Bringing light onto the Raunkiæran shortfall: A comprehensive review of traits used in functional animal ecology

Abstract

Trait‐based approaches elucidate the mechanisms underlying biodiversity response to, or effects on, the environment. Nevertheless, the Raunkiæran shortfall—the dearth of knowledge on species traits and their functionality—presents a challenge in the application of these approaches. We conducted a systematic review to investigate the trends and gaps in trait‐based animal ecology in terms of taxonomic resolution, trait selection, ecosystem type, and geographical region. In addition, we suggest a set of crucial steps to guide trait selection and aid future research to conduct within and cross‐taxon comparisons. We identified 1655 articles using virtually all animal groups published from 1999 to 2020. Studies were concentrated in vertebrates, terrestrial habitats, the Palearctic realm, and mostly investigated trophic and habitat dimensions. Additionally, they focused on response traits (79.4%) and largely ignored intraspecific variation (94.6%). Almost 36% of the data sets did not provide the rationale behind the selection of morphological traits. The main limitations of trait‐based animal ecology were the use of trait averages and a rare inclusion of intraspecific variability. Nearly 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 guide for standardizing trait collection that includes the following: (i) determining the type of trait and the mechanism linking the trait to the environment, ecosystem, or the correlation between the environment, trait, and ecosystem, (ii) using a “periodic table of niches” to select the appropriate niche dimension to support a mechanistic trait selection, and (iii) selecting the relevant traits for each retained niche dimension. By addressing these gaps, trait‐based animal ecology can become more predictive. This implies that future research will likely focus on collaborating to understand how environmental changes impact animals and their capacity to provide ecosystem services and goods.

ZooTraits: An R shiny app for exploring animal trait data for ecological and evolutionary research

“…We provide guidance (Figure 4) for integrating prior recommendations (Gonçalves-Souza et al, 2023;Keller et al, 2023) with the ZooTraits app to improve trait selection and data sharing for the future of global trait databases. One important clarification about the app is that it does not track changes in nomenclature, so we suggest users use tools and websites available to verify taxonomic names before using our app.…”

“…Furthermore, by encouraging users to contribute trait information, ZooTraits seeks to bridge knowledge gaps and foster a global community of scientists to advance trait-based ecology. As we move forward, the continued integration of this app with established frameworks (Damour et al, 2018;Gallagher et al, 2021;Gonçalves-Souza et al, 2023;Keller et al, 2023;Palacio et al, 2022;Rosado et al, 2013Rosado et al, , 2016Weiss & Ray, 2019) will contribute to a more predictive trait-based animal ecology.…”

“…This app serves as a tool to summarize information on traits across several animal taxonomic groups, ecosystems, and geographic regions to integrate multiple datasets centralized in the Open Trait Network to facilitate both the use of trait and contribution of trait data. The ZooTraits app provides: (i) access to species-level trait data accessible for over 23,000 species from 20 datasets included in the Open Trait Network, and raw data for ~2000 species from the AnimalTraits (Herberstein et al, 2022), (ii) a possibility to continuously update the dataset with newly published research that will stimulate the development of a global list of traits used in several taxonomic groups, (iii) a global overview of traits used in animal ecology based on a dataset compiled by Gonçalves-Souza et al (2023).…”

“…We hope this tool not only fosters comparisons within and across taxonomic groups that help to identify general patterns of trait variation but also contributes to increased transparency and widening the accessibility to trait information. Importantly, as this app only streamlines the process of acquiring trait information, trait selection must be linked to best practices recommended by previous studies (e.g., Gonçalves-Souza et al, 2023;Keller et al, 2023;Palacio et al, 2022), which suggest that trait selection should be mainly driven by biological hypotheses rather than solely relying on the data that are available. The ZooTraits app integrates different functionalities to explore, visualize, and download animal trait information.…”

“…However, when it comes to trait-based ecology, a key challenge lies in the knowledge shortfalls that hinder our ability to select appropriate traits or access information for certain taxonomic groups or geographical regions(Gonçalves-Souza et al, 2023;Maitner et al, 2023). Furthermore, previous authors argued that it is critical to investigate multiple trait dimensions since studies on animals and plants have mostly concentrated on a restricted number of dimensions(Gonçalves-Souza et al, 2023;Maitner et al, 2023). The ZooTraits could serve as an entry point for identifying these gaps, thereby stimulating new avenues for enhancing trait data collection.Nonetheless, the support of open-source apps and centralized hubs, such as the Open Trait Network, has the potential to transform traitbased ecology.…”