SUCCESSION AND BIODIVERSITY OF AN ARTIFICIAL REEF
MARINE PROTECTED AREA: A COMPARISON OF FISH
ASSEMBLAGES ON PROTECTED AND UNPROTECTED
HABITATS
A thesis submitted in partial fulfillment of the requirements for the degree
MASTER OF SCIENCE
in
ENVIRONMENTAL STUDIES
by
KEVIN J. KOLMOS June 2007
at
THE GRADUATE SCHOOL OF THE COLLEGE OF CHARLESTON
Approved by:
______Glenn F. Ulrich
______Robert M. Martore
______David Owens
______Melvin Bell
ACKNOWLEDGEMENTS
This project was completed with the help of many individuals over the past two years. I would like to thank Glenn Ulrich for his guidance and wealth of knowledge he imparted during my research. He was an excellent primary advisor and a true friend. He taught me many things about the marine world with this project as well as working on the
COASTSPAN and the Adult Red Drum projects. I would also like to thank my committee members: Dave Owens, Mel Bell, and Bob Martore who introduced me to the world of artificial reefs which was a major deciding factor in enrolling in the
Environmental Studies program at the College of Charleston. The project was greatly enhanced by the insight and observations of my committee. I would like to give a special thanks to Martin Jones for taking so much time to help me with the statistical analyses with this thesis. His assistance was invaluable. I also had a great experience working with Bryan Frazier, Carrie Hendrix, and Jon Richardson. My time with this project was memorable with the cruises and sampling trips we conducted together from taking pictures with Bryan’s fish, to pulling hooks out of Carrie’s finger, to arguing with Jon whether something was a scamp or gag in the UW videos. We made some awesome memories.
The artificial reef group was a great help in conducting underwater SCUBA surveys as well as diver observations. Thanks to Bob Martore, Daryl Stubbs, Ian Moody and Ryan Yaden; even though I had to pay Daryl a nickel for every fish he helped me
ii identify in the videos. I would also like to thank Paul Tucker and Rob Dunlap for captaining the R/V Silver Crescent.
Financial support was provided in part by the South Atlantic Fishery Management
Council Inshore Fisheries Section and the Artificial Reef Program at the South Carolina
Department of Natural Resources through a non-work study. The funding provided by these groups was genuinely appreciated.
I would like to give a final thanks to my family and friends. My mother, father, and sister have always been supportive in my quest for knowledge and understanding in the marine biology realm. They encouraged me to succeed in obtaining my dreams.
Even while being five states away, their love and support was greatly felt during times of adversity as well as triumph. They helped me more than they know. Also to my friends that I have grown with and experienced hand in hand the struggles and successes of the graduate school life. I can only hope I give as much support to those that have helped me.
iii
Table of Contents
TITLE AND APPROVAL PAGE…………………………………………………………i
ACKNOWLEDGEMENTS……………………………………………………………….ii
TABLE OF CONTENTS…………………………………………………………………iv
LIST OF FIGURES……………………………………………………………………….v
LIST OF TABLES …………………………………………………………………..viii
ABSTRACT……………………………………………………………………………...ix
INTRODUCTION………………………………………………………………………...1
MATERIALS AND METHODS…………………………………………………………8
RESULTS………………………………………………………………………………..16
DISCUSSION……………………………………………………………………………26
CONCLUSION…………………………………………………………………………..42
LITERATURE CITED…………………………………………………………………..44
FIGURES………………………………………………………………………………...51
TABLES…………………………………………………………………………………70
APPENDIX………………………………………………………………………………75
iv
List of Figures
Figure Page
1: An artificial reef unit used by the SCDNR and deployed at Area 53. This
picture was taken six months after units were deployed off the coast of
Charleston, SC. Photo by R.M. Martore……………………………………….51
2: Nylon dart tags used in marking and identifying individual fish.
Tags are color-coded for visual reference according to respective reef
orientation and also contain unique identification numbers as well as
contact numbers if found……………………………………………………….52
3: Gray triggerfish tagged on the left side of the body. Tags were inserted
past the pterigiophores to ensure a solid holding position………………………53
4: Fluctuations in individual site abundance based on the four identified
species: C. striata, B. capriscus, M. phenax, and M. microlepsis.………………54
5: 5a: Centropristis striata length frequency distribution between fished and
unfished sites during the three time intervals……………………………………55
v 5b: Centropristis striata trend lines for corresponding fished
and unfished locations during the three time intervals…………………………..56
6a: 6a: Centropristis striata length frequency distribution for each
individual site……………………………………………………………………57
6b: This illustration shows the C. striata trend lines for individual sites
during the three time intervals…………………………………………………..58
7: Centropristis striata mean lengths are compared between fished and
unfished locations. This graph illustrates the length frequency
distributions and shows how unfished locations have a steady increase
in mean length throughout the experiment and into future sampling
trips………………………………………………………………………………59
8: Centropristis striata mean lengths between all the sites………………………...60
9: 9a: Length frequency distribution for B. capriscus comparing fished and
unfished locations……………………………………………………………….61
9b: Balistis capriscus length frequency distribution trend lines
illustrate the responses to fishing pressure on fished and unfished
populations………………………………………………………………………62
vi 10: Balistes capriscus mean lengths are compared between fished and unfished
locations……………………………………………………………………….63
11: Balistes capriscus mean lengths are compared between each individual
site……………………………………………………………………………..64
12: 12a: Box plot for C. striata on growth/day between fished and unfished
locations………………………………………………………………………..65
12b: Box plot for B. capriscus on growth/day between fished and unfished
locations………………………………………………………………………..66
13: The equation for growth (mm) per day was determined using all
recaptured C. striata……………………………………………………………67
14: The growth(mm) per day was calculated between fished and unfished
locations for C. striata populations…………………………………………….68
15: The overall growth (mm) per day was calculated for B. capriscus
populations……………………………………………………………………..69
vii
List of Tables
Page
Table 1: Species present on Area 53 site …………………………………………71
Table 2: Species present on adjacent natural reefs………………………………..72
Table 3: Top six recaptured species data………………………………………….73
Table 4: Values for C. striata site population estimates…………………………74
viii
ABSTRACT
SUCCESSION AND BIODIVERSITY OF AN ARTIFICIAL REEF MARINE PROTECTED AREA: A COMPARISON OF FISH ASSEMBLAGES ON PROTECTED AND UNPROTECTED HABITATS A thesis submitted in partial fulfillment of the requirements for the degree
MASTER OF SCIENCE in ENVIRONMENTAL STUDIES by KEVIN J. KOLMOS June 2007 at THE GRADUATE SCHOOL OF THE COLLEGE OF CHARLESTON
The goal of the proposed research was to document the succession and characteristics of finfish communities on four artificial reef systems established at a depth of 33 m off the South Carolina coast. The location of the reefs has not been disclosed to the public allowing them to function as Marine Protected Areas (MPAs) and as an experiment to examine the dynamics of fish recruitment and responses to protection and exploitation. Two of the sites were randomly selected for intensive fish removals to simulate conditions in open-access fishing habitats leaving the remaining reef sites unfished, functioning as fully protected MPAs. The species diversity, size composition and abundance of recreationally and commercially exploited finfish species were compared on the protected and harvested sites through analysis of recapture data and video SCUBA surveys from both fished and unfished sites. Abundance of pooled Centropristis striata, Balistes capriscus, Mycteroperca phenax, and Mycteroperca microlepsis on protected sites were significantly greater than fished sites. Protected sites also had significantly larger C. striata and B. capriscus. Unfished reefs had greater biomass than exploited reefs; increasing the potential reproductive output and larval spillover of protected artificial reef systems. Locations that have a paucity of hard bottom habitat such as the South Atlantic Bight (SAB) would benefit from the establishment of a network of MPAs on artificially created hard bottom habitat. Artificial reef MPAs are a viable management strategy for the SAB to protect and enhance populations of commercial and recreationally important finfish species.
ix
Introduction
Declining fish populations and overexploited fish stocks have stimulated the search for new and more effective management of the fishing industry. Nearly 70% of the world’s fished stocks are listed as “fully fished, overfished, depleted, or recovering”, prompting fishermen and scientists to investigate alternative management options to protect these natural resources (World Resources Institute, 1996). One avenue of conservation management that could lead to the restoration of depleted stocks involves marine reserves that protect reef sites where fish live, feed, spawn, and find shelter
(Roberts, 1995; Halpern & Warner, 2002, 2003; Clark, 1996; Boersma & Parrish, 1999;
Lauck et al., 1998). Marine reserves and “No-take Zones” (Ballantine, 1996) are part of an overall trend toward utilization of Marine Protected Areas (MPAs) as management tools (Baelde, 2005).
The benthic communities existing on “hard bottom” topographies on natural reefs
(NRs) provide the valuable building blocks of marine food webs that lure small reef fish and eventually larger predators (Kauppert, 2002). Experimentation with MPAs on NRs has revealed numerous positive results. Initially, MPAs offer protection for ecosystem integrity and biodiversity while providing opportunities for education and research
(Parnell et al., 2005).
1 Establishing MPAs creates potential “source” populations by protecting spawning aggregations and providing fish with food and shelter during different life stages (Man et al., 1995). Natural reefs (NRs) off South Carolina are comprised of outcroppings and three-dimensional features creating microhabitats that attract many marine organisms.
Oceanic waters from Cape Hatteras North Carolina to West Palm Beach Florida, known as the South Atlantic Bight (SAB), have only five to ten percent of its area classified as
NRs and establishment of MPAs in those areas may produce significant economic hardships on commercial and recreational fishing interests (SCDNR). The introduction of artificial reef (AR) MPAs is an alternative that may supplement NR-MPAs by mimicking the characteristics of NRs in both form and function (Perkol-Finkel et al.,
2006). ARs can increase the biomass and spawning potential in the SAB, countering adverse effects caused by human exploitation. AR-MPAs increase the amount of “live- bottom” habitat without causing conflicts to user groups through closures of traditional fishing grounds. For example, proposed Type II MPAs on NRs in the SAB prohibit fishing and possession of snapper grouper species but allow fishermen to troll for pelagic species such as tuna, mackerel, and billfish (SAFMC). These proposed MPAs have caused much controversy between managers and fishermen because the NRs are heavily used but short in supply.
Creating MPAs on ARs may mitigate the controversial issues involved with closing NRs. Experiments on AR-MPAs have been conducted in tropical waters around
Australia, Africa, the Caribbean, and the Mediterranean with positive results however; few have proven the applicability of MPAs in more temperate waters, especially those limited by the scarcity of NRs.
2
Artificial Reefs as an Alternative
Properly designed and constructed artificial reefs should fulfill the same functions as NRs in creating hard bottom ecosystems that allows benthic organisms to recruit, grow, and reproduce. Deploying ARs augments the complexity of a habitat and has proven to enhance biodiversity and richness of fish assemblages (Charbonnel et al.,
2002). Structures used in AR design include concrete blocks, formed concrete units, polyvinyl chloride (PVC) pipe, ships, subway cars, bridge rubble, tanks, APCs, and shipping containers (SCDNR, Sherman et al., 2002).
Results from AR experimentations have revealed promising utilization of this management tool. For example, the transition of the seafloor from sandy bottom to rocky outcroppings was shown to produce greater survivorship in fish species (Lindholm et al.,
2001). Additionally, Walker et al. (2002) discovered that the deployment of ARs in a sandy substrate increased the abundance and richness of fish species. Hard bottom habitats and their associated resources are critical features for reef dependent fish species.
Many species require hard bottom communities for survival and the paucity of these areas can limit productivity (Bohnsack, 1989), biodiversity and richness, specifically in the SAB.
Management Tools and Principles of MPAs
Increased interest in MPAs has occurred in the wake of fishery collapses from inadequate traditional forms of fishery stock management (Halpern, 2003). MPAs may function to replenish overfished stocks and may alleviate overexploitation by allowing
3 growth and reproduction of fish populations and to maintain and enhance local biodiversity (Roberts et al., 2001; Boersma & Parrish, 1999; DeMartini, 1993). MPAs accounted for less than 1% of the world’s marine area in 1999 (Boersma & Parrish, 1999) despite the belief they are efficient and cost effective management tools (McNeill &
Fairweather, 1993; McCLanahan & Kaunda-Arara, 1996; DeMartini, 1993; Carter, 2003;
Roberts, 1995; Alder, 1996).
MPAs are implemented for various purposes with several levels of protection and different management regimes (Baelde, 2005). Currently, MPAs are declared primarily for consumptive and non-consumptive uses, (Carter, 2003) or referred to as conservation or enhancive reserves (Halpern & Warner, 2003; Roberts, 2000). Conservation reserves provide protection to vulnerable habitats or species. Enhancive reserves serve to increase populations of fish stocks to benefit consumptive purposes. Each type of MPA involves distinct social, biological, and economic parameters that influence the utilization of the marine reserve and associated resources affecting implementation. Many MPA locations and boundaries are based on economics and public interest, overlooking how ecology and biology affect the area (Roberts, 2000). MPAs ideally should be implemented for biological and managerial motives and not for political convenience.
Constraints
Establishment of MPAs are supported by general principles but are constrained by a lack of specific or detailed knowledge (Ballantine, 1996). The results are not immediate and require years to determine significant changes directly associated with
MPAs (Grossman et al., 1997).
4 Current management for the protection of fish stocks involves strategies such as bag limits and quotas, size limits, and closures. Solutions to achieve sustainable harvests are increasingly accepted in the fishing industry but are sometimes thwarted by the negative effects imposed on local fishing economies by closures or quota systems, especially in areas of limited fishing grounds. The deployment of AR also causes controversy among scientists and managers. Without natural live bottom habitat or the presence of ARs, fish biomass is spread throughout a system. Once deployed, ARs recruit marine species by becoming places for food and shelter as well as spatial reference among a featureless habitat, allowing species to be exploited regularly from a known locale. However, if these ARs are designated as MPAs the fish that are attracted to these sites are protected and have the potential to increase surrounding biomass through reproductive output. Disregarding any food constraints, habitat scarcity is the only likely factor limiting reef populations of many marine species (Randall, 1963).
Specifically, species that are limited by the lack of hard bottom habitat are enhanced by critical habitat supplied by ARs (Pickering & Whitmarsh, 1997). However, it is difficult to measure the value of population changes without complete control of the system and knowledge of reef dynamics.
Proposed Research
The South Carolina Department of Natural Resources Marine Resources Division has an ongoing project using AR-MPAs, funded in part by the South Atlantic Fishery
Management Council (SAFMC). This study investigated the use of an AR-MPA established on April 29th 2003. The experimental site involved an artificial reef grouping
5 off the coast of South Carolina that is undisclosed to the public; known as Area 53. This thesis project represents a valuable opportunity for the study and understanding of artificial reef dynamics off the coast of South Carolina. The controlled “laboratory” settings provided by the unrevealed location of the Area 53 system allowed objective determination of the differences between protected and harvested sites, independent of the effects of unknown fish removals.
Research was performed on recreationally and commercially important finfish populations in the Snapper-Grouper complex that live off the coast of SC and use natural reefs and structures such as Area 53 for food and shelter. This research focused on gag grouper (Mycteroperca microlepsis) and scamp grouper (Mycteroperca phenax) as well as gray triggerfish (Balistes capriscus), black sea bass (Centropristis striata), vermillion snapper (Rhomboplites aurorubens), red porgy (Pagrus pagrus) and red snapper
(Lutjanus campechanus), which are considered among the most important commercial and recreational reef fish along the southeastern US.
The goal of documenting the dynamics of fish assemblages, biomass and comparability of experimental reefs to control reefs was accomplished with tag and recapture data as well as underwater (UW) video surveys. Tagging data was used to determine species site fidelity and derive population estimates. Statistical analyses were performed on fish abundance, size, and growth data collected over the extent of this experiment. Biodiversity among reef sites was also examined. Documenting the dynamics of fish assemblages, biomass, species diversity and comparability of experimental reefs to natural reefs was achieved through the following objectives:
6 Conduct length frequency distributions for the AR-MPA over the duration of the study and analyze mean length fluctuations Conduct population estimates using the Schnabel method for key species Conduct analysis on SCUBA video surveys to detect changes in abundance Determine the level of site fidelity of key reef species on artificial reef MPAs through tagging studies. Compare fish assemblages between harvested and protected areas to determine significant differences including biomass, mean length, and length frequency distributions. Collect and analyze recapture information to determine growth Compare the biodiversity and fish assemblages on adjacent natural live bottom closest to the artificial site known as Area 53. Determine if AR-MPAs serve as spawning sites and could increase spawning stock biomass. Make a preliminary assessment for the potential utilization of AR-MPAs as practical conservation management tools.
7
Material and Methods
Study Area
Area 53 consisted of a 2.5 km X 2.5 km square area on sandy bottom. Four hundred concrete cones were deployed in 33 meters of water at Area 53 to develop a
“hard bottom” community. Each cone unit measured 0.91 m in height, 1.22 m in base diameter and 0.70 m in top diameter and had variable size holes cast in the structure to enhance habitat complexity. A picture of this AR unit is located in Figure 1. The reef system was arranged in a four-corner or quadrant format with 100 cone units at each corner creating four small “patch” reefs. The corners were designated NE, NW, SE and
SW according to their geographic positions within the permitted area. Initial dives took place on the 27th of May 2003 to inspect the units position and deployment pattern. A reef community was allowed to develop on the site for one full year before sampling began. The first UW video surveys were completed from the 27-29th of July 2004.
Video Surveys
SCUBA video surveys were conducted to assess species composition and abundance throughout the experiment, totaling six surveys in all. Each corner of the reef had three distinct permanent structures (e.g. screw anchors) where video camera pans were taken to standardize data collection. At least two divers were used on every
8 sampling dive, one as a cameraman and at least one other to develop a comprehensive list of all species encountered. The cameraman performed a 360-degree turn at the level of the reef units in a one-minute interval. This was performed three times per site, once at each standardized location on the reef. If permanent structures could not be found due to adverse diving conditions and visibility issues, divers substituted a location that encompassed AR units. Standardized dive logs were collected and analyzed in conjunction with UW videos.
Two viewers analyzed the video data. Each one-minute rotation was analyzed at least three times as both viewers identified and recorded the exact number of distinguishable individuals of all fish species. If any counts differed by more than 3% the rotation was recounted. All information was stored and formatted for statistical analysis.
The observer diver’s logs were also used to determine biodiversity at each site.
Tagging Operations
Tagging operations were performed to establish site fidelity, develop population estimates and analyze growth data on Area 53. Nylon dart tags were used in this experiment and were color coded for each specific corner on the reef to allow divers to determine movement between reefs visually. A picture of nylon dart tags is shown in
Figure 2. Tags had unique numbers corresponding to their deployment location as well as contact information to allow returns if caught by recreational or commercial fishermen. From July 2004 through August 2005, a base of at least 340 fish were tagged and released on each site. An additional 200 tags were deployed on each site during tagging operations between March 2006-June 2006. Crews of six to eight personnel were
9 used to capture fish. No more than three individuals were used in tagging operations; one individual measured and identified the fish, one individual tagged the fish, and one individual recorded the data associated with each fish.
Hook and line as well as fish pots were used to obtain fish for tagging purposes.
Terminal gear used for fishing was composed of a two-way swivel, two three-way swivels, two 3/0 or 5/0 J-hooks, an eight oz. sinker and 50lb. test leader material. Squid and cigar minnows (Decapterus punctatus) were used as bait to catch all species. Fish pots were baited with squid and mackerel.
Each fish brought on board was processed as quickly as possible to minimize stress. A large saltwater holding tank was used to accommodate large fish catches until they could be tagged. Each fish was identified to species, measured (mm) in total length and fork length, and tagged with corresponding site tags. Fish were tagged on their left side, under the dorsal fin locking the tag dart through the pterigiophores (Figure 3). Tags were applied using a stainless steel canula, inserted at an approximately 45-degree angle to the vertical midline of the fish. Fish that showed evidence of expanded swim bladders were “degassed” using a syringe and an 18-gauge needle inserted under the midpoint of the pectoral fin to aid their descent to the reef.
The SCDNR/MRD vessel R.V. Palmetto anchored or drifted over the corresponding reef location for survey and tagging operations in 2004-2005. The
SCDNR/MRD vessel R.V. Silver Crescent was used for all but one cruise to Area 53 for the 2006 sampling operations. The SC Marine Patrol boat Fountain was used for the final
SCUBA survey due to mechanical problems with the R.V. Silver Crescent.
10 Harvesting Operations
Two corners of the artificial reef system were randomly selected to be harvested sites where intense exploitation of fish species occurred to simulate the effects of commercial and recreational fishing activities. On the two harvested sites, NW and SE, we attempted to remove as many fish as possible and document the effects of these removals on abundance levels and changes in species and size composition. For greatest effects, bag limits were not observed due to our limited opportunities to make trips to the sites. Conventional hook and line fishing tackle as well as spearfishing was used for harvesting to simulate recreational and commercial methods. The terminal fishing gear used for harvesting was the same as described in tagging operations above. The other two corners, NE and SW, were considered control sites and were not harvested to simulate a MPA.
Harvesting occurred at two separate time intervals. The first harvest operations were carried out after tagging operations in 2004-2005 occurring between May 2005 and
August 2005. After August 2005 both tagging and harvesting ceased until tagging operations were conducted again from March 2006 through June 2006. After the latter tagging operations, heavy harvesting was initiated from June 2006 to August 2006. Any species below legal size limits were tagged and released.
Tag-recapture data were analyzed for determination of site fidelity and spillover effects as well as growth statistics. Tag-recapture data were utilized for population estimates and further analysis of temporal fluctuations.
11 Data Analysis
Statistical analysis was performed on the data to determine any significant differences associated with fish responses to exploitation and protection. Statistical analyses were performed on length, abundance, and growth for all the sites utilizing both
UW video and tag-recapture data. Minitab Statistical Software was used in video abundance data, length analysis, and growth analysis. ANOVAs were used for a majority of tests and differences were revealed with Tukey’s Pairwise Comparison test using 95%
Confidence Intervals (95% CIs). Full models were used to account for much of the variability leaving specified characteristics to explain the remaining error values.
Variability due to time was removed from the error for the analysis of these statistics in order to identify changes over time. Residual plots for corresponding analyses were performed to confirm normality and model assumptions, which can be found in Appendix
I.
Video Analysis:
Videotape results were analyzed in this study to determine the abundance of finfish species as well as determine biodiversity through counts and identification of finfish species particular to each reef site. Video counts were broken up into three time intervals that followed tagging/harvesting operations: Tagging Interval (T1), Intermediate
Interval (T2), and Harvest Interval (T3). Observations were pooled and averaged to reduce variability and facilitate statistical analysis. The T1 videos included data obtained during tagging operations performed from November 2004 through May 2005. The T2 videos included data during harvesting operations from August 2005 through tagging
12 operations in May 2006. The T3 videos included data collected during harvest operations from July 2006 through December 2006.
Each site in this system had two video survey dates for each time interval. All species that could be clearly identified in the videos were counted and recorded.
However, only four species were utilized in statistical analysis of abundance. The species that were used in the abundance analysis were black sea bass (Centropristis striata), gray triggerfish (Balistes capriscus), gag grouper (Mycteroperca microlepsis), and scamp grouper (Mycteroperca phenax). These species were chosen based on their continual presence in all videos and non-schooling behavior that otherwise would have influenced statistical results. These species were also the most often tagged in our experiment.
Each individual rotation was summed with the counts from C. striata, B. capriscus, M. microlepsis, and M. phenax. The summed counts provided every site with six values for each of the three time intervals with one exception. The T1 video at the
NW site only analyzed one rotation because of faulty camera equipment that made analysis of the remaining two videos impossible. The summed values were analyzed with Minitab Statistical Software to reveal significant differences between protected and exploited sites.
Length Analysis:
Length analysis was also divided by three time intervals that followed tagging- harvesting operations as described in the Video Analysis section. The dates described for each time interval were: T1: 7/24/04-4/21/05; T2: 5/10/05-6/6/06; T3: 6/6/06-8/24/06. C.
13 striata and B. capriscus were the only two species used in length comparisons over the three time intervals. Other species lacked sufficient data for each site and time period making statistical analysis invalid due to failure of reaching adequate sampling size.
Length frequency distribution as well as mean lengths for these species were analyzed.
Growth and Recapture Analysis:
All individuals recaptured were recorded and analyzed for growth using number of days at large and total growth. Again, only C. striata and B. capriscus fulfilled statistical assumptions due to larger sample sizes and greater recapture rates than other species. A non-parametric test was used to determine significant differences so as not to assume sampling normality. A Mann-Whitney test was performed to determine significant values based on the differences of the medians. Recapture data also produced information on movement and site fidelity for several species.
Population Estimates:
Population estimates on each site were conducted from tag-recapture data using the Schnabel Method for multiple censuses. The Schnabel Method was used to determine the population estimates for C. striata. This method regarded each days catch as a separate census (Ricker, 1958). The assumptions for this method call for a stable population with no mortality or migration during the time the experiment is carried out.
These conditions were only approximately satisfied considering that recruitment and mortality may have been occurring during the study. A range of population estimates was produced for each site to reflect the consequences of tag shedding or tag loss. For
14 this reason, a 5% tag shedding value was used for the lower end of the range while a 20% tag loss was used to generate the upper end of the range. These estimates were used based on studies conducted by the Howard Laboratory in Sandy Hook, NJ and by the
Rhode Island division of Fish and Wildlife that determined tag loss in C. striata was between 9.5%-10.1% (Consensus Assessment Report).
Biodiversity Analysis:
The biodiversity of Area 53 was compared to biodiversity found on surrounding
NRs. NRs were chosen based on similar depths and for geographic proximity to Area 53.
Biodiversity of the NR areas were determined from both fishery dependent and fishery independent studies. The SCDNR Marine Resources Monitoring, Assessment, and
Prediction (MARMAP) program provided fishery independent data. MARMAP used chevron traps to assess the species composition of reefs in 30m depths. The fishery dependent data or commercial data was collected with bandit/snapper reels. Both of these data sets were obtained in 2004.
15
Results
Video Results
Minitab Statistical Software was used for analysis of abundance data. Species abundance refers to summed counts of black sea bass (C. striata), gray triggerfish (B. capriscus), gag grouper (M. microlepsis), and scamp grouper (M. phenax).
When all sites were pooled, the abundance of these four species differed significantly over the extent of the data collection period (ANOVA p=0.001). According to Tukey’s pairwise comparison test the abundance during T2 was significantly greater than the abundance of T3 at the 5% significance level (T2-T3 95% CIs = –52.27, -
12.06). The significant difference between the time intervals is explained when evaluating abundance among fished and unfished locations. Seasonal effects were not analyzed because of insufficient seasonal coverage for dive operations.
An ANOVA testing abundance between fished/unfished locations explained the significant difference (p=0.036). Fished locations had statistically lower abundance than unfished locations (Unfished-Fished 95% CIs = 0.9521, 28.01).
Analyses were then performed on each individual site. An ANOVA testing abundance versus individual sites did show a significant difference (p=0.040). The fished sites had significantly lower values for total abundance. The unfished SW site had
16 significantly higher abundance than the fished SE site (SE-SW 95% CIs = -52.00, -3.00).
The representation of individual site abundance can be seen in Figure 4.
Length Results
Black sea bass
C. striata lengths were tested for statistical differences between sites and between pooled fished/unfished locations. Length frequency distributions were evaluated between the fished and unfished location (Figure 5a&b). Size distributions for all sites were approximately equal at the start of the experiment prior to harvest. The fished locations demonstrate a shift toward larger individuals from T1 to T2 indicative of individual fish growth. However, the populations show a small shift toward smaller individuals from T2 to T3 as well as a decrease in the size range distribution, demonstrating the effects of exploitation of larger individuals. Length frequency distributions on unfished locations have a gradual shift toward larger individuals throughout the experiment. Even with minimal sampling effort, period T3 still shows a marked increase in the length frequencies among unfished locations as well as a broader range of fish sizes as seen in
Figure 5a.
Length frequencies were also run between each individual site for C. striata
(Figure 6a & b). The unfished sites (SW & NE) again show a marked shift toward the right throughout the duration of the experiment. The fished sites do not appear to have as great a shift toward the right from T1 to T2. From T2 to T3, the NW site not only has a shift toward smaller individuals but the range of size distribution decreases (Figure 6b).
17 The SE site also has a smaller range of size distribution while both the unfished sites exhibit a shift to the right as well as an increased length distribution.
Analysis of all C. striata mean lengths over the extent of the experiment showed a significant difference between T1 and T2 as well as T1 and T3 (T2-T1 95% CIs = 45.23,
56.95; T3-T1 95% CIs = 49.08, 64.94). This difference can be explained when comparing mean lengths between fished and unfished locations (ANOVA, p<0.001). C. striata mean lengths were significantly larger on unfished locations than on fished locations (Fished-Unfished 95% CIs= 9.96, 19.16), as indicated in Figure 7.
Statistical analysis on mean lengths was also performed on each individual site.
Analyses of C. striata mean lengths between all sites for the extent of the experiment were significantly different (ANOVA, p<0.001). The fished NW site had significantly smaller sized C. striata than all other sites (SW-NW 95 % CIs= 16.70,32.97, SE-NW 95
% CIs= 5.017, 20.77, NE-NW 95 % CIs= 6.62, 24.08). In addition, C. striata on the unfished SW site had significantly larger sized individuals than on the fished SE and unfished NE sites (SE-SW 95% CIs = -20.23, -3.554; NE-SW 95% CIs = -18.54, -0.321).
Individual site mean lengths for C. striata are shown in Figure 8.
Gray triggerfish
B. capriscus lengths were also analyzed using the same method as C. striata.
Length frequency distributions for B. capriscus between fished and unfished sites are shown in Figure 9a&b. The length frequency distributions were approximately equal at the start of the experiment prior to harvest operations. Fished locations have a small shift toward the right from T1 to T2. However, length distributions then shift back to the left,
18 responding to intense fishing pressure for the fished locations. Lengths at unfished locations increase throughout the duration of the experiment and have a larger range than fished length frequencies during the T3 interval.
B. capriscus mean lengths were tested for statistical differences between sites and between pooled fished/unfished sites. Analyses of all B. capriscus mean lengths over the extent of the experiment showed mean lengths in T1 were significantly lower than T2 and
T3 (T2-T1 95% CIs = 40.35, 62.97; T3-T1 95% CIs =27.89, 51.26). In addition, T2 had statistically larger mean lengths for B. capriscus than T3 (T3-T2 95% CIs = -22.70, -
1.47). This difference can be explained by comparing fished and unfished locations.
Analyses of B. capriscus mean lengths between fished and unfished locations were significant (ANOVA, p<0.001). B. capriscus mean lengths in unfished locations were significantly larger than mean lengths of fished locations (Unfished-fished 95% CIs: =
11.39, 28.13). Figure 10 represents B. caprsicus mean lengths comparing fished and unfished sites.
Analyses of B. capriscus mean lengths between individual sites were significantly different (ANOVA, p<0.001). The fished NW site had statistically lower mean lengths than the unfished SW site and the unfished NE site (SW-NW 95% CIs = 11.875, 43.12;
NE-NW 95% CIs = 7.89, 38.16). The unfished SW site had statistically higher mean lengths than the fished SE site (SE-SW 95% CIs = -33.25, -4.03). The fished SE had statistically lower mean lengths for B. capriscus than the unfished NE site (NE-SE 95%
CIs = 0.12, 28.21). Individual site mean lengths for B. capriscus are shown in Figure 11.
19
Recapture and Growth Results
Growth was extremely variable for both C. striata and B. capriscus. Sample distributions were not normal for C. striata or B. capriscus as seen in the corresponding box plots (Figures 12a&b). The shapes of distributions are skewed for both C. striata and B. capriscus.
Black sea bass growth
A Mann-Whitney test revealed that at a 10% significance level C. striata growth was significantly different between fished and unfished locations (Mann-Whitney test
0.0964). C. striata growth was significantly higher on unfished sites than fished sites at the 10% significance level but not at the 5% significance level. An overall growth curve for all black sea bass is seen in Figure 13. According to the overall growth curve for C. striata the average growth/day for the combined fished/unfished locations was 0.1372 mm/day. Figure 14 shows the comparison between fished and unfished locations. The average growth/day for fished sites was 0.1207 mm/day and average growth/day for the unfished sites was 0.1617 mm/day.
Gray triggerfish growth
According to the growth curve for B. capriscus the average growth/day for the combined fished/unfished locations was 0.1521 mm/day. Figure 15 shows the overall growth curve for B. capriscus. A Mann-Whitney test was also used to determine significant differences between fished and unfished location for B. capriscus growth.
20 There was no significance at the 5% or 10% significance level (Man-Whitney test 0.736).
There was no evidence of a difference in growth in B. capriscus between the fished and unfished locations
Recapture Data & Movement
There were a total of 389 recaptures over the duration of this project. Of these recaptures: 290 were C. striata, 52 were B. capriscus, 23 were Pagrus pagrus, 22 were
Mycteroperca phenax, 3 were Mycteroperca microlepsis, and 1 was a Rhomboplites aurorubens. A breakdown of recaptured species can be seen in Table 3.
There were ten incidents of movement between sites on Area 53 and one incident of movement off the reef system. Seven cases involved fish moving from unfished to fished locations. Movement appeared to be random and does not represent any trends.
There were a large number of recaptured individuals and resulting movement would correlate to actual movement in this reef system. The very limited of movement demonstrates strong site fidelity among species, especially C. striata and B. capriscus.
21 Population Estimates
The Schnabel Method as explained by Ricker (1958) was used to determine C. striata population estimates. The following information was gathered to determine population estimates:
Mt the total tagged fish at large at the start of the tth day (i.e. the number
previously marked less any accidentally killed at previous recaptures)
M ∑Mt, the total number tagged.
Ct the total sample taken on day t.
Rt the number of recaptures in the sample Ct.
R ∑ Rt the total recaptures during the experiment.
We wish to estimate:
N the population present throughout the experiment.
The short formula for estimating the population determined by Schnabel (1938):
∑( Ct Mt)
N = ______
R
Each tagging and harvesting operation was counted as a separate census trip.
After each operation, population estimates were completed based on the data collected and transformed into the equation. The number of tagged C. striata at large (Mt) were altered to account for an estimated 5% tag loss for the lower range and a 20% tag loss for the upper range. The following table contains the raw population estimates along with the ranges with 5% and 20% tag loss.
22 NW SE fished fished 20% tag 5% tag 20% tag 5% tag N= loss loss N= loss loss 7/27/2004 0 0 0 7/28/2004 0 0 0 8/17/2004 550 440 523 7/29/2004 0 0 0 11/3/2004 1179 943 1120 11/17/2004 4853 3882 4610 2/15/2005 2706 2165 2571 2/15/2005 4211 3369 4001 5/10/2005 2165 1732 2057 5/10/2005 1836 1469 1744 5/11/2005 2290 1832 2176 8/2/2005 1519 1215 1443 8/4/2005 2250 1800 2138 8/4/2005 1524 1219 1447 5/4/2006 2673 2139 2539 5/4/2006 1555 1244 1477 5/10/2006 2798 2239 2658 5/5/2006 1339 1071 1272 6/6/2006 1922 1538 1826 6/6/2006 1130 904 1074 6/29/2006 1896 1517 1801 6/7/2006 1108 887 1053 7/17/2006 1872 1498 1779 6/29/2006 1030 824 979 8/24/2006 2073 1658 1969 7/17/2006 1025 820 974 8/25/2006 2057 1646 1954 8/24/2006 1027 822 976 SW NE Unfished unfished 20% tag 5% tag 20% tag 5% tag N= loss loss N= loss loss 7/27/2004 0 0 0 7/27/2004 0 0 0 7/28/2004 0 0 0 11/3/2004 4064 3251 3861 8/18/2004 4628 3885 4614 2/15/2005 3691 2953 3506 2/16/2005 8148 6641 7886 4/21/2005 2390 1912 2271 3/31/2006 5404 4360 5178 3/31/2006 3587 2870 3408 5/10/2006 2173 1749 2077 5/5/2006 1079 863 1025 3/6/2007 2241 1801 2139 5/10/2006 1085 868 1031 6/6/2006 1017 814 966 3/6/2007 1017 813 966
The unfished SW site had the highest values for all sites ranging between 2139 and 2241 individuals. The fished NW site had the second highest values and ranged between 1954 and 2057 individuals. The fished SE site had population estimates ranging between 976 and 1027 individuals while the unfished NE site ranged between 966 and
1017 individuals. Values fluctuated based on sample size and recaptured individuals with each additional sampling trip. Table 4 holds all the values put into the Schnabel population model equation for each individual site.
23
Biodiversity
The species that were present on each Area 53 site were recorded throughout the study and are located in Table 1. The biodiversity of this system was collected over a two-year period and a total of 42 non-cryptic species were identified for all of Area-53 during the study. Information of fish species on NRs adjacent to Area 53 were collected from fishery dependent and fishery independent data Table 2. There were a total of 16 species collected with chevron traps and bandit/snapper reels on the surrounding NRs.
The ARs appear to host a wider range of species and biodiversity at this depth than NRs.
However, the species recorded on Area 53 were from a combination of trap, hook and line, and SCUBA observations whereas the NR collections included only trap and hook and line gear. Hook and line collections on Area 53 accounted for 9 species. However, comparing all of the available data sets indicates that species present on surrounding NRs are very similar to those found on Area 53. No important commercial or recreational species found on NRs were absent from the Area 53 sites.
Further Information:
We can confidently say there was no outside fishing that occurred on Area 53 until the last stages of this project. Unfortunately, there was unauthorized exploitation that occurred on Area 53 during the harvesting operations from November 2006 to
January 2007. There is limited information on the extent of fishing that occurred during the illicit harvests but the activity was terminated. A majority of the data were collected prior to this unauthorized exploitation and this activity presumably did not disrupt any
24 results prior to heavy harvesting. Information that could have been influenced by this harvesting included fish composition of unfished sites during heavy harvest. It was thought that little impact was caused to fish stocks on the reef and this was confirmed through additional SCUBA analysis and hook and line tagging operations on each site.
Therefore, the results can still be considered reliable and may have only been slightly altered due to unauthorized harvesting.
25
Discussion
This experiment revealed promising potential utilization of ARs as MPAs in temperate regions in the SAB. Deployment of this reef system took place in April 2003 and shortly after this time the AR units had already been colonized by benthos and fish.
The communities continued to grow throughout the progression of this experiment.
Nevertheless, the fish community by no means stabilized and data suggest a relatively rapid colonization and a slow, gradual process of maturation throughout this research.
This process on an artificial reef was also recognized in a ten-year study performed by
Relini et al. (2002) in Italy. They found even after ten years there was ample space for species to inhabit, continuing an increase in abundance and biomass. The structural heterogeneity of an AR promotes the filling of different niches as it ages, increasing the biodiversity and richness of marine organisms (Perkol- Finkle et al., 2006). Perkol-
Finkle et al. (2006) also argue that given sufficient time, an AR and neighboring NRs offering analogous structural features will become almost impossible to differentiate based on community structure. The results from this experiment support the use of ARs in the SAB as well as other temperate regions restricted by a scarcity of hard bottom habitat.
26
Video discussion
Underwater SCUBA surveys validated the transformations in abundance of finfish species. Visual census was an appropriate, non-destructive method by which to assess temporal changes in fish assemblages of ARs used as a management tool in coastal areas (Relini et al., 2002). This experiment showed a marked increase in the abundance of finfish in temperate regions on AR similar to that seen in other NR marine reserves in the Caribbean (Roberts, 1995). The implementation of ARs and additional critical habitat increase the environmental carrying capacity and thereby abundance and biomass of reef species (Polovina 1994, Bortone et al., 1994). The number of species increased over time for both fished and unfished sites on Area 53 and included species that depend on available food sources living on hard bottom (e.g. B. capriscus) as well as general demersal feeders (e.g. C. striata).
There was a significant decrease in abundance from T2 to T3. This decrease can be seen in the graph located in Figure 4. The effects of exploitation on the fished locations had a huge impact on the overall values for the T3 interval. Unfished locations had significantly more individuals of the four species Centropristis striata, Balistes capriscus, Mycteroperca microlepsis, and Mycteroperca phenax. Based on the figure, the trend was similar at all locations even though numbers were different. Other environmental factors could cause these changes such as strong currents or this could be a response to seasonal trends. The site is still relatively young and may not have reached a fairly stable state making it more susceptible to external factors.
27 Based on personal observation and statistical evidence, the SE site responded rapidly to the effects of fishing. During our last harvest trip, minimal time was spent drifting over the SE site due to severe decreases in catch rates. Fishermen would not waste time and effort on depleted and nonproductive fishing locales, therefore, we mimicked the thought process of fishermen and moved to our other harvest location. Our assumptions of decreased fish populations based on catch rates on the SE site were confirmed by subsequent SCUBA observations.
Length discussion
A large amount of information was gathered from length data for C. striata and B. capriscus. Results showed a definitive response to fishing effort for these species.
Statistical analyses were run on only these two species because of the abundance of data and fulfillment of sampling assumptions. The curves described in the length frequency graphs suggest that median values were well represented by mean lengths in each of these species. The results from both the length frequency distributions and mean length analyses support one another in the response of species populations among fished and unfished ARs. Fish were larger in unfished sites than fished sites in this experiment, similar to what has been shown in other studies (Roberts, 1995; Cole et al., 2000;
McClanahan & Mangi, 2000; Halpern, 2003) as well as greater representation on the right (larger) side of the length frequency distribution.
28 Black sea bass
The length frequency distribution and mean length data for C. striata supported one another in the results of this experiment. The shifting of lengths toward larger individuals in the unfished locations along with greater mean lengths were a positive outcome for the protected sites. These sites also have a larger range of size classes. Cole et al. (2000) also found species within MPAs had larger individuals than surrounding fished areas regardless of the reserve size. The fished sites initially had a shift toward larger fishes but either stabilized or shifted back toward the left after intense harvesting
(Figure 5&6). Larger fish are apparently more vulnerable (aggressive at taking bait) to fishing pressure causing a decrease in the number of larger individuals.
C. striata mean lengths increased over the extent of the experiment as T2 and T3 individuals were significantly larger than T1 individuals on all unfished sites. C. striata mean lengths were also significantly larger on unfished sites than fished sites. C. striata mean lengths showed that unfished or protected sites host larger sized individuals than sites that are open access fishing habitats. McClanahan & Mangi (2000) studied the mean size and abundance of fish in a Kenyan reserve and revealed catches of individual species declined with distances away from reserve edges, suggesting that spillover was occurring.
The mean lengths for both unfished sites continued to increase through each time interval (Figure 8). The fished NW site initially increased between T1 and T2 but decreased in size from T2 to T3, presumably from fishing pressure. It is interesting that the mean lengths of the fished SE site continued to rise even after T2 when very few individuals were seen in videos or caught during harvest operations. The few individuals
29 that were left appeared to be larger in size and raised the mean lengths value for the SE site.
The increase in length frequency distribution along with an increase in mean size among the unfished populations would result in an increase in reproductive output for these sites. The fished locations did have an initial increase but after intense exploitation the species responded with a smaller range of individuals as well as a shift toward smaller individuals. This would negatively impact the reproductive output among these harvested locations.
Gray triggerfish
Length frequency distributions and mean lengths for B. capriscus showed similar results. There was a definitive shift toward larger individuals among unfished locations.
Fished locations responded much like C. striata in shifting the length frequency distributions toward smaller individuals as a result of exploitation. These populations did not have many large fish and also had a narrow range of lengths after intense fishing.
Even limited sampling effort showed a shift toward larger individuals in the unfished locations between periods T2 and T3 as seen in Figure 9.
The mean lengths of B. capriscus on fished locations were significantly smaller than unfished locations as well. Tupper & Rudd (2002) also found that length, biomass, and density of certain species of reef fishes were significantly lower in fished zones compared to marine reserves in the Turks and Caicos Islands. Both unfished sites had significantly higher mean lengths than both fished sites during the T2 and T3 intervals.
The SE site began with higher mean lengths than all other sites and still resulted in
30 significantly lower values for mean length than both unfished sites as seen in Figure 11.
The mean lengths for both fished sites decreased from T2 to T3 while the mean lengths for both unfished sites increased between these two intervals (Figure 11).
Biomass
Biomass data were not directly collected during the course of this study.
However, if data from video surveys and length frequency/mean length are compared, fluctuations in biomass can be determined. A significant increase in abundance among unfished sites as well as a shift toward larger individuals would result in a substantial increase in the biomass of unfished locations. Conversely, a decrease in the abundance of individuals along with a decrease in length frequency distributions and smaller individuals would result in a substantial decrease in the biomass among fished sites.
MPA experiments have shown increased biomass within areas established in the
Caribbean (Roberts, 1995) and increased fish densities in Southern California MPAs
(Parnell et al, 2005). Halpern (2003) performed a review of 89 separate reserve studies and discovered for all species: 63% of reserves had higher density, 90% had higher biomass, 80% had larger organisms, and 59% had higher diversity inside reserves compared to outside the reserves. A study in the Caribbean found biomass of groupers, grunts, snappers, and parrotfish were significantly higher in MPA zones compared to exploited areas (Roberts, 1995). AR’s reproductive output and spawning potential would potentially increase if designated as MPAs. This could have a substantial positive effect on larval spillover and recruitment if a region-wide network of AR-MPAs was established in the SAB. There was also a significant increase in biomass at unfished
31 sites in a similar AR off the coast of South Carolina (Gold, 2001). This site was in shallower water (20m) but used the same concrete reef units.
Recapture and Growth Discussion
Recapture information was difficult to analyze given extreme variability and dominance of more recent recaptures. Many of the recaptures were collected during the latter stages of this experiment. Standardized personnel were used during the second tagging operations on Area 53, which could have resulted in more efficient operations, less tag loss and post tagging mortality. Inexperienced tagging personnel, improper degassing, and not releasing fish close enough to capture locations could have caused problems in the first tagging operations. It is believe that technique improved over the extent of this project and released individuals during the second tagging operations had higher survival rates.
Nonetheless, there was a significant difference in growth rate for C. striata at the
10% significance level using non-parametrics testing. C. striata among unfished locations showed a greater growth rate than fished locations. This is counterintuitive according to competition theory. The decrease in individuals in a reef system should allow greater access of feeding opportunities to other individuals, allowing faster growth rates at that site. A possible explanation for this phenomenon could be that more voracious faster growing individuals on the fished sites were exploited before they could potentially increase in size. Therefore, individuals left in the population were less active and slower growing, which would likely decrease the growth rate in the system.
32 B. capriscus growth rates between fished/unfished sites were similar to one another and had very similar distributions. Continued monitoring of B. capriscus growth rates using future recaptured individuals may reveal evidence of changes in growth rates between fished and unfished sites.
Migration Discussion
The key to a functional MPA is to understand how these areas increase the biodiversity and biomass as well as how they export benefits (i.e. eggs, larvae, juveniles, adults) over adjacent areas to replenish depleted stocks (Roberts, 1995). Spillover of commercially important fishes and larvae from MPAs are suggested to be significant factors in replenishing populations adjacent to reefs in Africa, Australia, New Zealand and the Caribbean but are dependent on a number of variables including target species, prior fishing pressures, reef morphology, and current patterns (McClanahan & Mangi,
2000; Ballantine, 1996). Some of the previously mentioned experiments as well as this one have noted that species are larger and more abundant within reserves, increasing the potential fecundity and reproductive output of those areas (Polacheck, 1990). An increase in fecundity would allow a greater number of larvae to be exported to surrounding systems, acting as sources of recruitment (Man et al., 1995).
MPA success also depends on targeted species exhibiting moderate to high site fidelity (Boersma & Parrish, 1999; Halpern & Warner, 2002). In most cases, highly migratory species would not be protected through MPAs because of their transitory nature and propensity to leave the reserve and in a sense “find” the fishermen (Boersma
& Parrish, 1999; McClanahan & Mangi, 2000). Species with moderate to high site
33 fidelity would be protected within the MPA and would export benefits through minimal transitory behavior outside the reserve as well as generate benefits through larval export.
Migration was minimal during the experiment demonstrating high site fidelity on this reef structure. There were very few recaptured individuals that exhibited any movement within the system. The large portion of fish moving from unfished to fished locations may be due to spillover effects but more likely is due to higher degrees of fishing effort on fished sites, therefore, more individual movements to these sites were detected. Only a fraction of a percent of the tagged population exhibited movement and only one species
(B. capriscus) was recaptured off the reef system. Therefore, establishment of MPAs over concrete ARs would ensure protection for many individuals and would enhance populations by increasing reproductive output. A moderate to high degree of site fidelity is a requirement for successful MPAs (Polacheck, 1990; Pickering & Whitmarsh, 1997;
Grossman et l., 1997; McClanahan & Mangi, 2000).
Reserve size and connectivity are additional issues relating to MPA effectiveness.
Studies have examined the size and connectiveness of MPAs that would best suit the species and habitat (Pickering & Whitmarsh, 1997). Regions proposed and selected as
MPAs must be dealt with on an individual basis because of their unique features and responses involving environmental factors and target species characteristics. Halpern &
Warner’s (2002) review of MPAs concludes that most stakeholders’ interests can be satisfied with a general design of a network of reserves.
34 Population estimates Discussion
The validity of the population estimates is questionable. The assumptions of the method used require a stable population with no mortality or recruitment. The sites did attract new recruits and suffered from mortality, especially the harvested locations. Also, the efficiency of the operations during the first section of this experiment was problematic as explained in the previous section. Therefore, the population estimates were probably overestimated in the beginning of the experiment that led to a cascade effect through the rest of the analysis. UW video and diver observations did not correspond with the population census method.
Lincoln-Peterson estimates were also attempted to determine population estimates. However, these results proved highly variable and did not appear to reflect the actual changes in population size. The lack of confidence does not negate the analysis method but reflects procedural difficulties of the tagging operations in the beginning stages of this experiment and violation of critical assumptions of the method. The inefficient tagging processes that occurred early on in the experiment could have affected the populations on the reefs and/or their estimation. Establishing population estimates could be conducted using recent tagging and recapture operations as well as additional sampling operations.
Biodiversity Discussion
The observed biodiversity of the Area 53 system was greater than on NRs, more than doubling the number of species present. Species composition on the NRs was conducted by fishing effort only and did not utilize any SCUBA video surveillance for
35 additional identifications. SCUBA video surveillance on the NRs in conjunction with fishing effort would undoubtedly increase the number of fish species identified.
Nonetheless, it is clear the AR system is fully capable of mimicking the diverse species assemblages of NRs. Area 53 has the potential to benefit the numerous species drawn to this system as well as protect the future populations as an established MPA.
Attraction versus Production
An important aspect of ARs is the highly disputed concept of attraction versus production on these artificial systems. Many papers have been published on the roles of
ARs serving as: 1) attraction devices that merely concentrate fish around hard bottom habitat without a net increase in fish abundance and biomass and 2) productive sites that enhance fish abundance through the creation of new habitat (Bohnsack, 1989; Grossman et al., 1997; Pickering & Whitmarsh, 1997; Brickhill et al., 2005). Support of the attraction hypothesis states the continual deployment of ARs coupled with an increase in fishing pressure would significantly reduce reef fish populations (Bohnsack, 1989).
Grossman et al. (1997) adds that fish are more susceptible to exploitation because the biomass that would otherwise be spread among featureless topography would be concentrated to a known location without a net increase in biomass. The amount of hard bottom habitat available is not restricting populations so there is no net increase in fish abundance (Brickhill et al., 2005).
Alternatively, the opposing theory states that the addition of critical habitat increases the area’s carrying capacity (Bohnsack, 1989; Brickhill et al., 2005). Increased shelter and feeding opportunities encourage fishes to settle to reefs and a greater number
36 of juveniles are able to settle and survive to spawn as adults, contributing new individuals to the population. The AR promotes a net increase in abundance because new individuals can be accommodated by new habitat (Brickhill et al., 2005). Species that are dependent on hard bottom habitat for food and shelter such as B. capriscus and C. striata would be enhanced with added critical habitat while others that show less substrate dependency may not improve. Area 53 has shown enhancement of protected populations that are closely dependent upon hard substrate (e.g. B. capriscus and C. striata). The SAB is an environment where many of these species depend on hard bottom habitat but are constrained by the paucity of these habitat types. Many of the former experiments performed on MPAs were located in areas with high productivity, encompassing an abundance of contiguous NRs. Implementation of MPAs in regions with limited NRs would have greater consequences by affecting fishermen who rely on few available areas for income. This is where ARs have their greatest potential. Deploying ARs in low productivity areas could potentially create added benefits similar to those offered by NRs by protecting spawning stocks of fishes. The potential of ARs to effectively mimic NR may allow them to achieve the same results as NR-MPAs.
This AR system has proven the ability to increase abundance, lengths, and biomass of commercial and recreationally important species. The additional individuals on this reef and surplus of larval numbers allow a greater number of juveniles to mature and reproduce themselves (Sale, 1980).
The Area 53 system initially acted as an attractant in a sandy bottom environment where fish could seek shelter and/or food. A year after deployment of AR units on Area
53, many species of fish were cited and recorded. It is known from age/length keys that
37 individual species were older than one year and must have recruited to the AR as adults or subadults. However, we are also confident that as this system matured, species were utilizing the AR units and the surrounding area as reproductive sites even though spawning was not directly observed. Hundreds of fishes tagged and harvested during data collection were reproductively active and diver’s observations also recorded B. capriscus protecting nesting mounds on Area 53. The results and observations recorded from this research suggest that ARs have the capability of enhancing fish populations that depend on hard bottom topography.
Once established, adults on Area 53 have shown strong site fidelity and some species have been monitored as sexually active, utilizing Area 53 as a spawning site.
Migration of individual fishes and larvae away from their natal sites is a key component in developing the proper size and characteristics of an MPA to insure spillover is occurring into surrounding areas (DeMartini, 1993; McClanahan & Mangi, 2000; Lauck et al., 1998). Various species including C. striata, B. capriscus, and R. aurorubens were determined to be reproductively active when they were brought on board. Although spillover of adults was not yet evident from our observations it may occur in the future as populations increase and mature. The lack of spillover of juveniles and adults is however compensated by the function of Area-53 as a spawning refuge. Polacheck (1990) stated that a potential effect of a refuge is a shift in the age distribution towards older individuals. This shift in the age distribution augmented by enlarged body weight can result in substantial increases in the spawning biomass. Area 53 has revealed an increase in the abundance of fish as well as the size of fish on protected AR habitats that would create a substantial increase in the reproductive output in the SAB by supplying adjacent
38 reefs with larval supply and recruits as well as providing additional habitat for new recruits.
Compliance and Additional Research
A key component to the effectiveness of MPAs is user compliance. Informing the community and including them in the implementation process is important for a number of reasons. Successful MPAs should promote sustainable fisheries, where profit opportunities arise from the emigration of commercially and recreationally significant fish species (Tupper & Rudd, 2002). Reserves designed to mitigate losses incurred to fishing communities from closure of fishing grounds should provide an increase in catch rates through spillover (Halpern & Warner, 2003; Carter, 2003). MPA studies have shown fishery compliance is possible under successful reserve design (Roberts et al.,
2001; Lauck et al., 1998).
Calculating the effectiveness of MPAs, both natural and artificial, is critical in evaluating these potential tools for the conservation and enhancement of overexploited fish stocks. Utilizing AR-MPAs as a management tool may enhance biodiversity and prove to be very important to marine conservation efforts. AR-MPAs would accomplish the benefits that NRs offer while minimizing impacts on user groups. Any type of MPA should encompass a set of objectives such as safeguarding traditional sustainable uses, serving as research stations, providing ecological restoration, or guaranteeing public access (Alder, 1996). AR-MPAs can fulfill these objectives as well as various others without producing the harmful effects on traditional fishing grounds.
39 The limited hard bottom areas in the SAB generate intense pressure on resources in these communities. The introduction of various AR structures may transfer and alleviate pressure caused by human activities off of adjacent NRs (Leeworthy et al.,
2006). Intense exploitation on NRs may disrupt reef dynamics but ARs could supply additional grounds for many valuable resources, dissipating the stress in the system.
Valuable resources include fishing objectives, pharmaceutical prospecting, and other extractive uses as well as recreational diving areas, nursery grounds, and research/education tools (Adler, 1996; Carter, 2003; Boersma & Parrish, 1999). An important avenue for additional research in ARs as MPAs involves increasing the populations of commercially overfished species and providing non-consumptive opportunities.
Additional data collection that could have aided in this project would involve more precise biomass analysis and tag retention studies. For example, double tagging several individuals and determining the percentage of remaining tags could determine the tag retention percentage. Also using passive integrated transponders (PIT) tags along with visual tags would have aided in calculating tag retention information.
Weighing a number of individuals in conjunction with length and species data could have provided precise biomass information. A small scale used to weigh individuals before they were released or as they were harvested would have provided accurate length/weight keys so that accurate biomass data from each site could have been calculated and analyzed statistically.
In addition, Area 53 has the ability to utilize acoustic tags that could precisely indicate when certain species are using the reef system and when they are away from the
40 site. This information may reveal the level of dependence that species exhibit for this hard-bottom habitat.
41
Conclusions
This studies’ results support the potential utilization of created “artificial live– bottom” areas as MPAs and documented the succession of finfish species, levels of growth, and responses of fish species on this type of reef assemblage. This research increased understanding of AR-MPAs to fish populations by analyzing species response to the pressures caused by commercial and recreational fishing. Taking a low productive area such as sandy bottom area and creating a fertile region through an AR-MPA fulfills the purpose of having a beneficial reef without excluding fishermen from traditional fishing sites. An arbitrary study comparing 30 marine research papers reported almost all
(93%) recommended marine reserves to maintain and enhance biodiversity for fisheries management and tourism (Boersma & Parrish, 1999).
The research conducted on Area 53 also uncovered the ability of an AR to serve as a productive spawning site and mimic the effects of NRs. Spawning activity was confirmed by observation of B. capriscus, C. striata, and R. aurorubens with hydrated eggs during harvesting operations. In addition, diver’s observed B. capriscus protecting nesting mounds.
Few studies have shown definitive results when experimenting with MPAs because of a lack of control over removals. The complete control over exploitation on
Area 53 was a significant advantage in providing a scientifically sound experiment on the
42 use of AR-MPAs. The ability to demonstrate similarities between fish communities on
AR-MPAs and on NRs is information necessary for evaluating future utilization of AR-
MPAs for management.
The use of marine reserves could change the way fisheries conservation management operates throughout the world’s oceans. This experiment could be the building block toward the goal of replenishing fishing stocks without causing vast negative effects to the fishing community. Learning to integrate all the significant aspects from experimental design into MPA deployment can aid in the effort to enhance biodiversity and biomass among exploited fishes as well as benefiting fisheries and the community.
Species that are limited to hard-bottom habitat and their associated resources can be effectively enhanced with the introduction of artificial reefs. The results from this study prove that hypothesis. The increase in abundance and lengths results in an overall increase in biomass that could concurrently increase the reproductive output in the SAB if a significant network of AR-MPAs were established. Individuals on protected AR such as Area 53 have the potential to increase reproduction and reproductive potential through larval export. Deployment of ARs in areas with a scarcity of natural hard bottom habitat such as in the SAB have the potential to increase overall biomass and reproductive output that could aid overexploited reef-associated finfish populations.
43
Literature Cited
Alder, J. 1996. Have Tropical Marine Protected Areas Worked? An Initial Analysis of
Their Success. Coastal Management. 24:97-114.
Baelde, P. 2005. Interaction between the implementation of marine protected areas and
right-based fisheries management in Australia. Fisheries Management and
Ecology. 12:9-18.
Ballantine, Bill. 1996. ‘No-take” marine reserve networks support fisheries. Developing
and Sustaining World Fisheries Resources. 702-706.
Boersma, P. Dee & Parrish, Julia K. 1999. Limited abuse: marine protected areas, a
limited solution. Ecological Economics. 31:287-304.
Bohnsack, J.A. 1989. Are high densities of fishes at artificial reefs the result of habitat
limitation or behavioral preferences? Bulletin of Marine Science. 44: 631-645.
44 Bortone, S.A., Martin, T., Bundrick, C.M. 1994. Factors affecting fish assemblage
development on a modular artificial reef in a northern Gulf of Mexico estuary.
Bulletin of Marine Science. 55: 319-332.
Brickhill, M.J., Lee, S.Y., Connolly, R.M. 2005. Fishes associated with artificial refs:
attributing changes to attraction or production using novel approaches. Journal of
Fish Biology. 67: 53-71.
Carter, David W. 2003. Protected areas in marine resource management: another look at
the economics and research issues. Ocean & Coastal Management. 46:439-456.
Charbonnel, E., Serre, C., Ruitton, S. Harmelin, J., Jensen, A. 2002. Effects of increased
habitat complexity on fish assemblages associated with large artificial reef units
(French Mediterranean coast). Journal of Marine Science. 59: S208-S213.
Clark, Colin W. 1996. Marine reserves and the precautionary management of fisheries.
Ecological Applications. 6(2):369-370.
Cole, Russel G., Villouta, Eduardo, & Davidson, Robert J. 2000. Direct evidence of
limited dispersal of the reef fish Parapercis colias (Pinguipedidae) within a
marine reserve and adjacent fished areas. Aquatic Conservation of Marine and
Freshwater Ecosystems. 10:421-436.
45 Consensus Assessment Report. Assessment of the Northern stock of black sea bass. SAW
Coastal/Pelagic Working Group. SARC 39. Woods Hole, MA. May 4, 2004.
DeMartini, Edward E. 1993. Modeling the potential of fishery reserves for managing
Pacific coral reef fishes. Fishery Bulletin. 91: 414-427.
Gold, Hansje. 2001. Impact of the removal of black sea bass (Centropristis striata) from
artificial reef structures in the South Atlantic Bight. M.S. Thesis, College of
Charleston. 105.
Grossman, G.D., Jones, G.P., Seaman Jr., W.J. 1997. Do artificial reefs increase regional
fish production? A review of existing data. Artificial Reef Management. 22: 17-
23.
Halpern, Benjamin S. 2003. The impact of marine reserves: Do reserves work and does
reserve size matter?. Ecological Applications. 13(1):S117-S137.
Halpern, Benjamin S., Warner, Robert R. 2002. Marine reserves have rapid and lasting
effects. Ecology Letters. 5:361-366
Halpern, Benjamin S., Warner, Robert R. 2003. Matching Marine reserve design to
reserve objectives. Proceedings of the Royal Society of London. 270:1871-1878.
46 Kauppert, Petra Akiko. 2002. Feeding habits and trophic relationships of an assemblage
of fishes associated with a newly established artificial reef off the South Carolina.
M.S. Thesis, College of Charleston. 123pp.
Lauck, T., Clark, C., Mangel, M., & Munro, G.R. 1998. Implementing the precautionary
principle in fisheries management through marine reserves. Ecological
Applications. 8(1):S72-S78.
Leeworthy, V.R., Maher, T., & Stone, E.A. 2006. Can artificial reefs alter user pressure
on adjacent natural reefs?. Bulletin of Marine Science. 78(1):29-37.
Lindholm, J., Auster, P.J., Ruth, M., & Kaufman, L. 2001. Modeling the effects of
fishing and implications for the design of marine protected areas: Juvenile fish
responses to variations in seafloor habitat. Conservation Biology. 15(2):424-437.
Man, Alias, Law, Richard, & Polunin, Nicholas V.C. 1995. Role of marine reserves in
recruitment to reef fisheries: A metapopulation model. Biological Conservation.
71:197-204.
McClanahan, T.R., & Mangi, S. 2000. Spillover of exploitable fishes from a marine park
and its effect on the adjacent fishery. Ecological Applications. 10(6):1792-1805.
47 McClanahan, T.R., Kaunda-Arara, B. 1996. Fishery recovery in a coral-reef marine park
and its effect on the adjacent fishery. Conservation Biology. 10: 1187-1199.
McNeill, S.E., & Fairweather, P.G. 1993. Single large or several small marine reserves?
An experimental approach with seagrass fauna. Journal of Biogeography. 20:429-
440.
Parnell, P.E., Lennert-Cody, C.E., Geelen, L., Stanley, L.D., & Dayton, P.K. 2005.
Effectiveness of a small marine reserve in southern California. Marine Ecology
Progress Series. 296:39-52.
Perkol-Finkel, S., Shashar, N., & Benayahu, Y. 2006. Can artificial reefs mimic natural
reef communities? The roles of structural features and age. Marine Environmental
Research. 61:121-135.
Pickering, H. Whitmarsh, D. 1997. Artificial reefs and fisheries exploitation: a review of
the ‘attraction versus production’ debate, the influence of design and its
significance for policy. Fisheries Research. 31: 39-59.
Polacheck, T. 1990. Year around closed area as a management tool. Natural Resource
Modeling. 4: 327-354.
Polovina, J.J. 1994. Function of artificial reefs. Bulletin of Marine Science. 55: 258-263.
48
Randall, J.E. 1963. An analysis of the fish populations of artificial and natural reefs in the
Virgin Islands. Caribbean Journal of Science. 3:31-47.
Relini, G., Relini, M., Torchia, G., Palandri, G. 2002. Ten years of censuses of fish fauna
on the Loano artificial reef. ICES Journal of Marine Science. 59: S132-S137.
Ricker, W.E. 1958. Handbook of computations for biological statistics of fish
populations. Fisheries Research Board of Canada. Ottawa. 300pgs.
Roberts, Callum M. 1995. Rapid build-up of fish biomass in a Caribbean marine reserve.
Conservation Biology. 9(4):815-826.
Roberts, Callum M. 2000. Selecting marine reserve location: optimality versus
opportunism. Bulletin of Marine Science. 66: 581-592.
Roberts, C.M, Bohnsack, J.A., Gell, F., Hawkins, J.P, & Goodridge, R. 2001. Effects of
marine reserves on adjacent fisheries. Science. 294(5548):1920-1924.
SAFMC. South Atlantic Fisheries Management Council. South Atlantic Update. Summer
2006.
49 Sale, P.F. 1980. The ecology of fishes on coral reefs. Oceanography and Marine Biology.
An Annual Review. 18: 367-421.
SCDNR/MRD. South Carolina Department of Natural Resources Marine Resource
Division. http://www.dnr.sc.gov/marine/pub/seascience/artreef.html.
Schnabel, Z. E. 1938. The estimation of the total fish population of a lake. American
Mathematics Monthly. 45: 348-352.
Sherman, R.L., Gilliam, D.S., Speiler, R.E. 2002. Artificial reef design: void space,
complexity, and attractants. Journal of Marine Science. 59: S196-S200.
Tupper, M, & Rudd, M. A. 2002. Species-specific impacts of a small marine reserve on
reef fish production and fishing productivity in the Turks and Caicos Islands.
Environmental Conservation. 29(4):484-492.
Walker, Brian K., Henderson, Bruce, Speiler, Richard E. 2002. Fish assemblages
associated with artificial reefs of concrete aggregates or quarry stone offshore
Miami Beach, Florida, USA. Aquatic Living Resources. 15:95-105.
World Resources Institute. 1996. World Resources: A guide to the global environment:
The urban environment 1996-1997. Oxford University Press. Oxford. 365pp.
50
Figures
Figure 1. An artificial reef unit used by the SCDNR and deployed at Area 53. This picture was taken six months after units were deployed off the coast of Charleston, SC. Photo by R.M. Martore.
51
Figure 2. Nylon dart tags used in marking and identifying individual fish. Tags are color-coded for visual reference according to respective reef orientation and also contain unique identification numbers as well as contact numbers if found.
52
Figure 3. Tagged gray triggerfish on the left side of the body. Tags were inserted past the pterigiophores to ensure a solid holding position.
53
Figure 4. Fluctuations in individual site abundance based on the four identified species: C. striata, B. capriscus, M. phenax, and M. microlepsis. The NW and SE sites were fished locations. Note the sharp decrease from T2 to T3 on the SE site.
Video Abundance
100 NW 90 (fished) 80 SW 70 (unfished) 60 SE 50 (fished) 40 NE Average Counts 30 (unfished) 20 10 0 1 2 3 Time Interval
54
Figure 5a. Centropristis striata length frequency distribution between fished and unfished sites during the three time intervals.
C. striata Length Frequencies Normal
Fished Locations Unfished Locations 180 240 300 360 420 480 540 F-T1 Mean 326.4 7/24/04-4/21/05 StDev 60.98 40 N 590 T1 Uf-T1 Mean 315.5 20 StDev 58.74 N 563 0 F-T2 y Mean 358.6
c 5/10/05-6/6/06
n 40 StDev 49.22
e T2
u N 510
q 20 Uf-T2
e Mean 389.1 r
F StDev 42.00 0 N 333 F-T3 40 6/6/06-8/24/06 Mean 354.2 T3 StDev 40.20 20 N 309 Uf-T3 0 Mean 432.5 180 240 300 360 420 480 540 StDev 62.72 C. striata Length (mm) N 82
55
Figure 5b. Centropristis striata trend lines for corresponding fished and unfished locations during the three time intervals.
Length Frequency of C. striata
Fished Unfished
180 240 300 360 420 480 540 0.010 Time Interval 1 0.008 2
3 e
g Fished a 0.006
t Mean StDev N n
e 326.4 60.98 590 c
r 358.6 49.22 510
e 0.004
P 354.2 40.20 309 Unfished Mean StDev N 0.002 315.5 58.74 563 389.1 42.00 333 432.5 62.72 82 0.000 180 240 300 360 420 480 540 C. striata Length (mm)
56
Figure 6a. Centropristis striata length frequency distribution for each individual site.
C. striata Length Frequencies Individual Sites Mean 323.9 StDev 66.40 N 291 SE (fished) NE (unfished) Mean 320.6 NW (fished) SW (unfished) StDev 60.31 180 240 300 360 420 480 540 180 240 300 360 420 480 540 N 330 Mean 328.9 40 StDev 55.19 7/27/04-4/21/05 N 299 Mean 308.3 StDev 55.78 N 233 20 Mean 356.1 StDev 50.64 N 241 Mean 394.3 StDev 38.21 N 163 0 40 Mean 360.8 5/10/05-6/6/06 StDev 47.89
y N 269
c Mean 384.2
n StDev 44.90
e 20 N 170
u Mean 348.9
q StDev 37.50
e N 264
r Mean 427.9
F StDev 62.49 40 0 N 55 Mean 385.0 6/6/06-8/24/06 StDev 42.06 N 45 Mean 441.9 StDev 63.30 20 N 27
0 180 240 300 360 420 480 540 180 240 300 360 420 480 540 C. striata Length (mm)
57
Figure 6b. Centropristis striata trend lines for individual sites during the three time intervals.
Length Frequency of C. striata
Time Fished Unfished Interval 180 240 300 360 420 480 540 1 2 NW SW 0.0100 3
0.0075 NW Mean StDev N 0.0050 323.9 66.40 291
356.1 50.64 241 e
g 0.0025 348.9 37.50 264
a SW t Mean StDev N n 0.0000
e 320.6 60.31 330
c 0.0100
r SE NE 394.3 38.21 163 e
P 427.9 62.49 55 0.0075 SE Mean StDev N 0.0050 328.9 55.19 299 360.8 47.89 269 0.0025 385.0 42.06 45 NE Mean StDev N 0.0000 308.3 55.78 233 180 240 300 360 420 480 540 384.2 44.90 170 C. striata Length (mm) 441.9 63.30 27
58
Figure 7: Centropristis striata mean lengths are compared between fished and unfished locations. This graph is in support of the length frequency distributions and shows how unfished locations have a steady increase in mean length throughout the experiment and into future sampling trips.
C. striata Mean Length: Fished vs Unfished Sites
440.00
420.00
400.00 Fished
380.00 Unfished
360.00
Mean Length (mm) 340.00
320.00
300.00 T1 T2 T3 Time Interval
59
Figure 8: Centropristis striata mean lengths between all the sites.
Black Sea Bass Mean Lengths
455.00 435.00 415.00 NW 395.00 (fished) 375.00 SW 355.00 335.00 SE Mean Length (mm) 315.00 (fished) 295.00 NE 275.00 T1 T2 T3 Time Interval
60
Figure 9a: Length frequency distribution for B. capriscus comparing fished and unfished locations.
Length Frequency of B. capriscus Fished locations Unfished locations 250 300 350 400 450 500 550 600 F-T1 Mean 395.2 30 T1 StDev 69.43 N 106 Uf-T1 15 Mean 389.1 StDev 58.93 N 193 0 F-T2 Mean 430.8
y 30
c T2 StDev 56.79 n
e N 202
u Uf-T2 15
q Mean 448.9 e
r StDev 55.91 F N 111 0 F-T3 30 T3 Mean 412.2 StDev 49.72 N 319 15 Uf-T3 Mean 475.6 StDev 60.29 0 N 50 250 300 350 400 450 500 550 600 B. capriscus lengths (mm)
61
Figure 9b: Balistes capriscus length frequency distribution trend lines are shown to illustrate the responses to fishing pressure by fished and unfished populations.
Length Frequency of B. capriscus Normal Fished Locations Unfished Locations 250 300 350 400 450 500 550 600 Time Int 0.009 1 2 0.008 3
0.007 Fished locations 0.006 Mean StDev N
y 395.2 69.43 106 t i 0.005
s 430.8 56.79 202 n
e 0.004 412.2 49.72 319
D Unfished locations Mean StDev N 0.003 389.1 58.93 193 448.9 55.91 111 0.002 475.6 60.29 50 0.001
0.000 250 300 350 400 450 500 550 600 B. capriscus lengths
62
Figure 10: Balistes capriscus mean lengths are compared between fished and unfished locations.
Gray Triggerfish Lengths: Fished vs Unfished Sites
490.00
470.00
450.00 Fished Unfished 430.00
410.00 Mean Lengths (mm)
390.00
370.00 T1 T2 T3 Time Interval
63
Figure 11: Balistes capriscus mean lengths are compared between each individual site.
Gray Triggerfish Mean Length NW 500.00 (fished) 480.00 SW 460.00 440.00 SE (fished) 420.00 NE 400.00
380.00 Mean Length (mm) Length Mean 360.00 T1 T2 T3 Time Interval
64
Figure 12a: Box plot for C. striata on growth/day between fished and unfished locations. Note the skewed population samples toward small values causing a non-normal population.
Boxplot of Growth/Day 1.4
1.2
1.0 y
a 0.8
D
/
h t
w 0.6
o
r G 0.4
0.2
0.0
1 2 Fished/Unfished
65
Figure 12b: Box plot for B. capriscus on growth/day between fished and unfished locations. Note the skewed population samples toward small values causing a non- normal population.
Boxplot of Growth/Day
1.0
0.8 y
a 0.6
D
/
h
t w
o 0.4
r G
0.2
0.0
1 2 Fished/Unfished
66
Figure 13: Centropristis striata growth curve for recaptured individuals. The equation for growth (mm) per day was determined using all recaptured C. striata.
BSB Growth: All recaptures
140
120 y = 0.1367x + 0.1678 R2 = 0.6101 100
80
60 Growth (mm) Growth 40 All Recaptures Linear (All Recaptures) 20
0 0 100 200 300 400 500 600 700 Days at Large
67
Figure 14: The growth (mm) per day was calculated between fished and unfished locations for C. striata populations.
C. striata Growth: Fished vs. Unfished
Fished Growth 140 Unfished Growth Linear (Fished Growth) 120 y = 0.1587x + 1.1119 Linear (Unfished Growth) R2 = 0.5797 100
80
60 Growth (mm) y = 0.1214x - 0.2693 R2 = 0.6934 40
20
0 0 100 200 300 400 500 600 700 Days at Large
68
Figure 15: The overall growth (mm) per day was calculated for B. capriscus populations.
Gray Triggerfish Growth
160
140 y = 0.154x - 0.6799 2 120 R = 0.5402
100
80 All Sites 60 Growth (mm) Linear (All Sites) 40
20
0 0 100 200 300 400 500 600 700 800 Days at Large
69
Tables
70 Table 1: Species caught or identified on each site.
Common Name Scientific Name NW Site SW Site SE Site NE Site Black sea bass Centropristis striata X X X X Bank Seabass Centropristis ocyurus X X X Gray Triggerfish Balistes capriscus X X X X Queen Trigger Balistes vetula X Scamp grouper Mycteroperca phenax X X X X Gag grouper Mycteroperca microlepsis X X X X Warsaw Grouper Epinephelus nigritus X Red Snapper Lutjanus campechanus X X X X Vermillion snapper Rhomboplites aurorubens X X X X Red Porgy Pagrus pagrus X X X X Whitebone Porgy Calamus leucosteus X Banded Rudderfish Seriola zonata X Greater Amberjack Seriola dumerili X X X X Almaco Jack Seriola rivoliana X X X X White Grunt Haemulon plumierii X X X X Blue Angelfish Holacanthus bermudensis X X X X Atlantic Spadefish Chaetodipterus faber X X X X Spottail Pinfish Diplodus holbrooki X X X X Planehead Filefish Stephanolepis hispidus X X X X Tomtate Haemulon aurolineatum X X X X Margate Haemulon album X Southern Hake Urophycis floridana X X Barracuda Sphyraena barracuda X X X X Sand Perch Diplectrum formosum X Cubbyu Pareques acuminatus X X X Honeycomb Cowfish Acanthostracion polygonius X Pearly Razor Xyrichtys novacula X Sand tilefish Malacanthus plumieri X Blue Runner Caranx crysos X X X Jacknife fish Equetus lanceolatus X Spanish Hogfish Bodianus rufus X Loggerhead turtle Caretta caretta X X X X Frogfish Antennarius Sp. X Nurse Shark Ginglymostoma cirratum X X Spotted Moray Gymnothorax moringa X X Lionfish Pterois volitans X Greater soapfish Rypticus saponaceus X Round scad Decapterus punctatus X X X Scup Stenotomus chrysops X Reef Butterfly fish X Blenny X X X X Ocean sunfish Mola mola X X
71
Table 2: Species list on adjacent natural reefs using fishery dependent and independent data.
Fishery Fishery Common Name Species dependent independent Banded Rudderfish Seriola zonata - 1 Bank Sea Bass Centropristis ocyurus 32 72 Black Sea Bass Centropristis striata 112 1080 Dwarf Sand Perch Diplectrum bivittatum 1 - Mycteroperca Gag microlepis 1 - Gray Triggerfish Balistes capriscus 34 48 Greater Amberjack Seriola dumerili 1 - Knobbed Porgy Calamus nodosus 1 - Leopard Toadfish Opsanus pardus - 1 Pinfish Lagodon rhomboides - 23 Red Grouper Epinephelus morio 5 - Red Porgy Pagrus pagrus 45 90 Red Snapper Lutjanus campechanus 19 - Sand Perch Diplectrum formosum - 54 Scamp Mycteroperca phenax 14 3 Scup Stenotomus chrysops - 830 Spottail Pinfish Diplodus holbrookii 10 - Haemulon Tomtate aurolineatum 18 124 Rhomboplites Vermilion Snapper aurorubens 354 35 White Grunt Haemulon plumeri 40 2 Yellowtail Snapper Ocyurus chrysurus 2 - Total number of species 16 13
72
Table 3 Top six species recaptured throughout the duration of the experiment.
Number Number Number of Overall Recap Site Species Caught tagged recpatures Rate NW C. striata 783 342 80 0.234 B. capriscus 245 89 14 0.157 M. microlepsis 9 2 1 0.500 M. phenax 28 14 4 0.286 P. pagrus 88 39 7 0.179 R. aurorubens 234 85 1 0.012
SW C. striata 540 455 45 0.099 B. capriscus 160 155 4 0.026 M. microlepsis 7 7 0 0.000 M. phenax 16 16 3 0.188 P. pagrus 65 66 9 0.136 R. aurorubens 0 0 0 0.000
SE C. striata 620 325 102 0.314 B. capriscus 390 106 24 0.226 M. microlepsis 8 5 2 0.400 M. phenax 32 15 15 1.000 P. pagrus 110 82 6 0.073 R. aurorubens 52 25 0 0.000
NE C. striata 425 336 63 0.188 B. capriscus 189 171 10 0.058 M. microlepsis 3 2 0 0.000 M. phenax 5 5 0 0.000 P. pagrus 119 116 1 0.009 R. aurorubens 11 10 0 0.000
73
Table 4: Population estimates for C. striata using the Schnabel method (Schnabel 1938). The lower threshold used a 5% tag loss factor while the upper threshold used a 20% tag loss factor.
NW fished
Number Number # tagged at 5% at large 20% at large Recaptures Sum Sum 5% tag caught (Ct) tagged large (Mt) (Mt5) (Mt20) (Rt) Sum Recaps (R) Ct * Mt (Ct*Mt) N= (Ct*Mt5) (CtMt5) loss 7/27/2004 111 111 0 0 0 0 0 0 0 0 0 0 0 8/17/2004 40 38 110 105 88 8 8 4400 4400 550 4180 4180 523 11/3/2004 34 34 148 141 118 0 8 5032 9432 1179 4780 8960 1120 2/15/2005 82 71 182 173 146 1 9 14924 24356 2706 14178 23138 2571 5/10/2005 92 0 253 240 202 13 22 23276 47632 2165 22112 45250 2057 5/11/2005 21 0 240 228 192 1 23 5040 52672 2290 4788 50038 2176 8/4/2005 15 0 239 227 191 2 25 3585 56257 2250 3406 53444 2138 5/4/2006 101 78 237 225 190 5 30 23937 80194 2673 22740 76184 2539 5/10/2006 12 10 313 297 250 0 30 3756 83950 2798 3568 79753 2658 6/6/2006 115 0 323 307 258 33 63 37145 121095 1922 35288 115040 1826 6/29/2006 14 0 290 276 232 3 66 4060 125155 1896 3857 118897 1801 7/17/2006 1 0 287 273 230 1 67 287 125442 1872 273 119170 1779 8/24/2006 134 0 286 272 229 12 79 38324 163766 2073 36408 155578 1969 2/25/2006 3 0 274 260 219 1 80 822 164588 2057 781 156359 1954 SW Unfished
Number Number # tagged at Recaptures Sum Sum 5% tag caught (Ct) tagged large (Mt) 5% at large 20% at large (Rt) Sum Recaps (R) Ct * Mt (Ct*Mt) N= (Ct*Mt5) (CtMt5) loss 7/27/2004 18 18 0 0 0 0 0 0 0 0 0 0 0 7/28/2004 219 213 18 17 14 0 0 3942 3942 0 3745 4180 0 8/18/2004 23 18 231 219 185 2 2 5313 9255 4628 5047 9227 4614 2/16/2005 61 48 249 237 199 1 3 15189 24444 8148 14430 23657 7886 3/31/2006 100 83 296 281 237 7 10 29600 54044 5404 28120 51777 5178 5/10/2006 64 37 378 359 302 26 36 24192 78236 2173 22982 74759 2077 3/6/2007 55 38 411 390 329 9 45 22605 100841 2241 21475 96234 2139 SE fished
Number Number # tagged at Recaptures Sum Sum 5% tag caught (Ct) tagged large (Mt) 5% at large 20% at large (Rt) Sum Recaps (R) Ct * Mt (Ct*Mt) N= (Ct*Mt5) (CtMt5) loss 7/28/2004 100 93 0 0 0 0 0 0 0 0 0 0 0 7/29/2004 45 45 93 88 74 0 0 4185 4185 0 3976 3976 0 11/17/2004 40 37 138 131 110 2 2 5520 9705 4853 5244 9220 4610 2/15/2005 113 84 175 166 140 5 7 19775 29480 4211 18786 28006 4001 5/10/2005 113 0 259 246 207 25 32 29267 58747 1836 27804 55810 1744 8/2/2005 54 0 234 222 187 10 47 12636 71383 1519 12004 67814 1443 8/4/2005 1 0 224 213 179 0 47 224 71607 1524 213 68027 1447 5/4/2006 76 55 224 213 179 10 57 17024 88631 1555 16173 84199 1477 5/5/2006 33 11 277 263 222 16 73 9141 97772 1339 8684 92883 1272 6/6/2006 22 0 282 268 226 19 92 6204 103976 1130 5894 98777 1074 6/7/2006 5 0 263 250 210 3 95 1315 105291 1108 1249 100026 1053 6/29/2006 15 0 260 247 208 11 106 3900 109191 1030 3705 103731 979 7/17/2006 2 0 249 237 199 1 107 498 109689 1025 473 104205 974 8/24/2006 1 0 248 236 198 0 107 248 109937 1027 236 104440 976 NE unfished
Number Number # tagged at Recaptures Sum Sum 5% tag caught (Ct) tagged large (Mt) 5% at large 20% at large (Rt) Sum Recaps (R) Ct * Mt (Ct*Mt) N= (Ct*Mt5) (CtMt5) loss 7/27/2004 136 127 0 0 0 0 0 0 0 0 0 0 0 11/3/2004 32 31 127 121 102 1 1 4064 4064 4064 3861 3861 3861 2/15/2005 21 16 158 150 126 1 2 3318 7382 3691 3152 7013 3506 4/21/2005 40 36 174 165 139 4 6 6960 14342 2390 6612 13625 2271 3/31/2006 103 89 209 199 167 4 10 21527 35869 3587 20451 34076 3408 5/5/2006 57 18 298 283 238 39 49 16986 52855 1079 16137 50212 1025 5/10/2006 1 1 310 295 248 0 49 310 53165 1085 295 50507 1031 6/6/2006 9 2 310 295 248 6 55 2790 55955 1017 2651 53157 966 3/6/2007 26 16 311 295 249 8 63 8086 64041 1017 7682 60839 966
74
Appendix I
1: Residual plot of four species for video abundance data.
Residual Plots for Counts Normal Probability Plot Versus Fits 99.9 80 99
90 40
l
t
a
n
u
e
d c
50 i
r 0
s
e
e
P R 10 -40 1 0.1 -80 -100 -50 0 50 100 40 50 60 70 80 Residual Fitted Value
Histogram Versus Order 80 12
y 40
l c
9 a
n
u
e
d i
u 0 s
q 6
e
e
r
R F 3 -40
0 -80 -60 -40 -20 0 20 40 60 80 1 5 10 15 20 25 30 35 40 45 50 55 60 65 70 Residual Observation Order
75
2: Residual plots for C. striata lengths comparing fished/unfished locations over time intervals.
Residual Plots for BSB Length Normal Probability Plot Versus Fits 99.99 200
99 l
t 90
a 100
n
u
e
d c
50 i
r
s e
e 0 P 10 R 1 -100 0.01 -200 -100 0 100 200 320 340 360 380 Residual Fitted Value
Histogram Versus Order 200
200 y
150 l c
a 100
n
u
e
d i
u 100
s
q e
e 0
r R F 50 -100 0 -100 -50 0 50 100 150 200 1 0 0 0 0 0 0 0 0 0 0 0 20 40 60 80 00 20 40 60 80 00 20 Residual 1 1 1 1 1 2 2 Observation Order
76
3: Residual plots for C. striata lengths comparing individual sites over time intervals.
Residual Plots for BSB Length Normal Probability Plot Versus Fits 99.99 200
99 l
t 90
a 100
n
u
e
d c
50 i
r
s e
e 0 P 10 R 1 -100 0.01 -200 -100 0 100 200 300 320 340 360 380 Residual Fitted Value
Histogram Versus Order 200 200
y 150
l
c a
n 100
u
e
d i
u 100
s
q e
e 0
r R
F 50 -100 0 -100 -50 0 50 100 150 200 1 0 0 0 0 0 0 0 0 0 0 0 20 40 60 80 00 20 40 60 80 00 20 Residual 1 1 1 1 1 2 2 Observation Order
77
4: Residual plots for B. capriscus lengths comparing fished/unfished locations over time intervals.
Residual Plots for GT Length Normal Probability Plot Versus Fits 99.99 200 99
100 l
t 90
a
n
u
e
d c
50 i 0
r
s
e
e P 10 R -100 1
0.01 -200 -200 -100 0 100 200 380 400 420 440 460 Residual Fitted Value
Histogram Versus Order 200 80
100 y
60 l
c
a
n
u
e
d i
u 0 s
q 40
e
e
r R F 20 -100
0 -200 -150 -100 -50 0 50 100 150 1 100 200 300 400 500 600 700 800 900 Residual Observation Order
78
5: Residual plots for B. capriscus lengths comparing individual sites over time intervals.
Residual Plots for GT Length Normal Probability Plot Versus Fits 99.99 200 99
100 l
t 90
a
n
u
e
d c
50 i 0
r
s
e
e P 10 R -100 1
0.01 -200 -200 -100 0 100 200 380 400 420 440 460 Residual Fitted Value
Histogram Versus Order 80 200
100
y 60
l
c
a
n
u
e
d i u 0
40 s
q
e
e
r R F 20 -100
0 -200 -150 -100 -50 0 50 100 150 1 100 200 300 400 500 600 700 800 900 Residual Observation Order
79