Data from: Geographic variations in eco-evolutionary factors governing urban birds: the case of university campuses in China
Data files
Dec 11, 2023 version files 1.01 MB
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Dataset_S1.xlsx
1 MB
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README.md
11.75 KB
Abstract
- Urbanization alters natural habitats, restructures biotic communities, and serves as a filter for selecting species from regional species pools. However, empirical evidence of the specific traits that allow species to persist in urban areas yields mixed results. More importantly, it remains unclear which traits are widespread for species utilizing urban spaces (urban utilizers) and which are environment-dependent traits.
- Using 745 bird species from 287 university/institute campuses in 74 cities and their species pools across China, we tested whether species that occur in urban areas are correlated with regards to their biological (body mass, beak shape, flight capacity, and clutch size), ecological (diet diversity, niche width, and habitat breadth), behavioral (foraging innovation), and evolutionary (diversification rate) attributes.
- We used Bayesian phylogenetic generalized linear mixed models to disentangle the relative roles of these predictors further and to determine the extent to which the effects of these predictors varied among different cities.
- We found that urban birds were more phylogenetically clustered than expected by chance, and were generally characterized by a larger habitat breadth, faster diversification rate, more behavioral innovation, and smaller body size. Notably, the relative effects of the attributes in explaining urban bird communities varied with city temperature and elevation, indicating that the filters used to determine urban species were environment-dependent.
- We conclude that, while urban birds are typically small-sized, generalists, innovative, and rapidly-diversifying, the key traits that allow them to thrive vary spatially, depending on the climatic and topographic conditions of the city. These findings emphasize the importance of studying species communities within specific cities to better understand the contextual dependencies of key traits that are filtered by urban environments.
README: Data from: Geographic variations in eco-evolutionary factors governing urban birds: the case of university campuses in China
[Access this dataset on Dryad] (https://doi.org/10.5061/dryad.cnp5hqcbp)
A. Description
This dataset contains the data supporting the findings of the above article. In summary, this dataset includes 1,344 bird checklists from 287 university/institute campuses in 74 cities of China, resulting in a total of 745 species of birds (165 urban utilizers and 580 urban avoiders). The species-level information was also compiled, including their biological (body mass, beak shape, flight capacity, and clutch size), ecological (diet diversity, niche width, and habitat breadth), behavioral (foraging innovation) and evolutionary (diversification rate) attributes. In addition, the cities’ environmental and socio-economic status, and the detailed information on the references of avian checklists on university/institute campuses were provided.
B. Directory structure
This dataset (.xlsx format) includes five sheets:
- 01RawData
- 02Trait
- 03CityInfo
- 04PaperInfo
- 05BirdReport
C. Dataset description
01RawData: A data frame providing the avian checklist of 287 university/institute campuses in 74 cities of China.
Columns | Description |
---|---|
no | Sequence number |
Species | Species taxonomy according to Jetz et al. (2012) |
Campus | Name of university and academic campus |
City | City name |
Seasonal | Seasonal presence of the species in the city. R=resident; S=breeding season |
ReferenceType | Reference type of the data source |
SourceID | ID number of the reference |
02Trait: A data frame including information about urban avoiders or utilizers, and the biological (body mass, beak shape, flight capacity, and clutch size), ecological (diet diversity, niche width, and habitat breadth), behavioral (foraging innovation), and evolutionary (diversification rate) attributes of 745 avian species.
Columns | Description |
---|---|
no | Sequence number |
Species | Species taxonomy according to Jetz et al. (2012) |
UrbanBirdRep5 | Urban bird was defined as a bird species that was recorded more than 5 times in all of city checklists, whereas urban avoider was recorded among the species pool, but was not recorded in the city or recorded in less than 5 checklists. |
UrbanBirdRep10 | Urban bird was defined as a bird species that was recorded more than 10 times in all of city checklists, whereas urban avoider was recorded among the species pool but was not recorded in city or recorded in less than 5 checklists. |
BodyMass | Body mass (g) per species was obtained from Tobias et al. (2022) |
BillPC2 | Bill shape was extracted from a global analysis of avian beaks (Pigot et al., 2020) using the second principal component (PC2) |
HWI | Hand-wing index (HWI) data was obtained from Sheard et al. (2020) |
ClutchSize | Clutch size data was extracted from Jetz et al. (2008), Myhrvold et al. (2015) and Tobias & Pigot (2019) |
DietDiversity | Diet diversity was quantified by the Shannon Index on the proportions of 7 dietary categories reclassified from EltonTraits (Wilman et al., 2014) |
NicheBreadth | Climatic niche width was estimated using bioclimatic data obtained from the WorldClim database (version 2.0; Fick & Hijmans, 2017) |
DiversificationRate | The species-level diversification rate was calculated using the inverse of the equal-splits metric that calculates the per-species estimates of expected pure birth diversification rates for the immediate present moment (Jetz et al., 2012) |
HabitatBreadth | Habitat breadth were measured based on species co-occurrence patterns within each of the 101 habitat categories recognized by the IUCN habitat classification scheme (Ducatez et al., 2014) |
InnovationYN | The behavioral innovation information was extracted from the work of Ducatez et al. (2020). 0=absence; 1=presence |
03CityInfo: A data frame indicating the cities’ names, geographical coordinates, climatic conditions, elevations, populations, urban areas, and the belonging zoogeographical regions.
Columns | Description |
---|---|
no | Sequence number |
City | City names |
Longitude | Longitude of the city |
Latitude | Latitude of the city |
Bio1 | BIO1 climatic variable (i.e., mean annual temperature, ℃) |
Bio12 | BIO12 climatic variable (i.e., mean annual precipitation, mm) |
Elevation | Elevation (m) |
ElevationRange | Elevation range (m) |
Population | Human population of the city |
UrbanArea | Urban area of the city (km2) |
Zooregion | Zoogeographical regions to which each city belonging |
04PaperInfo: A data frame providing detailed information on the references of avian checklists on university/institute campuses in China.
Columns | Description |
---|---|
SourceID | ID number of the reference |
FullReference | Detailed information of the reference |
05BirdReport: A data frame providing detailed information on the bird recording reports on the university/institute campuses in China.
Columns | Description |
---|---|
SourceID | ID number of the bird recording report |
Campus | Name of university and academic campus |
City | City name |
Longitude | Longitude of the campus |
Latitude | Latitude of the campus |
ObervationTime | Observation time of the bird recording report |
SpeciesRichness | Species richness recorded originally by the bird recording report |
AssessDate | Assess date of the bird recording report |
Data was derived from the following sources:
Ducatez, S., Sol, D., Sayol, F., & Lefebvre, L. (2020). Behavioural plasticity is associated with reduced extinction risk in birds. Nature Ecology & Evolution, 4(6), 788-793. doi:10.1038/s41559-020-1168-8
Ducatez, S., Tingley, R., & Shine, R. (2014). Using species co-occurrence patterns to quantify relative habitat breadth in terrestrial vertebrates. Ecosphere, 5(12), 152. doi:10.1890/es14-00332.1
Fick, S. E., & Hijmans, R. J. (2017). WorldClim 2: new 1‐km spatial resolution climate surfaces for global land areas. International Journal of Climatology, 37(12), 4302-4315. doi:10.1002/joc.5086
Jetz, W., Sekercioglu, C. H., & Böhning-Gaese, K. (2008). The worldwide variation in avian clutch size across species and space. PLoS Biology, 6(12), e303. doi:10.1371/journal.pbio.0060303
Jetz, W., Thomas, G., Joy, J., Hartmann, K., & Mooers, A. (2012). The global diversity of birds in space and time. Nature, 491(7424), 444-448. doi:10.1038/nature11631
Myhrvold, N. P., Baldridge, E., Chan, B., Sivam, D., Freeman, D. L., & Ernest, S. K. M. (2015). An amniote life-history database to perform comparative analyses with birds, mammals, and reptiles. Ecology, 96(11), 3109-3109. doi: 10.1890/15-0846R.1
Pigot, A. L., Sheard, C., Miller, E. T., Bregman, T. P., Freeman, B. G., Roll, U., . . . Tobias, J. A. (2020). Macroevolutionary convergence connects morphological form to ecological function in birds. Nature Ecology & Evolution, 4(2), 230-239. doi:10.1038/s41559-019-1070-4
Sheard, C., Neate-Clegg, M. H. C., Alioravainen, N., Jones, S. E. I., Vincent, C., MacGregor, H. E. A., . . . Tobias, J. A. (2020). Ecological drivers of global gradients in avian dispersal inferred from wing morphology. Nature Communications, 11(1), 2463. doi:10.1038/s41467-020-16313-6
Tobias, J. A., & Pigot, A. L. (2019). Integrating behaviour and ecology into global biodiversity conservation strategies. Philosophical Transactions of the Royal Society B: Biological Sciences, 374(1781), 20190012. doi:doi:10.1098/rstb.2019.0012
Tobias, J. A., Sheard, C., Pigot, A. L., Devenish, A. J. M., Yang, J., Sayol, F., . . . Schleuning, M. (2022). AVONET: morphological, ecological and geographical data for all birds. Ecology Letters, 25(3), 581-597. doi:10.1111/ele.13898
Wilman, H., Belmaker, J., Simpson, J., de la Rosa, C., Rivadeneira, M. M., & Jetz, W. (2014). EltonTraits 1.0: Species-level foraging attributes of the world's birds and mammals. Ecology, 95(7), 2027-2027. doi:10.1890/13-1917.1