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).