10.5061/DRYAD.SF7M0CG2K
Ducatez, Simon
0000-0003-2865-4674
Centre for Research on Ecology and Forestry Applications
Sol, Daniel
Centre for Research on Ecology and Forestry Applications
Sayol, Ferran
0000-0003-3540-7487
University of Gothenburg
Lefebvre, Louis
0000-0002-6445-0292
McGill University
Behavioural plasticity is associated with reduced extinction risk in birds
Dryad
dataset
2020
Extinction risk
2020-02-27T00:00:00Z
2020-02-27T00:00:00Z
en
https://doi.org/10.1371/journal.pone.0089955
https://doi.org/10.1890/ES14-00332.1
https://doi.org/10.1890/13-1917.1
9781420064445 - CAT# 64444
http://datazone.birdlife.org/home
http://www.hbw.com
https://www.iucnredlist.org/en
https://doi.org/10.1038/nature11631
https://doi.org/10.1016/j.anbehav.2009.06.033
1182147 bytes
3
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Behavioural plasticity is believed to reduce species vulnerability to
extinction, yet global evidence supporting this hypothesis is lacking. We
address this gap by quantifying the extent to which birds are observed
behaving in novel ways to obtain food in the wild: based on a unique
dataset of >3,800 novel behaviours, we show that species with a
higher propensity to innovate are at a lower risk of global extinction and
are more likely to have increasing or stable populations than less
innovative birds. These results mainly reflect a higher tolerance of
innovative species to habitat destruction, the main threat for birds.
This dataset gathers information on foraging innovations, extinction risk,
population trend, threats, biogeographic range, diet and habitat breadth,
body mass, migratory behaviour, generation length, insularity and presence
in urban areas for 8645 bird species. "species" is the species
name using the IUCN taxonomy, "animal" is the species name
considering the taxonomy from Jetz et al. (2012). Innovation data: The
innovation data was compiled by systematically searching for reports of
new behaviours in the short notes of 204 ornithology journals published
between 1960 and 2018. A feeding behaviour was considered an innovation,
and hence was included in the database, if it was described in the report
with key words such as “novel”, “opportunistic”, “first description”, “not
noted before”, “unusual”, etc. Two variables are provided for species
foraging innovations: the total number of innovations reported
(TotalInnovations) and a binary variable with 0 for species with 0
innovation reported, and 1 for species with at least 1 innovation reported
(InnovationYesOrNo). In addition, we distinguished “consumer” innovations
(new behaviours involving slight changes, such as the incorporation of new
foods in a species diet) and “technical” innovations. Technical
innovations refer to reports where the author describes the searching and
handling technique itself as novel, regardless of whether the food type
was novel or not. The dataset includes the numbers of technical and
consumer innovations, and binary variables with 0 for species with no
consumer/technical innovation reported, and 1 for species with at least 1
consumer/technical innovation reported. IUCN data: Extinction risk,
CriterionB (binary variable determining whether a species was considered
at risk of extinction because of its small range), population trend,
threat exposure (HabitatDestruction, InvasiveSpecies, Overexploitation),
urbanisation (Urban: binary variable with 0 for non-urban species, 1 for
species occuring in urban habitats) and geographic region
(BiogeographicRange) were obtained from the IUCN website in February 2019.
Covariables: Information for all other variables were obtained from a
diversity of sources listed below (see details in the article's
methods). Body mass is in g, generation time in years. Research effort is
the number of papers published on each species between 1978 and 2008
according to the online version of the Zoological Record (from Ducatez
& Lefebvre 2014). Species insularity was coded as 0 for mainland
species and 1 for insular species; migratory behaviour as 1 for sedentary
or nomadic species, 2 for altitudinal migrant and 3 for long distance
migrant. As an index of habitat breadth, we used a recently developed
index based on patterns of species co-occurrence within 101 habitat
categories. Briefly, a species was allocated a quantitative score based on
the diversity of other taxa with which it co-occurs, such that a
generalist species is one that occurs in a range of habitat categories
that vary considerably in species composition, whereas a specialist
species is found only in habitats that contain a consistent suite of other
species (index available for all terrestrial vertebrates in Ducatez et al.
2014). We measured diet breadth by counting the number of food categories
consumed by adults of each species, using six food categories: vertebrate
carrion, vertebrate prey, invertebrate prey, nectar or pollen, fruit or
seeds, and leaves or stems (source for the food categories for each bird
species: Wilman et al. 2014). Data sources: Birdlife International.
http://datazone.birdlife.org/home (2019). del Hoyo, J., Elliott, A.,
Sargatal, J., Christie, D. A. & de Juana, E. Handbook of the Birds
of the World alive. Lynx Edicions, Barcelona. Retrieved from www.hbw.com
in November 2017. (2017). Ducatez, S. & Lefebvre, L. Patterns of
Research Effort in Birds. PLoS ONE 9, e89955 (2014). Ducatez, S., Tingley,
R. & Shine, R. Using species co-occurrence patterns to quantify
relative habitat breadth in terrestrial vertebrates. Ecosphere 5, art152
(2014). Dunning, J. B. CRC Handbook of Avian Body Masses. (CRC Press,
Inc., 2007). IUCN. The IUCN Red List of Threatened Species Version 2019-1.
IUCN Red List of Threatened Species https://www.iucnredlist.org/en (2019).
Jetz, W., Thomas, G. H., Joy, J. B., Hartmann, K. & Mooers, A. O.
The global diversity of birds in space and time. Nature 491, 444–448
(2012). Wilman, H. et al. EltonTraits 1.0: Species-level foraging
attributes of the world’s birds and mammals. Ecology 95, 2027–2027 (2014).
Population trend was unknown for 633 species (coded as "NA" in
the TrendCode column). The R code used to analyse this dataset is also
provided.