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].