biodiversity of fishes summary rainer froese (05.02.15)
TRANSCRIPT
Biodiversity of FishesSummary
Rainer Froese(05.02.15)
Phylogeny of fishes
Classes Common ancestor(million
y)
Orders(n)
Families(n)
Genera(n)
Species(n, %)
Myxini (hagfishes) 600 1 1 6 78 0.2
Cephalaspidomorphi (lampreys)[Petromyzontida]
450 1 3 10 47 0.1
Holocephali (chimaeras)[Chondrichthyes]
420 1 3 6 50 0.1
Elasmobranchii (sharks and rays)[Chondrichthyes]
420 12 51 188 1,158 3.5
Sarcopterygii (lobe-finned fishes)
420 3 4 4 8 0.04
Actinopterygii (ray-finned fishes)
400 46 487 4,833 31,608 95.9
Total 64 549 5,047 32,949 100
FishBase 11/2014http://www.fishbase.org/tools/Classification/ClassificationTree.php
Fish Diversity of the Oceans
Arctic 130
Atlantic4,900
Pacific10,500Indian
6,000
Pacific10,500
Antarctic 370
Total: ~16,000 marine or diadromous fishes, several thousand in more than one Ocean
Diversity in Large Marine Ecosystems
North Sea190
Mediterranean700
Caribbean1,600
Canary1,300
South Brazil970
Patagonian340
Benguela820
Greenland190
Humboldt750
California800
Alaska320
Hawaiian840
Red Sea1,200
Agulhas1,400
Bay of Bengal700
West470
Indonesian2,400
East1240
Australian
East-China1,040
Polynesian810
Weddell Sea25
Six Zoogeographic Realms
Alfred Russell Wallace, 1876. The Geographical Distribution of Animals
Permian, 225 m Triassic, 200 m
Jurassic, 135 m Cretaceous, 65 m
Size Matters• Largest fish: Whale shark, 18 m, 34 t• Smallest fish: attached male anglerfish, several
tiny cyprinids & gobies, 1 cm, 0.01g • Max growth rate, fecundity, speed, trophic level,
life span increase with size• Metabolic rate, relative brain size, relative gill
area and K, rmax and M decrease with size
• topt = 1.65/M, max growth = 0.296 Winf, max age tmax at 0.95 Linf = 4.5/M are constant
Size Distribution
0
500
1000
1500
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5
Length (log; cm)
Fre
qu
en
cy
Frequency distribution of maximum lengths in 23,685 species of fishes, Median = 15.9 cm
Relationship Between Weight and Length
W = a * Lb
with weight in grams and length in cm
For parameter estimation use linear regression of data transformed to base 10 logarithms
log W = log a + b * log L
Typical value for b ~ 3 -> isometric growth
For a = 0.01 (fusiform), 0.1 (roundish), 0.001 (eel-like)
Von Bertalanffy Growth Function
Lt = Linf (1 – exp(-K * (t – t0)))
Where Lt = length (cm) at age t (years)
Linf = asymptotic length if t = infinite
K = parameter indicating how fast Linf is approached (1/year)
t0 = hypothetical age at L = 0 (years)
Wt = Winf (1 – exp(-K * (t – t0)))b
b = 3 or exponent of length-weight relationship
Growth in Weight
0
2
4
6
8
10
12
14
16
18
0 5 10 15 20 25
Age (years)
Weig
ht
(kg
)
maturity
max growth
max reproductive biomass
asymptotic weight
Gadus morhua , Linf = 120 cm,K = 0.14, M = 0.2, rel Fec = 20%
average adult lifespan
max age
Whale shark vs Fin whale
0
500
1000
1500
2000
2500
0 10 20 30 40 50 60
Age (years)
Len
gth
(cm
)
Fin whale
Whale shark
The M Equation
Nt = N0 e –M t
Where
M is the instantaneous rate of natural mortality
N0 is the number of specimens at a t = 0
Nt is the number of specimens at time t
M = 0.2
0
200
400
600
800
1000
1200
0 5 10 15 20 25
Cohort age (years)
Co
ho
rt n
um
ber
s
Nt = Nts * exp(-M*(t - ts))
Average Adult Life Expectancy
x
x
y
xl
dl
E
y
ME
1
where Ex is the average life expectancy after reaching age x and l are the probabilities of reaching x and subsequent ages. If mortality M is constant, then the equation simplifies to
Reproductive Strategies
Froese & Pauly 2013, Fish Stocks, Encyclopedia of Biodiversity, Academic Press
Length at Maturity for Different Reproductive Strategies
Froese & Pauly 2013, Fish Stocks, Encyclopedia of Biodiversity, Academic Press
Stock-Recruitment Relationships
(N)
(tonnes)
Spawning stock biomass
Recruits
Use of Hockey-Stick in Management
Conceptual drawing of the hockey stick relationship between spawning stock size and recruitment. SSBlim marks the border below which recruitment declines, SSBpa marks a precautionary distance to SSBlim, and 2 * SSBpa can be used as a proxy for SSBmsy, the stock size that can produce the maximum sustainable catch [ContHS.xlsx]. (Froese et al. in prep.)
BioDivPopGrowthMSY.xls
Population Growth
BioDivPopGrowthMSY.xls
Logistic Curve Properties
The Schaefer Production Model
BioDivPopGrowthMSY.xls
Surplus Production Implications
• Surplus production (Y) is the production of biomass beyond what is needed to maintain current population size
• If a fishery only catches the surplus production, then the population size remains
• If a fishery catches more, then the population shrinks
• If it catches less, then the population grows
Fisheries Management Basics
0
2000
4000
6000
8000
0 20 40 60 80 100
Fishing Effort (hours)
Cat
ch i
n k
g a
nd
Val
ue/
Co
st i
n €
MSY
Cost of fishing
€
€€
MEY
Fpa
?
Flim
†
Economicoverfishing
Growthoverfishing
Recruitmentoverfishing
EU Fisheries Management
0
2000
4000
6000
8000
0 20 40 60 80 100
Fishing Effort (hours)
Cat
ch i
n k
g a
nd
Val
ue/
Co
st i
n €
MSY
Cost of fishing
€
€€
MEY
?
Flim
†
Subsidies
The Mechanics of Sex under Water
• Eggs have to be fertilized (or activated) by the right sperms
• Eggs are few and large (>1mm - 10 cm) or numerous and small (< 1 mm), internal, attached or drifting
• Sperms are very small, very numerous, mobile, outside
• Survival of gametes in water is short (few minutes)
• Courtship and mating aims to increase fertilization rate
Three trawling revolutions
1376 – the beam trawl is invented
1880s – trawlers gain steam power
Late 20th century – the deep sea comes within reach of the trawl
The Piscatorial Atlas1883
Questions?