44

5.5

7

8.5

10

11.5

13

14.5

(d) *

* 75 50 25 0 19

22

25

28

Age (dph)

31

34

6

7.5

9

10.5

12.5

14

Standard length (mm)

Figure 2. Mean % of time ± SE spent in coastal water (COA) or estuary water (EST) (a), (b) for different ages (days posthatch, dph) and (c), (d) for different size classes (mm SL) by Argyrosomus japonicus larvae for (a, c) Cohort 1 reared in 2013 and (b, d) Cohort 2 in 2014. Asterisks ()) indicate developmental stage at which significant choice emerged (P < 0.001, N ¼ 20 per experimental day).

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(a)

(b)

(c)

Figure 3. The key developmental stages of Macquaria novemaculeata (top) and Argyrosomus japonicus (bottom) larvae during the part of the pelagic larval phase covered by the experimental period: (a) notochord flexion, (b) chemotactic emergence and (c) settlement stage. Scale bar ¼ 5 mm. Table 1 General additive model (GAM) selection for smooth terms fitted to choice behaviour ontogeny in Australian bass, M. novemaculeata, and mulloway, A. japonicus, larvae

M. novemaculeata Age Size Year Ageþyear Sizeþyear Age)year Size)year A. japonicus Age Size Year Ageþyear Sizeþyear Age)year Size)year

edf

AICc

DAICc

Log likelihood

3.9 3.8 2 4.9 4.8 4.9 4.8

4023.3 4662.3 5458.8 4025.0 4549.5 4025.2 4549.5

0 639.0 1435.4 1.7 526.2 1.9 526.1

¡2007.7 2327.3 2727.4 ¡2007.5 2269.8 ¡2007.6 2269.8

3.9 3.9 2 4.9 5.0 4.9 5.0

2220.1 2278.8 2645.9 2217.3 2277.8 2217.3 2277.7

2.8 61.5 428.6 0 60.5 0 60.5

¡1106.0 1135.4 1320.9 ¡1103.6 1133.8 ¡1103.6 1133.8

Explanatory variables are ranked by estimated degrees of freedom (edf) and differences in model Akaike's information criterion for small sample size compared to the lowest of the set (DAICc; models best fitting the ontogenetic pattern in bold).

(Wilcoxon signed-rank test: Z ¼ 1.22, P ¼ 0.31, r ¼ 0.55). This was also true for A. japonicus larvae for different levels of salinity (Wilcoxon signed-rank test: Z ¼ 0.92, P ¼ 0.37, r ¼ 0.21), pH (Wilcoxon signed-rank test: Z ¼ 0.32, P ¼ 0.76, r ¼ 0.07) and seagrass cue (Wilcoxon signed-rank test: Z ¼ 0.19, P ¼ 0.86, r ¼ 0.04). Choice behaviour to these water properties emerged between the

Macquaria novemaculeata Estuary cue choice probability

0.8

COA chemotaxis emerges

0.6

Argyrosomus japonicus

0.7 COA chemotaxis emerges

0.6

0.5 COA chemotaxis emerges

0.4 Notochord flexion

Notochord flexion

0.3

19

22

25

28

31

34

37

40

43

Age (dph) Figure 5. Predicted relationship (GAM) between age (days posthatch, dph) and response to coastal habitat cues (COA) in mulloway larvae, Argyrosomus japonicus, during two cohort years with different size-at-age ranges. Estimated smooth terms of age by year indicates two phases in presettlement ontogeny: an initial period of ambivalence to olfactory cues after which a strong preference for coastal cues over estuary cues emerged from ca. 7 days after flexion. Dotted line indicates 50% choice probability (i.e. no preference between cues). Grey shading around smoothed fit indicates 95% confidence interval.

flexion and settlement stages for both A. japonicus (F2,114 ¼ 7.45, P < 0.001) and M. novemaculeata (F2,114 ¼ 9.46, P < 0.001; Fig. 6). Post hoc tests showed that by the time they were approaching settlement stage A. japonicus larvae avoided seagrass cues (P < 0.001), while M. novemaculeata larvae were strongly attracted (P < 0.001). This was in line with each species' choice for either COA or EST cues. The proportion of time spent in different levels of pH and salinity was similar, however, in both postflexion and presettlement stages for A. japonicus (P ¼ 0.99 and 0.69, respectively) and M. novemaculeata larvae (P ¼ 0.99 and 0.73, respectively).

0.9

0.7

Coastal cue choice probability

GAM smooth terms

0.8

0.5

DISCUSSION

0.4

Chemotaxis changes to EST

Notochord 0.3 flexion 25

28

31

34 Age (dph)

37

40

43

Figure 4. Predicted relationship (GAM) between age (days posthatch, dph) and response to estuary habitat cues (EST) in Australian bass larvae, Macquaria novemaculeata. The estimated smooth term for age (cohorts combined) effects indicates a brief initial preference for COA cues at ca. 30 dph before preference shifted to EST cues from 36 dph. Dotted line indicates 50% choice probability (i.e. no preference between cues). Grey shading around smoothed fit indicates 95% confidence interval.

Research into the biological factors influencing the ecology and dispersal of larval fishes is limited, particularly outside of the tropics. We found that larvae of two estuarine-associated temperate species had quantifiable behavioural milestones during the pelagic larval phase where responses to olfactory stimuli emerged or changed, and this was consistent across cohorts despite differences in growth rates of larvae prior to the formation of the caudal fin. These milestones are ontogenetically consistent with exponential increases in swimming speed and endurance and changes in in situ swimming direction (Clark et al., 2005; Leis, Hay, & Trnski, 2006), suggesting a developmental milestone during the pelagic larval duration whereby larvae begin to influence their movement in

J. J. O'Connor et al. / Animal Behaviour 132 (2017) 61e71

1

(a)

*

(b)

67

*

Days postflexion 1

Proportion of time in cue

15 0.75

0.5

0.25

0

pH

Salinity

Seagrass

pH

Salinity

Seagrass

Water treatment Figure 6. Comparison of mean proportion of time spent by (a) Argyrosomus japonicus and (b) Macquaria novemaculeata larvae in water treatment cues after first development of swimming competency (postflexion of notochord) and 2 weeks later (lines within boxes indicate median values, upper and lower boundaries indicate the upper quartile and lower quartile, respectively, and whiskers indicate maximum and minimum individual values). Dotted line indicates 50% choice probability (i.e. no preference between cues). Treatment cues comprised pH 8.2 (versus 7.8), salinity of 35 ppt (versus 28 ppt) and seagrass odour (seagrass-infused coastal water versus coastal water). N ¼ 20 for each comparison made; asterisks indicate significant differences (P < 0.0001).

relation to settlement habitat. From a lack of significant response at the time of notochord flexion, an apparently innate species-specific chemotactic behaviour emerged to olfactory cues from different habitats that was driven by the presence of organic matter such as seagrass cues. This paints a more complex picture of the influence of larval fishes on their dispersal, and adds another facet to the already important role seagrass habitats play in the sustainability of populations of many fish species. The ontogenetic development of olfactory responses in larvae of these temperate estuary-associated species indicates that the behavioural influence on movement is not static throughout the pelagic larval phase. This is consistent with one of the few other studies on sensory ontogeny in larval fish, whereby coral reef fish larvae changed their olfactory preferences from avoidance to attraction to cues from coral habitat between 5 and 7 dph (Dixson et al., 2011). Unlike these coral reef species, which hatch from demersal eggs in an advanced state of development and display choice behaviour directly upon hatch, no preference behaviour was detected in the temperate species used for our study (which hatch from pelagic eggs) until at least a week after notochord flexion. These contrasting developmental trends and cue responses should be taken into account when modelling larval dispersal of species in different environments, latitudes and spawning modes (Leis et al., 2013; Wolanski & Kingsford, 2014). In this way we can start to build more nuanced, biologically realistic dispersal models for different species. Once choice behaviour emerged it persisted until larvae had developed to settlement competency, indicating two distinct phases in the ontogeny of larval dispersal: (1) passive drift (before the developmental milestone, whereby vertical distribution may influence dispersal but horizontal swimming capability and behaviour do not) and (2) active movement (after the developmental milestone with swimming speed and endurance to contend with ambient current). Correlations between studies on sensory and swimming ontogeny of larval fishes suggest that there is a point in development during the pelagic phase when both sustained swimming ability and the response to olfactory cues emerge. The transition between different responses to olfactory cues was noted in clownfish larvae by Dixson et al. (2011) as occurring approximately halfway through the larval period, coinciding with the

development of sustained swimming ability in these species (Fisher, Bellwood, & Job, 2000). Although critical swimming speed in M. novemaculeata and A. japonicus measured in laboratory experiments increased linearly with growth during the larval phase, swimming endurance increased exponentially from approximately halfway through the pelagic larval period (Clark et al., 2005). As this capability correlates with the emergence of chemotaxis reported here, it suggests this is the point during development when swimming becomes an important factor in dispersal (Clark et al., 2005). Indeed, the ability to move in the horizontal plane despite current flow direction is of little use without a way to discern a favourable orientation. Responses to auditory cues also show a dramatic increase between early and late larval stages in M. novemaculeata (Wright, Higgs, & Leis, 2011). While larval ontogeny of sensory responses was consistent with size in each cohort, the patterns of individual choices over the experimental period were more strongly associated with days postflexion. This is perhaps surprising, as Clark et al. (2005) found age to be a poor predictor of changes in swimming performance with development in these species, in part due to the wide range of size-at-age and the narrow range of ages available in that study. Ontogenetic milestones are usually expected to reach a uniform size for a given species independent of age (Fuiman & Higgs, 1997); however, age-based patterns of choice behaviour during the pelagic larval phase may help to explain how larvae of different sizes can disperse at different spatial scales and maintain a similar pelagic larval duration (Booth & Parkinson, 2011). Although preflexion growth rates in A. japonicus differed between cohorts, as evidenced by the different ages at the flexion stage, the postflexion growth rates were more stable, and so here, in terms of the models, patterns of olfactory responses were explained best by age in days postflexion, rather than the age in total days posthatch. This suggests that once the presettlement milestone has been reached, age becomes a more important factor than size in the commencement of active horizontal swimming towards settlement habitat. In M. novemaculeata and A. japonicus larvae, seagrass cues elicited the strongest chemotactic response of the water characteristics we tested. These responses were only present after choice behaviour to different habitat cues was detected and the attraction

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to or avoidance of seagrass cues was correlated with the different habitat preferences of each species. Olfactory tests on reared settlement stage larvae (9e14 mm SL) of the sparid Pagrus auratus also show a preference for water taken near seagrass beds over water taken from the estuary mouth (Radford et al., 2012), which is similar to what we found in M. novemaculeata as they approached settlement stage (9e10 mm SL). This is perhaps expected as both species are known to settle in seagrass or otherwise vegetated environments (Trnski, 2002; Trnski et al., 2005). Rich in phenolic acids, cues from seagrasses and other vegetation have been shown to elicit olfactory responses useful for locating settlement habitat in larvae of various marine species (Forward, Tankersley, Smith, & Welch, 2003; Havel & Fuiman, 2015), which indicates that the contribution of seagrass odour to estuary plumes may be important for orientation in larvae of many estuary-associated species. These olfactory signals could be transported by estuary plumes kilometres from the outflow source, making them useful navigational aids for larvae coming to settle in estuaries from offshore coastal waters (Chant et al., 2008). Modelling of larval fish dispersal suggests that the logical progression of sensory cue use involves using olfactory cues to move towards or stay in the vicinity of habitat until close enough to utilize auditory cues to direct swimming (Wolanski & Kingsford, 2014). This role should be considered when informing management decisions on seagrass habitats which are already critical for use as postsettlement nurseries for many marine species (Dahlgren et al., 2006). In contrast to M. novemaculeata responses, A. japonicus larvae avoided seagrass cues when smaller than 14 mm SL. This preference for coastal water cues over estuary cues at this ontogenetic stage may be a mechanism to actively delay recruitment to avoid early predation and enhance dispersal potential. Genetic data for A. japonicus in Australia indicate panmictic subpopulations (Ferguson, Ward, & Gillanders, 2011), and extensive tagging studies of this species show that the large majority (83% in both South Africa and Australia) of tagged individuals (particularly juveniles) were largely sedentary, remaining close to their estuary of capture, although some individuals have moved distances up to 400 km as adults (Silberschneider & Gray, 2008). While little is known about the movement of A. japonicus during the pelagic larval stage, they are found in near coastal waters up to 200 m depths (Silberschneider & Gray, 2008), and while presettlement larvae have been captured entering estuaries (Miskiewicz, 1987), others estimate settlement size as <20 mm (Griffiths, 1996; West & Walford, 2000). Unlike M. novemaculeata, which surpassed their estimated settlement size of 9 mm in this experiment (Clark et al., 2005), there may be further ontogenetic changes in responses to cues with continued growth in A. japonicus. As new recruits are found in estuaries in deeper waters of the main river channels and rarely in the shallow vegetated fringes of estuaries, this preference may also guide swimming between habitats at smaller spatial scales within the estuary (Fielder & Heasman, 2011). Prior to a preference for estuary water cues, M. novemaculeata larvae also showed a preference for coastal water cues. In early stages of development, M. novemaculeata grow faster in higher salinities (20e35 ppt; Van Der Wal, 1985), so an initial chemotactic response towards coastal cues in both our study species could be a mechanism to locate optimal conditions for early growth. As spawning in M. novemaculeata occurs close to the mouth of the estuary in which the adults reside, an initial period of moving away from or delaying movement into the estuary may also increase the potential for dispersal and gene flow between estuaries (Bradbury, Campana, & Bentzen, 2008; Shaddick et al., 2011). Such selectivity to different habitats resulting in delayed settlement and an extended pelagic larval duration has been shown in red drum, Sciaenops ocellatus, another estuarine-associated species (Havel,

Fuiman, & Ojanguren, 2015). Other studies on red drum indicate predation mortality is inversely correlated with size in estuarine fishes around settlement, suggesting early avoidance of estuary chemical cues may also delay settlement of smaller larvae until they have reached settlement size as a mechanism to enhance survival (Rooker, Holt, & Holt, 1998). The response to chemical components driving the consistent choice behaviour between different cohorts may be related to a selected innate response as has been hypothesized in coral reef species (Atema et al., 2015). Indeed the olfactory ontogenies described here were consistent across cohorts, and differed between species despite all larvae being reared under similar conditions. The chemical cue from an estuary is likely to be spatially and temporally variable; however, a signature relying on associated plant and animal species may be more stable, at least at the temporal scales relevant to the larval development of the species in this study (Havel & Fuiman, 2015). A greater understanding of the chemical components important for chemotactic responses of dispersing fish larvae is critical, particularly in aquatic environments susceptible to anthropogenic impacts (Brooker & Dixson, 2016). Our results suggest that the ontogeny of behavioural responses to olfactory cues by presettlement larvae is more complex than previously thought and for the first time we suggest a particular ontogenetic transition when behavioural responses to sensory cues become relevant to dispersal. These olfactory responses are influenced by organic cues such as seagrass. This has important implications for management of estuaries, as anthropogenic disturbance and pollution have already been linked to changes in settlement behaviour and in turn recruitment of settling larval fishes (O'Connor et al., 2015; Siebeck, O'Connor, Braun, & Leis, 2014). Modelling of nektonic dispersal should therefore look at more nuanced species-specific approaches, incorporating information on cue attraction or avoidance and ontogenetic changes during the pelagic larval stage. More data on these ontogenetic milestones in sensory acuity and behaviour from a broader range of taxa could greatly improve the biological realism of models of larval dispersal (Staaterman, Paris, & Helgers, 2012). Acknowledgments We thank L. Cheviot, L. Vandenburg and B. Morton at Port Stephens Fisheries Institute and L. Pedini and S. Bertin at UTS for their logistical and hatchery support. We also thank J. Morrongiello for assistance with data analysis. This research was supported by ARC Discovery grant DP110100695 to J.M.L. References Anderson, D. R., & Burnham, K. P. (2002). Avoiding pitfalls when using informationtheoretic methods. Journal of Wildlife Management, 66, 912e918. Atema, J., Gerlach, G., & Paris, C. B. (2015). Sensory biology and navigation behavior of reef fish larvae. In C. Mora (Ed.), Ecology of Fishes on Coral Reefs (pp. 3e15). Cambridge, U.K.: Cambridge University Press. Battaglene, S. C., & Talbot, R. B. (1994). Hormone induction and larval rearing of mulloway, Argyrosomus hololepidotus (Pisces: Sciaenidae). Aquaculture, 126(1), 73e81. Boehlert, G. W., & Mundy, B. C. (1988). Roles of behavioral and physical factors in larval and juvenile fish recruitment to estuarine nursery areas. American Fisheries Society Symposium, 3, 51e67. Booth, D., & Parkinson, K. (2011). Pelagic larval duration is similar across 23 of latitude for two species of butterflyfish (Chaetodontidae) in eastern Australia. Coral Reefs, 30(4), 1071e1075. Bradbury, I., Campana, S., & Bentzen, P. (2008). Low genetic connectivity in an estuarine fish with pelagic larvae. Canadian Journal of Fisheries and Aquatic Sciences, 65(2), 147e158. Brooker, R. M., & Dixson, D. L. (2016). Assessing the role of olfactory cues in the early life history of coral reef fish: Current methods and future directions. Chemical Signals in Vertebrates, 13, 17e31.

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APPENDIX

Outflow

Fish larva

Water source A inflow

Mesh barrier

Water source B inflow

Figure A1. Olfactory flume (20  5 cm and 3 cm high). Water source A (e.g. coastal water) and B (e.g. estuary water) enter the chamber and inhabit right and left sides, respectively, of the test compartment (between the mesh barriers) due to laminar flow.

Figure A2. Dye test example with water of equal salinity. Dotted line indicates the maximum intrusion by stratified dye when testing water of different salinities.

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71

N

(2)

(3)

(1)

20°

30°

140°

150°

160°

Figure A3. Map of the Port Stephens estuary with collection sites for estuary water (1), seagrass samples (2) and coastal water (3) indicated by black circles. The research station is located at the estuarine collection point (1).