Mini-CLIP – Nov Case study studies for input to LTM, Mabel, some NPP In Lucid sites with LTM & Mabel: Relative importance of site drivers and “agents” in different periods, how related to LUC patterns and to wider changing economic, tenure, population and war/peace context. (first cut spring 2004, continuing through 2005) Comparisons between sites: compare LU patterns and drivers over time: identify what is common, unique, what common minimum variables are needed to project LUC in other sites, in region (spring to fall 2004) Possible other sites, e.g., Miombo, Mara, Rwanda, Gibe Valley Ethiopia, Eastern DRC: update LU, literature searches for drivers & temporal patterns, and if LC imagery linked to biophysical variables (fall 2004/ spring 2005) Scaling up questions: if/ how/ what patterns and drivers at local scale represent changes at wider scales (with wider land team, uncertainty analysis?: fall 2004)

Mini-CLIP – Nov Other studies input to initial and subsequent LU projections Urbanization study: rates (how vary with economics, population), spatial patterns (of urban cover and von Thunen rings of ag & woodfuel extraction/ planting), projections for E Africa. The rates may be accelerated in periods of climate change or other major tiggers. (summer 2004) Identify past LU and other strategies people have adopted in response to climate related events (drought, floods) and trends through literature review (spring 2005) and in case studies (using met data from Clair for some sites) Examine downscaling & NPP model results of potential distribution of crops, rangelands and natural ecosystems, compare to current distribution, examine results of “extreme” event analysis: identify “hotspots” where current LU systems most vulnerable to projected climate change (2005?)

Mini-CLIP – Nov Role playing simulations: feed into initializing Mabel and LTM, and evaluation of projected LUC Conduct RPS at MSU to finalize method –DJC fall 2004 Conduct RPS in East Africa with rural groups and policy makers to identify agents, drivers, how agents interact & compete to determine LUC, how drivers interact to affect LUC, and how groups may respond to climate change –DJC, Kostas? summer 2005

Mini-CLIP – Nov Expert systems 1: before results of and as inputs to LTM, Mabel, NPP and RCM DJC, JMO (not expert group): Define bookends with initial LTM output of region for use in first-cut sensitivity analysis of RCM –Spring 2004? Expert groups Define broad zones within countries, describe past major drivers (using low-res LCC maps by Lusch, Qi?) Provide idea of major future drivers and patterns within zones, & relative weight of drivers, for future decades Discuss relationship between drivers and available surrogate variables (what captured and not) –Ug or TZ in spring 2004 by JMO with Sam or Yanda; –Kenya and Ug or TZ: summer 2004 with JMO, DJC & Joseph

Mini-CLIP – Nov Expert system 2: following outputs of LTM, Mabel for region Critique LU modeled projection output: –How modeled projections are different from their expectations (of earlier meeting) –What modeled change is not realistic and why –What change is under-represented, whether drivers are missing –2005? JMO with Sam, Yanda, Joseph et al.

Mini-CLIP – Nov Feedback workshops Conduct focus group meetings in rural areas, and with policy makers & scientists, to present project results, ask for feedback and discuss response strategies –Years 3, 4

Mini-CLIP – Nov Links to LTM, Mabel, LC Define bookends with LTM, LC for initial RCM runs Define agents, drivers/ surrogates at case study and at regional levels (Case studies, expert systems, other studies and role playing simulations) Provide zones of expected LU change, drivers, types and rate of expected change (Expert systems) Critique initial and subsequent LU projection model results re spatial pattern, to refine drivers and model structure (Expert systems, key informants, feedback workshops)

Mini-CLIP – Nov Feedback loop from NPP, Biome, downscaling, and then to LU & LC projections: Responses to projected climate change Identify “hotspots” where current LU systems most vulnerable to change due to climate change Identify how people in different areas may respond by changing their land use, migrating, etc. (based on coping strategies studies, expert system input, key informants, RPS, feedback workshops)