AMER. ZOOL., 25:973-986 (1985)
Energy Budgets of Ectothennic Vertebrates1
JAMES R. SPOTILA AND EDWARD A. STANDORA
Biology Department, Stale University College,
Buffalo, New York 14222
SYNOPSIS. Ecological energetics provides a unifying focus for ecological studies. Heat
energy budget analysis is used to predict the body temperatures of animals and their
microclimatic requirements. Climate space diagrams, transient energy balance models and
operative environmental temperature models predict daily and seasonal activity patterns,
predator—prey interactions and energy requirements of vertebrate ectotherms. Food energy
budget (resource allocation) models are used to investigate the life history processes of
fish, amphibians and reptiles. Heat energy budgets and food energy budgets interact
through their effects on body temperature and metabolism. Coupled heat, food and mass
balance equations can serve as a unified energy budget model and are useful in determining
limits on the energy available to an animal for growth and reproduction. Bioenergetic
models have been successfully applied to some reptiles and fish. Complete energy budgets
are now needed for other ectothermic vertebrates.
INTRODUCTION
ingested and chemical energy is released
by metabolic processes such that potential
energy is available for the immediate work
demands of the animal, such as growth and
movement, and the excess may be stored
for later use in reproduction or maintenance.
Unfortunately, but perhaps understandably, physiological ecologists have gone
down two parallel but separate research
paths. Some have focused on various aspects
of thermoregulation and temperature
adaptation. This has led to the use of the
principles of physics to understand the
interaction of the physical microclimate
with the body temperatures of animals.
Thus, when these authors consider energy
exchange they mean heat-energy exchange.
Others, however, have concentrated on
various aspects of food intake and utilization such as foraging strategy, diet optimization, and the energetic cost of reproduction in an attempt to better understand
life histories. Thus, when these authors
consider energy exchange they mean food
or chemical potential energy exchange.
Neither of these approaches alone is sufficient to understand the mechanisms
responsible for the life history patterns of
animals. At this time, we need a unified
ecological energy budget theory that com1
From the Symposium on Animal Energetics: bines heat energy budgets and food energy
Amphibians, Reptiles, and Birds presented at the Annual budgets in an overall framework that will
Meeting of the American Society of Zoologists, 27- help us to understand the roles of heat
30 December 1983, at Philadelphia, Pennsylvania.
Ecological energetics is a focal point for
the science of ecology. Since its inception
as a professional discipline at the turn of
this century, ecology has been concerned
with the adaptation of plants and animals
to their environment. While ecology is
rightly concerned with populations, communities, and ecosystems and physiology
concentrates on the study of the individual
as an upper limit of organization (Allee et
ai, 1949), physiological ecology bridges the
gap between these disciplines by considering adaptations of individuals that are
manifest in ecological processes such as
foraging behavior, competition, predation, population dynamics, etc. Physiological ecologists study ecological energetics
because energy is an important currency
of the cell, organism and ecosystem (Gates,
1962; Odum, 1971) and the study of energy
flow provides a unifying focus for ecological studies.
Animals are bathed in energy and all life
is a dynamic balance between energy gain
and loss. Heat energy exchange modulates
the interplay of biochemical, physiological
and behavioral processes by determining
the animal's body temperature. Food is
973
974
J. R. SPOTILA AND E. A. STANDORA
exchange and resource allocation in the
life histories of animals. In this paper we
will review previous research on heat
energy budgets and food energy budgets,
and discuss approaches to the formulation
of unified bioenergetic models using as
examples recent models developed for reptiles and fish. Cost benefit analysis and optimality theory are considered as adjuncts to
unified energy budget models.
where
M
R
C
XE
G
HEAT ENERGY BUDGETS AND
BIOPHYSICAL ECOLOGY
Much has been learned about the thermoregulation of fishes, amphibians and
reptiles since the pioneering studies of
Benedict (1932), Cowles (1940), Cowles and
Bogert (1944), Fry (1947), Brett (1956) and
others. Recent advances have been
reviewed by Reynolds and Casterlin (1979),
Brattstrom (1979), Hutchison and Maness
(1979), and others in an American Society
of Zoologists symposium (Amer. Zool. 19:
191-384). Temperature regulation of reptiles has been discussed by Huey (1982),
Avery (1982) and Bartholomew (1982).
Since Gates (1962) published his monograph on energy exchange in the biosphere, several authors have applied the
principles of biophysical ecology to the
study of thermoregulation. These have
included Bartlett and Gates (1967), Norris
(1967), Porter and Gates (1969), Spotila et
al. (1972, 1973), Porter et al. (1973), Bakken and Gates (1975), Tracy (1976), Porter
and James (1979), Bakken (1981), and
Christian et al. (1983) among others. Biophysical modeling has recently been
reviewed by Tracy (1982) and biophysical
ecology was considered in detail by Gates
(1980).
Heat energy budgets are based on the
fact that animals obey the laws of thermodynamics. Thus, if all energy flows can
be quantified, the body temperature of an
animal can be calculated. For steady state
conditions, in simplest terms
ENERGY IN = ENERGY OUT
and following the conventions of Gates
(1980) this becomes
Qab, + M = R + C + \E + G
(1)
radiation absorbed by the surface of the animal
metabolic heat production
radiation emitted by the surface
of the animal
energy transferred by convection
heat exchanged by evaporation
or condensation of moisture
heat exchanged by conduction
(through direct physical contact
of the animal with soil, water, or
substrate)
and all terms reprsent a flow of energy
(watts m~2).
All surfaces radiate heat in proportion
to the fourth power of the absolute temperature (Tr) of the radiating surface and
according to the emissivity (e) of the surface. Thus
R = e<r(Tr + 273)4
(2)
where a is the Stefan-Boltzmann constant
(5.673 x 10-8 W/m 2 °K4) and T r is in
degrees Celcius such that T r + 273 represents absolute temperature in degrees
Kelvin. For a vertebrate ectotherm on land
T r = T s , where T s is surface temperature.
For an animal with added insulation such
as fur or feathers, T r is temperature at the
surface of the insulation. For an animal
totally submerged in water R = 0, because
thermal radiation is not propagated in
water.
The rate of heat transfer by convection
is affected by wind speed or rate of fluid
flow, properties of the fluid, characteristics
of the surface over which the fluid flows
and the temperature difference between
the surface and the fluid. These complex
interactions are accounted for by an empirically derived convection coefficient, hc,
such that
C = hc(Tr - Ta)
2
1
(3)
where hc is in W m~ "C" , and T a is fluid
temperature (°C). For detailed treatments
of convection from vertebrate ectotherms
see Porter and Gates (1969), Mitchell
(1976), Kowalski and Mitchell (1976),
Campbell (1977), Erskine and Spotila
ECTOTHERM ENERGY BUDGETS
975
50
o
Pond Slider
Turtle26-32'C
40
Clear sky plus
ground -
<t -10
-20
Black
body200
400
600
OQbs (Wm-2)
FIG. 1. Climate space diagram for the preferred
J F M A M J J A S O N D
temperatures of the alligator, Alligator mississippiensis
(34-37°C), a turtle, Pseudemys scripta (26-32°C), and
MONTH OF YEAR
a snake, Thamnophis sirtalis (26-32°C). Based upon
calculations of Spotila et al. (1972), Foley (1976), and FIG. 2. Predicted seasonal behavioral pattern of the
desert lizard, Dipsosaurus dorsalis, at Palm Springs,
Scott et al. (1982).
California. Modified from Porter et al. (1973). This
lizard should have a bimodal activity period during
(1977), Foley and Spotila (1978), Tracy and the hottest part of the year and a unimodal activity
Sotherland(1979), Spotila^al. (1981), and period in fall and spring.
Tracy (1982).
Evaporation of water from an animal
results in the loss of heat energy of approximately 2.430 x 106 J kg" 1 at 30°C. This
is the latent heat of vaporization of water
(\), which is a function of the temperature
at which vaporization takes place. The
thermal energetics and mechanisms of
evaporation from amphibians and reptiles
have been discussed by Spotila (1972),
Tracy (1976), Spotila and Berman (1976),
Foley and Spotila (1978), Tracy and Sotherland (1979), Spotila et al. (1981), and
Tracy (1982). For an animal submerged in
water E = 0, because water is exchanged
in the liquid phase.
Conduction is negligible when an animal
has little contact with the ground, but can
be an important component of the heat
energy budget for amphibians, and reptiles
such as alligators, snakes and lizards, whose
venters often contact the ground (Tracy,
1976; Waldschmidt, 1978; Terpin et al.,
1979; and Scott et al., 1982). In water, conduction and convection are the dominant
avenues of heat exchange (Erskine and
Spotila, 1977). For a detailed discussion of
conduction see Tracy (1982).
Several authors have used heat energy
budget modeling to make predictions about
the energetics of vertebrate ectotherms.
The development of the climate space dia-
gram by Porter and Gates (1969) allowed
them to make predictions about the behavior of the lizard Dipsosaurus dorsalis. Similar analyses were used by Spotila et al.
(1972) to make predictions about the
behavior and habitat use by alligators (Alligator mississippiensis), Tracy (1976) for frogs
(Rana pipiens), Foley (1976) and Standora
(1982) for turtles (Pseudemys scripta) and
Scott et al. (1982) for snakes (Fig. 1). Porter
et al. (1973) used a transient energy balance
model to predict daily and seasonal activity
patterns, available times for predator-prey
interaction, and daily, seasonal and annual
requirements for food and water for D.
dorsalis (Fig. 2). By computing heat energy
budgets for garter snakes (Thamnophis sirtalis) and leopard frogs (R. pipiens) Porter
and Tracy (1974) determined that a 50 g
garter snake in Michigan required the
equivalent of fourteen 40 g frogs during
its 20 week activity period for maintenance, growth and maximum reproduction while the same snake in South Carolina would require eighteen frogs during
its 40 week activity period (Fig. 3). In an
analysis of the heat exchange of the African rainbow lizard, Agama agama, Porter
and James (1979) found that this lizard
could save up to 29% of its energy require-
976
J. R. SPOTILA AND E. A. STANDORA
GARTER
SNAKE
DIET
Reproduction
Growth
\ 3 4 Frogs
5 Frogs
Michigan
18 Weeks Activity
South Carolina
4 0 Weeks Activity
FIG. 3. The relative food energy budgets predicted
for the garter snake, Thamnophis sirtalis, in Michigan
and South Carolina based upon heat energy calculations of Porter and Tracy (1974). A snake in South
Carolina would have to eat more frogs during its longer
activity period in order to provide for its maintenance
diet. We assume a frog weighs 40 g.
merits by lowering its upper temperature
for activity from 40 to 35.5°C. As was true
for D. dorsalis, predictions indicated that
climate should have a substantial effect on
time budgets of both A. agama and its prey.
These predictions were within the observed
range of values for lizard diurnal and seasonal activity patterns and food requirements as determined in the field (James and
Porter, 1979).
Finally, biophysical models have been
used to assess the ability of lizards to reach
particular body temperatures within the
space they occupy. Christian et al. (1983)
demonstrated that seasonal and weekly
adjustments in the home range of the large,
long-lived Galapagos land iguana, Conolophus pallidus, occur in response to differences in the thermal environment. Crawford et al. (1983) used multiple regression
equations to calculate an operative environmental temperature (Te) for pond slider turtles (Pseudemys scripta) based upon
air and substrate temperature, wind speed,
and thermal radiation load. This Tc was a
good predictor of basking behavior of this
species with basking not being initiated
until T c reached 28°C. Waldschmidt and
Tracy (1983) were able to predict the times
of activity of the small short-lived lizard,
Uta stansburiana, and Roughgarden et al.
(1981) suggested that lizards of the genus
Anolis were separated in niche space along
two dimensions, food size or type and space
utilization (site at which particular body
temperatures can be attained). Thus, temperature acts as an ecological resource
(Magnuson et al., 1979) because animals
compete for a space in the environment
that allows them to maintain a particular
body temperature. Therefore, biophysical
modeling allows us to put an upper and
lower limit on the energy requirements of
vertebrate ectotherms and to develop time
budgets and models of habitat usage that
indicate when and where these animals can
forage.
FOOD ENERGY BUDGETS AND
EVOLUTIONARY ECOLOGY
Evolutionary ecologists have made considerable progress toward understanding
the adaptive nature of life histories since
Fisher (1930) developed his genetical theory of natural selection. Many theoretical
studies have attempted to identify environmental and demographic factors important in determining life history strategies
of animals under particular conditions.
These have implicated the demographic
environment, resource allocation, age-specific allocation of resources to reproduction and other factors as being important
in fashioning life histories (Cole, 1954;
Gadgil and Bossert, 1970; Williams, 1966;
MacArthur and Wilson, 1967; Pianka,
1970, 1972; Hirshfield and Tinkle, 1975;
Schaffer, 1974; Schaffer and Rosenzweig,
1977, among others). Though an adequate
framework to deal with the complex nature
of life history patterns is still lacking, several reviews have clarified the difficulties
with available theories and data (Murphy,
1968; Pianka, 1976; Stearns, 1976, 1977).
Recent progress in this area of research has
been the subject of excellent reviews by
Congdon and Tinkle (1982), Congdon et
al. (1982) and Vitt and Price (1982).
One important conclusion of this body
of research is that different selective forces
can result in similar life history patterns
(Wilbur et al., 1974). Thus, to understand
the processes responsible for these life histories it is necessary to determine the agespecific allocation of energy to reproduction and the relative allocation of net
assimilated energy to growth, maintenance, storage and reproduction. Congdon et al. (1982) present a food energy bud-
ECTOTHERM ENERGY BUDGETS
get (resource allocation) model for several
reptiles. Their generalized form of the
model is the following equation
(4)
Co = P + R + F + U
where, Co (consumption) is total food
intake, P (production) equals the energy
content of the materials digested during a
specified time interval, less that respired or
rejected, R (respiration) is the energy converted to heat and lost in life processes and
F and U are the energy content of feces
and urine, respectively.
The energy budget of an animal from
birth to age x can then be represented as
Cb + Ea = 2 *{[Esm(y) + Eamr(y)
y-0
Eamo(y)]
[Eg(y) + Er(y)
(5)
where y equals time, and the series of terms
in the first brackets is Maintenance and the
series in the second brackets represents
Production. In this equation, Cb is the
energy content of the animal at birth, Ea
is total assimilated energy, Esm is standard
or resting metabolism corresponding to
time-temperature profiles of a given sized
animal in the field, Eamr is that portion of
activity maintenance energy devoted to
reproduction, Eamo is that portion of activity maintenance energy devoted to behavior other than reproduction (total activity
energy is the sum of Eamr and Eamo), Eg is
the portion of production energy invested
in growth, Er is the portion of production
energy contained in gametes (eggs, follicles, sperm) and E, is the net energy in total
fat reserves.
The sum of Esm + Eamr + Eamo equals the
actual metabolic rate of an animal under
field conditions and is called Daily Field
Respiration (DFR)by Congdon^a/. (1982).
Esm can be determined from laboratory
studies that provide data on temperature
and mass specific metabolic rates. These
data are available in the form of allometric
equations of the type
M = aWb
(6)
977
where M is standard metabolic rate in ml
O 2 h~', W is body mass in g and a and b
are empirically determined constants.
Equations for reptiles are provided by Bennett and Dawson (1976), for amphibians
by Whitford and Hutchison (1967) and
Hutchison et al. (1968) and for fish by Brett
(1965), Gordon <?*aZ. (1972,pp. 53-57)and
Brett and Groves (1979).
DFR can be determined for some terrestrial animals by assessing the total CO2
production using isotopic measurements
(Nagy, 1975, 1980, 1982; Congdon et al,
1978, 1979). Unfortunately this technique
is not reliable for aquatic organisms such
as turtles, fish and many amphibians
(Congdon and Standora, unpublished data).
Nevertheless, assuming that a measure of
DFR can be obtained, daily activity energy
(DAE) can be calculated as
DAE = DFR - Esn
(7)
Daily activity energy can be partitioned into
Eamr and Eamo in at least three ways: First,
by computing time budgets for the amount
of time spent in reproductive related
behavior as compared to the amount of
time spent on other behaviors. Second, by
assuming that the portion of the production budget going to reproduction (eggs,
follicles, sperm) can be used to estimate the
portion of activity energy going to harvest
reproductive energy. Third, by measuring
directly the energy costs of different reproductive related activities as was done for
courtship activities of plethodontid salamanders by Bennett and Houck (1983).
Several authors have used this approach
to investigate the life history processes of
fish, amphibians and reptiles. Brett (1983)
summarized the extensive research on the
energetics of salmon. He computed energy
budgets for each life history stage of the
sockeye salmon (Oncorhynchus nerka) and
found that smolt have a high food conversion efficiency (20.6%), which is the same
as growth (G) in Table 1. This occurs
despite restrictive food-limiting conditions
during the period of lake residence when
the fry are growing into smolt. Apparently
fry save considerable energy by daily vertical migration during which they feed at
the surface at dawn and dusk and digest
978
J. R. SPOTILA AND E. A. STANDORA
T A B L E 1.
Food
energy budget for sockeye salmon fOncorhynchus nerka^yVom smolt to spawning adult.'
Stage
Mass(g)
Age (yr)
i (kj/%)
M (kj/%)
G'(kj/%)
E (kj/%)
Smolt (freshwater)
Immature (ocean)
Maturing (coastal)
Adult (spawning)
5
420
1,670
2,200
1.0
2.0
3.0
3.3
125.6/100
10,972/100
48,938/100
52,292/100'
62.4/49.5
4,718/43.0
21,684/44.3
39,014/74.6
25.9/20.6
2,964/27.0
12,575/25.7
8,050/20.4"
37.7/30.0
3,290/30.0
14,680/30.0
5,228/3.0
* I is ingestion, M is metabolism, G is growth and E is excretion. Data taken from Brett (1983).
b
The value for G in percent is also equal to the gross food conversion efficiency.
' Total body energy involved. Salmon cease feeding when they enter a river on their spawning run.
d
Percentage of body energy remaining.
food and process chemical energy at lower in the thermocline of Lake Michigan at
temperatures in deep water during the day night and go to the cooler hypolimnetic
(Fig. 4). During ocean life salmon grow water during the day (Brandt, 1978; Jansrapidly and have a growth efficiency of 26%. sen and Brandt, 1980; Stewart, 1980). In
As spawning adults, salmon do not feed the laboratory, rainbow trout (Salmo gairdand body energy content is reduced to less neri) and brown trout (Salmo trutta) grow
than half of what it was when adults left better at fluctuating temperatures than at
the ocean and began their upstream migra- constant temperatures (Hokanson et al.,
1977; Spigarelli et al., 1982).
tion.
Several other species exhibit daily
Fitzpatrick (1973a, b) determined food
behavior patterns similar to those of sock- energy budgets for the salamanders Deseye salmon smolt and receive similar bio- mognathus ochrophaeus and Eurycea bislienergetic benefits. Tilapia (Tilapia ren- neata. In the former species assimilation
dalli) move inshore to warm, preferred efficiencies ranged from 86.3 to 88.2% and
temperatures to feed on abundant vege- reproductive activities (vitellogenesis and
tation during the day and move offshore brooding maintenance) cost 48.3% of a
to cooler temperatures at night (Caulton, female's annual energy flow. Eurycea bisli1978). Alewives (Alosa pseudoharengus) feed neata had assimilation efficiencies which
ranged from 79.6 to 90%. Energy budgets
for Plethodon cinereus (Merchant, 1970;
Burton and Likens, 1975) indicate that the
apportionment of assimilated energy to
reproduction was 47.7% as compared to
76.0-81.3% for D. ochrophaeus (Fitzpatrick, 1973a) and 72.1-78.7% for E. bislineata (Fitzpatrick, 19736).
By far the greatest amount of research
has concentrated on reptiles, especially lizards. This research was reviewed by Nagy
(1983) and Congdon et al. (1982). It is
100 §
interesting to note that the energy budget
for Uta stansburiana with a 2 year life cycle
in Nevada (Nagy, 1983) is similar to that
1200
1600
2000
2100 0400
0800
for the first 2 years of life of Sceloporus
TIME OF DAY (h)
jarrovi from Arizona, S. graciosus in the
FIG. 4. Temperatures and metabolic rates of sock- sagebrush west of the Rocky Mountains, 5.
eye salmon (Oncorhynchus nerka) in Babine Lake, British Columbia. During midsummer small (2 g) salmon merriami in Texas, and Urosaurus ornatus in
migrate to shallow water to feed at dawn and dusk. Texas (Congdon et al., 1982). However,
Descent to deep cold water during the day results in the latter four live 3 years and thus have
a lowering of body temperature and a corresponding higher total energy budgets. In addition,
reduction in metabolic rate. Based on figures in Brett
(1971,1983), and Hutchison and Maness (1979). Met- the energy committed to reproduction in
the third year is equal to or greater than
abolic rate indicated by area enclosed by solid lines.
979
ECTOTHERM ENERGY BUDGETS
TABLE 2.
Total annual food energ budgets for four species ofiguanid lizards and one speciesof freshwater turtle.
Metabohzable energy (kj)
Maintenance
Species
Year
1
2
3
Sceloporus jarrovi
Total
Sceloporus graciosus
1
2
3
Total
Sceloporus merriami
1
2
3
Total
1
2
3
Urosaurus ornatus
Total
1
2
3
4
5
6
Chrysemys picta
7
8
9
10
11
12
13
14
Total
Production
Total
Total
Resting
Activity
337.6
395.7
465.2
1,198.5
72.7
171.2
214.6
458.5
150.0
171.2
174.7
495.9
157.4
192.7
211.9
562.0
96.2
206.3
452.6
628.6
818.3
,028.4
1,177.9
1,591.3
1,704.6
,823.3
1,879.5
,908.9
1,960.9
1,996.9
17,273.7
264.8
349.6
412.6
1,027.0
59.8
127.6
175.5
362.9
116.8
144.7
148.6
410.1
128.0
164.7
182.1
474.8
89.6
191.2
411.2
596.8
786.6
981.8
,150.9
,314.3
,434.1
,540.2
,607.2
,637.5
1,679.8
1,718.4
15,139.6
134.3
192.4
228.0
554.7
29.6
65.0
91.2
185.8
60.2
75.6
77.7
213.5
65.6
85.9
95.1
246.6
47.7
101.9
218.5
316.1
415.4
518.5
606.3
692.6
755.2
811.4
846.1
861.9
884.4
904.4
7,980.4
130.5
157.2
184.6
472.3
30.2
62.6
84.3
177.1
56.6
69.1
70.9
196.6
62.4
78.8
87.0
282.2
41.9
89.3
192.7
280.7
371.2
463.2
544.6
621.6
678.9
728.9
761.2
775.6
795.4
813.9
7,159.1
Growth
46.1
15.8
7.2
69.1
8.9
9.8
3.4
22.1
16.1
1.1
0.5
17.7
11.8
2.6
1.9
16.3
5.7
13.1
36.1
27.7
27.6
40.6
23.5
37.7
20.5
24.6
8.8
5.4
12.2
6.2
289.7
Eggs
Residual
storage
12.0
32.0
45.0
89.0
12.7
0.0
4.0
9.2
2.3
24.7
33.4
58.1
11.6
24.7
25.1
61.4
12.7
24.5
27.2
64.4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
233.6
247.0
254.8
262.2
265.3
267.1
271.4
1,801.4
3.7
1.5
5.6
0.8
0.5
5.0
0.9
0.7
0.9
1.9
5.4
4.1
4.1
6.0
3.5
5.6
3.0
3.6
1.3
0.8
1.8
0.9
Modified from Congdon et al. (1982).
that of the first 2 years in S. jarrovi and 5. 14% of total energy expended during each
graciosus and is 40 and 42% of the total in of the reproductive years. When reproS. merriami and U. ornatus. Among these ductive effort (RE) is computed as a profive species, maintenance accounts for 80- portion of energy available for reproduc86% of the total energy budget. These tion, C. picta, the longest-lived species
results are similar to the maintenance cost represented in Table 2, has the highest
computed for U. stansburiana by Tinkle and relative RE (0.89) as compared to 0.82 for
Hadley (1975) and the 75% maintenance 5. merriami, 0.79 for U. ornatus and 0.61
cost computed for Anolis limifrons by for S. graciosus. The lowest RE is 0.50 for
the viviparous S. jarrovi.
Andrews (1979).
In contrast to lizards, turtles are long
These data are not consistent with curlived and can have more varied life history rent life history theories such as the r and
patterns. Chrysemys picta (Table 2) expends K selection of Williams (1966a, b) and the
a total of 17,274 kj of energy over 14 years stochastic models of Schaffer (1974) and
of life of which 86% is allocated to main- Schaffer and Rosenzweig (1977). Stearns
tenance. Reproduction begins after 7 years (1977) and Congdon et al. (1982) conclude
and the energy allocated to eggs is about that the tests of the deterministic and sto-
980
THFRMAI FNFRGY
ABIOTIC
I FACTORS,
J. R. SPOTILA AND E. A. STANDORA
CHFMICAI
FNFRC-V
BIOTIC
FACTORS
FIG. 5. Schematic diagram showing the relationship
between the heat energy budget and food energy budget of a vertebrate ectotherm. Body temperature
affects behavior which in turn affects heat exchange
and, therefore, body temperature. Body temperature
also affects food intake, which affects metabolism, itself
dependent upon, and in turn affecting body temperature. Behavior affects food intake as well as maintenance and activity.
chastic models are not empirically sufficient. Congdon et al. (1982) compare the
values for RE of a number of animals ranging from reptiles to crustaceans and gastropods and report that few patterns
emerge among animal groups. Thus, we
do not yet have a general and reliable theory of the evolution of reproductive effort.
Food or chemical potential energy budgets and studies of resource allocation have
been able to classify life history patterns
and to explain field data for specific species.
However, they have not allowed us to make
accurate predictions or answer specific
questions about life history patterns of any
species. For example, why do only 50-70%
of the females within a C. picta population
in Michigan lay eggs each year? And why
do 40-60% deposit a single clutch while
10% deposit two clutches (Tinkle et al,
1981)? How can we account for this variability? Can we predict the reproductive
effort of a particular female in a population? If not, how can we understand the
selective forces that determine the reproductive effort of the population as a whole?
Available energy budget studies are too few
and too site specific to provide sufficient
data to test existing theories and/or provide a data base for new theories. Clearly
a change in approach is needed. Such a
change should take into account individual
variability within a population and should
involve an increase in the level of sophistication of the questions asked and data
acquired. While several useful avenues of
research could be pursued, one that shows
particular promise is the development of a
unified energy budget theory that combines the predictive power of heat energy
budget analysis with the detailed ecological
and demographic data characteristic of
food energy budget or resource allocation
models.
TOWARD A UNIFIED ENERGY
BUDGET THEORY
Heat energy budgets and food energy
budgets interact through their effects on
body temperature and metabolism (Fig. 5).
Heat exchange sets the body temperature
but is modified by thermoregulatory
behavior. Metabolism is temperature
dependent but also tends to raise body temperature and may alter behavior. For
example, the metabolic rates of alligators,
Alligator mississippiensis, caiman, Caiman
crocodilus, and turtles, Pseudemys scripta, are
elevated 200-300% when these animals are
digesting as compared to when they are
unfed (Coulson and Hernandez, 1983;
Gatten, 1980; Hammond and Spotila,
unpublished data). Body temperature also
affects rates of growth, lipid mobilization,
hormonal cycles and reproductive cycles.
These in turn alter behavior which can
affect heat exchange and thus body temperature. Changes in body temperature
again affect all of the processes and behaviors involved in chemical energy (mass balance) exchange.
Interactions diagrammed in Figure 5 can
be represented in the form of equations
(Fig. 6) following Porter and Jaeger (1982)
and Figure 3.2 in Porter and Tracy (1983).
There are three interacting sets of equations: one for the heat energy budget (diagonal), one for the food energy budget (horizontal, intersecting with metabolism term
in heat energy equation and including
equations for the effect of temperature on
physiological processes within the animal)
and one set with a vertical component coming from metabolism and a horizontal component for mass balance of water intersecting the evaporation term of the heat
981
ECTOTHERM ENERGY BUDGETS
Ectotherm
Dish
Behavioral
Thermoregulation
FIG. 6. Interaction of heat budget equations (diagonal) and food energy budget equations (horizontal)
to determine the body temperature and food processing capacity of vertebrate ectotherms. CF is mass
of food consumed, FF is food lost in feces, UF is food
energy lost as urine, E, is energy assimilated, M is
metabolism, E m is standard metabolic rate, £„„. is
activity energy devoted to reproduction, £„„„ is activity energy devoted to activity other than reproduction, Eg is energy invested in growth, E, is energy
contained in gametes, E, is energy stored as fat, Q,b,
is heat gained from solar and thermal radiation,
(T r + 273)4 is heat loss through thermal radiation,
hc(Tr — T J is convection, E is heat exchange by evaporation or condensation of water, G is conduction of
heat to or from the substrate, MFCOj is mass of CO2
produced by metabolism, MFNHj+ is ammonia produced by metabolism, MFHjO is water produced by
metabolism, M w , is water ingested in food, M w o is
water defecated, MWp, is water assimilated, MWili is water
in urine and MWj is water that is stored in tissues. T b
is body temperature, g is growth, r is reproduction
and s is storage. Based on Porter and Tracy (1983)
and Congdon et al. (1982).
FIG. 7. Three dimensional floppy dish and lid model
for the bioenergetics of a vertebrate ectotherm. This
is a visualization of the interactions of the equations
in Figure 6. Space a is the potential for growth or
reproduction for this animal. Modified from Porter
and Tracy (1983).
process over again. Eventually the simultaneous equations will have a unique set of
solutions that do not change, within some
margin of error (e.g., 0.01°C of Tb). For a
given set of environmental conditions, and
given rate of food consumption, the energy
partitioned into maintenance and production can be predicted.
Coupled equations such as these serve as
energy equation. These equations can be a unified energy and mass budget model
solved simultaneously by using an iterative and are useful in determining limits on the
procedure such that body temperature (Tb) energy available to an animal for growth
is calculated from the heat exchange equa- and reproduction. Porter and Tracy (1983)
tion and serves as an input into the several diagram such limits using a three dimenequations for the temperature dependent sional graph (Fig. 7). Two dimensions are
nature of M, Eg) Er, and E5. These equations accounted for by the heat exchange equaare represented graphically in Figure 6. tion and the vertical axis is a representation
Solution of these equations determines the of the animal's ability to process food. The
amount of maintenance energy required interacting equations result in a response
and the production that can occur. A surface which Porter, Jaeger and Tracy
change in M affects the production of met- termed a floppy dish. The surface of the
abolic water and through the mass balance dish can move from its present low position
equations, E in the heat exchange equa- up to a limit imposed by the physiological
tion. A change in M and E requires a new lid, which represents the maximum food
solution for the heat exchange equation processing capacity of the animal. The dish
with the new values of M and E as inputs. rotates as windspeed changes or body size
This may change T b and start the iteration varies, and the dish rises and falls with
982
J. R. SPOTILA AND E. A. STANDORA
Behoviorol
Thermoregulation
Optimal
Foraging
TEMPERATURE PC)
FOOD ft BODY MASS
Simple
Bioenergetic
FOOD
8
Summary
TEMPERATURE
FOOD 8
DAY"')
Optimization
TEMPERATURE
FIG. 8. The effects of thermoregulation and foraging on the distribution of fish in a patchy environment. Behavioral thermoregulation and optimal foraging result in two different patterns of fish
distribution. A simple summation of these figures does
not give a good prediction of the actual distribution
of fish as seen in the bottom figure. Modified from
Crowder and Magnuson (1983).
activity level, health and body temperature. The space between the maintenance
dish and physiological lid represents the
animal's ability to process energy for
growth or reproduction. Using this
approach we can set boundary conditions
within which the animal must operate.
These set distributional limits, affect competitive interactions and influence time and
space utilization (Roughgarden etai, 1981;
Christian and Tracy, 1981, 1982; Christian et al., 1983; Porter and Tracy, 1983).
Within these limits animals are forced to
make choices about whether to spend time
thermoregulating, feeding, reproducing,
etc. Thus, variations in the environment
and different "choices" made by individual
animals are reflected in differences in
resource utilization and ultimately, in differential life history patterns.
To help understand how animals make
these "choices," on either an evolutionary
or individually learned basis, we can turn
to optimality theory (Krebs and Davies,
1978). This theory assumes that the overall
fitness of an animal increases as a function
of net rate of energy intake. Huey (1974)
and Huey and Slatkin (1976) use this
approach in their cost benefit analysis of
lizard thermoregulation. It also has a central role in the development of foraging
theory (Charnov, 1976; Oaten, 1977; Pyke
etal, 1977; Pyke, 1978a, b, 1979).
One of the best examples of this approach
was the use of a bioenergetics model to
predict fish foraging behavior in a heterothermal environment (Crowder and Magnuson, 1983). Kitchell et al. (1977a, b)
developed a bioenergetics model for simulations of fish growth. This model was
tested for several species of fish by Kitchell
etal. (19776, 1978), Megrey (1978), Weininger (1978), Breck and Kitchell (1979),
Kitchell (1979) and Kitchell and Breck
(1980). Crowder and Magnuson (1983)
used this model to predict the growth
response surface of a bluegill (Lepomis macrochirus) and from that the optimum habitat distribution of fishes foraging in an
environment varying in both food and
temperature (Fig. 8). The bioenergetic
model predicted a different distribution of
fish than that predicted from the responses
to food or temperature alone. They then
compared available field data for several
species of fish and concluded that these
data also supported the bioenergetic model.
Thus, fish do appear to optimize their use
of habitat resources in a manner similar to
that predicted by the bioenergetics model.
They do appear to make "choices" among
the different portions of the space between
their maintenance dish and physiological
lid.
CONCLUSIONS AND QUESTIONS
Unified energy budget models combine
heat energy budget and food (chemical
potential) energy budgets into a holistic set
of equations that can be solved in an iterative fashion to predict the body temperature and resource utilization of an animal. Successful attempts have been made
to apply this approach to reptiles as
in the case of the floppy dishlid model
of Porter and Tracy (1983) and for fish
in the bioenergetic-optimality model of
Crowder and Magnuson (1983). These
models should be useful in testing theories of the evolution of life history patterns and of different strategies of resource
allocation and reproductive effort. However, several kinds of data are needed to
test unequivocally these models. First,
complete energy budgets are needed for
many more vertebrate ectotherms, includ-
ECTOTHERM ENERGY BUDGETS
ing frogs, crocodilians, turtles, snakes, noniguanid lizards and fish. Next, the problem
of variability needs to be addressed to
determine if variation among individuals
of a given population represents their
response to different environmental factors such that each is tending towards a
different evolutionarily stable strategy
(MacArthur and Pianka, 1966) or whether
it represents a case of intense natural selection ongoing in the population. Finally,
detailed behavior and time-temperature
budgets should be completed for individuals of different species such that individual energy budgets can be completed. This
will help account for the problem of variability, and thereby, help test the energy
budget and optimal foraging models. These
types of data should now be attainable using
miniature radio transmitters, micrometeorological instruments, remote sensing
devices, and field portable microcomputers for data acquisition. However, even
with the application of new technology,
there will remain an important need for
the formulation of testable hypotheses and
the compiling of observational and demographic data that in the recent past was
considered passe because it was natural history.
983
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