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
Energy Content (kcal) Energy Content (kcal) Pattern of pike growth 2000 a) Males 1500 1000 500 Body Liver Gonad Total 0 2000 b) Females 1500 1000 500 0 M A M J J A S O N D J F M A M Month
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
Percent in Stomach 100 Ration methods Determine stomach contents and number of 75 empty stomachs Pattern = 50 asynchronous feeding with no diel pattern 25 At any time, meal frequency is percent empty related to 0 digestion time, fish with food estimate 0 3 6 9 12 15 18 21 24 meal size Time (h) Coupled with lab data at each temperature on digestion rate Ration = meal size divided by meal frequency
Frequency of occurrence Feeding pattern 450 400 350 300 250 N = 665 200 150 100 50 0 1 3 5 7 9 11 13 15 17+ Number of items per stomach
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 rations Month 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
Percent of Movements Distances moved 35 30 25 Winter (n=44) Summer (n=36) 20 15 10 5 0 100 300 500 700 900 1100 1300 1500 1700 1900 >2000 Distance Moved (m)
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 Time Active Inactive Summer Sunrise 19 (22%) 68 (78%) Day 71 (17%) 351 (83%) Sunset 16 (21%) 62 (79%) Night 1 ( 2%) 63 (98%) Total 107 (16%) 544 (84%) Winter Sunrise 9 (23%) 30 (77%) Day 34 (19%) 142 (81%) Sunset 26 (35%) 49 (65%) Night 1 ( 2%) 43 (98%) Total 70 (21%) 264 (79%)
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
Ration (kcal.kḡ 1.d -1 ) Budget balance 30 25 Actual Ration Predicted Ration 20 15 10 5 0-5 M J J A S O N D J F M A Month
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)
Predicted Ration (g. g -1. d -1 ) Other poor fits - esocids 0.08 Tiger muskie 0.06 0.04 0.02 0 Pike 0.06 0.04 0.02 0 Muskellunge 0.06 0.04 0.02 0 0 0.02 0.04 0.06 0.08 Measured Ration (g. g -1. d -1 )
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