Notes on Ontogenetic Habitat Shifts in Nassau Grouper (Dahlgren & Eggleston, 2000)

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• Topic: Ecological processes underlying ontogenetic habitat shifts in a coral reef fish (Nassau grouper, Epinephelus striatus).
• Core idea: Mobile animals balance foraging benefits against predation risk. A simple optimality model predicts habitat shifts in response to mortality risk (ϕ) and growth rate (g) to maximize net benefits. This study tests predictions using field experiments to quantify habitat-specific growth and predation risk for juvenile Nassau grouper across three size classes during off-reef nursery residence.
• Key hypotheses (non-mutually exclusive):
  • (1) Maximize growth rate: shift to habitat that yields higher g.
  • (2) Minimize predation risk: shift to habitat with lower ϕ.
  • (3) Minimize the ratio ϕ/g when trade-offs exist between growth and survival (i.e., choose habitat that minimizes ϕ/g).
• Major result preview: Small fish (in algal habitat) face a trade-off between higher growth in postalgal habitat and safety in algal habitat; ϕ/g is lower in algal for small fish, while for medium/large fish (which reside in postalgal habitats) ϕ/g is lower there. Overall, juvenile Nassau grouper use habitats consistent with the minimize ϕ/g hypothesis.
• Keywords to anchor future notes: Bahamas; caging experiments; Epinephelus striatus; growth rate; habitat; Laurencia; macroalgae; Nassau grouper; ontogenetic; optimization models; predation risk; refuge.

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• Context: Ontogenetic habitat shifts are common in mobile marine species moving from off-reef nurseries to on-reef habitats as they grow. The study addresses a gap in understanding the ecological processes and tests whether shifts align with the minimize ϕ/g hypothesis or other optimality models.
• Why this matters: Understanding nursery habitat function (prey refuges or foraging grounds) and the drivers of habitat shifts informs population dynamics and potential conservation strategies.
• Background on theory:
  • Habitat use often reflects trade-offs among foraging, predation risk, and reproductive conditions that change with growth (body size).
  • Simple optimization models can forecast habitat shifts in terms of fitness-maximizing strategies; for non-reproductive juveniles, survival to the next size class is a key fitness component.
  • Classic prediction: when trade-offs exist, organisms minimize ϕ/g across habitats as they grow (Gilliam & Werner literature cited).
• Lead-in to current study: The Nassau grouper recruits off-reef into macroalgal nurseries; at ~50 mm TL they shift to postalgal habitats; subsequent ontogenetic shifts continue to patch reefs and deep offshore reefs.

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• Species focus: Nassau grouper (Epinephelus striatus) – a large serranid (>20 kg) important commercially; juvenile recruitment occurs in macroalgal beds; early juveniles spend ~2 months in algal interstices before moving to postalgal habitats adjacent to macroalgae (50 mm TL threshold).
• Study design overview: quantify mortality risk (through tethering) and growth rates (through caging) for three size classes across two habitat types (algal vs postalgal) to test three hypotheses: maximize g, minimize ϕ, minimize ϕ/g.
• Study site: CMRC near Lee Stocking Island, Bahamas; tidal creeks (B3 and B4) with ~7,200 m^2 macroalgal beds (Laurencia sp.) and additional microhabitats (Porites rubble, seagrass, sponges, etc.); temperatures 20–35°C.
• Size classes defined: small 35–40 mm TL, medium 50–55 mm TL, large 70–75 mm TL.
• Experimental logic: sequential experiments per size class to avoid confounding cross-size effects; compare habitat-specific growth and mortality within each size class.

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• Nocturnal vs. diurnal distribution: prior daytime observations showed ontogenetic habitat shift; to avoid bias from diurnal confinement, nocturnal distribution was tested in lab. Macroalgal clumps rinsed to remove prey items were used so prey availability did not confound habitat choice in lab tests.
• Lab setup for diel tests: 154-L aquaria with 5 macroalgal clumps; one fish per aquarium; acclimation 12 h; observations 0800–1800 (day) and 2000–0600 (night). Red light used at night to minimize disturbance.
• Observation protocol: hourly checks; if not seen, assumed in/under algal clump; 10 fish per size class per day/night, identical conditions across trials.
• Preliminary statistical test: loglinear G test to compare proportion of time outside algae between day and night for each size class.
• Takeaway: Nocturnal/diurnal habitat associations were similar to daytime patterns, validating diurnal confinement during field experiments; supports realism of using day/night habitats in caging/tethering.

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• Do size-specific habitats maximize growth? Field caging experiments to estimate growth rates across habitats for three size classes.
• Experimental setup: field cages, 0.6 m radius, 0.7 m tall; bottom open; 1.2 m^2 area; placed in 40–60% macroalgal cover to allow independent replication (10 m apart).
• Treatments (per fish): (1) algal: access only to macroalgal interstices; (2) postalgal: access to postalgal microhabitats but not algal interstices; (3) control: access to both habitats.
• Ensured equal foraging area across treatments by using mesh bags to confine algae in algal treatments and to exclude algal access in postalgal treatments; control cages had ~50% macroalgae cover.
• Experiment duration: 6–7 weeks; weekly checks; fish measured for TL before and after to compute daily growth rate (mm/day).
• Statistical design: randomized complete block ANOVA with Site as block, Habitat as main factor; homogeneity of variances checked with Fmax; post-hoc contrasts to test a priori hypotheses:
  • (i) gcontrol =/≈ galgal or g_postalgal depending on natural habitat occupancy;
  • (ii) g_control and the natural habitat have higher g than the other habitat.
• Findings (summary): Growth rates were significantly higher in postalgal and control than in algal for all sizes; between-sites difference occurred for small fish (B3 had higher g than B4). See Fig. 2 and Table 1 for details (described in pages 7–8).

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• Assessment of potential caging artifacts: ensured macroalgal cover/volume did not systematically differ among treatments; end-of-experiment macroalgal cover and volume measured to check confounds.
• Findings: End-of-experiment macroalgal cover differed only for small fish (control higher than algal and postalgal); macroalgal volume differed by site for small and medium fish but within natural ranges for both sites; for large fish, sampling not done due to logistics.
• Additional artifact test: laboratory foraging with bagged vs unbagged macroalgae to check whether confinement reduces foraging; results: no significant difference in amphipod consumption between bagged and unbagged macroalgae (t-test, P = 0.7; small sample, ~30% power; means similar: 23.3 vs 25.3 amphipods in 72 h).
• Conclusion: caging design did not artifactually bias growth results.

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• Figure 2: habitat-specific growth rates (mean ± SE) for small, medium, and large juvenile Nassau grouper. Small mean ~38–40 mm TL; Medium ~54 mm; Large ~73 mm.
• Key point: Growth in postalgal and control habitats exceeded that in algal habitat for all sizes; sample sizes listed above bars; some bars not significantly different (paired contrasts).
• Table 1 (summary statistics): ANOVA results for growth rates, macroalgal cover, and macroalgal volume, across size classes. Highlights:
  • Small size class: significant effects of Site (block) and Habitat on growth rates; modest effect of algal cover and volume.
  • Medium size class: significant habitat effect on growth rates; mangrove/phyto habitat measurements showed some site differences in algal cover and volume.
  • Large size class: growth rates differed little among habitat treatments; some habitat-related differences in algal cover/volume by site.
• Overall interpretation: For all sizes, growth is enhanced in non-algal habitats or exposed to postalgal habitats; algal interiors constrain growth, supporting the hypothesis that growth potential differs by habitat.

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• Table 1 (continued): detailed ANOVA results for each size class (Small, Medium, Large) across Site, Habitat, and their interaction; significance levels indicated (NS, * P ≤ 0.05, ** P ≤ 0.01, *** P ≤ 0.001).
• Figure 3: habitat-specific predation rates from tethering experiments at site B3 across sizes.
• Key take-away: Small fish show significantly lower predation in algal habitat than postalgal; no significant difference for medium or large sizes between habitats.
• Important methodological note: tethering effectiveness was monitored; tethers kept fish in assigned habitats; predators encountered included Nassau grouper, Caranx ruber, Lutjanus apodus, Synodus intermedius, Epinephelus guttatus, and L. griseus among others.

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• Tethering artifact assessment: additional tests to evaluate simple and higher-order artifacts:
  • Simple artifacts: lab observations showed tethered and untethered fish behaved similarly; no deaths or injuries in 1.5 weeks; movement patterns similar; no escape from tethers observed in field checks.
  • Higher-order artifacts: tests for tethering interactions with habitat (e.g., easier escape or behavioral changes) found no evidence that such artifacts biased the comparison between habitats.
• Ratio ϕ/g: computations use tethering data for ϕ and caging data for g. For small fish, growth rates from some sites exhibited site-by-habitat differences; ϕ/g calculations use site B3 mortality for small fish and site B3 for medium/large when combining sites for g.
• Method note: randomization test to compare observed ϕ/g differences between algae vs postalgal against a null distribution generated by permuting habitat labels 5,000 times per size class.

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• Figure 4: habitat-specific ϕ/g values for each size class, showing minimize ϕ/g in algal habitat for small fish, and in postalgal habitat for medium and large fish.
• Figure 5: results of randomization tests comparing observed ϕ/g differences to simulated random distributions; shows that observed differences are significant for all three size classes (P ≤ 0.05 one-tailed).
• Table 2 (summary values): for each size class and habitat, reports mortality ϕ, growth rate g, and the ratio ϕ/g. Key patterns:
  • Small: ϕalgal = 0.05/day; galgal = 0.12 mm/d; ϕ/galgal ≈ 0.42; ϕpostalgal = 0.30/day; gpostalgal = 0.24 mm/d; ϕ/gpostalgal ≈ 1.25. Therefore, ϕ/g is lower in algal for small fish.
  • Medium: ϕalgal = 0.25/day; galgal = 0.02 mm/d; ϕ/galgal ≈ 12.50; ϕpostalgal = 0.15/day; gpostalgal = 0.26 mm/d; ϕ/gpostalgal ≈ 0.58. Therefore, ϕ/g is lower in postalgal for medium fish.
  • Large: ϕalgal = 0.13/day; galgal = 0.01 mm/d; ϕ/galgal ≈ 11.93; ϕpostalgal = 0.11/day; gpostalgal = 0.07 mm/d; ϕ/gpostalgal ≈ 1.48. Therefore, ϕ/g is lower in postalgal for large fish.
• Notes on interpretation: these values support the pattern described in the text: ϕ/g is minimized in the habitat consistent with observed field occupancy for each size class (algal for small, postalgal for medium/large).

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• Discussion: ontogenetic habitat shifts are explained by a trade-off where the ratio of predation risk to growth rate (ϕ/g) is minimized in the habitat where the size class is typically found in the field.
• Mechanisms behind observed patterns:
  • For small fish: algal refuges reduce predation risk; growth may be inhibited in macroalgal interiors due to foraging constraints or limited prey, but predation risk is the dominant selector, favoring algal refuges.
  • For medium/large fish: growth benefits in postalgal habitats (better foraging or reduced competition) outweigh predation risk, driving movement away from macroalgae toward coastal macroinvertebrate-rich postalgal habitats.
• No single fixed rule; pattern may reflect size-dependent predator guilds, refuge scaling with body size, and the concept of a “refuge in size” as fish grow.
• The study reinforces the idea that short-term behavioral decisions (patch choice, ontogenetic habitat shifts) align with minimize ϕ/g across life stages and may depend on hunger, sex, or life-history stage in other systems.
• The authors connect these findings to broader ecological ideas:
  • Habitat shifts influence population dynamics, community structure, and potentially meta-population dynamics (source-sink dynamics).
  • Macroalgal nurseries, although rare, can be crucial refuges that increase early juvenile survivorship and thus influence recruitment and population viability.
• Implications for conservation: protecting macroalgal nursery habitats may be critical for Nassau grouper populations, given their role as refuges and their potential to shape population trajectories through early survivorship.

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• Ecological processes underlying the habitat shift, summarized:
  • The shift out of macroalgal clumps by small juveniles is driven by the availability of higher growth in postalgal habitats but countered by higher predation risk in those habitats; net effect is a minimized ϕ/g in algal habitat for small fish.
  • As fish grow (medium and large), growth advantages of postalgal habitats become pronounced (gpostalgal > galgal) while predation risk becomes less habitat-dependent, leading to a minimized ϕ/g in postalgal habitats for larger sizes.
• Predation risk patterns and refuge explanations are discussed, including possible explanations such as changing predator guilds, improved refuge in size, and scale-matching refuge effectiveness as fish increase in body size.
• The paper emphasizes that macroalgal refuges may be especially important during the first month after settlement, a period often characterized by high mortality in reef fishes. Macroalgae may thus mediate early survivorship and influence population structure.
• Broader ecological framing: the study situates ontogenetic habitat shifts within the larger context of size-structured populations, risk-foraging trade-offs, and habitat selection theory.

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• Continued discussion on ecological implications:
  • Habitat quality and availability can constrain recruitment and population persistence; macroalgal nurseries, though occupying a small fraction of shallow-water habitat, can disproportionately affect early-stage survivorship.
  • The authors reference source-sink dynamics: macroalgal nurseries may function as sources of recruits, while other habitats can represent sinks with higher mortality.
• They also reflect on methodology and generality:
  • The minimal evidence for universal fixed-size thresholds for habitat shifts suggests the possibility of flexible, condition-dependent thresholds or rapid behavioral adjustments in response to perceived risk and growth opportunities.
  • The results align with broader theories on patch choice and predator-prey dynamics, including the idea that short-term choices track the profitability of habitats under risk.
• The paper closes with implications for coral reef fish management and conservation strategies, emphasizing the ecological and population-level importance of nursery habitats.

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• Comprehensive references illustrating the breadth of the food-for-growth vs. predation-risk framework across taxa and ecosystems; numerous foundational studies cited (Werner & Gilliam 1984; Gilliam & Fraser 1987; Lima & Dill 1990; Utne et al. 1993; Utne & Aksnes 1994; Gilliam et al. 1993; Hixon & Beets 1989, 1993; Shulman & Ogden 1987; Sogard 1994, 1997; etc.).
• Key concept reiterated: ontogenetic habitat shifts are shaped by size-dependent changes in predation risk and growth prospects; minimizes ϕ/g provides a robust explanatory framework for observed habitat use.
• Final takeaway: The Nassau grouper study demonstrates how behavioral responses to ecological processes (predation risk and growth potential) determine distribution patterns of mobile marine animals and highlights the conservation importance of off-reef nurseries in coral reef ecosystems.

Summary of Core Concepts and Formulas

• Core variables:
  • Growth rate: g (e.g., mm/day)
  • Mortality risk:
    ho ext{ or }
    ightarrow \phi (daily probability of mortality; per-day rate)
  • Ratio of mortality to growth: rac{
    ho}{g} ext{ or } rac{
    ho}{g} = rac{ ext{mortality rate}}{ ext{growth rate}} = rac{\phi}{g}
• Hypotheses tested (non-mutually exclusive):
  • Maximize growth: habitat with higher g
  • Minimize mortality: habitat with lower \phi
  • Minimize ϕ/g: habitat that lowers the risk-to-growth trade-off
• Experimental design highlights:
  • Field caging: three habitat treatments (algal, postalgal, control) across two sites; 6 replicates per habitat per site; three size classes; duration ~6–7 weeks; growth measured as daily rate g = \Delta TL / \Delta t
  • Tethering: assess relative predation risk by tethering juveniles in algal vs postalgal habitats; check for predators; analyze presence/absence as a function of habitat and size class
  • Nocturnal vs diurnal test in lab to verify diel habitat use patterns are consistent with field observations
• Key results to remember:
  • Small fish: ϕ/g is lower in algal habitats (≈0.42) than postalgal (≈1.25), implying a predation-risk-minimizing habitat dominates for small fish
  • Medium and Large fish: ϕ/g is lower in postalgal habitats (≈0.58 and ≈1.48, respectively) than algal (≈12.50 and ≈11.93), favoring postalgal habitat for larger juveniles
  • Overall, observed ontogenetic habitat shifts align with minimize ϕ/g across sizes
  • No strong caging artifacts detected; tethering artifacts were not detected; predator observations corroborate the ecological relevance of the macroalgal refuges

Practical and Ethical Implications

• Ecological significance: Nursery macroalgal habitats function as refuges that can enhance early-stage survivorship, thereby influencing recruitment and population dynamics of Nassau grouper.
• Conservation relevance: Protecting macroalgal nurseries may be critical for the persistence of Nassau grouper populations in the Bahamas and similar reef systems, given their role in mediating predation risk and growth during a vulnerable life stage.
• Broader relevance: The minimize ϕ/g framework can be applied to other taxa experiencing growth-dependent predation risk and habitat quality changes during ontogeny, with potential applications in fisheries management and habitat restoration.

Key Equations (LaTeX)

• Ratio of mortality risk to growth rate (central metric):
  rac{\phi}{g}
• Hypotheses and decision rule (conceptual):
  • Maximize growth: choose habitat with g{ ext{habitat}} = \max(g{ ext{habitat}})
  • Minimize mortality: choose habitat with \phi{ ext{habitat}} = \min(\phi{ ext{habitat}})
  • Minimize trade-off: choose habitat that minimizes \frac{\phi}{g}, i.e., minimize {\phi}/{g} across available habitats
• For small fish (example from Table 2):
  \phi{\text{algal}} = 0.05, \quad g{\text{algal}} = 0.12, \quad \frac{\phi}{g}\big|{\text{algal}} = 0.42 \phi{\text{postalgal}} = 0.30, \quad g{\text{postalgal}} = 0.24, \quad \frac{\phi}{g}\big|{\text{postalgal}} = 1.25
• For medium fish (example from Table 2):
  \phi{\text{algal}} = 0.25, \quad g{\text{algal}} = 0.02, \quad \frac{\phi}{g}\big|{\text{algal}} = 12.50 \phi{\text{postalgal}} = 0.15, \quad g{\text{postalgal}} = 0.26, \quad \frac{\phi}{g}\big|{\text{postalgal}} = 0.58
• Randomization test approach: compare observed \Delta(\phi/g) = (\phi/g){\text{algal}} - (\phi/g){\text{postalgal}} against a null distribution generated by randomly reassigning habitat labels (5,000 iterations) to test if the observed difference is significantly different from zero with a one-tailed test at \alpha = 0.05.

Connections to Earlier Lectures and Foundational Principles

• Optimal foraging theory and habitat selection: This study extends the idea that animals make habitat choices by weighing costs (predation) and benefits (growth/foraging) as they grow, linking to classic models by Werner, Gilliam, and Fraser.
• Life-history theory and ontogenetic niche shifts: The work exemplifies how life-stage changes alter risk and resource use, consistent with size-structured population concepts.
• Predator–prey dynamics and refuges: Results reinforce the importance of refuges in shaping survival and growth, echoing themes in Hixon, Beets, and Shulman’s work on shelter and habitat structure.
• Meta-population and source–sink dynamics: The discussion invokes the idea that high-quality nurseries can act as sources and influence larger-scale population dynamics, aligning with Pulliam’s sources/sinks framework.

Takeaway for Exam Preparation

• Be able to explain the three hypotheses tested and why their predictions differ across size classes.
• Understand how growth rate (g) and mortality risk (ϕ) are measured experimentally (caging for growth, tethering for predation risk) and how these feed into the metric ϕ/g.
• Recall the key findings: small fish favor algal refuges to minimize ϕ/g, while larger juveniles favor postalgal habitats to minimize ϕ/g due to greater growth opportunities; overall pattern supports the minimize ϕ/g hypothesis.
• Recognize the importance of validating methods (artifact controls) and using randomization tests to evaluate ecological hypotheses.
• Appreciate the ecological and conservation implications of nursery habitats in shaping population dynamics of reef fishes.

Quick Reference: Key Terms

• ϕ: mortality risk (per day)
• g: growth rate (mm/day)
• ϕ/g: ratio of mortality risk to growth rate; lower values indicate a better balance between safety and growth in a given habitat.
• Alg algal habitat: interstices within macroalgal clumps and macroalgal-covered coral areas.
• Postalgal habitat: outside or adjacent to macroalgae, in more structurally complex microhabitats.
• Ontogenetic habitat shifts: changes in habitat use as an organism grows.
• Randomization test: a nonparametric method used to assess the significance of observed effects by comparing to a distribution generated by random reassignment of treatments.
• Refuge in size: the concept that refuges scale with body size, altering predation risk as individuals grow.
• Source–sink dynamics: framework describing how certain habitats may contribute net recruits (sources) while others absorb them (sinks).