Environmental links to pelagic fish
life cycle, abundance, and
distribution: determining governing
factor (LMR/PEL/09-03&04)
PI: DAWIT YEMANE AND JANET COETZEE
DEPARTMENT OF AGRICULTURE, FORESTRY & FISHERIES
BRANCH: FISHERIES MANAGEMENT
Talk structure
• Background
• Objectives
• Results
– Angola
– Namibia
– South Africa
• Current state of the project
• Next step
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Background
• It is widely known that environmental variables do
influence the distribution and abundance of pelagic
fishes
• However the extent, the direction of the influence, and
its temporal consistency is still the topic various
studies both at the regional level and globally
• Environmental variables influence distribution
directly and indirectly
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Spatial dynamics of the bearded goby and its key predators off Namibia
varies with climate and oxygen availability (Salvanes et al. in press)
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Background
• Considering the long-term changes observed both
globally and regionally and the relevance of pelagic
fishes in the BCLME it becomes important that we
study the influence of environmental variables on
pelagic fish distribution, and abundance
• There a number of ways the effect of environmental
variables on pelagic fish distributions/abundance can
be studied
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Approach
•Selection of species
•The following species were included in this study: Anchovy, Sardine, Round
herring, and cape horse mackerel [South Africa]; cape horse mackerel
[Namibia]; Sardinella and horse mackerel [Angola]. These species were
included in the study as they spend most/all of their life cycle in the pelagic
system.
•Data sources: biological
•All of the biological data used in this study were obtained from routine
biomass assessment surveys conducted off the coast of the three countries in
the BCLME: Angola, Namibia, and South Africa.
•Data comes from the two types of surveys that are commonly carried out in
the three countries: the pelagic hydro-acoustic survey and the demersal trawl
survey.
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Approach cont…
•Data sources: environmental
•Sea Surface Temperature (SST) and Sea Surface Chlorophyll
(SSChl) data corresponding to the spatial domain of each of
the three countries were extracted as the mean per pixel over
the two to three month during surveys in each country
•Data analysis
•Different types of statistical models are commonly used in
link the distribution and abundance of pelagic fish species to
the prevailing environmental condition: In this talk results
from Generalized Additive Model (GAM) will be presented.
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Result: South Africa
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Result: South Africa
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Result: South Africa
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Result: South Africa
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Result: South Africa
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Result: Namibia (horse mackerel)
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Result: Angola (horse mackerel)
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Result: Angola (Sardinella)
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Summary
•Summary:
–The result of this study demonstrate the potential
use of remote sensing data, combined with various
novel statistical tools, to understand habitat
preference of pelagic fishes in the BCLME region.
–The result of this preliminary analysis also shows the
difference in the direction of influence of the different
environmental variables (as deduced from the
response curves)
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Current state
• Country specific updates
• South Africa (most of the remaining work
is write up of the papers and the report)
• Namibia (remaining work download the
new sst, update analysis and write up)
• Angola (same as for Namibia)
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Acknowledgement
All collaborators on Benguela Current Commission (BCC)
funded project
Collaborators on a NANSCLIM project
Branch Fisheries Management of the Department of
Agriculture, forestry and fisheries
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