Accounting for intraspecific trait variation in predicted
responses to global change
In our review, only 38 papers specifically reference investigating the
intraspecific trait variation in their system, while interspecific
variation dominated in most of the papers either explicitly or
implicitly. In practice, the acquisition of high-resolution trait
information measured for individuals within populations is labour
intensive and often specific to a temporal, spatial, and ecological
context (e.g., lipid content or energy density of prey species).
Aggregate values of this information, when available, can be taken at a
species level and used to model broader patterns in the responses to
environmental or ecological variables of population-to-species. The
majority of large-scale trait-based modelling occurs at the population
to species resolution (e.g. Spencer et al. 2019). But species do vary in
the magnitude of intra- versus inter-specific variation in their traits
(i.e. many species vary greatly in traits across ontogeny). Individuals
within a population may possess traits that confer advantages for
dispersal to or persistence within changing ecosystems (Muñoz et al.
2016, Archambault et al. 2018). Coarse resolution trait-based modelling
may therefore overlook nuanced ecological processes when intraspecific
variation is ignored; therein lies a trade-off between trait-to-system
relevance and high data collection effort, compared to reduced
information availability and low trait-to-system specificity. The choice
ultimately comes down to the need for understanding system-specific
processes versus trait-based synthetic products that can provide answers
to practitioners and managers now but that may contain intra-specific
inaccuracies. Issues with aggregating information at a
population-to-species level need to be explicitly acknowledged, where
for example traits are known to vary within species and at the scale of
the environmental gradients examined. Best practice in trait-based
analyses of ecological variance should strive for the selection of
appropriate trait resolution (i.e. binary, categorical, continuous) and
the scale of trait measurements (i.e., spatial/temporal scales as well
as scales of intraspecific variation). Our review highlights the need
for international efforts to aggregate and make accessible trait
information (ranging from individual to species-level metrics) via
platforms for knowledge sharing and reporting. Prominent examples
include FishBase (for fish, Froese and Pauly 2019), SeaLifeBase (for
marine invertebrates, Palomares & Pauly 2019), TRY (for plants, Kattge
et al. 2011). But many studies report undertaking significant additional
curation of the information acquired from these databases. Manual
curation, handling, cleaning, and archiving of trait-based data is
labour intensive and costly, ideally requiring consultation with
taxonomic experts, and represents a significant barrier to elaborating
trait-based approaches. Online repositories that facilitate collation of
regional, ecosystem-specific, or taxon-specific trait data collections
could help to address some of these barriers, however such efforts
sustained baseline funding to maintain data archives, address user
issues, and continually evolve the repository and products to address
emerging needs (see Gallagher et al. 2020).