LB 10-128 - Bringing light into the Raunkiæran shortfall: a comprehensive review of traits used in functional animal ecology

Background/Question/Methods:

Trait-based approaches elucidate the mechanisms underlying biodiversity response to, or effects on, the environment. Unlike plant systems, applying this approach to animals is challenging due to the lack of knowledge about species traits and their functionality (the Raunkiæran shortfall). We conducted a systematic review to investigate the trends and gaps in trait-based animal ecology in terms of taxonomic extension and resolution, trait selection, ecosystem type, and geographical region. Furthermore, we aimed to develop a standardized protocol for guiding trait selection to explore within and cross-taxon comparisons.

Results/Conclusions:

We found 1,655 articles using virtually all animal groups (Cnidaria, Ecdysozoa, Prostotomia, Spiralia, and Chordata), from 1999 to 2020. Most studies used traits representing trophic and habitat dimensions to the detriment of life history, defence, and metabolic dimensions. Additionally, most studies rely on response traits (79.4%) while ignoring intraspecific variation (94.6%). Almost 36% of the datasets did not provide the rationale behind the selection of morphological traits. We also highlighted gaps in the knowledge across taxonomic groups, ecosystem types, and zoogeographical realms. Studies were concentrated in vertebrates, terrestrial habitats, and the Palearctic realm. Almost one-fifth of the studies based only on response traits conclude that trait diversity impacts ecosystem processes or services without justifying the connection between them or measuring them. We propose a protocol for standardizing trait collation that includes the following stages: identifying the type of trait and the underlying mechanism linking trait-environment, trait-ecosystem, or environment-trait-ecosystem correlation, using the periodic table of niches to select the appropriate niche dimension to support a mechanistic trait selection, and choosing the relevant traits on each retained niche dimension. We argue that resolving these gaps will allow trait-based animal ecology to be more predictive.