Richard D.M. Nash (WP leader)

UNCOVERWP 1: Fisheries and Environmental Impacts on Stock structure and

reproductive potential

Fisheries and Environmental Impacts on Stock structure and reproductive potential

Tasks

1.1 Estimation of changes in stock reproductive potential [Jonna Tomkiewicz]

1.2 Resolution of changes in genetic composition of stocks [Einar Eg Nielsen]

1.3 Evaluation of fisheries induced evolution [Ulf Dieckmann, Mikko Heino]

1.4 Determination of changes in stock distributions and migrations[Geir Huse]

Estimation of changes inreproductive potential

• Growth, maturation and energy allocation

• Fecundity and realised egg production

• Egg quality and viability of offspring

• Models for understanding and predicting stock reproductive potential

Task 1.1

Sub-tasks:

All cases studies and stocks to the extent possible

Working hypotheses

• Growth and energy allocation is influenced by population density, food availability and hydrographic conditions

• Sexual maturation and individual fecundity is influenced by growth and energy stores

• Fecundity, egg quality and viability relates to female size, energy stores and food availability

• Realised and viable egg production is a function of stock demography and parental condition

• Models or improved indices of population egg production are necessary for understanding and predicting stock reproductive potential

Task 1.1

ObjectivesTask 1.1

1. Compile available data and develop process models to predict:- immature fish growth and sexual maturation, and - seasonal reproductive investment of adults, considering abiotic and biotic factors

2. Review and evaluate egg quality and viability of offspring under differing stock structures depending on maternal characteristics and environmental factors (literature study)

3. Establish models capturing variability in stock reproductive potential under varying stock size, demography and environmental conditions

Work description and time schedule

• Identify and evaluate existing datasets and relevant studies

• Initial analyses and process models of growth, maturation, fecundity and energy allocation

• Preliminary estimates of realised egg production and

• Review of information on egg quality and viability of offspring (literature study)

• Final process models and models to evaluate and predict stock reproductive potential{

Continuous collaboration with other tasks and WP’s

Milestonemonth

8

20

32

Task 1.1

Expected results and deliverablesTask 1.1

1. A review, time series and synthesis of available data on growth, maturation, condition, fecundity, potential and realised egg production, egg quality and viability of offspring

2. Process models on growth, energy storage and reproductive investment considering species specific characteristics including reproductive strategy and variation in habitats among case studies

8. Operational models predicting stock reproductive potential under varying stock size, demography and environmental conditions ….. that can be combined with other WP1 results, compared with traditional SSB indices etc in other WPs

Resolution of changes in genetic composition of stocks

• Genetic population structure

• Levels of genetic variation

• Genes affecting important biological traits

• Evaluate/model the effect of different management strategies on the maintenance genetic variability in harvested fish populations

• Population structure of sprat in the Baltic Sea and adjacent waters.

Task 1.2

Anthropogenic drivers of genetic changes in stocks

• Random genetic drift

• Migration

• Selection

• Human mediated reductions in Effective Population Sizes (Ne)

• Human mediated obstruction or facilitation of migration

• Human mediated selective fisheries or environmental changes (e.g. global warming)

Task 1.2

How do we monitor genetic changes?

• ”Semi-ancient DNA”, historical collections

tt0 t1

Effective size

Rate

of change

Task 1.2

Estimates of genetic changes

• Effective population size:– New Zealand snapper →

low 100´s, Ne/N ≈ 10-5

(Hauser et al. 2002)

– Red drum → Ne/N ≈ 10-3

(Turner et al. 2002)

– Atlantic cod → below 100, Ne/N ≈ 10-5 (Hutchinson et al. 2003)

– Atlantic cod → several thousand (Poulsen et al. 2006)

• Loss of variation:– Hutchinson (2003) cod at

Flamborough Head (North Sea), three microsatellites: 1954, 46 alleles; 1960, 42; 1970, 37; 1981, 42; 1998, 45

– Poulsen et al. (2006) cod at Moray Firth (North Sea) nine microsatellites: 1965 allelic richness 110; 2002, 118

– Poulsen et al. (2006) cod at Bornholm Basin (Baltic Sea) nine microsatellites: 1928 allelic richness 88; 1997, 91

Task 1.2

How do we monitor selective changes of the genetic composition over time?

• Monitoring changes in ”candidate genes”

– Candidate genes are genes of known function suspected to have a large influence on a given trait

– Candidate genes can be structural genes or genes involved in a physological process

– The working hypothesis is that a molecular polymorphism is related to phenotypic variation

Conover and Munch (2002)

Task 1.2

The Overlooked Evolutionary Dimension

• Modern fishing results in such substantial changes of mortality patterns that evolutionary responses of stocks are inevitable.

• Such changes are not as slow as is widely believed: Significant evolution can occur within 10 or 20 years.

• Evolutionary changes are not necessarily beneficial, neither to the stock nor to the exploiting agents.

• Once evolutionary changes have occurred, they may be very difficult to reverse.

• In short: Fishing does not only change the numbers, but also the traits of exploited fish.

Ulf DieckmannTask 1.3

Fisheries-induced Evolution: A Caricature

Initial compositionInitial composition After fishingAfter fishing After reproductionAfter reproduction

Ulf DieckmannTask 1.3

Evolutionary Change in Northeast Arctic Cod

19231923

19901990

Significant shift in maturation reaction normSignificant shift in maturation reaction norm

Age (years)

Leng

th (c

m)

5 12

50

100Northeast Arctic codNortheast Arctic cod

Ulf DieckmannTask 1.3

Evolutionary Change in Northern CodLe

ngth

at 5

0% m

atur

atio

n pr

obab

ility

(cm

)

Early warning

Early warning

MoratoriumMoratorium

3L females3L femalesmaturing at age 5maturing at age 5

Ulf DieckmannTask 1.3

Using Eco-Genetic Models

0

200

0 25Age

Size

(cm

)

Historical Regime Current Regime

0 25Age 0 25Age 0 25Age

Age 10.1

Size 97.5 cm

Age 4.2

Size 48.4 cm

EvolutionaryEvolutionarychangechange

Ulf DieckmannTask 1.3

Conclusions• Fisheries-induced evolution has been with us for

several decades without having been properly recognized.

• The speed of such evolution is much faster than previously believed .

• Fisheries-induced evolution affects yield, stock stability, and recovery potential.

• Models suggest that each year during which current exploitation continues may require several years of evolutionary recovery:

A “Darwinian debt” to be paid by future generations.

Ulf DieckmannTask 1.3

Determination of changes in stock distributions and migrations

• Objective: Examine and model the known distribution and migration patterns of the target species under high and low stock sizes and evaluate the consequences of changes in environmental conditions during periods of stock recovery

Task 1.4

Changes in thorny skate distribution during a stock decline

From Kulka & al 2004

Contracted range

Task 1.4

Changes in Norway pout distributionduring a stock decline

1999 2002

2000 2003

2001 20042004

0

2000

4000

6000

8000

10000

12000

14000

1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003

Ab

un

da

nce

ind

ex

(1+

)

0

2000

4000

6000

8000

10000

12000

14000

1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003

Range upheld

Task 1.4

Topics

• Variability in distributions and migration patterns

• Resolution of factors driving migrations and distribution

• Modelling of optimal or realised habitats• Assessing the risk for collapse and

likelihood of recovery due to different spatial patterns

Task 1.4

Work plan• Gather data to describe seasonal and

interannual distribution/migration of target stocks

• Analyse distribution/migration with regards to: – Environmental variability– Demography– Density depedence

• Develop models for migration/distribution

Task 1.4