118 
Fishery Bulletin 1 14(1) 
Table 1 
Number of tourists compared with residents in 2010 for the Caribbean countries and territories where the top 10 greatest 
number of stopover visitors were reported that year. 
Country 
Stopover 
visitors 
(10 3 ) J 
Cruise 
visitors 
(10 3 U 
Total 
visitors 
(10 3 ) 
Resident 
population 
(10 3 U 
Stopover 
visitors as 
% of resident 
population 
Mean length 
of stay for 
stopover visitors 
(nights ) 1 
Aruba 
824 
569 
1394 
108 
763 
7.8 
Bahamas 
1370 
3810 
5180 
347 
395 
6.8 
Barbados 
532 
665 
1197 
275 
194 
9.8 
Cuba 
2532 
unavailable 
unavailable 
11,242 
23 
10.9 
Dominican Republic 
4125 
353 
4477 
9974 
41 
9.2 
Jamaica 
1922 
910 
2831 
2702 
71 
9.0 
Martinique 
476 
75 
551 
400 
119 
13.3 
Puerto Rico 
1369 
1191 
2560 
3979 
34 
2.6 
St. Maarten 
443 
1513 
1956 
37 
1198 
unavailable 
U.S. Virgin Islands 
691 
1859 
2550 
110 
628 
unavailable 
1 Source: Caribbean Tourism Organization. 
The combined demand for local fishes in The Baha- 
mas by a burgeoning tourist industry and a growing 
resident population raises an important question: can 
domestic fisheries keep up with the current patterns 
of fishing and seafood consumption of both groups in 
the long term? To address this question, comprehen- 
sive statistics on total removals from commercial and 
noncommercial fishing sectors and on patterns of local 
demand on fisheries by tourists and residents are fun- 
damental, as are assessments of the status of stocks of 
the main target species. The government of The Baha- 
mas, however, currently lacks the financial resources 
and technical expertise needed to adequately assess 
fish stocks (CFU 4 ), and it does not track the local de- 
mand on fisheries by either residents or tourists. Simi- 
larly, although some national statistics exist for com- 
mercial landings, catch from other important noncom- 
mercial sectors, like recreational fishing, are ignored. 
Fisheries in The Bahamas, like most tropical near- 
shore fisheries of the Caribbean, western Pacific, and 
Southeast Asia, are data poor in that they lack con- 
ventional, “scientific” data (e.g., on stock age structure, 
natural and fishing mortality, catch per unit of effort 
over time) or lack rigorous analyses of reliable data 
(Johannes, 1998; Bentley and Stokes, 2009). In such 
instances, a variety of alternative approaches to tradi- 
tional stock assessment have been used to develop ref- 
erence points for management — methods that include 
sequential trends analysis (e.g., depletion-corrected 
average catch [DCAC], MacCall, 2009; cumulative sum 
[CUSUM], Manly and Mackenzie, 2000), vulnerability 
analysis (e.g., productivity-susceptibility analysis of 
4 CFU (CARICOM Fisheries Unit). 2001. Report of the mul- 
tidisciplinary survey of the fisheries of the Bahamas, 43 p. 
CFU, Belize City, Belize. [Available at website.] 
vulnerability [PSA], Field et ah, 2010), and extrapola- 
tion (e.g., Robin Hood approach. Smith et ah, 2009). 
These methods for analysis of data-poor fisheries of- 
ten overlap, are complementary, or are nested within 
other methods. Moreover, these methods differ in their 
requirements for the quality and quantity of data and, 
therefore, involve varying degrees of uncertainty and 
require precautionary buffers (Honey et al., 2010). For 
example, a variety of techniques are used in sequen- 
tial trends analysis to detect trends and infer changes 
in fish populations or stocks from available time-se- 
ries data, whereas extrapolation methods, such as the 
Robin Hood approach, are used when virtually no con- 
ventional, scientific data are available. For the latter 
analyses, the local knowledge of fishermen and other 
resource users are used, as well as the information in- 
ferred from assumptions based on data-rich fisheries 
(Honey et al., 2010). 
In this study, we used the recent, globally estab- 
lished catch reconstruction approach of Zeller et al. 
(2007, 2015) for data-limited fisheries, a method that 
also has been used successfully in nontropical areas 
(e.g., Zeller et al., 2011a, 2011b), to retroactively es- 
timate a time series of commercial and noncommer- 
cial marine fisheries catches for The Bahamas during 
1950-2010. We chose the year 1950 as our starting 
point because it is the first year for which data were 
available in the global landings database of the FAO. 
Another objective of this study was to estimate local 
demand on fisheries by the tourist industry over the 
same period. As described previously, tourism is the 
primary industry in The Bahamas and is closely linked 
to fisheries. To better understand historical trends in 
fisheries catches (and predict future trends), we must 
view these patterns in light of changes in tourist de- 
mand on local fisheries. 
