Lecture 2 review

• Maximizing long term harvest can generally be achieved by following a “fixed escapement” harvest rule WHICH BRINGS STOCK TO ITS MOST PRODUCTIVE SIZE AS QUICKLY AS POSSIBLE THEN HOLDS STOCK AT THAT SIZE

• Nearly the same long term harvest can be achieved by following a “fixed exploitation rate” rule, much less damaging to fishers

• Tactics for regulating harvest rates involve either input (effort) or output (catch) controls

• Output controls are dangerous and require accurate assessments of stock size

• Complex management objectives and performance measures are an invitation to gridlock in decision making

Limits to compensatory responses• Most populations exhibit high juvenile

survival at very low densities

• But occasionally (5-10%?) compensation fails at low densities, leading to low equilibrium or extinction

N

SJ

SJ

N

-Allee effect (eggs don’t get fertilized, eg scallops); rare

-Cultivation/depensation (competitors/predators of juveniles increase when N is low, eg bass-bluegill)

-Trophic cascades (green water/clear water states)

-Botsford’s effect (size dependent cannibalism)

(Invasive species have to exhibit this ability)

Life history trajectories

• Whenever you handle a fish, ALWAYS ask yourself these questions:– How old is it?– Where was it spawned?– Where will it spawn?

Life history stanzas (partitions of the life history trajectory)

The eggie

Larval drift, density-independent mortality

Juvenile migrationFirst juvenile nursery area: small, strong density-dependence in mortality

Spread into larger juvenile nursery area(s), mortality much lower

Adult foraging areas, most often with complex seasonal migration patterns

Spawning migration

Fractal, complex diurnal movement

Characteristics of LHT

• There is typically very strong selection for behaviors that take fish back to spawn in the places where they were successfully produced (this is not just a salmon thing)

• Seasonal migrations become more pronounced as fish grow

Time

Random model

Distance from tagging site

Migration model

Distance from tagging site

Time

Characteristics of LHT

• Natural mortality rates vary as M=k/(body length), starting at a few percent per day and often falling to a few percent per year

• Body growth typically follows a vonBertalanffy length curve of the form

length=L[1-e-K(a-ao)]• Sometimes there is a “kink” in the growth curve,

with small juveniles either showing extra fast growth (if they seek warm microhabitats) or extra slow growth (if they face very high predation risk).

Is the Beverton-Holt invariant M/K=1.6 a valid generalization for stock

assessment?

y = 2.1161x

R2 = 0.5872

y = 1.6372x

R2 = 0.3182

y = 2.0041x

R2 = 0.8567

y = 1.1363x

R2 = 0.2195

0.01

0.1

1

10

100

0.01 0.1 1 10

vonBertalanffy K

Na

tura

l mo

rta

lity

ra

te M Age structure data

Length converted catchcurve

Tagging

Z vs E plot

Characteristics of LHT• Maturation typically occurs at 50%-70% of maximum

body length, with fecundity then being proportional to body weight

0

10

20

30

40

50

60

70

0 2 4 6 8 10 12

Age (years)

Len

gth

(cm

)

0

500

1000

1500

2000

2500

3000

3500

4000

Wei

gh

t (g

)

Length (cm)

Hayes model Length

wt (kg)

Hayes Model weight

But some fish like these New Zealand brown trout practically stop growing at maturity, and make massive (45%) investments in eggs (Hayes et al TAFS 2000)

Representing LHT in models

• Age structure accounting (block trajectory by even age intervals)

• Stanza structure accounting (Ecosim)

• Individual-based models (track movement)

[N1 N2 N3 …]t [N1 N2 N3…]t+1 (easy in spreadsheets)

Log Numbers at age

Age (months)

Weight at age

Log Numbers at age

Age (months)

Weight at age

X,Y positions and fates of large sample of individuals

Ways to represent space in models

• Total areas by habitat class, without regard to spatial arrangement (A1,A2,…)

• Irregular spatial areas (“polygons”)

• Regular spatial cells (“rasters”)

A1 A2

Spatial Management

Dealing with complex dynamics

Spatial management is not just about MPAs

• Dynamic organization of shrimp fisheries: lessons for assessment, cooperative management

• Fishing for information: using logbook data to understand spatial stock structure and opportunities for more selective fishing practices

• Methods for modeling spatial stock dynamics

A tale of two gulfs

Spatial stock structure (Western king prawn)

Spatial life history

Nursery

Juveniles

Fishery(Adults)

St Vincent Gulf fishery

Spencer Gulf fishery

Contrasting management regimes

• St. Vincent Gulf (collapsed)– Ethnic fishery– Combative participants, severe misreporting– Assessments based on simple catch-effort

relationships• Spencer Gulf (sustained)

– Cohesive fishing communities– Neil Carrick: dogged persistence, many bar fights to

develop cooperative approach– Regulatory structure based on adaptive fishing policy

(time-area closures) based on repeated surveys and openings each year

Cooperative spatial surveys in Spencer Gulf

Assessment modeling options

• Empirical approach: fishing for information to map stock distribution and abundance several times during each season, cpue-based rule for ending annual fishery before depletion of spawning stock

• “Mechanistic” approach: develop detailed spatial model of physical drivers (currents, temperature, salinity), predict prawn recruitment, survival, movement

• (The mechanistic approach led to very costly research and modeling, never worked)

Multispecies fisheries: tradeoffs caused by technical interactions so

some stocks overfished at MSY

0

100000

200000

300000

400000

500000

600000

700000

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.55 0.6

Overall exploitation rate

Ave

rge

Yie

ld

SALIX CREEK

MOTASE LAKE

AZUKLOTZ CREEK

PINKUT BELOW WEIR

PINKUT ABOVE WEIR

PINKUT CHANNEL #1

FULTON BELOW WEIR

FULTON ABOVE WEIR

FULTON CHANNEL #2

FULTON CHANNEL #1

TWAIN CREEK

TSEZAKAWA CREEK

TAHLO CREEK

TACHEK CREEK

SOCKEYE CREEK

SIX-MILE CREEK

SHASS CREEK

PIERRE CREEK

PENDELTON CREEK

NINE-MILE CREEK

MORRISON CREEK

FOUR-MILE CREEK

BABINE - UNACCOUNTED

BABINE RIVER (SECTION4)BABINE RIVER(SECTIONS 1 - 3)ZYMOETZ RIVER - UPPER

NANIKA RIVER

CLUB CREEK - UPPER

CLUB CREEK - LOWER

SOUTHEND CREEK

ALASTAIR LAKE

KITSUMKALUM LAKE

CEDAR RIVER*

WILLIAMS CREEK

SOCKEYE CREEK

SCHULBUCKHANDCREEKBLACKWATER CREEK

SHAWATLAN CREEK

PRUDHOMME CREEK

J OHNSTON LAKE

DIANA CREEK

Lake

Skeena River sockeye salmon example: many stocks overfished at Fmsy

Selective fishing practices to achieve variable F targets over species

• Most common: forced discarding of sensitive species (e.g. escape ramps for dolphins)

• Modification of gear deployment (e.g. bait types, set depths, mesh sizes, escape gaps and grids)

• Selective space-time openings (e.g. salmon)

Temporal selectivity: Skeena River gillnet fishery example

Spatial selectivity

• Use detailed logbook and survey data to map species distributions, identify areas of high overlap and/or density of sensitive species (e.g. Fishmap)

• Adaptive spatial closures based on the mapping (e.g. Carrick’s shrimp fishery)

• Also use the mapping to develop “folly-fantasy” spatial cpue indices for long-term stock assessment

Partial separations in spatial distributions, BC trawl fishery

Sensitive species (longspine rockfish, Fmsy=0.05)

Productive species (English sole, Fmsy=0.2)