A complex systems approach to dynamic spatial simulation modeling: LandUse and LandCover change in the Ecuadorian Amazon

The Ecuadorian Amazon, lying in the headwaters of the Napo and Aguarico River valleys, is experiencing rapid change in LandUse and LandCover (LULC) conditions and regional landscape diversity uniquely tied to spontaneous agricultural colonization and oil exploration. Beginning in the early 1970s, spontaneous colonization occurred on squattered lands located adjacent to oil company roads and in government development sectors composed of multiple 50 ha land parcels organized into “piano key” shaped family farms or fincas. Since fincas are managed at the household level as spatially discrete, temporally independent units, land conversion at the finca-level is recognized as the chief proximate cause of deforestation within the region. Focusing on the spatial and temporal dynamics of deforestation, agricultural extensification, and plant succession at the finca-level, and urbanization at the community-level, cell-based morphogenetic models of LandUse and LandCover Change (LULCC) were developed as the foundation for predictive models of regional LULCC dynamics and landscape diversity.; Two cellular automata models were developed and used to integrate biophysical, geographical, and social variables to characterize temporally dynamic landscapes. The human, geographical, and biophysical dimensions of land use and land cover change were examined, specifically deforestation, anthropogenic extensification, and reforestation. Remotely-sensed data ranging temporally from the 1970s through 1999, combined with thematic map coverages of biophysical gradients and geographical accessibility, were linked to household and community survey data collected in 1990 and 1999. Image processing techniques for LULC characterization and spatial analyses of landscape structure were used to assess the rate and nature of LULCC throughout the time-series. In addition, LULC and LULCC associated with secondary plant succession and agricultural extensification were assessed and simulated for specific landscape strata and study area locations related to development corridors along transportation networks and expanding urban environments. The presented research combines household survey data with biophysical and geographical data through a spatio-temporal modeling context that links complexity theory and landscape ecology to a GIS and remote sensing analytical framework to increase the understanding of landscape dynamics across time, space, and landscape strata.