Land Use and Cover Change Modeling as an Integration Framework: A Mixed Methods Approach for the Southern Coast of Jalisco (Western Mexico)

The rapid loss of forests with negative consequences for biodiversity and ecosystem services has drawn the attention of scientists and decision makers to deforestation and land use change. Over the last two decades, a broad range of models of land use and cover change (LUCC) have been developed to assist in land management and to better understand, evaluate and project the future role of LUCC. Pattern-based LUCC models are empirical approaches based on the observation of past LUCC, including the spatial dimension of change patterns from which the underlying behavior can be inferred, through the statistical relationships of model parameters. Even though these models present a number of drawbacks such as data intensity and limited capacity to connect to other driver scales, they offer a framework to integrate data from multiple disciplines. In this chapter, we present a case study that shows land use and cover change modeling as an integrative framework for cross-referencing among different data sources. Spatial information on LUCC, econometric models and stakeholder perceptions were generated in an interdisciplinary working group in order to obtain insights into LUCC at the regional level. Land use and cover (LUC) maps were the starting point for the spatial analyses of historic changes, which together with ancillary data were used to establish change probabilities for the main change processes. Econometric models showed historic tendencies of agricultural production and a panel analysis clarified the relation between variables. Local stakeholder perception gave the historic background and participatory fuzzy cognitive maps shed light on the underlying drivers of change. By cross-referencing the different data sources, we show that for this particular region the official LUC maps do capture the main change processes. Both local stakeholder perceptions and econometric models confirm deforestation and agricultural expansion, especially livestock farming, as the main processes. The econometric models confirm the difference in magnitude between the large growth in areas for livestock farming and much more restricted growth of agricultural areas and show that beef production and pasture for cattle ranching is displacing the production of maize and beans. As regards the drivers of change, the different data sources complement each other quite well as they cover different scales: the stakeholder elicitations revealed a set of indirect drivers related to the direct drivers identified in the spatial analysis of historic change. The indirect drivers included the political, social, cultural and economic forces behind agricultural expansion, especially cattle ranching. The analysis of the spatial factors related to change showed that a large array of variables play a role in LUCC. The mixed method approach is helpful in unravelling the different levels of connection between drivers.