LIFE HISTORY THEORY AND THE FAST-SLOW CONTINUUM
The life history of an organism determines its fitness, as life history
dictates the numerical representation of future generations [1].
Life history is therefore the filter via which selection on phenotypic
traits operates, and via which environmental variation generates
population, community, and ecosystem dynamics. This idea is underpinned
by the canonical Euler-Lotka identity \(1=\int_{x=1}^{\omega}{\lambda^{-x}l_{x}m_{x}\text{dx}}\), with
fundamental components describing the schedules of survival (\(l_{x}\))
and reproduction (\(m_{x}\)) to the maximum age x =ω[1]. This identity characterises how survival and reproduction over
the life course (x = age) determines population growth
(\(\lambda\)). However, this equation tells us nothing about potential
covariation between survival and reproduction, between early-life and
late-life reproduction, or whether age is the best predictor of fitness;
indeed, it has been recently argued that size is a better predictor in
many species [20]. A comprehensive theory of life history strategies
must at the very least describe measurable directions and strengths of
these potential trade-offs, but in reality, life history is much more
complicated (Box 2).
Schedules of survival and reproduction can be measured in many ways.
Examples include life expectancy , longevity, age at first
reproduction, lifetime reproductive output , measures ofactuarial and reproductive senescence , andgeneration time . Although some of these demographic metrics
often do a good job as proxies for life history continua [21], no
single one of these life history traits adequately captures
every characteristic of the demographic schedules \(l_{x}\) and\(m_{x}\). Therefore, comparative studies often use several life history
traits and apply methods of dimension reduction to yield emergent,
composite measures. The nonlinearity of these schedules, together with
the influence of density dependence and stochasticity [22],
complicate measurement of their covariance. These complications remain
even if the conceptual framework describing life history structures and
competing processes of energy allocation is relatively well known (Box
2).
The fast-slow continuum [2] remains the standard framework for
understanding life history diversity across the Tree of Life and is
characterised using various life history traits mentioned above. ‘Fast’
creatures tend to have quick development and early-life allocation of
resources to profuse reproduction over survival. ‘Slow’ creatures have
protracted development, delayed maturation, and allocate resources to
survival over reproduction. The fast-slow continuum continues to emerge
as an important explanator of eco-evolutionary dynamics across taxa, and
more recently in the fields of trophic [23] and disease ecology
[24] too.
As well as being a canonic ordination of life history variation, the
fast-slow continuum predicts species’ response to global change.
Compared to fast-lived species, slow-lived species show higher
sensitivity of population growth to sea temperatures in fishes [25],
higher extinction rates in mammals and birds [26], and more negative
responses of mammals to human disturbances [27]. These
characteristics render long-living species less resilient than
fast-living species to environmental insults, making the populations of
the former more likely to decline (the so-called “malediction of
long-lived species” [28]). However, fast species are more sensitive
to increases in temporal autocorrelation of the environment [29].
Such patterns have wider implications for future ecosystem function
[26] and conservation success [30].