Introduction
Complex life cycles, whereby organisms pass through distinct
life-history stages before reaching the adult stage, are ubiquitous
across the tree of life. Life-history stages can be quite different from
each other in terms of morphology, trophic mode and even habitat—but
they are also linked, both ecologically and evolutionarily. Ecological
studies of complex life histories first focused on numerical links
across the life cycle—the number of individuals entering and exiting
each phase determines the dynamics of the adult population . More
recently, the role of phenotypic links between life-history stages,
termed “carry-over” or “latent” effects have also been recognised as
ecologically important . Links among life-history stages have
evolutionary significance as well—the popular “adaptive decoupling
hypothesis”, argues that metamorphosis reduces the strength of genetic
links across the life history, such that different stages can evolve
independently to their particular optima . Accordingly, an increasing
number of studies explore the phenotypic and genetic links among
life-history stages, both at the macro- and microevolutionary scales .
As the number of studies grow, it becomes possible to identify the
aspects of complex life histories that have been relatively well
studied, and we can also locate any important knowledge gaps that
remain.
It is unclear whether all life-history stages have been studied equally
or if biases with regards to particular stages exist. For example, a
cursory reading of literature implies that links between the larval and
juvenile stages are of particular interest in studies of marine
invertebrates , insects , frogs But other stages can regulate
populations—for example, the egg stage may determine adult densities .
Identifying emphases in the literature, and the extent to which some
stages/links are less examined, would allow future studies to address
these gaps, and provide a more complete understanding of complex life
histories, such that no one stage remains a ‘black box’.
Different experimental designs for studying life histories provide
access to different inferences—how we study the life cycle determines
whether we can make inferences about links between stages. Broadly,
there are three experimental design approaches to studying life
histories: (1) single stage, (2) cohort longitudinal—following one
cohort through multiple stages, and (3) individual
longitudinal—following specific individuals through multiple stages.
Single stage studies are useful for characterising a particular stage of
the life history, but they can tell us little about phenotypic links,
because they preclude the estimation of covariances between
stages—using different cohorts for each stage means that
within-species covariances (be they genetic or phenotypic) cannot be
estimated. Single stage studies are also useful for estimating
covariances among species but increasingly, the focus is on
within-species links of the life history. To make inferences about these
links, estimating the (co)variances in traits following single cohorts
(cohort longitudinal), or individuals (individual longitudinal) through
the life cycle is essential. Even then, the two longitudinal approaches
have different strengths and weaknesses. Cohort longitudinal approaches
are susceptible to Simpson’s Paradox whereby trait relationships
observed across cohorts may not reflect the trait relationships for
individuals; the trend at the individual-level could even be opposite of
that at the cohort-level (Figure 1; note that among-species comparisons
are also vulnerable to Simpson’s Paradox). As such, if one wishes to
make inferences about phenotypic links among life-history stages,
then individual longitudinal studies are most appropriate, as they
estimate trait (co)variances at the appropriate scale and avoid the
potential for Simpson’s Paradox. On the other hand, individual
longitudinal studies are potentially laborious—rearing individuals can
be much harder than rearing cohorts. If one is interested in quantifyinggenetic links among life-history stages, and a quantitative
genetics breeding design is used, the scale of replication is cohort
from a single sire, and therefore cohort longitudinal approaches are
appropriate (e.g. .
The nature, strength and variability of links between life-history
stages vary systematically between laboratory-based study and those done
in the field . Controlled laboratory conditions make experimental
manipulations easier and are sometimes the only way to examine certain
life-history stages . Nevertheless, field experiments provide
information that cannot be gained from laboratory experiments alone .
Identifying the relative abundance of field and laboratory studies
should allow us to identify where and when field studies should be
priority.
Here, we use a systematic map of marine invertebrates to describe the
state of our knowledge and outline the field’s strengths and knowledge
gaps. Systematic maps use a repeatable methodological framework to
quantify what has been studied. Unlike systematic reviews and
meta-analyses, systematic maps do not statistically analyse combined
data from empirical studies . Instead, a systematic map collates,
catalogues and describes studies, outlining the current state of
knowledge for a particular topic . Marine invertebrates are an ideal
model system because of their numerous phyla, diverse life-history modes
and long history of study from the perspective of complex life cycles .
We collected methodological data for studies of life histories across
the following six stages: (1) F0 adult; (2) embryo; (3)
larva; (4) metamorphosis; (5) juvenile; and (6) F1 adult
(Figure 2a) and recorded the experimental design used for each study.