ClimateAnalyzer: set of scripts to delimit regions based on bioclimatic variables
Data files
Jan 24, 2024 version files 1.51 MB
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00_set_stage_ondemand.R
2.53 KB
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00_set_variables.R
1.83 KB
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00_set_your_data.R
2.81 KB
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000_download_data.sh
7.11 KB
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000_install_packages.R
2.86 KB
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01_set_analyses.R
5.08 KB
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02_run_all_postanalyses.R
5.78 KB
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03_get_climatespace.R
4.25 KB
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compareArea.R
6.83 KB
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compareClimate.R
2.71 KB
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makeClimateData.R
8.12 KB
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makeElevationData.R
1.64 KB
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makePolygonDelim.R
21.47 KB
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README.md
2.68 KB
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shapefiles.zip
1.42 MB
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wrapper.R
18.28 KB
Abstract
Habitat stability is important for maintaining biodiversity by preventing species extinction, but this stability is being challenged by climate change. The tropical alpine ecosystem is currently one of the ecosystems most threatened by global warming, and the flora close to the permanent snow line is at high risk of extinction. The tropical alpine ecosystem, found in South and Central America, Malesia and Papuasia, Africa, and Hawaii, is of relatively young evolutionary age, and it has been exposed to changing climates since its origin, particularly during the Pleistocene. Estimating habitat loss and gain between the Last Glacial Maximum (LGM) and the present allows us to relate current biodiversity to past changes in climate and habitat stability. In order to do so, 1) we developed a unifying climate-based delimitation of tropical alpine regions across continents, and 2) we used this delimitation to assess the degree of habitat stability, i.e. the overlap of suitable areas between the LGM and the present, in different tropical alpine regions. Finally, we discuss the link between habitat stability and tropical alpine plant diversity. Our climate-based delimitation approach can be easily applied to other ecosystems using our developed code, facilitating macro-comparative studies of habitat dynamics through time.
https://doi.org/10.5061/dryad.5qfttdzcz
ClimateAnalyzer is a set of script written in R to delimit areas based on bioclimatic variables.
The scripts have been developed to delimit tropical alpine areas based on bioclimatic variables from CHELSA (https://chelsa-climate.org/downloads/). The work has been presented in Kandziora et al (under review) "The ghost of past climate acting on present-day plant diversity: lessons from a climate-based delimitation of the tropical alpine ecosystem".
Description of the data and file structure
The uploaded GIS shapefiles and figures are based on a delimitation based on the mean temperature of the coldest and warmest quarter (bioclim 10 and bioclim 11) of -3 to +10 °C, plus a restriction to the tropics based on bioclim 3, the ratio of diurnal variation to annual variation in temperatures, ranging from 50 to 300 °C/10.
The delimitation was done for current climatic conditions as well as two reconstructions of the climate during the last glacial maximum, based on MPI-M_MPI-ESM-P (abbreviated to MPI) and MIROC_MIROC-ESM (abbreviated as MIROC).
Sharing/Access information
All scripts and files are licenced under CC0 v.1
Code/Software
In order to repeat the analysis users have to rerun script 01 and 02. Script 01 is delimiting the areas based on the bioclimatic variables and script 02 compares different delimitations with each other.
The scripts can also be adapted to any other region, or use of different bioclimatic variables to delimit certain areas.
Getting started
- download the bioclimatic raster layers (000_download_data.sh)
- install all needed packages (check 000_install_packages.R and adapt 'path_to_libraries' and working directory)
- load all packages (00_set_stage_ondemand.R)
- load 00_set_variables.R - here the different bioclimatic limits are being defined, elevation, resolution and projection are set
- make sure that the climate data is downloaded (see 000_download_data.sh) and that the path to the raster layers is correctly provided (function 'get_path_data' in 00_set_your_data.R)
- run 01_set_analyses.R to get the areas delimited by the bioclimatic variables
- run 02_run_all_postanalyses.R to compare different areas to each other
- run 03_get_climatespace.R to do a PCA and get the niche space per area
In case you want to analyze your own climatic delimitation/region, adapt regional limits and names within the function 'get_extent_area' (00_set_your_data.R)
Shapefiles
The uploaded shapefiles are the result of running the scripts to delimit the tropical alpine ecosystem as described in the corresponding publication.
The dataset consists of a set of script developed for the corresponding publication using CHELSA v.1.2 (https://chelsa-climate.org/downloads/) to delimit tropical alpine regions based on bioclimatic variables.
Using the scripts and setting the limits of the respective bioclimatic variables, will result in the GIS shapefiles with the delimitied region. Here, we provide the corresponding GIS shapefiles and figures for the above mentioned publication, that were the outcome of running the R scripts. The shapefiles and figures are based on the mean temperature of the coldest and warmest quarter (bioclim 10 and bioclim 11) of -3 to +10/+18°C respectively, plus a restriction to the tropics based on bioclim 3, the ratio of diurnal variation to annual variation in temperatures, ranging from 50 to 300 °C/10.