Environmental Engineering Reference
In-Depth Information
loss but also the flux of CO
2
in the expired air (DeLany
1997). The technique's relative simplicity, high accuracy,
and advances in its use (including implantable data log-
gers and externally mounted transmitters) have made it
the method of choice for reliable FMR determinations
(Butler et al. 2004).
Nagy's (2005) scaling of FMR was based on a set of
229 free-living mammals, birds, and reptiles whose me-
tabolism was measured by the DLW method. Daily en-
ergy expenditures ranged nearly 6 OM, from 0.23 kJ for
a gecko to 52.5 MJ for a seal, and the exponent for the
entire set was 0.808, with extremes ranging from 0.59
for marsupials to 0.92 for lizards. Nagy's (2005) conclu-
sions were that allometric slopes for FMR are not well
represented by the 3
=
4 power law, and FMR slopes are
not identical to BMR slopes (fig. 4.2). The analysis also
confirmed the expected importance of thermoregulation:
more than 70% of the variation was due to variation in
body mass, but most of the rest was explained by differ-
ences in specific metabolic rates (W/g), with FMRs of
mammals and birds being, respectively, 12 and 20 times
those of equally massive reptiles.
FMRs of wild terrestrial vertebrates also reveal interest-
ing differences in the specific metabolism below the class
level (Nagy, Girard, and Brown 1999; Nagy 2005).
FMRs of marsupials are about 30% lower than those of
the eutherian mammals, and the rate for the primitive
monotreme echidna is only about 20%-30% of an equally
massive hare. In contrast, FMRs of Procellariiformes
(storm-petrels, albatrosses, and shearwaters) are nearly
1.8 times as high as those of desert birds and about 4.3
times higher than those of desert mammals. The low
FMRs of desert vertebrates reflect their adaptation to pe-
riodic food shortages and to recurrent or chronic scarcity
of water. Some notable outliers, such as sloths, can be
explained by environmental adaptations, but there are
also many unexplained specific departures
from the
norm.
There may be no convincing evidence for any single
universal exponent relating metabolic rates to body mass,
but there is no doubt about the allometric nature of the
relation, and its obvious corollary (whatever the actual
scaling exponent may be) is the exponential decline of
specific BMRs (total BMR divided by body mass). With
BMR scaling as M
0
:
75
, the decline scales as M
0
:
25
;
with BMR scaling as M
0
:
66
, the decline scales as M
0
:
33
.
For the latter case this would mean that a 10-g kangaroo
mouse metabolizes 16 mW/g, a 10-kg coyote uses just
1.6 mW/g, and a 1,000-fold jump in body mass reduces
the specific metabolism by 90% (fig. 4.2). This scaling
has another important implication: its exponents have a
very similar range but the opposite sign when compared
with the relation between lifespan and M (exponents
0.15-0.30). Consequently, the product of these expo-
nents, the mass-specific expenditure of energy per life-
span, with mean values of about
0.07,
is essentially
independent of M.
This means that during its lifetime 1 g of animal tissue
would process the same amount of energy regardless of
whether it is in a shrew's or an elephant's tail. Speakman
(2005) argues that this long-standing interpretation is in-
correct because BMR or RMR are poor measures of total
energy metabolism. His comparison, using daily energy
expenditure (DEE), showed that lifetime energy expen-
diture in mammals is not independent of M and that
smaller animals process more energy per unit mass than
larger creatures. Bird data showed only an insignificantly
negative trend, but independent of M, over its lifetime
1 g of bird tissue expends roughly 3.5 times more energy
than 1 g of mammalian tissue; moreover, there is enor-
