RECOMMENDATIONS FOR AN HYPOTHESIS-DRIVEN, EMPIRICALLY SUFFICIENT ERA
Recent increases in available life history trait data unlock our ability to further understand the prevailing patterns of global variation in life history strategies, their evolutionary and ecological drivers and constraints, and their consequences for the extinction risk, invasiveness, and ecosystem functioning. We expand on Stearns’ [2] original conditions to identify a number of contemporary challenges concerning life history data and analyses, as we strive to attain the “empirical sufficiency” required to test modern theories of life history evolution.
Moving towards universal life history traits, derived from demographic schedules of survival, reproduction and development.Such data can be implicitly measured in a single currency of rates per standard unit of time [51]. This unit harmonisation will strengthen the links between life history, demography, and fitness [1], given their explicit treatment of time in the canonical Euler-Lotka equation. Such rates still need credible transformation during statistical analysis [52]. We further encourage the development of theories and methods to drive our understanding of life history evolution using state variables that are not measured using time but linked to other currencies, with energy being a primary candidate.
Filling gaps in life history trait data across the Tree of Life, especially for microbes, fungi, and invertebrates . There are challenges inherent to this recommendation, since for many organisms we lack a good working definition of life cycles and life histories, let alone what constitutes an individual, death, or reproduction. Variation in lifestyle (e.g., sedentary vs. mobile, diet, habitat), bauplan (e.g. , modular vs. unitary, degree of mobility, brain development), growth pattern (e.g., determinate vs.indeterminate growth) and reproductive modes (e.g., sexualvs. asexual) further complicate the comparative landscape. Attempt to fill data gaps should prioritise measures that will facilitate broad comparisons of life history across taxa. As information gaps across species fill in, it is worthwhile to consider the need for data on vital rate variation within species [53]. Moreover, time series vital rate data exist for a relatively small number of species, and so comprehensive assessments of density-dependent mechanisms driving vital rate variation remain rare.
Embracing life history traits comparative across broad taxa and levels of biological organisation . Besides some exceptions [54,55], multivariate studies seeking to understand axes of life history variation across kingdoms of life emerged only recently [29,56,57]. Previous studies that have encompassed a broad taxonomic range were limited to bivariate analyses [55]. Naturally, continuing taxon-specific lines of enquiry will play an important role, especially in taxa with rich data quality. However, limiting analysis only to separate groups of organisms implies a perceived wisdom that gross differences in the morphology, physiology, and lifestyle of different groups will inevitably create different selection pressures on their life history strategies. This presumption should be backed up with empirical analyses of whether and how the dominant axes of life history variation change among taxa. Existing evidence is they do not [29].
Achieving consensus regarding evolutionary ancestry across all species to implement robust phylogenetic analyses. Recent advances in phylogenetics have yielded trees describing the relationships among species across ever larger taxonomic groups [58–60]. Despite these advances, the details of ancestral relationships in many parts of these trees, and particularly in deeper evolutionary time, remain debated and with multiple gaps to fill. We require better consensus on the best way to deal with phylogenetic covariance. The classic assumption of Brownian trait evolution is often not supported, with increasing recognition for the need to incorporate evolution towards trait optima and to identify and account for shifts in trait optima across taxa [61]. There is a strong potential to find patterning in life history strategies common across all species, but we should be ready to be surprised by deep-rooted differences in how natural selection has shaped strategies in particular clades.
Adopting analytical approaches that infer explicit links between life history traits and emergent axes of life history variation. We see a role for the wider use of Factor Analysis [47] to help discover life history axes as latent factors of observed vital rates. Further development of FA algorithms will be key to help test hypotheses derived from life history theory, and particularly phylogenetically-controlled confirmatory FA methods. We also urge for the development and application of Canonical Correlation Analysis to reveal associations between the multivariate life history traits of species and their multivariate suites of demographic, phenotypic, and ecological features.