LC-01 Abstract

Modeling the Scale Dependent Drivers of LCLU Dynamics in Northeastern Ecuador: Simulating Patterns of Landscape Change and Assessing their Cause and Consequence through Multi-Level Models and Cellular Automata

Richard E. Bilsborrow, University of North Carolina (US-PI)
Alicia Ruiz,  CEPAR (SA-PI)
Stephen J. Walsh, University of North Carolina (US-PI)

Using longitudinal household survey data collected in 1990 and 1999, a 2000 community survey, a multi-resolution remote sensing time series, GIS coverage of resource potentials and endowments, and field verification and geodetic control data, we analyze the determinants of changes in LCLU at the plot, sector, and regional levels, and annual and decadal periods. 

The fundamental research questions revolve around (a) the rates, and mechanisms of forest conversion to agricultural and urban uses, (b) the relative importance of exogenous and endogenous variables on these land uses, (c) the associated scale dependant drivers of LCLU dynamics and patterns operating across socio-economic and demographic, biophysical, and geographical domains; (d) rate and pattern of land conversion from forest to agricultural crops, pasture, secondary plant succession, and urbanization, as well as the rate and pattern of land abandonment at the farm level; and (e) plausible scenarios of future land cover change and their policy implications as assessed multi-level models that are responsive to multi-scale effects as well as spatial simulations of LCLU dynamics through a cellular automata approach.

The survey periods and the assembled satellite time-series images serve as our reference dates that are integrated to define relationships through (1) multivariate logit models of LCLU for 1990, 1999, and for changes between those two survey periods; (2) satellite image classifications and change-detections of LULC dynamics, space-time trajectories of pixel histories, and pattern metrics of landscape organization to define LCLU composition and spatial structure; (3) LCLU simulation through cellular automata, informed by the satellite and multivariate models of LCLU change, to create spatial simulations of LULC dynamics; and (4) multi-level models to integrate variables and effects from multiple scales into an integrated model of LCLU dynamics to assess the scale dependence of variable interactions on LCLU patterns. 

The analysis will be framed within a dynamic systems approach that emphasizes non-linear relationships, feedback, mechanisms, and critical thresholds in population-environment interactions. Theoretical foundations include principles involving the interplay of political ecology, human ecology, landscape ecology, and complexity theory.