Patterns and drivers of knowledge gaps in global databases of mammal traits

Aim

Knowledge gaps in biodiversity, particularly in species traits, can hinder an accurate understanding of species roles in ecosystems, limiting our comprehension of ecosystem functions, maintenance and stability. In this study, we quantified data completeness in terrestrial mammals trait databases to identify knowledge gaps and data biases, and assess their potential drivers.

Location

Global.

Methods

We gathered trait information from seven widely used global databases and quantified the data availability for each terrestrial mammal species (n = 5706). We used this data to evaluate whether and how 11 different biological, geographical and socioeconomic factors (e.g., year of description, threat status and range area or research capacity of the countries in which the species is distributed) influence the variability in trait information available for each species by employing generalised linear mixed models (GLMM).

Results

Our results show that trait data completeness is uneven across species. While traits like habitat type, diet and body mass are well-documented for over 97% of species, more complex traits such as hibernation torpor or reproductive characteristics are available for less than 17% of species. GLMM results indicate that threat status, year of species description, research effort, range size, and accessibility significantly influence trait data availability. Specifically, species categorised as data deficient, described by science more recently, narrowly distributed, far from large cities, and with fewer published papers tend to have the least information available about their traits.

Main Conclusions

It is necessary to increase trait data collection efforts and improve database integration, prioritising underrepresented traits and species. Bridging the gaps in global databases is crucial for developing a deeper understanding of species' functional roles when analysed at broad spatial scales, and for supporting more effective biodiversity conservation policies.