Data from: Riparian reforestation on the landscape scale – Navigating trade-offs among agricultural production, ecosystem functioning and biodiversity
Authors/Creators
- 1. Helmholtz Centre for Environmental Research GmbH - UFZ, Department of Computational Landscape Ecology
- 2. Ghent University, Aquatic Ecology Research Unit, Department of Animal Sciences and Aquatic Ecology
- 3. University of Waikato, Te Aka Mātuatua - School of Science
- 4. Swedish University of Agricultural Sciences - SLU, Department of Aquatic Sciences and Assessment
Description
Short description
This repository contains the relevant data and code used for the analyses of the scientific publication: "Riparian reforestation on the landscape scale – Navigating trade-offs among agricultural production, ecosystem functioning and biodiversity", published in the Journal of Applied Ecology.
For further details please see the original article and its supplementary materials.
Organization of the data
The repository contains two main folders:
1. Target indicators & spatial analysis
‘target indicators.csv’: Measured variables that have been quantified at the CROSSLINK field sampling campaign in the Zwalm catchment (EPT taxa richness, diatoms functional evenness, cotton-strip assay).
‘bio-suitability segments.csv’: Biophysical suitability for food production of the arable land for each riparian segment of the Zwalm.
‘spatial analysis.xlsx’: Results of the Zwalm spatial analyses addressing land-use and physiographic properties of the (1) local riparian corridors; (2) full riparian corridors within in the upstream catchments and (3) total upstream catchment areas for each sampling site.
‘Summary model development Zwalm.pptx’: Additional information on the models that have been used in the CoMOLA optimization framework.
2. CoMOLA input & parameterisation
The files in this folder can be used for the parameterisation of the Python tool CoMOLA (Strauch et al., 2019). Source for CoMOLA, including user manual: https://github.com/michstrauch/CoMOLA
‘config.ini’: Basic configuration file of CoMOLA (needs to be adjusted to local settings)
‘input’ folder: Includes the CoMOLA input files that have been used in our study. See CoMOLA manual for more details on each file.
‘models’ folder: Includes the Python code of the models that are used for the calculation of all target indicators within the optimization framework (‘Zwalm_4_Models_v1_utf8.py’). The sub-folders ‘GIS_temp_files’ and ‘Input’ contain all files that are needed and have been used to run the Python code.