Data from: Spatial and seasonal variation in thermal sensitivity within North American bird species
Data files
Oct 19, 2023 version files 110.24 KB
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README.md
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species_list.csv
Abstract
Responses of wildlife to climate change are typically quantified at the species level, but physiological evidence suggests significant intraspecific variation in thermal sensitivity given adaptation to local environments and plasticity required to adjust to seasonal environments. Spatial and temporal variation in thermal responses may carry important implications for climate change vulnerability; for instance, sensitivity to extreme weather may increase in specific regions or seasons. Here, we leverage high-resolution observational data from eBird to understand regional and seasonal variation in thermal sensitivity for 20 bird species. Across their ranges, most birds demonstrated regional and seasonal variation in both thermal peak and range, or the temperature and range of temperatures of greatest occurrence. Some birds demonstrated constant thermal peaks or ranges across their geographic distributions and while others varied according to local and current environmental conditions. Across species, birds typically invested in either geographic or seasonal adaptation to climate. Local adaptation and phenotypic plasticity are likely important but neglected aspects of organismal responses to climate change.
README: Spatial and seasonal variation in thermal sensitivity within North American bird species
Responses of wildlife to climate change are typically quantified at the species level, but physiological evidence suggests significant intraspecific variation in thermal sensitivity given adaptation to local environments and plasticity required to adjust to seasonal environments. Spatial and temporal variation in thermal responses may carry important implications for climate change vulnerability; for instance, sensitivity to extreme weather may increase in specific regions or seasons. Here, we leverage high-resolution observational data from eBird to understand regional and seasonal variation in thermal sensitivity for 20 bird species. Across their ranges, most birds demonstrated regional and seasonal variation in both thermal peak and range, or the temperature and range of temperatures of greatest occurrence. Some birds demonstrated constant thermal peaks or ranges across their geographic distributions and while others varied according to local and current environmental conditions. Across species, birds typically invested in either geographic or seasonal adaptation to climate. Local adaptation and phenotypic plasticity are likely important but neglected aspects of organismal responses to climate change.
Description of the data and file structure
Code sheets
1: models_sdm.R
Species distribution modeling workflow using spatiotemporal exploratory models, allowing predictions to vary over space and time.
2: patching_outputs.R
After workflow runs for all species (models_stem sheet), use this to compile relevant climate data and fit models to get metrics of variation in sensitivity to thermal conditions at the species level.
3: thermtol_cross_sp.R
Linear models and figure generation to describe patterns across all species in our dataset.
4: Propensity_scores.R
A supplementary analysis to examine the influence of weather on human observers.
Dependencies all found in /source/ directory
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Datasets
1: species_list.csv
A master list of species in our analysis
Column headings:
Common: species common name
Scientific: species latin name
Abbr: four letter species banding code
Code: ABA birding code describing species commonness. 1= common, 2= uncommon
ebird_code: six-letter species code
TAXON_ORDER: species numeric ID
category: species or subspecies classification
scientific name: species latin name
range: description of species range
order: taxonomic order
family: taxonomic family
Missing data code: NA
Sharing/Access information
Data was derived from publicly accessible data available at www.ebird.org
Software
R and RStudio
Methods
eBird dataset was obtained from the Cornell Lab of Ornithology. Similar dataset (organized differently, does not contain environmental information) availabile via www.ebird.org
Usage notes
Data was processed in R and RStudio