Opportunities and challenges
Overall, our literature review indicates a strong interest in the
consequences of population outcrossing across ecology and evolutionary
biology. Yet, explicit and robust empirical estimates of heterosis in
the context of natural dispersal within metapopulations are apparently
remarkably lacking. The few broadly relevant studies are still mainly
inspired by traditional research agendas of agriculture, conservation
genetics and speciation fields. Consequently, they tend to focus on
highly inbred and/or highly differentiated populations, or do not
attempt to characterize the connectivity level across populations
studied. Crosses between isolated populations provide valuable
information on the genetic architecture of population differentiation
and on possible ecological and evolutionary consequences within contexts
such as genetic rescue or biological invasion. However, natural
dispersal and interbreeding between these populations are unlikely,
unless these populations come under secondary contact.
Although many study systems have been used to quantify demographic
consequences of dispersal in natural populations (e.g. see Millon et al.
2019), most such study systems were notable for their absence from the
list of retained studies that fulfilled our current criteria (Table 1).
This may be because quantifying multi-generational fitness in wild
populations is certainly challenging. For instance, 18 years of
fieldwork still resulted in a small sample size for natural immigrants
in song sparrows (Marr et al. 2002), constraining the strength of
evidence for heterosis. However, the increasing number and length of
available individual-based field studies should soon make such analyses
feasible in at least some systems (e.g. reviewed in Clutton-Brock &
Sheldon 2010). Our search found several studies contrasting fitness of
immigrants and residents but that did not investigate the fitness of
descendant generations, even if some fitness metrics include aspects of
offspring fitness (e.g. number of fledglings in birds). The existence of
such studies implies that failure to explicitly quantify and compare
target individuals is not entirely due lack of data, but at least partly
reflect that such ambitions are not currently on the radars of many
population and evolutionary ecologists.
Logistical considerations are certainly prohibitive for some taxa. For
example, invertebrates and other small sized taxonomic phyla are
traditionally studied under artificial conditions, often using
laboratory stock populations, due to the difficulties marking and
identifying individuals in their natural environments. As a consequence,
future estimates of heterosis in natural populations cannot rely on
strategies such as long-term individuals-based studies, which typically
involve vertebrates (but see “new methods” below). For other taxa,
however, traditional approaches may simply require reconsideration. Ease
of manipulation may present such a cost-effective approach in comparison
to field-based parentage analyses in plants, that experimental crosses
are often the method of choice. Alternatively, these choices may
represent a historical oversight that is only now being corrected (see
e.g. Ellstrand 2014).
The preponderance of experimental crossing approaches, however, may be
another symptom of the disconnect between research silos. Indeed, we
found that studies often presented methodological priorities that
greatly limit inferences about demographic and evolutionary outcomes of
outbreeding within the context of dispersal and resulting immigration in
natural populations. For example, lack of knowledge regarding the origin
of parental individuals may result in categories of parental and filial
generations that include a mixed set of ancestries. Consequently, both
means and variances within the categories compared are affected,
rendering results difficult to interpret. Additionally, by not
investigating the natural occurrence of interbreeding between
populations, we lack information on the frequency with which different
types of individuals are produced within a population. It then becomes
difficult to predict the ultimate eco-evolutionary consequences of
genetic effects manifested through outcrosses. For instance, even if
F2 descendants of immigrants have very low fitness, any
impact would be trivial if F2s are rarely conceived in
the first place. F2s could be rare, even in the case of
high fitness of F1s, if F1s rarely mate
due to non-random mating within and among immigrant lineages, or if
F1s are themselves rare and/or temporally segregated.
Note, however, that even our proposed research agenda may lead to
variable recommendations regarding experimental approaches. In
principle, the ability to manipulate breeding presents several
advantages, such as a larger sample size across categories. In addition,
artificial or semi-artificial experimental setting provide easier means
to rear offspring under several environmental conditions and, for some
taxa, the ability to rear different generations under the same
environmental conditions. As maternal effects might be significant,
experimental crossing also gives the opportunity for the systematic
incorporation of such effects in the experimental design. Moreover,
combining crosses between residents and immigrants from different
sources into a global effect of outcrossing may be preferable in certain
contexts. Logistically, it may be impossible to categorize immigrants
into their exact population of origin and, even when possible, low
source-specific immigration rates likely would prevent disentangling the
heterotic effects across pairwise population combinations or filial
generations. More importantly, when attempting to understand the
eco-evolutionary consequences of immigration within the perspective of a
focus population, the average effect of different population crosses may
better represent the relevant outcome to the eco-evolutionary dynamics
of that population. Therefore, methods and statistical considerations
will depend on several logistic opportunities and limitations of the
individual taxa/populations under study. In any case, methods applied
must involve proper characterization and reporting of statistical
expectations and errors.