An Analysis of Survey Methodology for Muraena Helena in the Ligurian Sea By: Ian Moffitt and Connor Gervais

An Analysis of Survey Methodology for Muraena helena in the Ligurian Sea By: Ian Moffitt and Connor Gervais

Abstract

The Underwater Visual Census (UVC) is a commonly used method for estimating population abundances and distributions of marine organisms, but this method is time intensive and often underestimates the density of cryptic and cave dwelling organisms, such as moray eels. Trapping methods may more efficiently depict population densities of such species. We investigated the density of the Mediterranean moray eel, Muraena helena, using UVCs along with traps, and identified factors responsible for variation in M. helena density. We determined the area from which pairs of traps draw M. helena within our study site to be approximately 1666m². We verified that conducting a second UVC pass yielded 31.4% higher density estimates than a single pass alone. We also found that M. helena is significantly more likely to be observed on high rugosity habitat, particularly at night. Our results demonstrate that the diel distribution and habitat associations of species must be considered when choosing a sampling method.

Introduction

Accurate methods for estimating abundance and distribution of organisms is essential to the field of ecology. Underwater visual censuses (UVCs) are commonly used to quantify the density of fish populations because they are both accurate and non-intrusive. However, UVCs tend to underestimate the density of those species which are cryptic or concealed by their habitat, such as moray eels(Willis 2001, Brock 1982). Gilbert et al. (2005) proposed a modification to the UVC in order to more accurately quantify moray density. This consisted of performing two passes along the same transect while specifically targeting small scale habitat features preferred by morays, such as crevices. While this method provides more accurate estimates of moray populations in Barbados, it is time consuming and labor intensive. Trapping methods, while not traditionally used for estimations of moray eel density, are a more efficient method for sampling benthic fish and invertebrate populations. Density can be extrapolated from capture rates, given the area from which traps attract individuals is known; however, this area is often unknown. We explored the efficacy of both UVCs and traps to estimate the density of a moray species at a site in the Ligurian Sea. The Mediterranean moray eel, Muraena helena, is primarily observed in rocky, highly complex habitat, and can be difficult to see due to its cryptic coloration. It is generally considered to be nocturnal, but has been observed foraging during the day (Azzuro et al. 2007). Moray eels are important apex predators that are known to have a large effect on prey species in a variety of other ecosystems (Young and Winn

2003; Gilbert et al 2005; Abrams et al 1983). However, the density and distribution of M. helena remains poorly understood. We conducted a study designed to identify the area from which a pair of traps draw M. helena, and the efficacy of modified UVCs at STARESO research station in Calvi Corsica, France. We also investigated which habitat types and times of day are associated with higher densities of this species. We incorporated estimates of site fidelity in order to support our methods’ accuracy. Specifically, we asked five questions: 1) From what size area do baited traps draw M. helena? 2) Does a second UVC pass achieve higher density estimates of M. helena? 3) Does M. helena density correlate with rugosity, and at what spatial scale? 4) Do densities of M. helena change during the day versus night? 5) Do individuals show site fidelity? If so, on what spatial scale?

Methods

We conducted an observational field study at Station de Recherche Océanographiques et sous-marines (STARESO) from October 8th through October 29th. The study was conducted to analyze if the Gilbert et al. methodology could be used to identify an area that traps draw M. helena from, as well as identify diel distribution and rugosity associations.

Figure1: STARESO research center near Calvi, Corsica, France.

Study site This study was conducted in Revellata Bay near Calvi, Corsica, France at STARESO (Université de Liège) (42˚34'48.85”N , 8˚43'26.89”E)(Figure 1) research station. The bay is comprised of rocky reefs in the shallows that transition into

Mediterranean sea grass, Posidonia oceanica, beds in deeper water. Two sites were chosen for the study, one to the north of the STARESO jetty and the other to the south (Figure 2, Figure 3 ). The northern site has a defined area of 3715.9m² and the southern site has a defined area of 3371.5 m² (Determined using google maps). While both sites have similar geomorphology and depth ranges, the northern site has highly stratified habitat complexity, that consists of large granitic outcrops near shore, transitioning to boulder fields, and flattening out into P. oceanica fields at approximately 7 m. Due to this habitat stratification, this site was ideal for a habitat association study. This site was not ideal for a trapping study, as the habitat stratification could pose a bias because the trapped eels could all be coming from one area of high complexity. The southern site consists of P. oceanica beds that interweave with granitic boulder fields. Furthermore, it is relatively secluded from other areas of more stratified habitat complexity. The eastern boundary of the southern site is formed by a continuous P. oceanica bed, while the northern and southern boundaries are formed by large granitic outcrops extending all the way to the surface. The relative seclusion, as well as the less stratified habitat complexity, makes the southern site ideal for our trapping study.

Figure 2: Left: South site with trap placement sites marked (Area=3371m²). Right: Location of transects conducted in the south site.

Figure 3: Northern site (Area =3715m²). Green lines are low rugosity transects, and the orange lines are high rugosity transects.

Study design

Southern Site Area Determination and Gilbert et al. 2005 Methodology Eight transect locations were picked haphazardly and modified swath transects (30x 4 m) developed by Gilbert et al were used to obtain density estimates of M. helena on the south side of STARESO research station during the day. Each diver would slowly zig zag back and forth, one on either side of the transect tape, remaining within .5 m of the substrate and mark all occupied moray dens within 2 m of the transect tape with flagging tape. Dive lights were used to look deep into crevices. The location of each moray along the transect tape was recorded, and the size was estimated by measuring the length from opercle to snout with calipers when possible. When both divers reached the end of the transect, the divers switched sides. The transects were then redone in reverse and the time it took for the transect to be completed was recorded. After all the swaths were completed, 2 pairs of baited traps (4 total) (33x4x66 cm) (Figure 4) were placed in separate coves in the south study site (Figure 2). Equal amounts of fresh fish (Serranids and Labrids) were used to bait the traps. These were located at a depth of 3.7 m, and were located approximately 5m apart in each cove. They were set every evening (8 days total) at 1730 and were retrieved the following morning at 0930 for a total soak time of 16 hours. Captured eels were tagged, and placed into a pen in the harbor so as to deplete the local populations. Tagged eels were released 4 days after the initial trapping event, 0.8 km away in similar habitat. This reduced the risk of saturating traps with recaptured individuals.

Figure 4: Image of the traps used in Southern site.

Northern site Classification of habitat complexity We selected 3 areas within the north site based upon visual observations of stratified habitat complexity. We classified each area as consisting of two zones defined by low and high complexity transects, for a total of 6 transects (Figure 3). To verify our visual estimation of habitat complexity, we ran out a 30 m tape and kept it taught over the contours of the substrate. Another diver at the start of the transect would then reel out a 50 m transect tape over the 30 m tape so that it matched all the contours of the substrate. At each meter mark on the 30m tape, the distance on the 50m tape was recorded. In this way, we could identify rugosity on varying spatial scales.

Eel probability: Rugosity, and Spatial scale We haphazardly conducted 6 30x4 m transects (3 low, 3 high complexity) in the north site at the same locations that we verified habitat complexity, in order to see if there is an increased probability of seeing an eel on high or low rugosity. The first round of transects were performed every day at 0930 on the 12th, 13th and 16th of October. The start and end of each transect was marked with different color flagging tape so the transects could be repeated. The methods used to find eels matched the methods used in the south.

Rugosity and Diel Distribution Every evening we conducted night transects overlaid on top of the transects done during that day (3 high complexity, 3 low). These transects were completed using the same methods as the day transects. The night transects were always conducted at 2230 so as to keep the temporal variation constant. Narrow beam dive lights were used so as not to alter behavior of morays further down the transect.

Site fidelity

The site fidelity of M. helena in the North was documented by observing the number of recounted eels in the same dens over the course of the study. This was determined by redoing the same transects, during the day and night, 12 days after the original transects were completed. Morays of similar size (±60mm), sighted within 5m of a marked den, were considered a recount if the original den was not occupied.

Mark Recapture Analysis

To account for the morays that were missed on the swath transects, Gilbert et al.(2005) developed a correction factor modified from mark recapture theory. The catchability (q), from mark recapture theory, is redefined by Gilbert et al (2005) as N₁/N, which should equal the probability of seeing an eel (P). In our analyses, N₁ is the amount of eels caught on the first trapping event and N is the total number of eels present in the area the trap is drawing from.

Since we caught N eels on the first trapping event, the number of new eels 1 caught in the second trapping event(N2) must equal:

Substituting N1/P for N allows us to solve for P, the probability of catching an eel.

Once the probability of catching new individuals (P) is obtained, we are able to estimate the population (N) of eels present in the area that the traps are drawing from (unknown).

Results

Over all the swaths conducted, 43 individual sightings (4 in the South, 39 in the North) were recorded. Of those 43 sightings, 32 individual eels were recognized.

South Side Area Determination On the south side, 4 eels were observed in an area of 960m² (area of all eight transects). The ratio of eels observed over the area surveyed is the slope of the line used to estimate the area that a trap is drawing from (Figure 5). During the trapping trials, 8 eels were caught the first day and 3 the second, with less eels caught each day(Total eels captured=14) (Table 1). Using mark recapture equations employed by Gilbert et al. (2005), the probability of catching an eel was calculated to be 5/8, and 12.8 eels were expected to be in the area that the traps were drawing from. Combining the number of eels observed over a known area on the transects with the number of eels caught, the estimated area that all four traps were drawing eels from was estimated to be 3333m² (Figure 5). The area that one trap was drawing from was estimated to be 833m²(Figure 5). If it is assumed that the pairs of traps were located close enough together to be considered one trap, then the effective area each pair of traps was drawing from was estimated to be 1666m² (Figure 5).

Figure 5: Slope= 4 eels/960m². The bold vertical line represents the total area drawn upon by all 4 traps. The blue vertical line to the left of this represents the total area drawn upon by each pair of traps. The vertical blue line closest to the y axis represents the area drawn upon by each trap.

Table 1: Trapping results

Gilbert et al. 2005 Methodology The methodology used by Gilbert et al. (2005) increased the number of M. helena seen on a transect by 31.36%. This was calculated by using this equation((total-P1)/total). The second pass accounted for approximately 14 eels that would have otherwise not been observed.

North Side Classification of Habitat Complexity The transects in the north, visually classified as either low or high complexity, were correctly assessed so that the assigned high complexity zone was the more rugose habitat (Figure 6, p=.019).This was verified by running a 1 sample t-test.

Figure 6: The difference in rugosity between transects labeled high rugosity and low rugosity (p=.019)

Eel probability: Rugosity, and Spatial Scale There is a relationship between the probability of spotting an eel and the rugosity of the habitat. Running a logistic regression model shows that as the rugosity of a habitat increases, the probability of finding an eel also increases (Figure 7). However, this relationship is only significant at intermediate spatial scales. At the 5m scale there is a significant relationship linking rugosity with eel probability(p=0.003).

Figure 7: The effect of spatial scale on the relationship between rugosity and eel probability. Rugosity index is the ratio between the taught transect tape and the loose transect tape.

Rugosity and Diel Distribution The number of eels observed on any particular transect is dependent on both the rugosity as well as the time of day. Each factor does not significantly affect the amount of eels observed independently(rugosity p= 0.74, time of day p=0.61). However, when both factors are taken into consideration, it is shown that sampling at night on high rugosity habitat (defined on the 30 m scale) will significantly increase the probability of seeing an eel. (Figure 8, p=0.015). This was determined through a 2 way analysis of variance model.

Figure 8: Eels observed with respect to time of day and rugosity of the transect. (p=0.015 for both factors paired. On their own each factor is insignificant.)

Site fidelity In the second set of transects performed 12 days later, 8 eels out of 29 were re-sighted within 5m of a marked den. Of the 8, 5 were within 1m of the original den and 3 were within 3m. The probability of seeing five eels within 1m is 4.1x10-

8 -8 and the probability for finding all 8 resighted eels within 3m is 1x 10 . We also recaptured 2 out of 8 tagged individuals released from out trapping expexeriment.

Discussion

We have shown that it is possible to calculate the area from which each trap draws M. helena by coupling this method with modified UVCs. It was assumed that there was no migration into or out of our study site. Modified swath transects developed by Gilbert et al (2005) appear to be an appropriate method for determining density of this species.

Area Determination Through the combined use of the method developed by Gilbert et al (2005) and the trap-depletion method, we estimated the area from which a pair of traps draws M. helena at our study site. We believe our estimate to be accurate for several reasons. First, the area calculated for all four traps is similar to the expected area based on habitat features, that likely serve as natural barriers. Second, our tagging data suggests M. helena displays site fidelity, supporting the assumption that there was no migration in or out of our study site. Additionally, we observed a steady reduction in number of eels captured in our traps, suggesting that we successfully depleted the population without drawing upon individuals outside the study site. Third, the lack of habitat stratification in our southern site removed the bias that all of the eels could be coming from one location of high density. The estimation of area drawn upon for each trap in this study is essential for the future study of M. helena. Traps should be spaced far enough apart to limit area overlap, and trials should be carried out long enough to assess population replenishment. It would also be interesting to know if the amount of bait could increase the area drawn upon by each trap. Our results emphasize the efficacy of the modified UVC method coupled with trapping in order to estimate population density.

Validating the Gilbert et al (2005) method in the Mediterranean We found that the methods developed by Gilbert et al (2005) can be used to obtain higher density estimates of M. helena in our study site by performing a second pass. It also provides additional perspective, by facilitating sightings of an organism in its natural habitat. By doing this, information with respect to diel distribution and habitat association can be gathered. We found that the probability of seeing M. helena increased significantly with rugosity on a 5 meter scale, but not on a 1,2, and 30 meter scale. Gilbert et al (2005) found that 65.5% of the variation of eel density with respect to site, species, structural complexity, and the interaction between site and species was not explained by their model. Our results show this could have been due, in part, to small scale variation of rugosity within a transect.

Diel Distribution Studies of other species of moray have shown that the best time to sample in order to obtain the highest density estimates, is variable (Abrams et al. 1983, Gilbert et al. 2005). Interestingly, we found that on a 30 meter scale, high rugosity and night observations are associated with significantly higher probabilities of seeing an eel . However at lower levels of rugosity, surveying at night will not significantly increase the probability of seeing an eel. Transects should be performed at night on high rugosity habitat for the future study of M. helena in order to obtain more accurate density estimates.

Conclusion Through the combined use of the method developed by Gilbert et al (2005) and the trap-depletion method, we estimated the area from which a pair of traps draws M. helena at our study site. We believe the density estimates obtained through both methods are accurate representations of the population present at our study site. Furthermore, by using modified UVCs, we have identified important information with regard to M. helena diel distribution, habitat association, and site fidelity.

Acknowledgements We’d like to thank the staff at STARESO for the use of the station and their ongoing support and patience. A special thank you to chef Richard for the ridiculously amazing food!

Thank you to all the amazing people in Bio 159. The class as a whole inspired us to work hard, and have fun doing it!

Thanks to Jimmy O’ Donnell, Gary Longo, and Kristin De Nesnera for their ongoing support, hilarity, and mad card skillz.

Special thanks to Rita Mehta for her advice, endless wealth of knowledge, and for putting up with our never-ending stream of questions.

We would especially like to thank Pete Raimondi and Giacomo Bernardi as they had to deal with our never ending questions on a daily basis. Kudos to Pete Raimondi (stats master) as he had to put up with us for a whole two weeks longer WITHOUT the help of Giacomo. I don’t know how the heck he managed!

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