Organizational Context
This study will take place in the Amazonian region of Madre de Dios, Peru, located on the early stage of the forest transition curve, meaning both forest cover and deforestations rates are high. Fuelled by a variety of intentions i.e. carbon credits, conservation, economic development, etc., the smallholder farmers in this region see their farming system intervened in a variety of ways. This research will aim to understand how key drivers and interventions influence change towards more diverse and resilient agricultural systems in early stages of forest transition and, thereby, to explore and co-construct promising interventions with the use of participatory methods. First, the trend in resilience in the farming system will be analyzed with the heuristic model of panarchy (chapter 1). Second, the local social-ecological farming system will be characterized with household surveys and Fuzzy-Cognitive Mapping (FCM) with multiple stakeholders (chapter 2). Third, the farm-level decision-making will be explored through the creation of a serious game (chapter 3) and, finally, this game will be used to explore and co-construct interventions with stakeholders for more diverse and resilient farming systems (chapter 4).
Roles
The PhD candidate is responsible for collecting and managing data in collaboration with all supervisors. Some field technicians and students will also help with the data collection under the PhD candidate's supervision. Some data will be collected in collaboration with the PRODIGY project (Koblenz-Landau University), that the PhD candidate is also associated with. At the end of the PhD work, all data will be shared with supervisors and made publicly available online whenever possible. The data collected by the candidate will be owned by WUR and Koblenz-Landau University.
All data will be analysed by the PhD candidate, using R, Atlas.it and excel; sometimes with the support of research assistants and students.
Short and long term storage
All data will be stored on my local harddisk in a folder called Thesis.
Within this Thesis folder, I'll create per chapter the folders: Data, Paper and Scripts. The Data folder has two sub-folders called: Raw and Processed.
Folder contents:
- Data - Raw sub-folder: Contains all raw data and meta-data (a description of your data).
- Data - Processed sub-folder: Contains all processed data.
- Paper folder: Text of a chapter / paper.
- Scripts folder: Contains all scripts used.
The complete content of my local Thesis folder will be stored on my YoDa-drive.
During periods I'm abroad, I'll backup the complete content of my local Thesis folder to a Dropbox or MS-Onedrive Thesis folder and share the contents with my supervisor(s).
The complete content of my local PhD folder will be uploaded on my Microsoft-Teams storage.
Sharing and Ownership
The data collected by the candidate will be owned by WUR and Koblenz-Landau University. We will strive to make all data and tools developed in this PhD publicly available within a reasonable time on the model portal of PPS: http://models.pps.wur.nl/. The data management will follow the PPS data management recipe, for example by storing raw data in ASCII formatted files when possible, documenting all nature and content of data files with meta-data and variable definition, and providing commented scripts to ensure a reproducible pathway from raw data to results.