Implementing Trap Vents CFMC has provided $5,000 This will purchase 6,250 Vents for 3,125 Traps

SpeciesControl CPUEVent CPUEReduction % Reduction from Control CPUE Holacanthus ciliaris % Acanthurus coeruleus % Haemulon melanurum % Chaetodon striatus % Holacanthus tricolor % Calamus calamus % Sparisoma chrysopterum % Lutjanus apodus % Acanthurus chirurgus % Pomacanthus arcuatus % Balistes vetula % Lutjanus synagris % Haemulon plumieri % Holocentrus rufus % Sparisoma viride % Pterois volitans % Epinephelus guttatus % Haemulon sciurus % Epinephelus fulvus % Lactophrys bicaudalis % Lactophrys quadricornis % Lactophrys triqueter % Lactophrys poligonius % Ocyurus chrysurus %

Species Reduction in CPUE TL Increase Acanthurus bahianus 90%10% Cantherhines pullus 90%28% Holocanthus ciliaris 89%14% Acanthurus coeruleus 81%4% Chaetodon striatus 73%1% Calamus calamus 68%5% Sparisoma chrysopterum 53%1% Acanthurus chirurgus 45%3% Pomacanthus arcuatus 38%17% Cantherhines macrocerus 54%20% Balistes vetula 30%3% Aluterus schoepfi19%6%

randomization test reference: Manly, B. F. J Randomization, Bootstrap and Monte Carlo Methods in Biology, 3rd Edition. Chapman and Hall/CRC.

Traps3,125 Set Length (dys) 9.7 Hauls/Year38 # Trap Hauls118,750 Impact of CFMC Vents Species Control CPUEVent CPUE % Reduc- tion Control CPUE Catch without Vents Catch with Vents Reduction /Increase Holacanthus ciliaris %4,2753, Lutjanus buccanella %4,8694, Acanthurus coeruleus %89,65668,04421,613 Haemulon melanurum %4,8693,6811,188 Chaetodon striatus %7,8385,2252,613 Holacanthus tricolor %6,2944,0382,256 Calamus calamus %17,81310,5697,244 Sparisoma chrysopterum %15,7946,5319,263 Lutjanus apodus %16,9815,70011,281 Acanthurus chirurgus %38,95012,46926,481 Pomacanthus arcuatus %12,3502,8509,500 Balistes vetula %85,02510,68874,338 Lutjanus synagris %5, ,869 Haemulon plumieri %31, ,519 Holocentrus rufus %38,950 0 Sparisoma viride %15,794 0 Epinephelus guttatus %42,63148,688-6,056 Pterois volitans %6,2947, Haemulon sciurus %15,79419,831-4,038 Epinephelus fulvus %7,2449,263-2,019 Ocyurus chrysurus %3,8008,075-4,275 Tota l 472,150268,900202,590 (Releases only)

STFA/SCCFA Spiny Lobster Project Second Progress Report 3/26/2013

Tagging and Measuring Floy “Spaghetti” Tags Measure with calipers to the nearest 1 mm CL Inject tag between the tail and end of carapace Check tag security

Trip Summary IslandMonth# Trips # Measured # Tagged Project Recaptures Non Project Recaptures # Kept St. CroixSeptember St. CroixOctober St. CroixNovember St. CroixDecember St. CroixJanuary St. CroixFebruary St. Croix Total St. ThomasSeptember St. ThomasOctober St. ThomasNovember St. ThomasDecember St. ThomasJanuary St. ThomasFebruary St. ThomasMarch St. Thomas Total

% of Lobster by CL (Complete Trips)

CV for Average Carapace Length

Lobster Growth STT and Cuba ( ∞ = ∞ (1− (−(− 0 )) )

Recaptures (Days at Large)

Mortality Calculation

Full Recruitment (N=137) L ∞ N=1 Z=0.316 St. Thomas Complete Trips 7.1 Years

Full Recruitment (N=112) L final N=2 Z=0.959 St. Croix Complete Trips 2.4 Years

Total Mortality (Z) Calculated from TIP Data

Yield Per Recruit

Population Analysis Review of CCR data showed that following 1997, the data for total traps owned was input instead of daily trap hauls. Only affects fishermen hauling more than one day per week (i.e. bigger fishermen). Interviewed all fishermen showing “unreasonable” daily trap haul numbers. Multiplied interview results by number of trips to obtain adjusted trap haul values.

Comparison Between Annual Trap Hauls and CCR Reports and Fishermen Interviews

Comparison of CPUE

From: To: CC: Sent: 2/12/ :00:32 A.M. Paraguay Standard Time Subj: Re: Fishermen Trap Haul Survey Dear David We have been asked by the VI DFW to have all requests for VI data routed through them so that they can be aware of all requests for their data and to respond to those requests if it is within their capability. Therefore would you please forward your requests to the chief fisheries scientists at DFW. The SEFSC Fisheries Statistics Division is be willing to assist the VI DFW with meeting such requests where we have capabilities for extracting information which they might not have. Regards Steve Turner Chief, Fisheries Statistics Division

Monthly Landings: St. Thomas

Monthly Landings: St. Croix

Population Estimation St. Thomas AverageLandings # Lobsters Cum # Tagged % Tagged % Recap- tured # Recap- tured Estimated Pop Size September7.3%9,4684, %0.17%7284,759 October8.2%10,6504, %0.35%16361,421 November8.6%11,1324, %0.38%18420,510 December10.7%13,8005, %0.52%31360,202 January10.6%13,6805, %0.48%28453,665 February9.2%11,8595, %0.43%22564,171 March9.4%12,1915, %0.33%17828, Landings129, Average weight lbs St. Croix AverageLandings # Lobsters Cum # Tagged % Tagged % Recap- tured # Recap- tured Estimated Pop Size September9.2%11,9745, %0.00%0 October8.0%10,4144, %0.16%7517,526 November8.5%10,9494, %0.32%15364,194 December8.1%10,4414, %0.16%7812,470 January9.1%11,7425, %0.08%41,617,897 February8.0%10,3864, %0.07%31,907, Landings134, Average weight lbs

Virgin Islands Spiny Lobster Landings

Island Differences in Methods 2006 CCR Data Island DivingTraps St. Thomas/St. John 15.9% 97.6% St. Croix84.1%2.4% Average sizes are significantly different between Islands (F= 102.7, p<0.001) Difference between size of Trap and SCUBA caught lobsters on St. Croix not significant (F=0.76, p=0.38)

Island Differences in Sizes CFMC Project Complete Trips Island Average CL St. Thomas/St. John mm St. Croix91.9 mm

Lobster Assessments Evidence/Data Catch by gear. CPUE-based abundance indices (calculated from summary data due to lack of access). Size distribution of catches. Analysis Statistical estimation of initial population size, recruitment history, and fishing mortality rates by fitting catch, CPUE, and size data.

Assessment Details Drivers of this assessment model: Size data and catch-CPUE data series give two pictures of fishing mortality rates and recruitment strength. Potential for conflict between these two datasets. Recruitment No attempt at fitting a stock-recruitment relationship within the model. Instead, this relationship can be evaluated after the fact.

Draft Results St. Thomas-St. John—conflict between two sources of information: – Increasing catches without signs of decrease in CPUE or average size. Model provides increasing recruitment but this conflicts with relatively stable age distribution. St. Croix—similar conflict albeit with increasing CPUE May be a data problem, particularly in recent years. May be an artifact from the way the SEFSC query was constructed.

Management Advice Results are not yet suggestive that we understand the productive capacity of this stock. Things may be complicated by a stock range that spans beyond the assessment area (BVI, PR, etc). May not apply to St. Croix (isolated sea mount not connected). Results are suggestive that current fishing pressure is sustainable—no evidence of decline in CPUE or average size on St. Thomas, however decline in average size observed on St. Croix. National Standard 1 advice on data-poor stocks with no evidence of decline: set catch limits as a function of average landings. Average landings have been increasing and current ACLs include low years at the start of the period, thereby reducing average. St. Croix may have data problem, and raises more concerns because the average size lobster is smaller and sizes have been decreasing.

Preliminary Conclusions Combination of catch weight, catch per unit effort, and size distribution of catches may be sufficient to assess the lobster stock. Recent data are necessary, as is further review of the catch, index, and size data. Even if assessment results are uncertain, management advice can be provided via a management strategy evaluation that compares policies against objectives (see Nowlis 2004, Bulletin of Marine Science)

2.4 Years