Demography-environment relationships improve mechanistic understanding of range dynamics under climate change

This is supplementary material to the publication:

"Demography-environment relationships improve mechanistic understanding of range dynamics under climate change"

by Anne-Kathleen Malchow, Florian Hartig, Jette Reeg, Marc Kéry, and Damaris Zurell.

It contains the R scripts and data needed to reproduce all results. The code uses a developmental version of the R package RangeShiftR, which can be found in the RangeShiftR repo under the development tag v.1.1-beta.0.

Funding

AM and DZ were supported by Deutsche Forschungsgemeinschaft (DFG) under grant agreement No. ZU 361/1-1.

Data provision

The study uses data from the Swiss breeding bird survey (Schmid et al., 2004) and the Swiss breeding bird index (Knaus et al., 2022) provided by the Swiss ornithological institute, Sempach. The repository contains processed versions of this data.

Schmid, H., Zbinden, N., and Keller, V. (2004). Überwachung der Bestandsentwicklung häufiger Brutvögel in der Schweiz. Swiss Ornithological Institute.

Knaus, P., Strebel, N., & Sattler, T. (2022). The State of Birds in Switzerland 2022. Swiss Ornithological Institute. http://www.vogelwarte.ch/state

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Folder data

All input data required to run the model calibration: Raster maps of climate variables, the habitat models and derived maps, the initial distribution models and spatially aggregated counts from the Swiss breeding bird survey.

Folder scripts

scripts/data_prep

Scripts to generate the input data from the original data sources, i.e. Chelsa climate v2.1 and CORINE land cover.

scripts/calibration

The scripts to run the model calibration. The routine is contained in calibration_main.R, which loads functions defined in the other scripts.

scripts/analysis

The scripts to process and analyse the MCMC chains produced in the calibration. Extracts the demography-climate relationships and performs prior/posterior predicitons. Creates all plots. All routines are contained in "analysis_main.R*, which loads functions defined in the other scripts.

Folder model

Contains the RangeShiftR folder structure.

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Session info

The calculations were run under the following setup:

R version 4.0.4 (2021-02-15)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Debian GNU/Linux 11 (bullseye)

Matrix products:
default BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0 LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0

Locale:
LC_CTYPE=en_US.UTF-8; LC_NUMERIC=C; LC_TIME=C; LC_COLLATE=en_US.UTF-8; LC_MONETARY=C; LC_MESSAGES=en_US.UTF-8; LC_PAPER=C; LC_NAME=C; LC_ADDRESS=C; LC_TELEPHONE=C; LC_MEASUREMENT=C; LC_IDENTIFICATION=C

Attached base packages:
stats; graphics; grDevices; utils; datasets; methods; base

Other attached packages:
RangeShiftR_1.0.3; raster_3.5-21; sp_1.5-0

Loaded via a namespace (and not attached):
compiler_4.0.4; rgdal_1.5-27; tools_4.0.4; Rcpp_1.0.7; codetools_0.2-18; grid_4.0.4; rbibutils_2.2.8; Rdpack_2.3.1; lattice_0.20-41; terra_1.5-34