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?