View source for Decision support/network analysis of a complex socio-ecosystem in rural Zimbabwe


==Project plan==
''Upcoming schedule''<br>
Meetings in Lecture hall at St. John's unless otherwise noted<br>
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Wednesday June 24th 3-5 pm '''NA''' work on analysis, '''4 pm''' Meet with Mark Newman at SFI<br>
Wednesday June 24th 6-7:30 '''ABM''' Andre and Melissa work on ODE model <br>
Thursday June 25th 10:30-12 pm '''ABM''' Meet with Stephen Guerin to show him ABM<br>
Thursday June 25th 3-5 pm '''ABM''' finish implementing complexifications<br>
Friday June 26th 1:30-3 pm '''NA''' reviewing results so far (possibly finish friday night)<br>

Sunday June 28th 10 am (until done) in library upstairs seminar room '''ALL''' meet to finish analysis and create and practice presentations<br>


Once Sunday 28/Monday 29/Tuesday 30: '''ALL''' Skype with Ken/Abraham to show them the presentations, revise presentations<br>
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Wednesday 31st: '''ALL''' quickly practice presentations one last time<br>

Goal before we leave SFI: most modeling complete, preliminary literature search complete (only finding papers, not yet reading them)<br>
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July: '''ALL''' reading literature/writing literature review<br>
August: '''ALL''' drafting paper, sending to Ken and Abraham and community<br>
September: '''ALL''' revising paper, sending to journal/SFI<br>

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''Past meetings''<br>
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*Tuesday June 23rd 7-11:30 pm '''NA''' work on temporal networks, integrate marriage data<br>
*Monday June 22nd 4:15-5 pm '''NA''' visualize households over family network, try geffe, visualize projections<br>
*Sunday June 21st 6-7 pm '''ABM''' implement easiest complexifications<br>
*Sunday June 22nd 12-2:30 pm '''ALL''' Skype call with collaborators - present ABM and work on complexification, integrate marriage data into network analysis, show network results so far; ''ABM'' discuss next complexifications to undertake<br>
*Friday June 19th 4:15-5 pm and dinner/after dinner '''NA''' more network analysis, discussing different network structures to address questions<br>
*Friday June 19th 10:45-12 '''ABM''' Andre and Melissa meet with Josh at 10:45 to talk about differential equation model, all work on scenarios to show Ken/Abraham on Sunday<br>
*Thursday June 18th 4:15-5 pm '''ABM''' continue to code in NetLogo<br>
*Thursday June 18th 1:30-3 pm '''ABM''' coding in NetLogo<br>
*Wednesday June 17th afternoon Andre and Melissa work on diffeq<br>
*Tuesday June 16th afternoon Melissa and Kleber finish UML diagrams, Melissa and Andre work on diffeq, Melissa and Chao look at network diagrams, '''ALL''' meet with Josh <br>
*Monday June 15th 9:30-10:30 pm Skype with collaborators, '''ALL''' check simple ABM structure, ask questions about network data<br>
*Monday June 15th 3-5:30 pm '''NA''' working on first network diagrams/analysis<br>
*Sunday June 14th 8-11:30 am '''ABM''' diagramming out simple model<br>
*Friday June 12th after lunch (1:30 pm) '''ABM''' Juan shows how to do UML <br>
*Friday June 12th at 10:45 at SFI conference room '''ALL''' to Skype with collaborators from community<br>
*Thursday June 11th at 9 am/4:15 in the Senior Commons Room, '''ALL''' further discussion about system and models<br>
*Wednesday June 10th at 10:45 am in the Senior Commons Room, '''ALL''' discussing who is interested in which models<br>

==Participants and Tasks==
''Agent-based model''<br>
*Sola: literature collection, literature review<br>
*Kleber: initial NetLogo programming, literature review<br>
*Melissa: differential equation model, advice on UML/design, administrative, literature review<br>
*Andre: advice on UML/design, differential equation model<br>
*Juan: advice on NetLogo programming, UML/design, application as decision tool/game<br>
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''Network Analysis''<br>
*Chao: initial network analysis in NetworkX, literature review<br>
*Haitao: literature collection, literature review<br>
*Melissa: advice on model design, literature review, administrative<br>
*Masa: potential comparison with R network packages<br>
*Carolina/Junming: advice on Newtork Analysis (multilayer, multiplex, dynamic networks)

==Project Description==

''Context''
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Many communities in Africa have been surprisingly resilient in the face of a host of devastating challenges. The people of Mazvihwa Communal Area in Zimbabwe have lived through more than a century of rapid change through the colonial, liberation war, and post-colonial periods. There have been dramatic changes in public health (ranging from better control of communicable diseases after World War II, to child vaccination programs after independence, to the AIDS pandemic especially from the mid-1990s to the end of the 2000s) and in land access and use (with repeated removals, resistance, and returns of communities to land designated for white settlement). These shifts in population distribution have interacted with rapid natural increase in population (especially in the period 1950-1990) driven by high fertility and declining mortality; followed by recent decades of declining fertility and high AIDS-related mortality.  Differences in religious beliefs mean that these changes are uneven across households and areas. The country's economy has meanwhile gone through a series of long cycles of boom and busts, and during the 2000s experienced inflation reaching a billion billion billion per cent.
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The Muonde Trust is a Zimbabwean non-governmental organization established to help support the community in Mazvihwa to continue developing and deploying bottom-up solutions in response to these challenges. Mazvihwa has a semi-arid subtropical climate with remnant woodlands and a combination of largely subsistence agriculture and livestock production. From the point of view of most of the people in Mazvihwa, and as taken up by the community network of the Muonde Trust, the “sustainability” of their area now requires a series of linked changes in land use and investments in natural capital.
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''Data and Questions''
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The data we have on this community and ecosystem originates from an ongoing community-based participatory research project originally begun in the 1980s and since continued by the Muonde Trust. It includes robust quantitative data on human demography, health, nutrition, agricultural practices, rainfall, land use choices, woodland dynamics, household assets, and land tenure. Our goal at SFI is to develop theoretical or simulation studies which would help us to better understand the resilience and sustainability of this system, which would eventually be informed by the data. Questions we might address using complex systems methods include:
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1) How do individuals and resources flow through households and communities?  (Empirical data shows that the composition of households changes rapidly, even though most analyses of these societies tends to assume they are static and natural units of analysis).  It is clear that individuals are variously strategizing through households as well as within other kin, religious and clan groups.  At the same time households also have emergent properties.  In contexts of rapidly shifting demography and changing resource access, are there ways that we can use network analysis to illuminate these complexities?  
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2) How best can community as a whole allocate their land to agriculture, pasture, and woodland when these components interact and feedback to each other? One of the main land-use decisions facing the community is the trade-off between agricultural cultivation (which requires fencing to keep out livestock as well as water harvesting techniques) and retaining woodland areas that have cultural value as well as providing grazing space and forage for livestock (and many other economic benefits). This relationship is complex, with livestock providing benefits to agriculture (manure for fertilizer and draft power for cultivation), and vice versa (well-tended fields provide considerable feed for livestock). The community derives benefits from all these land uses, including food for subsistence from agriculture, meat and milk from livestock, and cultural values and a wide variety of benefits from woodland (including fuelwood, construction materials, a variety of foods and medicines, and improved soil characteristics). In addition, community members may sell livestock, as well as using them for bridewealth and compensation in the case of some deaths. How can this system be represented and manipulated in a model to create optimal strategies for the well-being of the system?
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''Possible methods''
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Our methodology is open to what we learn during the summer school, but some ideas include: network analysis to study the way people and resources connect and flow through the households and other components of the system; an analytical mathematical model of the interacting components of the system, e.g. coupled differential equations; cellular automata which can represent the land use category of each part of a farmer's land and underlie a decision support tool.
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Contact: mveitzel@ucsc.edu