SHEFS - SDM pipeline

author: Vivienne Groner

date: 09.03.2022

source: my_path

DATA PRE-PROCESSING, SDM RUN ON CLUSTER, POST-PROCESSING

prepare GBIF occurence records (download, clean, rarify, create background and pseudoabsences, extract environmental data)
```
 01_SA_prep_occurrence_2021.R (loop over list of species in folders, my_path/04_occurrence_records/GBIF_raw)
```

create sh and R jobs for cluster

 02_job_maker.R

 SA_dummy.R

 SA_dummy.sh

 03_make_batch_files.R

run SDM on cluster (present (1979-2013) and RCP45, RCP85 for 5 GCMs)

the following data need to be on cluster:

copy tar.zip files from myriad to RDS

 login myriad -> login xxxxxxx@transfer02

untar folders
```
 04_untar.R

 cmd < cmd_call.txt
```
reorder SDM output in new structure (-> I copied core folders to my_path/11_SDM_output/data/)

resample land cover data to 1 km resolution (reclassifed to PREDICTS and high level land cover classes in ArcMap)
```
 05_SA_NLC_2020_resample.R
```
create land use and intensity suitability map

calculate effect sizes for each group (arthropods, birds, amphibia, reptiles, mammals, gastropods)
```
 06_PREDICTS_subset.R 
```
create map for 2020 and 2080 ssp245 and ssp585
```
 07_create_LCC_scenarios_CropNatUrbWat.R
```

	SA_functions_CBER_analysis.R

read SDM output and create dataframe with presence locations

	08_SDM_df_climate_current.R

	08_SDM_df_climate_future.R

and calculate LUI effect:

	08_SDM_df_climate_lui_current.R

	08_SDM_df_climate_lui_future.R

distribution of AUCs for all species

	code: 09_sensitivity_analysis_AUC.R

sensitivity test of buffer size and density for pseudoabsences

	code: 10_sensitivity_analysis_pseudoabsence.R

output: my_path/04_occurrence_records/buffer_test/

sensitivity test LUI factors

	code: 11_sensitivity_analysis_LUI_factors.R

	output: my_path/02_environmental_data/LUI_sensitivity/