Quantifying intraspecific and interspecific trait variability is critical to our understanding of biogeography, ecology and conservation. But quantifying such variability and understanding the importance of intraspecific and interspecific variability remain challenging. This is especially true of large geographic scales as this is where the differences between intraspecific and interspecific variability are likely to be greatest.
Our goal is to address this research gap using broad‐scale citizen science data to quantify intraspecific variability and compare it with interspecific variability, using the example of bird responses to urbanization across the continental United States.
Using more than 100 million observations, we quantified urban tolerance for 338 species within randomly sampled spatial regions and then calculated the standard deviation of each species' urban tolerance.
We found that species' spatial variability in urban tolerance (i.e. standard deviation) was largely explained by the variability of urban cover throughout a species' range (R2 = 0.70). Variability in urban tolerance was greater in species that were more tolerant of urban cover (i.e. the average urban tolerance throughout their range), suggesting that generalist life histories are better suited to adapt to novel anthropogenic environments. Overall, species differences explained most of the variability in urban tolerance across spatial regions.
Together, our results indicate that (1) intraspecific variability is largely predicted by local environmental variability in urban cover at a large spatial scale and (2) interspecific variability is greater than intraspecific variability, supporting the common use of mean values (i.e. collapsing observations across a species' range) when assessing species–environment relationships. Further studies, across different taxa, traits and species–environment relationships are needed to test the role of intraspecific variability, but nevertheless, we recommend that when possible, ecologists should avoid using discrete categories to classify species in how they respond to the environment.