Latitude-specific responses of European birds’ population growth rates to temperature and water availability
Data files
Sep 09, 2025 version files 3.15 GB
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Climate_growth_rate.zip
3.15 GB
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README.md
3.52 KB
Abstract
Climate limits the distribution of species and varies along a latitudinal gradient. However, studies relating climate variation to species population growth rates in different climatic zones while taking into account species’ ecological traits are scarce. We assessed species population responses to the main climatic constraints at a continental scale by studying how precipitation and temperature at different latitudes influence interannual growth rates while considering species’ life-history traits. We gathered data on the abundance of 141 European breeding bird species from national breeding bird monitoring schemes in the Mediterranean (Catalonia, NE Spain), temperate (Czech Republic), and boreal (Sweden) climatic zones for the period 2002–2022. We used generalized linear models to relate the interannual population growth rates of bird species to spring and winter temperature, water availability and heavy rainfall in the breeding season. We considered migration strategy as a covariate possibly shaping bird responses to climate. We found general positive effects of spring and winter temperatures and water availability, and negative effects of heavy rainfall. Increased temperatures affected residents more positively in southern Boreal than in continental and Mediterranean climatic zones. Long-distance migrants responded negatively to temperatures in continental and northern Boreal zones. Higher water availability supported residents and short-distance migrant populations more in lower and higher latitudes than in mid-latitudes. Heavy rainfall tended to affect birds, especially residents, more negatively towards the north, where we revealed the strongest effect among the considered climate variables. Similarly, short-distance migrants suffered more from the intensive rains in northern Boreal than in other climatic zones. Previously, temperature has been shown to be a strong climatic constraint of bird population dynamics. Our results suggest that future changes in precipitation regimes during the birds’ breeding season should also be considered among the important climatic pressures on bird population growth rates in different climatic regions.
Data and R script allowing to reproduce the modelling in the accompanied journal article. The models are stored for convenience. All files are available in Climate_growth_rate.zip.
Description of the data and file structure
File tree
- data
- model
Data
dt_growth_r_clim.csv Data set containing the following variables:
EURING= bird species codeSpec_name= bird species nameReg= breeding region, i.e., MED = Mediterranean, CONT = Continental, S_BOR = Southern Boreal, N_BOR = Northern BorealYear= year corresponding to breeding season (2002 to 2021)Growth_r= interannual population growth rate (ratio of annual population indices in year t+1 and t)Growth_r_SE= standard error of population growth rateDens= population density (log-transformed annual population index)Dens_SE= standard error of population densityMigr= migration status, i.e. R = resident, S = short-distance migrant, L = long-distance migrantDiet= species' diet (values 1 to 5, from obligatory herbivores (1) to obligatory insectivores (5))Bmass= species' body mass (g)Therm_coord= thermal coordinate (range from 0 to 1, from species occupying relatively cold to relatively warm sites of their European breeding range)MC1= MC1 scores describing species' habitat preference (a position along a gradient from coniferous and deciduous forests (negative values) to wetlands and water bodies (positive values))MC2= MC2 scores describing species' habitat preference (a position along a gradient from rocky habitats and mountain meadows (negative values), through grasslands (around zero), to wetlands and water bodies (positive values))Temp= temperature (breeding season, °C)ETr= water availability (range from 0 to 1, a ratio of actual evapotranspiration to potential evapotranspiration)R10= heavy rainfall (mean number of heavy rainfall days, i. e., daily rainfall ≥ 10 mm)Twin= winter temperature relevant for residents only (°C)
Model
m1_clim.rds Stored model testing the overall effects of climate variables, can be loaded instead of fitting the model.
m2_clim.rds Stored model testing the effects of climate variables in regions and in migration strategies, can be loaded instead of fitting the model.
m3_clim.rds Stored model testing the effects of climate variables in migration strategies within regions, can be loaded instead of fitting the model.
m4_clim.rds Stored model testing the overall effect of winter temperatures on residents, can be loaded instead of fitting the model.
m5_clim.rds Stored model testing the effects of winter temperature on residents in particular regions, can be loaded instead of fitting the model.\
Code/Software
R-script_bird_growth.R R script for preparing the data, fitting the models, and deriving various statistics for the effects of climate variables. R is required to run the code.
Usage notes
R is required to run the script R-script_bird_growth.R, as well as to load the stored models (.rds files). The models can be loaded using the base R function readRDS(), but we recommend following the code provided in the R script in order to assign names to the models anticipated within the workflow.
Microsoft Excel or a similar spreadsheet editor can be used to open dt_growth_r_clim.csv data set.