Nov 12, 2005 - catch estimates with limited hard data requires interpo- ... local fisheries agencies (but see Rawlinson et al. ..... 2005), recovering 'lost' data or.
Historical and research information on marine protected areas was obtained from various published and ... Kunduchi reefs, the reefs off Zanzibar town, Menai.
dress the full range of issues for managing coral reef fisheries in the Florida Keys. The .... meets assumptions regarding the error probability distribution. A key step in the ... The third tenet is to maximize information content at minimum cost. .
*Email: [email protected]. Reducing bycatch in ... Escape gaps reduce neither the catch of high-value fish, nor the
Dec 17, 2007 - 1University of Miami, Rosenstiel School of Marine and Atmospheric Science, 4600 ... and > 110 species of invertebrates for the aquarium trade.
PhD position in Coral Reef Fisheries Ecology/Modeling. Background: Gear-based fisheries restrictions are an effective al
Dec 15, 2011 - Monitoring partnerships. Monitoring of coral reefs in Kenya constitute part of Global. Coral Reef Monitor
Jul 21, 2003 - Are the Coral Reef Finfish Fisheries of South Florida ...... Sciences and Applied Technology, Mariano Marcos State University, Currimao 2903,.
Jul 11, 2008 - developed cooperatively by BNP and the Florida Fish and Wildlife Conservation ..... National. Park Service, Natural Resource Technical Report.
Pacific Island coral reefs enter the cash economy (Dalzell et al, 1996), and the commercial imperative for constant ... (John Munro pers. comm.), and Pacific ...
Aug 21, 2012 - Sara Hughes a,1,*, Annie Yau a,2, Lisa Max b, Nada Petrovic c,3, Frank Davenport d,. Michael ..... ment was estimated using the average scores from the surveys conducted by ... vulnerability score and three is the highest possible ....
Florida's future, exploitation of reef fish stocks must be reduced. Fishery management ..... habitats. NOAA Tech. Memo. ..... of the month, following the full moon schedule), and. March and April 2008 ..... Academic Press, San Diego, pp. 149-170.
Nov 14, 2017 - Handling Editor: Robert Arlinghaus. Abstract. 1. In response ... pend on (DÃaz et al., 2015; Moberg & Folke, 1999; Rogers, Blanchard,. & Mumby ...
Giant clams, coconut crab, turtle, crocodile and, lately, the export trade in live groupers are all examples of such "high-risk" fisheries. Recovery times for such ...
height in predicting daily biomass, no adjustments were made for ..... ultimately reduce adult fish stocks (Berkeley et al. 2004; ..... Prentice Hall, New Jersey.
Sep 25, 2011 - of the Northern Mariana Islands (CNMI), Guam, Yap, and. Pohnpei. ...... expansion, and a growing cash-based economy. Despite the likely use ...
Notes: In the ecological domain, exposure and sensitivity create impact potential. The impact ... the ecological vulnerability, or exposure, in the social domain.
Published by Elsevier B.V. This is an open access article under the CC BY-NC-SA license ..... hood, possession of a bank
Steps towards the evaluation of coral reef restoration by using small .... added to each vial to dissolve the calcium salt, followed by 2.5 ml of Instagel scintillation ...
A principal cause of reef damage in Florida is ships running into reefs. The other major human ..... quently recruit by fragments that break, become lodged in the reef, ..... Tech. Mem. 41, 88. Curtis, A.S.G., 1968. Quantitative photography. In: Engl
1 May 2010 - such as the algae (Bula-Meyer 1990, DÃaz-Puli- ... used to estimate the percentage of the substrate ..... CARICOMP Methods manual, levels.
Jun 22, 2000 - Coral Reef Rehabilitation â Technical Options and necessary Political .... Each of the cubes was then weighted until the destruction of the cube.
Has ecosystem research advanced coral reef science? The answers cannot be ... calcium-carbonate secreting organisms which, with its as- sociated water ...
and weighed life histories in 62 reefs in high compliance closures >15 years old along the ... virgin biomass with no variable picked as significant by the stepwise ...
Coral reef fisheries benchmarks in WIO By Tim McClanahan WCS
Introduc)on Evalua=ng the status of fisheries requires establishing benchmarks derived from unfished ecosystems. Reef fish biomass data were used to calculate a benchmark and weighed life histories in 62 reefs in high compliance closures >15 years old along the east African coastline. Characteris=cs of the biomass and life histories were classified and described for total, fishable, target, and non-target groups. Benchmark varia=on with 18 variables including habitat, number of species, life histories, and thermal and produc=vity environments was evaluated.
Results Fisheries target and non-target biomass were not sta=s=cally different from each other, sharing an equal propor=on of the total biomass, but different from total and fishable biomass . Total
Fishable
Target
Non-target
F-
biomass
biomass
biomass
biomass
value
1124 ± 451.8a
1050 ± 437.1a
590.3 ± 329.0b
466.4 ± 232.2b
48.57
0.0001
22.79 ± 2.21a
23.82 ± 2.17b
27.06 ± 2.27c
19.91 ± 2.11d
114.35
0.0001
Optimum length (cm)
25.47 ± 2.79a
26.73 ± 2.78a
30.91 ± 2.92b
21.69 ± 2.51c
119.39
0.0001
Maximum length (cm)
42.84 ± 4.5a
45.02 ± 4.43b
50.43 ± 5.03c
38.47 ± 4.749d
71.03
0.0001
Life span (yr)
9.50 ± 0.74a
9.83 ± 0.81a
10.75 ± 1.17b
8.71 ± 0.72c
57.66
0.0001
Generation time (yr)
2.97 ± 0.21a
3.04 ± 0.24a
3.31 ± 0.36a
2.71 ± 0.18b
32.8
0.0001
2.29 ± 0.16a
2.36 ± 0.17a
2.52 ± 0.26b
2.16 ± 0.16c
39.18
0.0001
Growth rate (cm yrˉ¹)
0.45 ± 0.04a
0.44 ± 0.04a,b
0.42 ± 0.06b
0.45 ± 0.04c
6.51
0.0001
Natural mortality (M)
0.95 ± 0.08a
0.90 ± 0.09a
0.83 ± 0.09b
1.00 ± 0.13c
34.38
0.0001
Trophic level
2.89 ± 0.18a
2.90 ± 0.20a
3.19 ± 0.29b
2.52 ± 0.16c
103.01
0.0001
Biomass category
Mean ± SD Length at first maturity (cm)
Age at first maturity (yr)
P-value
Life history metrics were poor predictors of total virgin biomass with no variable picked as significant by the stepwise regression using BIC criteria.
AIC Intercept Number of species
t-
F-
ratio
ratio
142.42 ± 274.43
3.57
0
0.61
20.95 ± 5.87
0.52
12.75
0.0007
Estimate (mean ± SE)
Nine variables were not significant following AIC.
P>|t|
VIF
1.0
R2
p>F
0.19
0.0007
Number of species was significant and posi=ve for all biomass categories and explained 19% and 14% of the variance in virgin and fishable, biomass, respec=vely.
Habitat and environmental associa=ons predicted 33% of the variance in the virgin biomass but indicated only a few significant variables. AIC Intercept Ocean exposure Multivariate stress model Erect algae
F-
Estimate (mean ± SE)
t-ratio
2128.23 ± 413.18
5.15
0
0.0001
-300.67 ± 81.35
-3.7
13.66
0.0008
1.2
-1178.97± 478.32
-2.46
6.08
0.019
1.1
-13.2 ± 6.33
-2.08
4.34
0.04
1.11
ratio
P>|t|
VIF
14 variables were not significant after conducting the step-wise regression analysis.
R2
p>F
0.33
0.003
Small decreases in biomass however may trigger a sequence of events leading to declines in key ecosystem processes (McClanahan et al., 2011).
The variability of maximum sustained yields increased from B0, to z, to r for the likely ranges of these values.
Conclusions and recommenda)ons Differences between total and fishable biomass were small but target and non-target biomass yields were around half the total yields Target biomass had larger body sizes, longer life span, lower natural mortality metrics, and higher trophic levels. Therefore, target fish would need to mature longer than non-target groups to achieve op=mum yields. Consequently, high effort should lead to increasing dominance of non-target groups with faster life histories, which may maintain produc=on but at the cost of reducing valuable stocks.
