Publications by Bioshifts group
Global climate velocity
rm(list=ls()) gc() ## used (Mb) gc trigger (Mb) max used (Mb) ## Ncells 528699 28.3 1180377 63.1 660382 35.3 ## Vcells 964835 7.4 8388608 64.0 1769918 13.6 # devtools::install_github("GMBA-biodiversity/gmbaR") list.of.packages <- c("terra","ggplot2","tidyverse","MultiscaleDTM","forcats") new.packages <- list.of.packages[!(l...
1224 sym Python (14770 sym/68 pcs) 44 img
SDM results
Table of contents 1 Setup 2 Load data 3 Models 4 1) Bioclimatic velocities as predictors of observed range shifts 4.1 The simple model 4.1.1 Terrestrial 4.2 Marine 4.3 The complex model 4.3.1 Terrestrial 4.3.2 Marine 5 2) Mismatch 5.1 Mismatch simple 5.1.1 Terrestrial 5.1.2 Marine 5.2 Mismatch absolut 5.2.1 Terrestrial 5.2.2 Marine Explo...
2256 sym Python (39978 sym/105 pcs) 8 img
Bioclimatic vs biotic
Table of contents 1 Load data 2 SDM evaluation results 3 Explore relationships 3.1 N shifts per parameter 4 How related are observed shifts and climate exposure metrics? 5 Bioclimatic velocity 5.1 Angle 5.1.1 Frequency 5.1.2 Magnitude 5.2 Direction match 5.3 Scatter plots 5.3.1 Eco 5.3.2 Taxonomic class 5.3.3 Mismatch 5.3.4 Duration 5.3.5 N ...
5749 sym Python (70487 sym/211 pcs) 63 img
SDM Exposure
Table of contents 1 Load data 2 Concept figure pieces 2.1 Fig 1b 3 Explore relationships 3.1 N shifts per parameter 4 How related are observed shifts and climate exposure metrics? 4.1 Bioclimatic velocity 4.2 Climate velocity 4.3 Weighted climate velocity 4.4 Weighted climate velocity vs Bioclimatic velocity 5 Difference observed shift and b...
2501 sym 17 img
Adaptive potential Merge genetic data
1 Load libraries and source code # devtools::install_github('EcologicalTraitData/traitdataform') rm(list=ls()) list.of.packages <- c("ggplot2","data.table","dplyr","tidyr","parallel","bdc","taxadb","traitdataform","pbapply","tidyverse","readxl","lme4","coefplot","sjPlot","sjmisc","effects","rgdal","maptools","rgeos","terra","MuMIn","rnaturalea...
7302 sym Python (140031 sym/710 pcs) 114 img
Geneti
1 Load libraries and source code rm(list=ls()) list.of.packages <- c("ggplot2", "data.table", "dplyr", "tidyr", "parallel", "bdc", "taxadb", "traitdataform", "pbapply", "tidyverse", "readxl", "lme4", "coefplot", "sjPlot", "sjmisc", "effects", "rgdal", "maptools", "terra", "MuMIn", "lsmeans", "GGally", "tidyterra", "glmmTMB", "DHARMa") new.pac...
3498 sym Python (29978 sym/134 pcs) 34 img
Global velocities
rm(list=ls()) gc() ## used (Mb) gc trigger (Mb) max used (Mb) ## Ncells 519074 27.8 1152877 61.6 660382 35.3 ## Vcells 946706 7.3 8388608 64.0 1769619 13.6 # devtools::install_github("GMBA-biodiversity/gmbaR") list.of.packages <- c("terra","ggplot2","tidyverse","MultiscaleDTM","forcats") new.packages <- list.of.packages[!(l...
2769 sym Python (22895 sym/88 pcs) 36 img
Methodological adjustments
1 Instructions: All R-scripts and files used to generate this report are available at: https://github.com/Bioshifts/MethodologicalAdjustment Code demonstrating the entire processes is bellow, including data processing and decisions made along the way. Note that code is hidden by default – considering that most would be interested in the output...
6337 sym R (79296 sym/201 pcs) 94 img
Adaptive potential - Merge genetic data to bioshifts
1 Load libraries and source code rm(list=ls()) library(ggplot2) require(data.table) library(dplyr) library(tidyr) require(parallel) library(bdc) library(taxadb) library(traitdataform) library(pbapply) library(tidyverse) library(readxl) library(lme4) library(coefplot) library(sjPlot) library(sjmisc) library(effects) library(rgdal)...
4616 sym R (111539 sym/405 pcs) 113 img
Adaptive potential - models
1 Load libraries and source code rm(list=ls()) library(ggplot2) require(data.table) library(dplyr) library(tidyr) require(parallel) library(bdc) library(taxadb) library(traitdataform) library(pbapply) library(tidyverse) library(readxl) library(lme4) library(coefplot) library(sjPlot) library(sjmisc) library(effects) library(rgdal)...
3378 sym R (144948 sym/268 pcs) 29 img