Food security in a changing world – The effects of climate-smart agricultural practices on food security at different scales considering natural resource constraints and future trends.

Submitted by jannike.wichern on
    Organizational Context
    Name
    Jannike Wichern
    Chairgroup
    Plant Production Systems
    Graduate school
    Production Ecology and Resource Conservation
    Start date of project
    Abstract

    East Africa’s rain-fed smallholder agriculture is expected to be heavily affected by climate change, which, together with a growing population and increasing competition for resources, will result in an increasing challenge in the future to achieve food security for households and regions. The resulting need to increase food productivity for food security simultaneously with the capacity of agricultural systems to adapt to climate change while also reducing greenhouse gas emissions lead to the development of the concept ‘Climate-Smart Agriculture’ (CSA). CSA is currently promoted to East African policy makers who are challenged to increase food security in a changing climate.

    For comprehensive policy planning, the question arises to what extent CSA-related farm management changes can increase household level and regional food security while ensuring sustainable resource use. Studies that take into account dynamics and cumulative effects of farm management changes at the landscape scale are lacking.

    This study therefore aims to assess food security at different scales considering future changes and to determine the potential of CSA-practices for increasing food security under sustainable use of natural resources. For this, a simple scaling approach will be developed that enables us to identify promising CSA-intervention options at regional and national scales. We will determine correlations between household level food security and spatial characteristics across Tanzania and Uganda and test the applicability of household data for determining food security and its key drivers at different scales. CSA-practices will be tested for their potential to increase food security while considering future changes and sustainable natural resource use.

    Role supervisor

    Daily supervision will be done by the supervisors Mark van Wijk (ILRI) and Katrien Descheemaeker (PPS, WUR). Prof. Giller is the overall supervisor and promotor of the PhD candidate. The full supervisory team will meet with the PhD candidate on a monthly basis. Thematically the role of Mark van Wijk is in the area of household modeling and food security analyses as well as upscaling of household data and will be contact person for cooperation with researchers at ILRI and within the CCAFS project.

    Katrien Descheemaeker has experience in farming systems analyses and climate change analyses and will support the PhD candidate in the development of analysis frameworks for systems analyses at farm and regional level.

    Additional support for the spatial statistical analyses will be searched within the networks of ILRI and WUR.

    If for some reason the composition of the supervisory team will change, appropriate substitution will be sought withing WUR or the involved parties of the CGIAR.

    Who's collecting the data

    Household data are provided by the CCAFS project of the CGIAR and will be accessible via ILRI (Mark van Wijk), IITA (Piet van Asten), CIAT (Peter Läderach), who are directly or indirectly involved in the PhD research. Additional household data is provided by the World Bank (LSMS-ISA database), which is publicly available.

    Spatial data and census data are obtained from public sources. Remaining knowledge gaps are filled with data collection activities, such as interviews with key stakeholders performed by the PhD candidate.

    Who's analysing the data

    All analyses will be done by the PhD candidate, with support by ILRI. Assistance will be obtained for spatial statistical analyses from the WUR or ILRI.

    Location short 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: DataModelPaper 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. 
    • Model folder: Complete listing of the model and the model results & analysis.
    • Paper folder: Text of a chapter / paper.  
    • Scripts folder: Contains all scripts used.
    Backup procedure

    The complete content of my local Thesis folder will be stored on the backup server of PPS. 

    During periods I'm abroad, I'll backup the complete content of my local Thesis folder to a Dropbox Thesis folder and share the contents with my supervisor(s). 

    Research data with value for long term storage

    All datasets used for my project, analysis reports, publications, posters.

    Plans for sharing data?

    As far as possible all data will be publically available.

    How to access data once you leave?

    The PhD Library site of PPS: On this location all data for each chapter of my thesis will be stored in a separate zip file.

    Specific funders requirements for sharing data, or to impose embargo?

    No.

    Other parties involved? Agreements on data sharing?

    No.

    Other persons contributing (e.g. writing code)

    M. van Wijk is the contact person for ILRI and will support the data collection from the CCAFS project and the analyses of the household data. The R analysis tool for household food security has been developed by ILRI with M. van Wijk as co-author and he will support the use and further development of this tool for this research (agreements are being made for its use and responsibilities).

     

    Other persons with specific responsibility for data?

    I am responsible for collecting and managing the data used in my research, in consultation with my supervisor. At the end of my PhD project my data will be made publically available online, if possible, and my supervisors will receive a full copy of my data.

    Privacy, security issues? How you deal with them?

    All privacy sensitive data will be excluded from the datasets that will be made publicly available.