Cocoa and coffee agroforestry on hillslopes: agroecology and farmer management options

Submitted by rika.ratnasari on
    Organizational Context
    Name
    Rika Ratna Sari
    Chairgroup
    Plant Production System (PPS)
    Graduate school
    Production Ecology and Resource Conservation (PE&RC)
    Start date of project
    Abstract

    Simultaneously achieving policy goals on climate change, biodiversity, productivity and farmer income is highly desirable at the farm/forest interface. Development pathways to bridge ecological and socioeconomic objectives have become important challenges in the agricultural sector. Perspectives differ on the role the diversity of agroforests plays in sustaining ecological benefits and smallholder livelihoods. As the top five largest coffee and cocoa producer in the world, Indonesia contributes to the growing global demand for both, mostly through smallholder production in agroforestry systems using various shade trees, with limited use of inputs such as fertilizer. Tree diversity in agroforestry systems can maintain ecosystem functions that forests generally provide, through maintaining lower temperatures and higher humidity, providing various types of organic matter input, maintaining soil carbon stocks, nutrient cycles, and the hydrological cycle. This research aims to evaluate the aboveground characteristics in cocoa and coffee-based agroforestry in relation to land management and farmer preferences for companion trees. Study sites in Southeast Sulawesi and East Java provided low-to-medium and high human population density examples. Tree composition, diversity, and carbon stocks were measured. Surface litter residence times and decomposition rates were compared to those in secondary forest to evaluate soil protection and recycling. Litter quality, microclimate and ‘home-field advantage’ could be identified as interacting factors. A ‘natural experiment’ of volcanic ash deposition provided a resilience test for the farmers, the trees and the agroforestry systems. Serious games will provide a pathway to participatory scenario analysis of the management options available and their likely farm and the consequences for sustainability.

    Role supervisor

    Prof. Meine van Noordwijk (WUR and ICRAF) is the promotor and overall supervisor of the PhD candidate. Dr. Danae Rozendaal is the daily supervisor from WUR for the whole PhD project. Whereas, Prof. Kurniatun Hairiah is the daily field supervisor from Brawijaya University (UB), Indonesia when the PhD student stay in Indonesia for data collection. She is involved in the chapter 1 to 3 of the Thesis which focus on the agroecology part of agroforestry systems. Dr. Erika Speelman is involved in thematic research particularly on the development of participatory approach of serious game about farmer management options in chapter 4.

    Who's collecting the data

    Most of the data was collected by the PhD candidate together with colleagues and students from some institutions.

    Data collection for chapter 1 and 2 in Southeast Sulawesi, Indonesia during 2 years of fieldwork was performed in collaboration with Danny Dwi Saputra (PhD candidate from PPS) since we share the research location and was funded under the same research project from World Agroforestry Centre/ICRAF Southeast Asia region (Indonesia) through AgFor project.

    The research data for chapter 3 was collected in East Java, Indonesia together with colleagues from WUR (Danny Dwi Saputra), research group of Tropical Agroforestry, Brawijaya University (UB) and students from UB. This research works was funded by Brawijaya University through PUPT, HPP, and BOPTN scheme and Directorate General of Resources for Science, Technology and Higher Education, Indonesia. For this chapter we will compare this data with previous research data collected by Dr. Rosyida Priyadarsini (UPN University, Surabaya, East Java, Indonesia) in 2006.

    Data collection for chapter 4 was collected together with two PhD candidates from Forest Ecology and Management (FEM) group (Lisa Tanika and Arief L Hakim) and enumerators. This research activities were funded by Directorate General of Resources for Science, Technology and Higher Education, Indonesia and INREF, Wageningen University and Research under the SESAM project.

    Who's analysing the data

    The data will be analysed by PhD candidate with assistance from supervisors and colleagues.

    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 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). 

    Research data with value for long term storage

    Datasets, scripts, photos, posters and publications might be stored for long term storage.

    Research data excluded for long term storage. Why?

    Data collected by different institution that is used in my research project will be excluded from long term storage. Clear agreements for long term storage will be discussed and made with the data owner under confidentially agreements.

    Plans for sharing data?

    All data and outputs might consider to be publicly available when possible. In this case, it should be in line with the regulation of institution which provide the funding. However, some data will remain in ownership of the institution who collected and funded the research data.

    How to access data once you leave?

    Data will be stored in Yoda drive and PhD library (when possible). These data will be shared with all supervisors and (related) collaborator. In the case of restricted/unpublished data that cannot access openly, there will be a contact person for requesting access to those data.

    Other parties involved? Agreements on data sharing?

    All data collected and outputs generated within the PhD project are mostly in collaboration with join responsibility of PhD candidate (WUR) with partners (Brawijaya University, ICRAF, and UPN University).

    Other persons contributing (e.g. writing code)

    Danny Dwi Saputra (PhD candidate from PPS) is the contributor for Chapter 1 and 2 by providing detailed data of soil organic carbon and involving in some data analysis. Dr. Rosyida Priyadarsini is the contributor from UPN University for Chapter 3 by providing/sharing her research data for comparison study. Lisa Tanika and Arief L Hakim (PhS candidate from FEM) is the contributor for Chapter 4.

    Other persons with specific responsibility for data?

    Dr. Rosyida Priyadarsini (UPN University) is the data owner of floristic and decomposition study in 2007, which is used in the Chapter 3 of the Thesis for comparison study.

    Privacy, security issues? How you deal with them?

    All privacy-sensitive data will be excluded from the datasets prior to storing/sharing/publishing.