Data from: Relative brain size is associated with natal dispersal rate and species’ vulnerability to climate change in seabirds
Constanti Crosby, Laurel; Sayol, Ferran; Horswill, Catharine (2023), Data from: Relative brain size is associated with natal dispersal rate and species’ vulnerability to climate change in seabirds, Dryad, Dataset, https://doi.org/10.5061/dryad.cfxpnvx9g
The cognitive buffer hypothesis proposes that species with larger brains (relative to their body size) exhibit greater behavioural flexibility, conferring an advantage in unpredictable or novel environments. Therefore, behavioural flexibility – and relative brain size – are likely to be important predictors of a species’ vulnerability to anthropogenic pressures and, ultimately, extinction risk. However, current evidence linking brain size to species vulnerability and extinction risk is inconclusive. Furthermore, studies examining the relationship between relative brain size and behavioural flexibility have mainly focused on foraging innovations, whilst other forms of behavioural flexibility remain unexplored. In this study, we collate species-specific information and examine links between relative brain size, rates of natal and adult dispersal (a measure of flexibility in breeding site fidelity), vulnerability to six anthropogenic threats and extinction risk for 131 species of seabird. We focused our study on seabirds, a highly threatened group that displays large variation in both relative brain size and dispersal behaviour. We found a significant positive relationship between relative brain size and natal dispersal rate, suggesting that relative brain size could enhance flexibility in breeding site choice in seabirds, consistent with the cognitive buffer hypothesis. However, this relationship does not persist when we consider adult dispersal, possibly reflecting constraints imposed by mate selection and knowledge transfer in seabirds. We also show that relative brain size is negatively associated with vulnerability to climate change. These findings have immediate application for predicting interspecific variation in species’ vulnerability to climate change and identifying priority species for conservation.
Dataset 1: Brain and body size
Published measures of brain size (g) for 131 species of seabird. Brain size estimates were generated from the measurement of adult skulls in museum collections using the endocast method. For each species, multiple specimens were measured and a mean value was calculated to provide a single, species-specific brain size estimate. To account for the allometric relationship between brain and body size, we also obtained information on body size (g).
Dataset 2: Natal and adult dispersal rates
We collated data on natal and adult dispersal rates by conducting a systematic literature search using the online database, Web of Science. The literature search generated a total of 793 papers and reports and from these, we extracted natal and adult dispersal rates. Here, natal dispersal is defined as the annual proportion of fledglings recruiting into a colony different from their natal colony, and adult dispersal is defined as the annual proportion of adults relocating to a new breeding colony. The final dataset included dispersal estimates from 47 studies and 29 species. For studies that provided multiple dispersal rate estimates, i.e., for different adult age classes or for males and females (n=9), we calculated a species mean value. For this final list, we also collated information on age at first breeding and fledging time. We selected age at first breeding to reflect the species-specific time that is available to prospect different colonies, and fledging time to reflect maternal investment. Where multiple species-specific values were provided for age at first breeding, we calculated the mean weighted by the percentage of individuals that had bred by each age. Where a range was provided for fledging time, we took the midpoint.
Dataset 3: Extinction risk and threats
We extracted a species’ threat status from the IUCN Red List database (iucnredlist.org, 2020) and their vulnerability to six relevant anthropogenic threats listed under the Threats Classification Scheme (v. 3.3, IUCN, 2020). The six anthropogenic threats we considered were: climate change, biological resource use (e.g., fishing), human intrusions and disturbance, invasive species, energy production and mining, and pollution. Threat vulnerability was classified as: ‘vulnerable’ or ‘not vulnerable’. We used the IUCN classifications to group species into two broader categories of extinction risk. Here, species classified as Critically Endangered (CR), Endangered (E) and Vulnerable (V) were defined as ‘threatened’, and species listed as Near Threatened (NT) and Least Concern (LC) were defined as ‘non-threatened’.
Agència de Gestió d'Ajuts Universitaris i de Recerca, Award: 2020 BP 00067
H2020 Marie Skłodowska-Curie Actions, Award: 838998