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Library Representing large-scale land acquisitions in land use change scenarios for the Lao PDR

Representing large-scale land acquisitions in land use change scenarios for the Lao PDR

Representing large-scale land acquisitions in land use change scenarios for the Lao PDR

Resource information

Date of publication
december 2018
Resource Language
ISBN / Resource ID
MLRF:2661
Pages
1857-1869

Agricultural large-scale land acquisition (LSLA) is a process that is currently not captured by land change models. We present a novel land change modeling approach that includes processes governing LSLAs and simulates their interactions with other land systems. LSLAs differ from other land change processes in two ways: (1) their changes affect hundreds to thousands of contiguous hectares at a time, far surpassing other land change processes, e.g., smallholder agriculture, and (2) as policy makers value LSLA as desirable or undesirable, their agency significantly affects LSLA occurrence. To represent these characteristics in a land change model, we allocate LSLAs as multi-cell patches to represent them at scale while preserving detail in the representation of other dynamics. Moreover, LSLA land systems are characterized to respond to an explicit political demand for LSLA effects, in addition to a demand for various agricultural commodities. The model is applied to simulate land change in Laos until 2030, using three contrasting scenarios: (1) a target to quadruple the area of LSLA, (2) a moratorium for new LSLA, and (3) no target for LSLA. Scenarios yield drastically different land change trajectories despite having similar demands for agricultural commodities. A high level of LSLA impedes smallholders’ engagement with rubber or cash crops, while a moratorium on LSLA results in increased smallholder involvement in cash cropping and rubber production. This model goes beyond existing land change models by capturing the heterogeneity of scales of land change processes and the competition between different land users instigated by LSLA.

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