reproductive value and plotting them to produce a fitness contour (e.g. Sibly &
Atkinson, 1994 ). Trade-off curves can then be superimposed on fitness contours
to identify the trait values that yield highest fitness.
Relationship of traits to fitness While the link between some phenotypic traits
and fitness may be weak, many life-history traits are either components of
fitness (age-specific survival and fecundity) or are strong correlates of fitness
(e.g. growth rate, offspring size; Lessells, 1991 ). Blanckenhorn ( 2000 ) and Brown &
Sibly (2006) summarized the typical fitness advantages of large size as increased
fecundity, success in size-dependent competition for resources (including
mates), escape from size-limited predators, greater diet breadth, and greater
physiological homeostasis and hence tolerance of environmental fluctuations.
Trade-offs A trade-off occurs when a genetically determined change in one trait
that contributes to fitness has an inverse effect on the fitness contribution of
other traits. An example of a trade-off in organisms with the same growth rate is
when juvenile development is accelerated leading to earlier maturity, but this
will be at a smaller size, which typically reduces the number of offspring a
mother produces (Caswell, 1989 ), and may even reduce mating success and
adult survival (Blanckenhorn, 2000 ).
Possible costs of large adult size, summarized by Blanckenhorn ( 2000 ) and
Brown & Sibly (2006), include: (i) increasing risks of dying before breeding
because large size is achieved by extending the juvenile period (hence the period
of mortality risk) or increasing growth rate (which may incur costs); (ii)
increased risk of being killed by predators, parasitism or environmental stres-
sors or reduced reproductive success because of reduced agility, increased
detectability, higher energy requirements or heat stress; (iii) decreased lifetime
reproductive success due to late reproduction; (iv) decreased rate of mass-
specific production, including reproduction.
In optimality modelling, optimization is performed within a limited range of
possible life histories that is determined by constraints such as geometry and
physical and chemical laws. An example is the scaling of metabolic rate to body
size raised to the power 3/4, which West, Brown & Enquist ( 1997 ) proposed was
due to physical and geometrical constraints on the supply of resources to
metabolizing cells as body size is increased (see alsoBrown, Allen & Gillooly,
this volume). Variation not explained by this scaling relationship may then be
amenable to other forms of explanation, such as variation in selection pres-
sures, hence life-history analysis. Just how firmly the 3/4 power law constrains
biological rates, will be discussed later in this chapter.
Adaptive dynamics
More recent modelling approaches that take account of realistic population
dynamics, usually referred to as adaptive dynamics (Waxman & Gavrilets,
LIFE HISTORIES AND BODY SIZE 35