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NEKTON

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Nekton:contrary to plankton, nektonic organisms are not passively carried by ocean currents. They may be characterized as "swimmers" because they, at least to some degree, can determine their movements and position in the water.

Marine nektonic organisms include several animal groups:

• molluscs (snails, cephalopodes)• crustaceans (shrimps, swimming crabs)• fishes (cod, herring, salmon)• reptiles (water snakes, turtles)• mammals (seals, dolphins, whales, sea utters)• sea birds (cormorants, puffins)

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The present course will focus on one particular group of nekton, namely fishes. However, some field methods and many lab methods are similar or identical in studies of other groups.

We shall focus on how to explore the individual and general biology of fishes, their distribution in the oceans (currents, migrations), and their genetic properties and population structures (in other words the subdivision of fish species into separate reproductive units). Note that a reproductive unit, or a population, may not mean the same as a stock, which is a much more loosely defined group. Fisheries management has traditionally been about stocks. Ideally it should be focusing on populations, i.e. the real reproduction units. Those units are identified and characterized by both biological and genetic methodology.

In this course we will demonstrate measurements, instruments, laboratory methods and statistical tools that can help us gain information of and insight into these topics with the aim to improve our management of marine resources.

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BI3060H08 Fish(eries) biology and population genetics

Fish stocks; methods for identification, delimitation, and characterization.

Stock identification• Catch statistics (movements of fleet, landings)• Tagging-recapture studies (Lea-tag, Floy-tag, PIT tags, eye-tags)• Biological characterization (growth, age at first maturity etc)• Genetic characterization (gene markers, allele frequencies)

Practical sampling• Length, weight, age, sex, gonadic stage, maturity age• Fish scales and/or otoliths for ageing, tissue biopsy and autopsy• Blood- og tissue samples for genetic and clinical chemistry analyses• Securing data and measurements in e.g. Excel spreadsheets

Analyses• Age determination (scales, otoliths) • Electrophoretic analyses (blood, isozymes, DNA markers)• Relative yearclass strength from age composition in samples• The term MLY (maximum long term yield) or MSY (...sustainable...)

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A research vessel equipped for trawling is a basic prerequisite.This is the research vessel R/V "Gunnerus" of NTNU, Norway.

Fish(eries) biology and population genetics

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Fish stocks and migrations

North-East Arctic cod (NEAC; skrei)


Nursery areas, migration routes, and spawning areas for the NEAC cod stock.

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Herring in the Trondheimsfjord



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Atlantic salmon

The Atlantic salmon (Salmo salar) is found on both sides of the north Atlantic. The main salmon stocks today are Norwegian(ca 500 salmon waterways). After some years in fresh water the salmon parr smoltifies, and miigrates to nutrition-rich oceanicwaters..It reaches maturity after 1-3 years there, and returns to its birth river to spawn. Norwegian river stocks utilises the Norwegian Sea for its marine growth stage, but salmon from western European (Ireland, Spain) countries migrates more frequently to Greenlandic waters for the ongrowth period.



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Salmonids are anadromous, i.e. the migrates to fresh water for reproduction. Salmon are capable of traversing strong rapids and high waterfalls on its route to the spawning places.


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NEKTON AND FISHERIES

OCEANOGRAPHY


The large oceanic current systems dictate both climate and pelagic transport routes in the North Atlantic.

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Bottom topography of the north Atlantic

NEKTON AND FISHERIES OCEANOGRAPHY

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The termination of the last glaciation marks the start of the expansion period which resulted in the current distribution of fish species in the north Atlantic, including Scandinavia.

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Methods in fish(eries) biology

Fish(eries) biology and population geneticsBI3060H08

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The morphology of fishes is basis for species identifications, and clue to their habitats and way of life. The "bird" and three dorsal fins are, e.g. characteristic of gadoids. Internal anatomies and organs are more or less variations on the same theme for vertebrates.



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Migrations: Tagging-recapture

Four commonly used fish tags. From top: PIT tag (passive integrated transponder tag), Floy anchor tag, Lea hydrostatic tag, and another Floy tag. The Floy tags are pushed by a tagging pistol into the fish muscle, whereas the Lea and PIT tags are put in place with special-made needles. Inside the Lea tag is a letter in English, Russian and Norwegian, in which the Finder is asked to return the tag with data on size, sex, and date, gir and depth of catch. Also the otolith, which is used for age determination, is asked for.



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Fish stocks; methods for identification, delimination, and characterization.

Year-class strength estimated from age composition in samples

Approach:

• Sampling with non-selective gir (fine-mesh trawl)• Determine individual age of specimens (otoliths)• Tabulate number in different age groups (year-classes)• Linear regression to find mean annual mortality• Put mortality into formula for number at time=t • Express each year-class as percent of the best year-class• Draw the curve for relative year-class strength on a time scale


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Age determination bymeans of annual zones in theotoliths.

Photos are from codFrom the Trondheims-Fjord (Photo Ekli).

Determination of the deposition pattern duriing the first year of life is a critical step in ageing.It can be difficult to interpret, and warrants a time series of one year.

The age composition in a sample can be used to calculate relative year-class strength for the stock under study.


Year-class...

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Relativ årsklassestyrke Borgenfjord torsk

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40

60

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100

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1963 1965 1966 1969 1970 1971 1972

Årsklasse

% a

v st

ørs

te

Year-class Percent

1963 100

1965 49

1966 61

1969 39

1970 16

1971 23

1972 14

Relative year-class strength; example

Cf method of calculations on the next slides


Year-class...

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Calculating annual mortality:Use formula Nt=N0e-zt, in ln-format:ln(Nt) = ln(N0)

- zt [ corresponds to Y=a + bX in linear regression ]

Put in paired values for t and ln(Nt) in some statistical programmePerform an linear regresion.The slope in the regression will be the z in the formula at top of pageAnnual survival S will then be e-z, and annual mortality (x) is (1-S)

Calculation of relative year-class strength: Use the formula N0 = Nt / (1-x)t , where x is the mean annual mortality (calculated as shown above).Get the intrinsic strength relations for the year-classes.Set the largest year-class to 100%, and let the other be proportional to that value.Plot the sizes on a time scale (years).


Year-class...

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Assume a sample caught in the year 1990 with the followingage distribution obrained by otoilitg readings:bestemt ved otolittlesning:2 years: 710 individuals (year-class 1988)3 years: 240 individuals (year-class 1987)4 years: 50 individuals (year-class 1986)

Nt=N0e-zt

ln(Nt) = ln(N0) – zt

t Nt ln(Nt)

2 710 6.5653

3 240 5.4806

4 50 3.9120

A linear regression of ln(Nt) on t gives a slope (=regression coefficient) z = - 1.3266.Converting back gives z = (2.718^(-1.3266))=0.2654. Annual survival (S) is thus: S = 0.2654, and annual mortality x = (1-S) = 0.7346. By the formula N0 = Nt / (1-x)t

the relative year-class strengths (relative in parenthesis): 2 years (1988) : 1315.5 (100%)3 years (1987) : 605.4 (46 %)4 years (1986) : 171.7 (13%)


EXAMPLEYear-class...

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MLY (maximum MLY (maximum long term yield)long term yield)


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Population genetics methodsPopulation genetics methods


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Population genetic methodsPopulation genetic methods

has gained increased interest for the detection and delimination of reproductive units of marine stocks in the last 4-5 decades, particularly for species which do not lend theirselves easily to tagging-recapture studies. In order to apply genetic tools we need to know the individual genotype for specific heritable traits. Such information is readily obtained by various electro-phoretic methods (cf figures to the right, and later slides).

In this course we use the individual genetic signature for species identification of anonymous tissue samples, as well as for establishing genetic characteristics for populations.


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Population genetic methodsPopulation genetic methods

When having collected samples and performed electrophoretic determination of individual genotype for some character (e.g. LDH or PGM as in this course), there are two basic types of statistical tests to be performed:

First, we want to test whether each of our samples are drawn from unit populations, i.e. from "pure" populations in so-called Hardy-Weinberg equilibrium (cf HW-slide).This we do with the so-called Chi-squared Goodness-of-fit test (cf HW-slide).

Secondly, we want to test whether there are genetic differences between our samples, i.e. whether they may have been drawn from different populations with different genetic characteristics. This is done with another chi-square test, the so-called Chi-squared RxC contingency table test, also called the chi-squared test of homogeneity (cf RxC slide).

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Methods for characterising stocks by their frequencies of various ndividual enotypes

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Genetic population characterization Populations which are fully or partly reproductively isolated from other populations within a species may, over time, develope genetiic differences which may be characteristic for each population. The characteristics may be such as growth rates and age at maturity, which are ”polygenic traits” influenced by genes at many loci. Other traits, like blood type and eye color in man, are determined by only one locus and are called single-locus traits. Such traits can be very usefull for characterizing different populations, because the frequency of the different gene variants according to genetics theory are constant over generations for any given population (under a set of assumptions). Such traits are used in genetic investigations of stock structure. Instead of looking for external morphological characteristics, it is usually more efficient to perform biochemical analyses which can discover the “genotype” of the individuals for non-visible traits like tissue enzymes, haemoglobins etc. These analyses are the same as those used in fathership tests and forensics. Protocols exist for a long series of tissue enzymes (more than100) for routine use. One advantage with such analyses id that the individual variation is very easy to interpret genetically. The systems are not hampered by such things as dominance and recessivity, meaning that one in the laboratory can identify the contribution from both the father and the mother to an individual’s genotype. Usually, the technique of electrophoresisi is used in such studies. This technique is based on the fact that all proteins are coded for by one specific gene (one locus). The genes are often represented in various variants through mutations, and it is the frequency of the different variants which is a population characteristic. Proteins coded for by different gene variants differ in amino acid sequence, which gives rise to differences in electric charge at a specific pH (the proteins are “amphoteric” and have their own specific isolectric point). Hence, it is possible to identify different genes by mobility of their products (i.e. proteins) in an electric field. To determine whether variation between individuals is genetic, one performs crossing experiments with parents with known genotype to confirm Mendelian inheritance of the variants (leftmost in figure next page). Also on the next figure is a hypothetic collection of different genotypes determined by electrophoresis. In this collection we count 2 individuals of type AA, 6 AB, and 8 BB. If we count the single bands we find 32 altogether, of which there are 10 A bands. Thus, the frequency of the A gene in the collection is (10/32=)0.31, and likewise the frequency of the B gene is 0.69. These frequencies are expected to be constant over generations and are therefore charateristics for the population from which the sample was drawn.


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Genetic nomenclature (jargon):

Synonyms: Gene frequency = allele frequency = allelic proportion

The frequency of an allele (e.g. A) is often abbreviated qA, qB, qC, etc,or alternatively, pA, qB, rC etc.

In general, the phenotypes (e.g. active isozymes, proteins) are written in normal font (e.g. AA phenotype) while genotype is written in Italic (AA genotype). However, there is no general consistency between textbooks in how this is handled.


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• Populations are the real evolutionary units.• The raw material of evolution are mutations, which can accumulate with time• in populations and species, and result in multiple alleles at many loci.• Evolution can thus be defined as "any change in allele frequencies".• The frequencies of different alleles at a locus can be changed by the • 4 evolutionary forces, which are:

• MutationsMutations• Random genetic driftRandom genetic drift• Gene flow (immigration)Gene flow (immigration)• SelectionSelection

If these forces are nullified, we have what is called a "Hardy-Weinberg population"; apanmictic (random mating), statistically ideal population where the allele frequencies, and thereby the genotype frequencies, are constant and do not change over generations (a socalled H-W equilibrium). The population genetic approach is to assume a H-W equilibrium situation, and then study how the 4 evolutionary forces each, and in combinations, influence the allele- and genotypic frequencies within and between populations.


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Underlying assumption for the H-W law about genotypic proportions:

• Panmixi (random mating)• No mutations• No random genetic drift (i.e. infinitely large population)• No gene flow between populations (i.e. no immigration)• No selection (same fitness of all genotypes)


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The Hardy-Weinbergs law:

"In a panmictic, statistically ideal population, the genotypic proportions are determined by the allele frequencies (p and q in the formula below) at the locus, according to the binomial formula (multinomial if more than two alleles)":

(p+q)2 = p2 + 2pq + q2 (if only two alleles)

The allele frequencies will be constant over generations and restore the same genotypic proportions in each new generation.Allele- and genotype frequencies can thus serve as population characteristics.


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Methods for the study of frequencies of single genes


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FF FS SS N Freq. F Freq. S Observed 10 28 12 50 0.48 0.52 Expected (11.5) (25.0) (13.5) (50.0)

Goodness-of-fit to Hardy-Weinberg expected distribution: chi-square = 0.742, df=1, P = 0.389, i.e. not significant deviation between observed and expected genotype distribution.

Chi-squared test for goodness-of-fit to H-W proportions

Assume that we have studied a locus with two alleles by electrophoresis. We have named the alleles F and S according to their electrophoretic migration distance (Fast and Slow). There are three possible genotypes (FF, SF og SS). In a sample of N=50 individuals from a natural population we observed 10 with genotype FF, 28 with genotype SF, and 12 with genotype SS. We want to test if this genotype distribution is reasonably close to the H-W expected values calculated from the observed allele frequencies in the sample. For this we use a so-called chi-square Goodness-of-fit test (table below). We use a table of critical values of the chi-square distribution in some text book to check the significance level of the chi-square value calculated. The degrees of freedom (df) is caclulated as the number of genotypes minusthe number of alleles (i.e. df = 3-2 =1).


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To test for differences in allelic or genotypic proportions between samples we use a RxC (rows by columns) chi-square contingency test. We usually test for both genotypic and allelic heterogeneity between samples. The latter is statistically the most powerfulI one. Consider two samples of N=100 each, and one polymorphic locus with two alleles (A og B):

Genotypes_______ Samples AA AB BB N ---------------------------------------------------------------------------------------------Sample 1 36(26) 48(48) 16(26) 100 Sample 2 16(26) 48(48) 36(26) 100---------------------------------------------------------------------------------------------Total 52 96 52 200 =====================================================Our "Null hypothesis" for test is that the samples are taken from one and the same population. If so, our best estimate of the true genotype and allele distribution in the materials is found in the "Total". We therefore use the distribution in the "Total" to estimate what "should have been" in the two single samples (we "forget" about the H-W distributions in this test).The expected number of AA genotypes in Sample 1 is then, e.g., ((52/200)*100)=26. As in all chi-square tests we find the test observator in this way: Take the square of the difference between observed and expected value, and divide it by the expected value. Do this for all genotypes in both samples, and sum the results. The number of degrees of fredom in a contingency table (RxC) is calculated differently from the "H-W Goodness-of-fit". Degrees of fredom is here calculated as (R-1)(C-1). For the genotypic values in the table above, we find a chi-square value of 15.38, and 2 degrees of freedom. In a textbook table of the chi-square distribution we find that this corresponds to a significance level of P < 0.001. (actually the exact P-value is 0.00046). For testing for homogeneity of allelic proportions in the same two samples, the RxC table will look like this: Allele _ Sample A B N----------------------------------------------------------------------------------------------Sample 1 120(100) 80(100) 200 Sample 2 80(100) 120(100) 200----------------------------------------------------------------------------------------------Total 200 200 400=====================================================The chi-square for this table is 16.00. However, here we have only one degree of freedom. Therefore the P-value for this outcome (P=0.00006) is lower than in the genotype test. In both tests, the null hypothesis can be safely rejected. Our samples are not from the same population.

Chi-squared RxC test of genetic homogeneity of different samples (populations)

BI3060H08Fish(eries) biology and population genetics

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Results from electrophoretic analyses H08Results from electrophoretic analyses H08

Genetic species identifications:

Muscle tissue from 13 individual fish of various species were analysed for the tissue enzyme LDH (Lactate dehydrogenase; E.C. No. 1.1.1.27) by IFPAG, according to a protocol handed out as a leaflet in the lab.

The individual banding patterns for the muscle LDH locus were diagnostic to species for the 13 individuals (cf photo next slide). Minor "muscle" LDH activity was also observed in blood haemolysates (cf photo next slide).

In the cod, a known polymorphism at the anodic LDH "heart locus" was manifested as homo- and heterozygote patterns typical for a tetrameric protein (cf photo next slide). The other species were monomorphic.

The cod inter-locus hybrid bands were consistent with hybrid tetrameric molecules between the monomorphic muscle locus and the polymorphic heart locus (cf photo next slide).


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Below: Photo of IFPAG gel stained for LDH in 13 individual fish on the BI3060 course H08


+

-

IFPAG gel T=5%, C=3%, Servalyt 4-9 T

From left to right: 5 cod, 2 pollack, 2 cod, 2 pollack, 1 saithe, and 1 poor cod.

Upper frame shows non-diagnostic heart locus bands; cod heart locus polymorphism evident.

Lower frame showsmuscle locus bands; these bands are diagnostic to speciesin Norwegian gadoids.

Bands in-between theframes are inter-locushybrid molecules of theLDH tetramer.

Genetic species identifications

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Starch gel electrophoresis of the tissue enzymes LDH and and PGM in a sample of cod from the Trondheimsfjord in March/April 2008. Results from individual genotype counts.

LDH-3* 100/100 70/100 70/70 Total

Observed 14 18 5 37

PGM-1* 100/100 100/80 100/120 Others Total

Observed 32 4 1 0 37

For Chi-squared HW-goodness-of-fit tests of these two genotypedistributions, refer to procedure on slide # 33.


Genetic characterization of populations

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Genetic characterization of populations

Sampling loc. & date 100/100 70/100 70/70 Total

Verrabotn 08-03-31 1 ) 14 18 5 37

Borgenfjord 83-10-12 2 ) 98 122 42 262

LDH-3* genotypic distributions in two samples of cod from the inner partof the Trondheimsfjord, sampled with 25 years interval (1983 and 2008).

1) Materials from LTS cruice March/April 2008, analyzed at BI3060 course autumn 20082) Published data from Mork & Sundnes 1985 ("O-group cod in captivity...")

To check (with a chi-squared RxC test) whether the genotypic proportions in the two samples from the Trondheimsfjord are homogeneous, refer to statistical procedureon slide # 34.

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SEPARATION SLIDE

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INSTRUMENTS AND KITS USED ON THE COURSEINSTRUMENTS AND KITS USED ON THE COURSE


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Starch gel electrophoresis setup

Power supplyCirculatingcooler

Electrophoresis cell


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Age determination by otoliths is done in a stereo-microscopewith low magnification (10-16 X ocular, no objective).


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DIALUX microscope used for study of blood smears.


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Instrument for clinical-chemical analyses (Reflotron "dry chemistry")


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Instrument for Isoelectric focusing in polyacrylamide gel (IFPAG)


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Haematocrit centrifuge


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Scanner device for PIT tags (passive integrated transponder)

PIT tags (1x10 mm)


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Tagging needle and Lea hydrostatic tag


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Tagging gun and Floy anchour tags


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Biopsy needle


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Merck "Hemocolor" quick staining kit for blood smears


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Glass cassette and recipe for molding gel for IFPAG


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Close-up photo of IFPAG gel stained specifically for the enzymeLDH, lactate dehydrogenase (E.C. 1.1.1.27). The three commongenotype patterns for the "heart locus" polymorphism are seen inthe uppermost (anodic) part of the gel.

Heart locus (1 or 5 bands)

Muscle-heart hybrid bands (1 or 3 bands)

Muscle locus (1 band)

Gel patterninterpretation

Anode ( + )

Cathode ( - )


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The appearance of Trypanosoma sp. in a blood smear from Atlantic cod (Gadus morhua L.).


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Table 1 from Mork (1988) showingthe prevalence of Trypanosoma sp. in various locations in Norwegiancoastal waters.


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Example of Excel database. Notice the date format, which make possible sorting by chronological order. For genotypes, a fixed scheme for notation must be established to avoid sorting confusion.


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bi3060h08

Documents

main salmon stocks

population structures

salmon waterways

age composition

general biology of fishes

trondheimsfjordfish

salmon reptiles water

salmon parr smoltifies