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CaribbeanNaturalist

No. 18 2014

Day–Night Patterns in Natural and Artificial Patch Reef Fish Assemblages of The Bahamas

Martha J. Zapata, Lauren A. Yeager, and Craig A. Layman

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Cover Photograph: Juvenile grunts (Haemulidae spp.) rest during the day on a natural patch reef in the Sea of Abaco, July 2012. Photograph © Lauren A. Yeager and Martha J. Zapata.

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BarbadosScott Jones, Smithsonian Institution, Caribbean Coral Reef Ecosystems, Carrie Bow Cay, BelizeHeather Judkins, Department of Biological Sciences, University of South Florida, St. Petersburg, FL, USACraig A. Layman, Department of Biological Sciences,Florida International University, North Miami, FL,

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Caribbean Naturalist

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M.J. Zapata, L.A. Yeager, and C.A. Layman2014 No. 18CARIBBEAN NATURALIST2014 No. 18:1–15

Day–Night Patterns in Natural and Artificial Patch Reef Fish Assemblages of The Bahamas

Martha J. Zapata1,2,*, Lauren A. Yeager1,3, and Craig A. Layman1,3

Abstract - Back-reef seascapes encompass a heterogeneous mosaic of patch reef and sea-grass habitats, often linked by reef-associated species that forage in soft-bottom habitats at night. These foraging patterns contribute to turnover between day and night fish assem-blages; yet the degree of this turnover is difficult to quantify with standard visual survey methodologies without affecting fish behavior. In this study, we evaluated reef fish com-munities within natural and artificial reefs around Abaco Island, Bahamas. We compared fish densities across midday, dusk, and night during one-hour periods using fixed-area, time-lapse photography illuminated by infrared lighting. Fish assemblages associated with both natural and artificial habitats exhibited a significant diel shift typified by a decline in total fish density at night. Cross-habitat movement by nocturnal species, especially those of Haemulidae, is a central driver of this turnover. Although underestimating fish species rich-ness on natural reefs, the time-lapse infrared photography provided comparable estimates of species richness to roving diver surveys on the smaller artificial reefs, representing a non-invasive approach to study temporal dynamics in shallow-reef fish communities.

Introduction

Tropical back-reef ecosystems are characterized by a mosaic of mangrove stands, seagrass beds, and patch reefs that function as essential habitat for fishes (Adams et al. 2006, Dahlgren et al. 2006). Among near-shore juvenile-fish habitats, patch reefs have been found to support more species per unit area (Mateo 2002). Yet, these important coastal habitats are threatened by various anthropogenic dis-turbances, such as nutrient input and overfishing (Lotze et al. 2006). In the face of reef habitat degradation, resource managers establish monitoring practices of fish communities in order to track trajectories of ecological change. Almost all such fish-monitoring approaches are focused on diurnal assemblages, potentially ignor-ing important day–night differences. Past research has documented notable shifts in reef community composition from day to night (Azzuro et al. 2007, Nagelkerken et al. 2000, Starck and Davis 1966). Diurnal reef assemblages are generally characterized by roaming herbivores and invertivores, yet many reef-associated species are cathemeral or primarily nocturnal. During twilight, certain fishes leave to forage on adjacent seagrass beds and sand flats. For example, the grunts (Haemulidae) are known to have predictable

1Marine Sciences Program, Department of Biological Sciences, Florida International Univer-sity, 3000 NE 151st Street, North Miami, FL 33181. 2Current address - School of Environment and Natural Resources, The Ohio State University, 2021 Coffey Road, Columbus, OH 43210. 3Current address - Institute of Marine Sciences, University of North Carolina at Chapel-Hill, Chapel Hill, NC 27599. 3Current address - Department of Applied Ecology, North Carolina State University, Raleigh, NC 27659. *Corresponding author - [email protected].

Manuscript Editor: Alfonso Aguilar-Perera

Caribbean NaturalistM.J. Zapata, L.A. Yeager, and C.A. Layman

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nightly migration patterns between reef and seagrass habitats (Burke 1995, Ogden and Ehrlich 1977) and demonstrate high site fidelity by consistently returning to the same patch reef (Yeager et al. 2014). Underwater visual surveys are widely applied to study reef fish communities, but are less feasible during the night without the use of disruptive artificial lighting. One method for gathering high-resolution data related to animal habitat use involves remote-camera technologies. In terrestrial systems, motion-sensing cameras are commonly used to track movements of elusive, larger-bodied animals (Cutler and Swann 1999). A similar approach may be applied in marine systems. When comple-mented with remote-imaging systems, infrared (800–1000 nm) lighting can serve as a valuable tool for obtaining less-invasive nighttime observations (Holbrook and Schmitt 1997, Pelletier et al. 2011) because coastal marine fishes do not perceive these wavelengths (Lythgoe and Patridge 1989, Shcherbakov et al. 2013). Develop-ing such technologies for marine environments would provide for informative and cost-efficient monitoring approaches (Cappo et al. 2003). This study aimed to quantify day–night turnover in fish abundance on natural and artificial reefs in Abaco Island, Bahamas, using remote time-lapse imaging illuminated with infrared lighting. Artificial reefs are often used to model natural patch reefs for scientific studies and to enhance degraded fish habitat (Carr and Hixon 1997). Examining diel patterns of community composition on artificial reefs would further our understanding of their function as fish habitat. A secondary objective was to draw a focused comparison of day–night variation in habitat use by Haemulids, as juveniles of these species are very common in this seascape and have well-studied diel behaviors (Appeldoorn et al. 2009, Nagelkerken et al. 2000, Ogden and Ehrlich 1977). Finally, we compared diurnal fish community structure as measured by time-lapse surveys and underwater visual census to assess these techniques for quantifying patch-scale fish assemblages.

Field-Site Description

This study was conducted in the Sea of Abaco, Abaco Island, Bahamas. This water body extends ~10 km in width and has a maximum depth of ~10 m. The ben-thos is comprised of carbonate sediment and Thalassia testudinum Banks ex König (Turtle Grass) interspersed with patch reef and hard-bottom habitat. We focused on five natural and five artificial patch reefs (Fig. 1). Natural patch reefs were dominated by Montastraea cavernosa L. (Great Star Coral), Siderastrea sp. (starlet coral), Eusmilia fastigiata (Pallas) (Smooth Flower Coral), Porites astreoides Lamarck (Mustard Hill Coral), and coral rubble. Macroalgae, along with massive and semi-encrusting sponges, established secondary reef structure. Artificial reefs were constructed in May 2011 by assembling 30 cinderblocks in a cuboid configuration (0.8 m x 0.6 m x 0.75 m). All reef sites were <3 m in depth and separated by ≥80 m to minimize fish movement among sites (Yeager et al. 2011). Natural patch reefs were larger in area, ranging from ~60 to 400 m2. Based on benthic transect surveys conducted within a radius of 100 m from reef structure, we estimated mean seagrass cover to be 42 ± 12 (SD) percent for natural patch reefs and 52 ± 13 (SD) percent for artificial patch reefs.


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M.J. Zapata, L.A. Yeager, and C.A. Layman2014 No. 18

Methods

Patch reefs were surveyed using fixed-area time-lapse photography during three time periods, hereafter referred to as midday (1230 to 1330 h), dusk (1900 to 2000 h), and night (2100 to 2200 h). Dusk observations were set to end at local sunset timing (DST) throughout the study period. For adaptation to underwater and low-light conditions, a GoPro HERO2® camera was modified with dive housing and an infrared lens. The camera was fixed onto a cinderblock base positioned 40 cm from the reef structure (Fig. 2a). Images were captured at one-minute intervals. During dusk and night, the sampling area was continuously illuminated by a 9-watt LED dive light modified with an infrared filter. Midday, dusk, and night time-lapse data were recorded within one 24-hr period at each of the five natural and five arti-ficial reef sites. All surveys were carried out during July 2012. Photographs were analyzed using ImageJ 1.47b software (Rasband 1997–2012). Due to the rapid attenuation of infrared light at night, observation win-dows were based on the area visible at each reef during night (Fig. 2c). We recorded fish assemblages within the same reef area (as determined by the nighttime area) across the three time periods. Estimations were done by creating point-in-polygon overlays of fish individuals by taxa for each frame. Reduced resolution of night-time images limited species identification. Due to this limita-tion, our analyses focused on comparisons of total fish and grunt (Haemulidae) density across the time periods.

Figure 1. Locations of natural and artificial patch reef sites in the Sea of Abaco, Bahamas.


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Targeted analysis of the grunts included individuals ≥50 mm total length (TL) belonging to the species Haemulon plumierii (White Grunt), H. flavolineatum (French Grunt), H. sciurus (Blue-striped Grunt), and unidentified Haemulon spp. Individuals <50 mm TL were not included as they are not known to make nightly foraging migrations (Appeldoorn et al. 2009, Helfman et al. 1982). In cases of poor image resolution, we included individuals that could not be identified as a discrete species and fit grunt morphological features (e.g., continuous dorsal fin, steep-sloped forehead, forked caudal fin). We view this inclusion as conservative for the analysis since we expected grunt abundances to be lowest at night. For each time period, the total number of fishes and grunts, independently, were divided by the number of frames (60 per time period) to attain average abundance within the fixed area. This value was then divided by the observed volume, based on reef area surveyed (calculated using pixel-to-cm scale based on known length of reef features) and its distance from the camera (40 cm). Fish abundance observed within each survey frame is then expressed per unit volume (referred to as density, hereafter). The maximum number of individuals (MaxN) of each species observed within a given frame was composited for each time period as another proxy for to-tal fish abundance. This metric is commonly used for investigations of relative fish abundance for camera-based studies (e.g., Cappo et al. 2003, Lowry et al. 2012). Underwater visual censuses were performed between 1000 and 1330 h, using a non-categorical roving diver technique (Schmitt and Sullivan 1996). The roving diver technique can allow for species detection at higher resolution than transect surveys (Holt et al. 2013). We adopted this method to obtain observations at a higher spatial resolution from reef sites that are variable in size and habitat configuration. Each survey was conducted by a team of two snorkelers (M.J. Zapata and L.A. Yea-ger), who swam a non-linear path to identify and enumerate all fishes present within

Figure 2. Camera and light (A) were placed 40 cm from patch reefs. Communities were surveyed during midday (B), dusk (C), and night based on the area illuminated at night for each reef.


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2 m of the reef structure over a 10-minute period. We conducted two roving diver surveys, separated by at least 24 h, at each reef site during July 2012. Abundance estimates for each species were then averaged between observers and survey dates, resulting in one average density estimate per reef. Midday camera (1230–1330 h) and roving diver surveys were not conducted simultaneously in order to minimize any human presence-induced response in fish behavior or correlated observations. We conducted all roving diver surveys within 4 days, on average, of time-lapse surveys, allowing us to make relative comparisons of daytime fish community com-position on reefs. Fish density data from time-lapse surveys were log-transformed to meet as-sumptions of normality and equal variances. We performed separate two-way repeated-measures ANOVA’s using SigmaPlot (v. 12.5) to discern the effects of reef type (artificial vs. natural) and time of day (independent variables) on (1) total fish density, (2) grunt density, and (3) total fish MaxN (maximum number of individu-als per species). The total fish density, grunt density, and MaxN ANOVA’s were performed with and without one outlier for a dusk observation on an artificial patch reef. Excluding this outlier did not affect the overall pattern of the data, but improved model fit. If main effects or interaction terms were significant, pairwise comparisons were drawn with post-hoc Tukey tests. We used a two-way ANOVA to compare species richness of daytime natural and artificial reef assemblages as estimated by each survey method. If a significant inter-action was found, we employed a post-hoc Tukey test to determine where differences lie. Fish community structure was analyzed based on Bray-Curtis similarity matrices of square-root transformed abundances (e.g., Clarke 1993). We then used analyses of similarity (ANOSIM) to evaluate whether community structure varied between natu-ral and artificial reefs based on either method. We employed a similarity percentages (SIMPER) analysis to identify which species were most important in driving differ-ences between reef types. Similarity in fish communities among reefs was rendered graphically with a multi-dimensional scaling (MDS) plot. All community structure analyses were performed using the software package PRIMER v.6.

Results

The analyzed time-lapse dataset consisted of ten reef sequences of 180 frames captured during midday, dusk (with the exception of the outlier 60-frame se-quence), and night at the natural and artificial patch reefs. Observations included fishes belonging to 48 species representing 18 taxonomic families (Appendix 1). Day–night patterns of fish density varied considerably at natural and artificial reefs. Two-way repeated-measures ANOVA revealed an interactive effect between reef type and time on total fish density (F2,15 = 5.8, P = 0.014; Fig. 3a). Post-hoc comparisons using Tukey tests indicated that both natural and artificial reefs were typified by lower fish densities at night (mean ± SE = 2.6 ± 0.9 fish/m3 on natural reefs and 5.6 ± 1.9 fish/m3 on artificial reefs; P < 0.05). On natural reefs, average fish density was higher at both midday and dusk (90 ± 12.4 fish/m3 and 82.3 ± 23.5 fish/m3, respectively), whereas density peaked during dusk (34.9 ± 9.8 fish/m3) on artificial reefs (Fig. 3a).


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Grunt densities varied between reef types (repeated measures ANOVA: F1,16 = 13.9, P = 0.006), being generally higher on natural reefs (mean ± SE = 67.1 ± 17.4 grunts/m3) when compared to artificial reefs (9.6 ± 4.7 grunts/m3) (Fig. 3b). Grunt densities also varied among the three times of day (F2,16 = 16.2, P < 0.001; Fig. 3b). On both artificial and natural reefs, fewer grunts were observed at night (2.3 ± 1.5 grunts/m3 and 1.5 ± 0.7 grunts/m3, respectively) compared to midday or dusk (P < 0.001; Fig. 3b). Total fish MaxN varied across time (ANOVA: F1,15= 13.0, P < 0.001) on natu-ral and artificial reefs, where estimates were relatively consistent during midday (mean ± SE = 33 ± 7.9 and 32 ± 7.2 individuals on natural and artificial reefs, respec-tively) and dusk (30 ± 10.6 and 32 ± 1.8 individuals on natural and artificial reefs, respectively) (Fig. 4). MaxN of all fishes were typically lower (2.0 ± 0.6 and 5.0 ± 0.9 individuals on natural and artificial reefs, respectively) at night (Fig. 4).

Figure 3. Average fish density (A) and grunt density (B) ± SE as observed through time-lapse surveys at midday, dusk, and night time periods. Similar letters denote groups that do not differ at α = 0.05.

Figure 4. Average MaxN ± SE for all reef fishes as observed by time-lapse sequence across midday, dusk, and night. Similar letters denotes groups that do not differ at α = 0.05.


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Individuals of 58 fish species from 22 families were recorded during roving diver surveys (Appendix 1). Survey method and reef type had an interactive effect on species richness (ANOVA: F1,16 = 34.3, P < 0.001; Fig. 5). Tukey pairwise com-parisons suggest that species richness was underestimated by time-lapse surveys on the larger, natural patch reefs (P < 0.001; Fig. 5). Species richness estimates were similar between survey methods for artificial reefs (P = 0.7; Fig. 5). Diurnal reef fish communities were dominated by benthic invertivores, including Haemulon plumierii, H. flavolineatum on both reef types, H. sciurus on natural reefs, and Myripristis jacobus (Blackbar Soldierfish) and Halichoeres poeyi (Blackear Wrasse) on artificial reefs. Daytime fish community structure, as estimated through both methods, varied between reef types (ANOSIM: R = 0.552, P = 0.008 for time-lapse; R = 0.904, P = 0.008 for roving diver; Fig. 6). Dissimilarity between diurnal assemblages on natural and artificial reefs was partially attributed to higher propor-tion of planktivores and benthic invertivores on artificial reefs and overall higher trophic diversity represented in the natural patch reef fish assemblages. For example, the absence of species that were consistently recorded on natural reefs—including Haemulon sciurus, Thalassoma bifasciatum (Bluehead Wrasse), Halichoeres gar-noti (Yellowhead Wrasse), Scarus guacamaia (Rainbow Parrotfish), Caranx ruber (Bar Jack), Ocyurus chrysurus (Yellowtail Snapper), and Lutjanis griseus (Gray Snapper)—from artificial reefs drove differences seen between reef types. Estimates of fish community composition on artificial reefs were consistent between survey

Figure 5. Species richness as estimated by time-lapse and roving diver surveys. Similar let-ters denotes groups that do not differ at α = 0.05.


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methods (ANOSIM: R = -0.076, P = 0.64), but there was a method-based discrep-ancy in estimating the larger, natural reef communities (R = 0.42, P = 0.008).

Discussion

Differential structural components, reef age, and seascape context of the focal natural and artificial reefs in this study most likely contribute to the differences observed in diurnal fish communities, which are consistent with findings of greater fish abundance and species richness at natural reefs when these factors were con-trolled (Hixon and Carr 1997). These intrinsic habitat variables affect basal re-source pools (Perkol-Finkel and Benayahu 2007, Perkol-Finkel et al. 2006), larval recruitment and settlement (Svane and Peterson 2001), survivorship (Hixon and Beets 1989, Shulman and Ogden 1987), and behavioral preferences of reef fishes (Folpp et al. 2013, Hitt et al. 2011). Combining the use of infrared lighting and remote time-lapse imaging represents a useful technique to survey reef habitats. This study demonstrated its potential as a non-invasive approach to monitor temporal shifts in reef fish assemblages. Artificial and natural patch reefs in the Sea of Abaco supported diverse fish communities that experience marked declines in total fish and grunt abundance at night. Quantifying these patterns builds upon earlier studies that have suggested differences between day and night reef fish assemblages (Azzuro et al. 2007, Nagelkerken et al. 2000). One mechanism that may drive this turnover is cross-habitat movement of species to adjacent foraging habitat. Numerous reef-associated fishes that were commonly observed during daytime surveys, including Haemulon sciurus, H. plumierii, and H. flavolineatum, are known to feed in soft-bottom habitats at night (Burke 1995, Nagelkerken et al. 2000, Ogden and Ehrlich 1977) and dem-onstrate high site fidelity (Yeager et al. 2014, Verweij and Nagelkerken 2007). Cross-habitat foragers can mediate reciprocal energetic linkages in heterogeneous seascapes, and thus play an important role in ecosystem function (Allgeier et al. 2013, Burkepile et al. 2013, Layman et al. 2013, Meyer et al. 1983). Grunts were

Figure 6. Multidimensional scaling plot depicting fish community structure based on Bray-Curtis similarity matrices of species abundances.


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common throughout this seascape (Yeager et al. 2014) and seemed to be largely absent from natural and artificial reefs during the night. Natural and artificial patch reefs exhibited similar diel patterns in fish densities, suggesting that nocturnal fish movement between reefs and seagrass beds may help preserve seascape connectivity. While both reef types had much lower fish densi-ties at night, subtle differences were found between the other times periods. Spe-cifically, natural habitats exhibited highest fish and grunt density during midday, whereas peak densities on artificial reefs occurred during dusk. This discrepancy can result from size-specific variation in timing of foraging migrations (Appel-doorn et al. 2009, McFarland and Wahl 1996). Haemulon plumierii on artificial reefs were generally smaller in size than those observed on natural reefs (M.J. Zapata et al., unpubl. data), suggesting that the increase in fish abundance during dusk on artificial reefs may reflect trade-offs related to predation risk and foraging effort. Fish density increased at dusk on artificial reefs where smaller prey fishes may seek refuge earlier, and emerge later, relative to crepuscular intervals of high predation risk (Danilowicz and Sale 1999, Hixon 1991). In describing fish communities, time-lapse surveys better corresponded with rov-ing diver surveys on artificial reefs than on natural reefs. These results were likely related to differences in reef size and community diversity. For the larger, natural, patch reefs, time-lapse photography was only able to capture a limited snapshot of the entire fish community. However, had our snorkel surveys of the natural reefs focused on the scale of a coral head (similar to the scope of the infrared lighting), re-sults drawn from both methods may have been more consistent. Lowry et al. (2012) found a similar discrepancy in estimating fish assemblages on estuarine artificial reefs, in which baited remote underwater video only recorded a proportion of the total assemblage detected by stationary-point underwater visual census. The rela-tively narrow scope of fixed-area time-lapse photography may make it more useful at surveying at smaller spatial scales or habitat patches. Future studies employing this method should consider spatial range of focal species in sampling design. Employing arrays of multiple cameras should increase its utility in surveying adjacent habitat patches and diel changeover in fish assemblages. Increasing infrared lighting could broaden the visible scope and refine image resolution at night. Utilizing time-lapse photography in combination with other survey approaches to describe the patch-reef fish assemblages could yield valuable information about temporal shifts in marine communities, especially in clear-water, tropical systems. By focusing survey efforts on diurnal fish assemblages, we may be able to assess the value of patch reefs as fish habitat; however, we may be underestimating the importance of surrounding soft-bottom habitats to these species at other times (Berkström et al. 2012, Kopp et al. 2007). Diel patterns in fish communities can change in response to altered natural lighting regimes that govern periodicity of fish behavior (Helfman et al. 1982, Mc-Cauley et al. 2012) or via release from predation (Danilowicz and Sale 1999, McCauley et al. 2012). Camera-based surveys can be applied to efficiently mon-itor changes in diel fish behavior and community interactions that are known


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to affect seascape connectivity and ecosystem health (Allgeier et al. 2013, Burkepile et al. 2013, Meyer et al. 1983).

Acknowledgements

We thank J. Peters and S. Sebilian for assistance in the field, Friends of the Environment for logistical support, and the Department of Marine Resources of the Bahamas for grant-ing a research permit. We extend our appreciation to W. Goldberg, A. Aguilar-Perera and three anonymous reviewers for constructive comments on the manuscript. This project was funded by a NSF Graduate Research Fellowship and a FIU Dissertation Year Fellowship to LAY, as part of a summer research program for MJZ associated with NSF OCE #0746164 and #1405198 to CAL.

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13


App

endi

x 1.

Mea

n fis

h ab

unda

nce

(rov

ing

dive

r su

rvey

s), d

ensi

ty, a

nd M

axN

(tim

e-la

pse

surv

eys)

dur

ing

the

dayt

ime

on a

rtific

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A)

and

natu

ral (

N)

patc

h re

efs.

Spe

cies

are

org

aniz

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mily

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rvey

met

hod

R

ovin

g di

ver

Tim

e-la

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A

bund

ance

D

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ty

Max

N

(n /

reef

) (n

/ m

3 ) (n

/ fr

ame)

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mon

nam

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mily

Sp

ecie

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N

A

N

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Blu

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ng

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nthu

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anth

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loch

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ider

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60

3.80

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63

0.16

0.

60

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eon

fish

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nthu

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Ac

anth

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spp

. 1.

40

6.90

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38

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y Tr

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aem

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2014 No. 18

14

Su

rvey

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hod

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appe

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15


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0.40

Caribbean Naturalist - NCSU Applied Ecology...The Caribbean Naturalist. . . ♦ A peer-reviewed and...

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Transcript of Caribbean Naturalist - NCSU Applied Ecology...The Caribbean Naturalist. . . ♦ A peer-reviewed and...