Using agent-based modelling and landscape metrics to assess landscape fragmentation in Iskandar Malaysia

Aliyu Salisu Barau, Salman Qureshi
2015 Ecological Processes  
Special economic zones (SEZs) emerge as new forces driving Asian economic transformation and triggering rapid landscape fragmentation. It is imperative to map out the present and future spatial patterns of SEZs in order to understand how they undermine sustainability. Drawing from the experience of Iskandar Malaysia, one of the most successful SEZs in Southeast Asia, this study measures how biophysical and cultural landscapes are being affected by the most recent accelerated land development in
more » ... land development in the area. Methods: With aid of a hybrid model, namely the special economic zone landscape fragmentation measurement (SeLaFragment), which combines Geographic Information System (GIS), FRAGSTATS and NetLogo, the current and future fragmentation dynamics were analysed using land use data of the study area from the beginning of intensive landscape transformation in 2007 until 2010. Iskandar Malaysia's cultural and biophysical landscapes were extensively fragmented. Results: The analysis showed that urban built-up areas increased from 13% in 2006 to 24% in 2010. Mangrove swamps were the worst affected ecosystem as they lost 20% of their areal coverage between 2006 and 2010. The simulation of the future scenarios suggested that, in the future, fragmentation and landscape homogenisation will intensify and pose more risks to landscape quality, functions and socio-ecological services. Conclusions: It is obvious that rapid landscape fragmentation compromises sustainability of a wide range of ecosystems and their functions and services in and around urban areas. It is difficult to see how existing environmental strategies have been effective in addressing the emerging sustainability challenges of rapid landscape change. The best way to respond to this kind of situation in the SEZs is by focusing on holistic approach to landscape sustainability.
doi:10.1186/s13717-015-0033-1 fatcat:oygt3hxdwrahdbc5tjo72eguq4