Bale Mountain Exile Hypothesis DFG2358
Published August 23, 2022 | Version v1
Dataset Open

Data set to Remote sensing-supported mapping of the activity of a subterranean landscape engineer across an afro-alpine ecosystem

Creators

  • 1. Department of Geography, Environmental Informatics, Philipps-Universität Marburg, Deutschhausstraße 12, 35032 Marburg, Germany
  • 2. Department of Biology, Conservation Ecology, Philipps-Universität Marburg, Karl-von-Frisch-Straße 8, 35034 Marburg, Germany
  • 3. Department of Geography, Environmental Informatics, Philipps-Universität Marburg, Deutschhausstraße 12, 35032 Marburg, Germany; Department of Biology, Plant Ecology and Geobotany, Philipps-Universität Marburg, Karl-von-Frisch-Straße 8, 35034 Marburg, Germany
  • 4. Department of Biology, Plant Ecology and Geobotany, Philipps-Universität Marburg, Karl-von-Frisch-Straße 8, 35034 Marburg, Germany; Department of Plant Biology and Biodiversity Management, College of Natural and Computational Sciences, Addis Ababa University, Addis Ababa, Ethiopia
  • 5. Department of Plant Biology and Biodiversity Management, College of Natural and Computational Sciences, Addis Ababa University, Addis Ababa, Ethiopia
  • 6. Department of Geography, Vegetation Geography, Philipps-Universität Marburg, Deutschhausstraße 10, 35032 Marburg, Germany
  • 7. Department of Biology, Plant Ecology and Geobotany, Philipps-Universität Marburg, Karl-von-Frisch-Straße 8, 35034 Marburg, Germany; Swiss Federal Research Institute WSL, Zürcherstrasse 111, 8903 Birmensdorf, Switzerland

Description

This data set is part of the article Wraase et al. (2022): Remote sensing -supported mapping of the activity of a subterranean landscape engineer across an afro-alpine ecosystem. Remote sensing in Ecology and Conservation. (https://doi.org/10.1002/RSE2.303)

The repository contains a Readme file ("readme.txt") and two additional folders labeled: “input data” and “script”.

The first folder contains 13 data files further divided into three subfolders “cca_analysis”, “main_modelling_prc_texture_idx” and “vectors”. Data formats are .csv format for all tables, .rds files for model objects from R and .shp format for all vector data.

The second folder contains all 31 R-scripts necessary to do the analysis, as described in the article. Additionally, the folder is further categorized into five subfolders equivalent to the main analysis operations: “cca_analysis”, “landsat_temp_modelling”, “main_modelling_prc”, “maxent” and “texture_idx”.

Notes

This research was funded by the German Research Council (DFG) within the framework of the joint Ethio‐European DFG Research Unit 2358 "The Mountain Exile Hypothesis. How humans benefited from and re‐shaped African high‐altitude ecosystems during Quaternary climate changes" (NA 783/12‐2, OP 219/5‐2, FA‐925/14‐1 und SCHA‐2085/3‐1, MI271/33‐2). We thank the Ethiopian Wildlife Conservation Authority, the College of Natural and Computational Sciences (Addis Ababa University), the Department of Plant Biology and Biodiversity Management (Addis Ababa University), the Philipps‐Universität Marburg, the Frankfurt Zoological Society, the Ethiopian Wolf Project and the Bale Mountains National Park for their cooperation and kind permission to conduct fieldwork. We are grateful to Awol Asefa, Wege Abebe, Katinka Thielsen, Tiziana Li Koch, Kevin Frac, Terefe Endale, Geremew Mebratu for helping to prepare the fieldwork and this manuscript.

Files

dataGRR.zip

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Additional details

References

  • Wraase et al. (2022): Remote sensing -supported mapping of the activity of a subterranean landscape engineer across an afro-alpine ecosystem

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