reza hakimimofrad- fish populations abundance estimates
TRANSCRIPT
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Estimating Abundance
Reading: Chapter 10
Survey design Visual censuses
Acoustic methods
Trawl surveys
Depletion estimates
Mark-recapture estimates
Egg Production Methods
Fishery-dependent CPUE
Estimating Abundance
Why do we need to estimate abundance?
To estimate:
1. Stock size
2. Recruitment
3. Mortality
4. Spatial distribution
Estimating Abundance
Survey design
A central problem is obtaining an abundanceindex that is proportional to stock size
Well-designed survey should provide estimates of: average fish abundance or density and
Spatial distribution (survey boundaries?)
Accuracy vs. Precision
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Accuracy Precision
Estimating Abundance
Survey design
A central problem is obtaining an abundanceindex that is proportional to stock size
Well-designed survey should provide estimates of:
average fish abundance or density and
Spatial distribution (survey boundaries?)
Accuracy vs. Precision
Bias vs. Variance
precision ( error) = $
Sample size (n)
5 10 15 20 25 30 35
SampleE
rror(%)
40
50
60
70
80
90
100
110
Sample error vs. sample size
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Estimating Abundance
Survey design
Stratification by habitat type or depth Combine abundance estimates across strata
Increases precision
Systematic vs. Random sampling
Systematic can be more precise and generallyreduces costs
Estimating Abundance
Visual censuses
Require clear, shallow waters
Best with non-cryptic fish that dont avoid divers
Can see fish and habitat Transects most common
Point counts (timed or instantaneous)
Behavior
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Estimating Abundance
Acoustics
Use of sound waves to detect fish (swim bladder)
Best for pelagic fishes
Target strength is species-specific and must bedetermined experimentally
Simultaneous trawling to ground-truth catch
Problems with acoustic shadows and avoidance
Very promising for well understood pelagic stocks
Estimating Abundance
Depletion (or Removal) estimates
Relation between abundance and catch rate
Requires:
Closed population
Short fishing period (no recruitment) Catchability proportional to abundance
CPUE (C/f) = qNtNt = N0 KtCPUE (C/f) = qN0 qKt
Plot CPUE vs. cumulative catch (K) (known as Leslie method)
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Kt
CPUE
Leslie Method
Estimate of N0Slope = -q
Consecutive sweeps with 100ft. seine (Fall 2003)
1st haul 2nd haul 3rd haul
Numbercaptured
0
5
10
15
20
25
30
35
40
45
Pinfish
Cumulative Catch
40 50 60 70 80 90 100
CPUE
0
10
20
30
40
50
Mullet
Cumulative Catch
20 25 30 35 40
CPUE
0
5
10
15
20
25
Spot
Cumulative Catch
5 10 15 20 25
CPUE
0
2
4
6
8
10
12
14
Shrimp
Cumulative Catch
5 10 15 20 25
CPUE
0
2
4
6
8
10
Depletion estimates of abundance (Fall 2003)
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60ft seine pulled inside 100ft seine (Fall 2003)
1st haul 2nd haul 3rd haul 4th haul
Numbercapture
d
0
5
10
15
20
25
Mullet
Spot
Pinfish
Blue crab
Fort Fisher Field trip 2004Depletion estimation using 100ft. seine
Seine haul
1st haul 2nd haul 3rd haul
Numberscaptured
0
20
40
60
80
100
120
140
Pinfish
Mojarra
Atl silverside
Ladyfish
Total fish
Pinfish
K70 80 90 100 110 120 130
CPUE
0
20
40
60
80
100
All species
K75 100 125 150 175 200 225 250 275 300
CPUE
0
20
40
60
80
100
120
140
160
180
200
Mojarra
K0 50 100 150 200
CPUE
0
10
20
30
40
Atl. silverside
K0 10 20 30 40 50
CPUE
0
5
10
15
20
Depletion estimates of abundance (Fall 2004)
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Pinfish
Cumulative catch (K)
500 520 540 560 580
CPUE(#perhaul)
-100
0
100
200
300
400
500
600
Atl. silverside
Cumulative catch (K)
70 80 90 100
CPUE(#perhaul)
0
10
20
30
40
50
60
70
80
Atl. croaker
Cumulative catch (K)
7.8 8.0 8.2 8.4 8.6 8.8 9.0 9.2 9.4
CPUE(#perhaul)
0
2
4
6
8
10
All species
Cumulative catch (K)
850 900 950 1000 1050
CPUE(#perhaul)
-200
0
200
400
600
800
1000
Depletion estimates of abundance (Fall 2005)
Total Length (mm)
0 20 40 60 80 100 120 140
Relativefrequency(%)
0
10
20
30
40
50
60
20 ft seine
Total Length (mm)0 20 40 60 80 100 120 140
Relativefrequency(%)
0
2
4
6
8
10
12
14
16
60 ft seine
n = 71
n = 210
Size-selectivity of beach seines (Fall 2005)
Estimating Abundance
Depletion (or Removal) estimates DeLury Method
CPUE (C/f) = qNtCPUE (C/f) = qN0(Nt/N0)
ln CPUE = ln qN0 + ln (Nt/N0)
Substitute Nt/N0 = e-qE
ln CPUE = ln qN0qE
Plot ln CPUE vs. cumulative effort (E)
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Cumulative effort (E)
lnCPUE
DeLury Method
slope = -q
y-int. = ln qN0
Estimating Abundance
Trawl surveys
Very widely used, most common
Mesh size regulates fish size
Constant catchability (q) essential; lack ofstandardization is major problem
Consistent gear design, tow speed, duration helpto maintain q
C = qfN
CPUE = qD
Stock biomass = D x area
Estimating Abundance
Trawl surveys
Many factors affect catchability (q)
Tow speed
Depth
Time of day Vessel noise
Mostly, q is unknown, but..
If q is constant, then estimated stock biomass willbe proportional to actual stock size
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Surveys
Annual method
Daily method
Estimating Abundance
Whats wrong with using CPUE from fishery?
It provides catch and effort data from large areasover long time scales, so why not use it?
Often times it is used, only data available
Landings data omits discards (bycatch, undersize)
Catch/effort data hard to get for every boat
CPUE (LPUE) rarely proportional to abundance
No gear standardization
Capture efficiency increases with time
Fishers dont fish randomly
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Fig. 10.15. Spatialdistribution
of commercialtrawling effort(hours per year)in the North Sea
Fig. 4.16. Distributionof Atlantic cod in theGulf of St. Lawrence,showing range expansionand contraction overtwenty years
Fig. 4.17. Occurrence oflow, medium, and highcatches of Atlantic cod
in research vesselsurveys as thefishery collapsed
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Fig. 4.18. How the
calculation of meancatch rate can affectthe interpretation offishery trends, examplefrom northern cod
0
1
2
3
4
5
6
7
8
9
0 1000 2000 3000 4000
Biomass (Tons)
CatchabilityCoefficien
Abundance
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Hypoaggregation
Hyperaggregation
Abundance
Density
Abundance
CatchperEffort(CPUE)
CPUE remains high due to aggregation of fish