The Use of a Roving Creel Survey to Monitor Exploited Coastal Fish Species in the Goukamma Marine Protected Area, South Africa

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The Use of a Roving Creel Survey to Monitor Exploited Coastal Fish Species in the Goukamma Marine Protected Area, South Africa The use of a Roving Creel Survey to monitor exploited coastal fish species in the Goukamma Marine Protected Area, South Africa by Carika Sylvia van Zyl A thesis submitted in fulfillment of the requirements for the degree of Masters in Technoligae, Nature Conservation Nelson Mandela Metropolitan University 2011 i I, Carika Sylvia van Zyl (s208027504) hereby declare that the work in this document is my own. ii Abstract A fishery-dependant monitoring method of the recreational shore-based fishery was undertaken in the Goukamma Marine Protected Area (MPA) on the south coast of South Africa for a period of 17 months. The method used was a roving creel survey (RCS), with dates, times and starting locations chosen by stratified random sampling. The MPA was divided into two sections, Buffalo Bay and Groenvlei, and all anglers encountered were interviewed. Catch and effort data were collected and catch per unit effort (CPUE) was calculated from this. The spatial distribution of anglers was also mapped. A generalized linear model (GLM) was fitted to the effort data to determine the effects of month and day type on the variability of effort in each section. Fitted values showed that effort was significantly higher on weekends than on week days, in both sections. A total average of 3662 anglers fishing 21 428 hours annually is estimated within the reserve with a mean trip length of 5.85 hours. Angler numbers were higher per unit coastline length in Buffalo Bay than Groenvlei, but fishing effort (angler hours) was higher in Groenvlei. Density distributions showed that anglers were clumped in easily accessible areas and that they favored rocky areas and mixed shores over sandy shores. Catch documented between October 2008 and December 2009 included a total of 361 fish, of 27 species from 12 families. Sparidae had the highest contribution (12 species). A Shannon-Weiner diversity index showed that diversity was higher in Buffalo Bay (0.81) than Groenvlei (0.57). Catch composition of retained fish (336 individuals) showed that the six numerically most important species were blacktail (Diplodus sargus capensis) (66% of catch), followed by galjoen (Dichistius capensis) at 11 %, Cape stumpnose (Rhabdosargus holubi), belman (Umbrina robinsonii) and strepie at 3%, and elf (Pomatomus saltatrix) at 2 %. Catch composition of an earlier study in Goukamma (Pradervand and Hiseman 2006) was compared with the present study, as well as data from the De Hoop MPA, which iii is closed to fishing. A multi-dimensional scaling plot of catch composition showed tight clustering of the De Hoop samples, and high variability among the Goukamma samples. A bray-curtis similarity index and dendrogram of similarity between study sites and study periods showed that there was an 83% similarity among De Hoop samples and a 75% similarity among Goukamma samples (ignoring the two outliers). The two sites are different with respect to species composition, but this is expected because they are different areas. Differences between time periods in Goukamma (i.e. the previous study versus the present study) were not significant. The most significant result from the catch composition analyses is the high variability among the Goukamma samples. This can be explained by the variable fishing methods used by anglers in Goukamma, compared with the standardized fishing methods used by researchers in De Hoop, and the fact that fish are more abundant and populations are more stable in De Hoop – giving higher sample sizes which reduce the variability in the statistics. Species-specific CPUE was calculated for the six numerically most important species. In both sections, CPUE was highest for blacktail, with an average of 0.133 fish per hour for Groenvlei, and 0.060 fish per hour for Buffalo Bay, over the 12 months. The second highest CPUE values per section were 0.030 for galjoen in Groenvlei and 0.039 for strepie in Buffalo Bay. Remaining CPUE values ranged from 0.014 (belman in Groenvlei) to the lowest value of 0.001 (strepie in Groenvlei). Total estimated CPUE for these six species in the MPA using the estimated effort and catch results amounted to 0.018 fish per hour. An annual estimated 3897 fish were landed in the reserve during 2009. Most fish (n=2481, 64%) were caught in the Groenvlei section. Numbers of blacktail were the highest of all species, within both sections (2353 fish). Strepie was the next most common (561 fish), but was caught almost entirely within the Buffalo Bay section (97% of individuals), followed by galjoen (548 fish) caught mostly within the Groenvlei section (92% of individuals). Size comparisons of the six species between the Goukamma and De Hoop MPAs showed that ranges in size are similar, but there are substantial differences in mean sizes between the two MPAs. Sample sizes of all species from the Goukamma MPA were too small to draw conclusions about stock status, except for blacktail. iv The Goukamma MPA is a popular fishing destination and angler effort is high. It can be considered a node of exploitation for surf zone fish, for which it provides no protection. Even though the MPA allows shore angling, sustainable fishing practices should be incorporated in management plans if the MPA is expected to protect and conserve its stocks. Of noteworthy concern is the occurrence of illegal night fishing (the public may not enter the reserve between sunrise and sunset) which leads to underestimates of catch and effort (night surveys were not conducted because of safety concerns). It is recommended that more communication should take place between the angling community and the reserve management. Sign boards giving information on species which are under pressure, and why they are under pressure, with a short explanation on their life cycles, is advised. The roving creel survey method was suitable for the study area and delivered statistically rigorous results. I thus recommend that it is continued in the future by management. I make some recommendations for reducing costs of future surveys, as well as for altering the survey design if funds are very limited. v Table of Contents Page Chapter 1 1 Introduction 1 1.1 Problem Statement 1 1.2 Background 1 1.3 Study Area 7 1.3.1 Location 7 1.3.2 Vegetation and topography 8 1.3.3 Intertidal habitat and subtidal reefs 8 1.3.4 Access to coastline 11 Chapter 2 13 Review of monitoring methods for shore based fishing 13 2.1 Background 13 2.2 History of monitoring of shore-based fishing in South Africa 14 2.3 Review of monitoring methods for shore-based fishing 20 2.3.1 Methods for monitoring shore-based fishing 20 Fishery-dependent and -independent data 20 Off-site and on-site survey methods 21 Sampling frames 22 Off-site surveys 23 (i) Mail surveys 23 (ii) Telephone surveys 24 (iii) Door-to-door surveys 25 (iv) Logbooks, diaries and catch cards 26 On-site surveys 27 (i) Roving creel surveys (RCS) 27 (ii) Access point surveys 28 (iii) Aerial surveys 28 The present study 29 vi Chapter 3 30 Methods: the roving creel survey 30 3.1 Background 30 3.2 Week day versus weekend day sampling ratio 32 3.3 Questionnaire 35 3.4 Effort, Catch and CPUE 36 3.4.1 Background 36 3.4.2 Length frequencies 42 3.4.3 Spatial analysis 44 3.4.4 Comparison of catch composition among three data sets and diversity index 45 Chapter 4 46 Results and Discussion: Angler effort 46 4.1 Temporal distribution of anglers 46 4.1.1 Estimated angler averages - Buffalo Bay 48 4.1.2 Estimated angler averages - Groenvlei 48 4.2 Estimated angler hours 50 4.3 Spatial distribution of anglers 52 4.3.1 Angler density per habitat type 52 4.3.2 Angler density per 100 m section 53 4.4 Discussion 54 Chapter 5 57 Results and Discussion: 57 Catch composition, catch per unit effort and total Catch 57 5.1 Catch composition 57 5.1.1 Comparison of catch composition between three data sets 59 5.2 Size distribution of retained fish 64 5.3 Catch per unit effort 66 5.3.1 Size composition of individual species 68 (i) Blacktail 68 (ii) Galjoen 70 (iii) Strepie 72 vii (iv) Cape stumpnose 73 (v) Belman 74 (vi) Elf 76 5.4 Catch Estimates 78 5.5 Discussion 80 Chapter 6 85 Conclusions and recommendations 85 Glossary 92 References 94 Appendices (Electronic – please see attached CD) viii List of Figures Figure 1 Inshore bioregions of South Africa (Lombard et al. 2004) and the Goukamma study site. Figure 2 The Goukamma Marine Protected Area showing the two sampling sections. Figure 3 The Goukamma MPA boundary and reef systems. Figure 4 Intertidal habitats found in the Goukamma Marine Protected Area (based on Clark and Lombard 2007). Figure 5 Western access to the Goukamma Marine Protected Area at Platbank (red arrow). Figure 6 Eastern access to the Goukamma Marine Protected Area (red arrows). Figure 7 Comparisons of different week day (WD): weekend day (WE) sampling ratios, and different number of surveys per month, with respect to the total fishing effort sampled. Figure 8 The average number of anglers encountered per month during 2009 in the Groenvlei (GV) and Buffalo Bay (BB) sections of the Goukamma MPA. Bars indicate one standard error and Y axis average number of anglers. Figure 9 GLM predicted average number of angler counts through the year, and by day type, at Buffalo Bay. WE = weekend days and WD = week days. Figure 10 GLM predicted average number of angler counts through the year, and by day type, at Groenvlei. WE = weekend days and WD = week days.
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