A field energy budget for northern pike, an aquatic

piscivore

James S. Diana

School of Natural Resources and Environment

University of Michigan

Philosophical debate

• A man has only enough time to do what he truly thinks is necessary (Goethe)

• An animal only has sufficient energy to do what is important to improve its fitness– Evolutionary fitness = maximize production of

successful offspring– Measures of fitness = number of eggs produced,

number of spawnings, growth rate– Basic theoretical constraint behind energy budgets,

which are believed to be highly evolved

Energy budget• Really defines how an animal makes a living• Can parallel it to a bank account

– Paycheck = amount of food eaten

– Uses = body maintenance, activity, growth, reproduction

– Can borrow on the short term from energy reserves in lipids, body protein, etc.

– On long term – has to balance, no loans

Bioenergetic models

• Take known physiological information, along with growth rate, prey types, and temperature of an ecosystem/species to predict food consumption by prey type

• Unless ration is also measured in field, there is no way to corroborate predictions

• Usually assumes something regarding fish activity, for example, no cost of activity or activity doubles metabolic rate

• Used widely in fishery management

Energy budget for pike in Lac Ste. Anne

• We set out to determine all components of pike energy budgets in order to evaluate growth dynamics of pike and growth-reproduction tradeoffs

• Measured growth, activity, and ration in field, metabolism, feeding efficiency, and digestion costs in lab at field temperatures

• Then applied to test fit of model to real data, and evaluate reasons for errors

Growth methodology

• Collect and sacrifice fish over regular periods of summer (monthly) and winter (every 2-3 months)– Gillnets as collection method– Only feasible method for winter collection– Not very size selective for pike because they

mainly catch by their teeth

• Evaluated seasonal dynamics for 3-year-old fish, annual values for ages 0-4

Pattern of pike growth

0

500

1000

1500

2000

En

ergy

Con

ten

t (k

cal)

Body

Liver

Gonad

Total

a) Males

0

500

1000

1500

2000

M A M J J A S O N D J F M A M

Month

Ene

rgy

Con

tent

(kc

al)

b) Females

Pike pattern• Males and females grow in

body over summer• Females grow in gonads over

winter, males in body• Ovary growth much higher

than testicular growth• Overall females grow faster

than males, must eat more

Age Body kcal Gonad kcal

Males

0 554 4

1 372 19

2 284 18

3 177 22

4 541? 34

Females

1 376 177

2 141 268

3 373 436

4 278 454

Ration methods

• Determine stomach contents and number of empty stomachs– Pattern = asynchronous feeding with no diel

pattern– At any time, meal frequency is percent empty

related to digestion time, fish with food estimate meal size

• Coupled with lab data at each temperature on digestion rate

• Ration = meal size divided by meal frequency

0

25

50

75

100

0 3 6 9 12 15 18 21 24

Time (h)

Per

cen

t in

Sto

mac

h

Feeding pattern

0

50

100

150

200

250

300

350

400

450

1 3 5 7 9 11 13 15 17+

Number of items per stomach

Fre

qu

ency

of

occu

rren

ce

N = 665

Diet and ration contribution

Species Number eaten Calories eaten

Perch 970 (69%) 6286 (54%)

Spottail shiner 322 (24%) 829 (7%)

Burbot 71 (5%) 1313 (11%)

Sucker 29 (2%) 2592 (22%)

Whitefish 3 (0%) 140 (1%)

Walleye 2 (0%) 366 (3%)

Pike 1 (0%) 23 (0%)

Size of food important

• Shiners and perch numerous but small

• Suckers and burbot rare but large– Contribute over 1/3

of annual consumption

Daily rationsMonth Sex Meal Size (kcal/kg) Time between

meals (days)Daily ration (kcal/kg/d)

May Male 30.4 3.1 9.6

Female 32.4 2.3 14.0

June Male 35.0 1.9 18.1

Female 66.5 2.2 30.9

July Male 36.5 2.1 11.5

Female 54.1 2.8 19.2

August Male 23.1 3.8 6.0

Female 25.4 2.6 9.8

September Male 22.5 3.5 6.4

Female 31.4 4.2 7.5

October Male 17.4 2.2 7.9

Female 16.5 1.9 8.6

January Male 9.8 34 0.3

Female 22.0 23 1.0

March Male 10.9 22 0.5

Female 21.6 26 0.8

April Male 14.8 59 0.3

Female 14.8 59 0.3

Ration results

• Females eat more than males (17.4 vs. 11.4)

• Highest consumption in spring (30-18)

• Spawning fast in April

• Low but significant consumption all winter

Telemetry• Surgically implanted transmitters

• Followed fish using boats and hydrophones

• Had to use shore landmarks and compasses for location

Northern pike movements

• Moved largely over nearshore zone

• Returned to similar locations at time

• Home range? – if so very large

• Did use specific habitats

Distances moved

0

5

10

15

20

25

30

35

100 300 500 700 900 1100 1300 1500 1700 1900 >2000

Distance Moved (m)

Perc

ent o

f Mov

emen

ts

Winter (n=44)

Summer (n=36)

Pike habitat

Characteristic

Summer

Winter

Depth 0-1.9 m 23 (52%) 4 (21%) 2-3.9 19 (43%) 12 (63%) 4+ 2 ( 5%) 3 (16%) Vegetation Emergent 31 (49%) 2 (12%) Submergent 29 (46%) 0 ( 0%) None 3 ( 5%) 15 (88%) Distance from 0-99 m 27 (40%) 21 (21%) shore 100-299 26 (38%) 54 (53%) 300-599 13 (19%) 23 (23%) 600+ 2 ( 3%) 3 ( 3%)

Pike activity methods

• Measure regularly from multiple points• Determine locations over short time intervals• Can evaluate activity pattern and swimming

speeds• Could also use buoy array or other new

methods

Pike diel activity

Activity summary

• Fish were commonly inactive, sit-and-wait predators

• No displacement over 80% of the intervals observed

• When moved, generally moved rather slowly but constantly

• Most likely the cost of activity is negligible in an energy budget

Overall energy budget balance

• Calculate ration from observations, compare to ration predicted from Wisconsin bioenergetics model

• Evaluate errors and determine fit

• Evaluate reason for errors

Budget balance

-5

0

5

10

15

20

25

30

M J J A S O N D J F M A

Month

Rat

ion

(kca

l.kg-1

.d-1

)

Actual Ration

Predicted Ration

Budget balance

• Lots of variation in summer, but correct overall trend

• Error most likely due to errors in ration estimate

• For next part, accept that models of metabolism and measured growth are accurate

Pike age-related costs

Growth Reproduction Maintenance

Males 0 558 (42%) 0 776 (58)

1 137 (8) 77 (4) 1606 (88)

2 238 (10) 108 (5) 1992 (85)

3 192 (7) 94 (4) 2391 (89)

Females 1 102 (5) 279 (14) 1662 (81)

2 190 (7) 286 (11) 2081 (81)

3 287 (8) 549 (16) 2609 (76)

Other poor fits - esocids

0

0.02

0.04

0.06

0.08Tiger muskie

0

0.02

0.04

0.06

Pre

dict

ed R

atio

n (g

. g-1

. d-1

) Pike

0

0.02

0.04

0.06

0 0.02 0.04 0.06 0.08

Measured Ration (g . g-1

. d-1

)

Muskellunge

Applying bioenergetics and energetic models

• Growth and reproductive tradeoffs – Larger size = more energy for

protecting nest, also more capable

– Larger size = more fecundity

– Older age = less likely to survive to breed

– Maturation is a shift of energy away from future growth into current reproduction

– Natural selection acts strongly on this

Latitude and pike energetics

• Growth of pike in Michigan– Variation in winter 3 to 5 months– Similar levels of maximum temperature– Compared growth and maturation across 3 lakes– Found no major differences in growth for fish

from each lake

Latitude and pike maturation

Murray Houghton Vieux Desert

Males 1 71% 100% 80%

2 80% 100% 94%

3 100% 100% 100%

Females 1 17% 80% 31%

2 67% 100% 100%

3 100% 100% 100%

Pike maturation

• Not a clear latitudinal cline

• Was related to intensity of fishing

• Fishing adds mortality, size selective for older fish, that may reduce frequency of late maturing fish in gene pool

Stunting in pike

• Common pattern in inland lakes

• Mature early, grow slowly, all adults reach a terminal size

Stunting in pike

• Common ideas for mechanisms– High density and competition– Warm water and lack of thermal refuge– Lack of large prey?

• Perfect system for energetic modeling

Temperature profiles

Stunting simulations

Problems with such simulations

• No limits on fish growth, unlike nature

• Produces potential growth but not necessarily possible growth

Conclusions

• Energy budgets can describe major decisions and allocations that have evolved in animals

• They require much site specific work to produce a corroborated budget

• They can lead to good understanding of the limits to fitness

• They can be useful in understanding how animals adapt to environmental challenges