Jon Norberg, Dept. Systems Ecology, Div. of Natural Resource Management, Stockholm University, "Agent Perception of Ecological Dynamics and Minimal Models of Social Memory."

Catherine Tucker, Research and Outreach Coordinator, CIPEC, "Chapter 8 of the CIPEC book."

Chandra Giri, Senior Staff Associate, Center for International Earth Science Information Network (CIESIN), Columbia University. "Monitoring of Land Use/Land Cover Change in Continental Southeast Asia."

Land use/land cover change particularly that of tropical deforestation and forest degradation have been occurring at an unprecedented rate and scale in Southeast Asia. The rapid rate of economic development and demographics are believed to be the underlying forces responsible for the change. Accurate and up-to-date information to support the above statement is however, not available. The available data, if any, are outdated and are not comparable for various technical reasons. Time series analysis of land cover changes and identification of driving forces responsible for such changes are needed for the sustainable management of natural resources and also for projecting future land cover trajectories. We analyzed the multi-temporal and multi-seasonal NOAA AVHRR satellite data of 1985/86, and 1992/93 and SPOT VEGETATION data of 1999/2000 to (1) prepare historical land cover maps and (2) to identify areas undergoing major land cover transformations (called "hot spots") in the region. The identified "hot spot" areas were investigated using high-resolution satellite data such as Landsat and SPOT supplemented by intensive field survey. Shifting cultivation, intensification of agricultural activities and change of cropping patterns, and conversion of forest to agricultural land were found to be the principal reasons for land use land cover change in Oudomxay province of Lao P.D.R, Mekong Delta of Vietnam and Loei province of Thailand respectively. Moreover, land use/land cover dynamics of the region and a typical land use/land cover change patterns of the 'hot spot' areas were also examined. We also developed a field-based methodology for land use/land cover change analysis at the national level with the help of national remote sensing institutions.

*Chandra Giri1, Surendra Shrestha2, & Marc Levy1

Building quantitative models to forecast households' responses to environmental changes and to identify suitable policy interventions remains a challenge. An ideal model would incorporate biophysical as well as socio-economic processes and capture the dynamic effects of human decision-making. It should make allowance for the potentially path-dependent feature of adjustment; be capable of exploring the likely impacts of different technology and policy options; and thus generate useful information for policy formulation and analysis. Promising candidates to meet these demands are integrated simulation models based on the multiple-agent systems approach.

A recent attempt to develop and apply such a model was made in Berger (2001). He developed a class of spatially explicit, interacting farm-household models and tested it empirically in Chile. Mathematical programming models for each actor represent the individual choice of a farm-household among available land and water use, consumption, investment and marketing alternatives. Key behavioral responses and constraints of the heterogeneous farm-households are explicitly considered, as are their social and spatial interactions. These inter-household linkages include communication concerning the adoption of technical innovations, allocation of water return-flows and land/water markets. The model's economic and hydrologic components are tightly connected into a spatial grid-based framework. Each cell or pixel has several attributes associated with it such as soil quality, water supply, and land use. The model agents, i.e. the farm-households and non-farm owners, largely determine these attributes over time.

Glen Green, Charlie Schweik and Phil Keating, CIPEC Book, Chapter 4. "Seeing Change with New Eyes: Space, Time, and Remote Sensing."

Joint Forest Management (JFM) in India began its journey from the south-western forests in West Bengal. It took some time for the Forest Department to replicate JFM in the northern, sub-Himalayan regions of the state. The present paper is an attempt to develop a methodology to quantify the level of collective action across the Forest Protection Committees and Eco-Development Committees, as well as among the user groups not covered under JFM from 12 IFRI sites spread across the two sub-Himalayan districts of West Bengal, namely, Jalpaiguri and Darjeeling. The next attempt has been to find out the relationship between the estimated values of collective action and some other variables like:

• heterogeneity within the user groups,

• dbh and height of trees in the forests under use etc.