Three ideal point-based multi-criteria decision methods (MCDM), i.e., iterative ideal point thresholding (IIPT), compromise programming (CP) and a newly-proposed CP variant, called balanced compromise programming (BCP), were applied to the Tabacay catchment in Ecuador with the aim of finding a distribution of land use types (LUT) that optimizes regional land performance. This performance was expressed in terms of several conflicting on-site ecosystem services (ESS), namely water conservation, soil protection, carbon storage and monetary income. IIPT selects the best performing LUT on a per-land unit basis, that is the assignment of a LUT to a land unit is completely independent with respect to other land units. CP and BCP, on the other hand, aim at optimizing the integrated regional performance. These methods produce a LUT distribution that is as close as possible to the absolute optimal performance that would be achieved when conflict among ESS is not considered. In general, similar results were obtained with CP and BCP. This was not the case when the results produced by these two methods were contrasted with IIPT. For most ESS under consideration, CP and BCP produced balanced results that were closer to the absolute optimal values when compared to IIPT. We conclude from our results that, when optimization of land performance at a regional scale is at stake, CP-derived models emerge as the preferable option over IIPT, especially when balanced solutions are a requirement.

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BIOLP is an Integer Programming model based on the Balanced Compromise Programming multi-criteria decision method. The aim of BIOLP is to determine how a set of land use types should be distributed over space and time in order to optimize the multi-dimensional land performance of a region. Trajectories were defined as the succession of specific land use types over 30 years, assuming that land use changes can only occur at fixed intervals of 10 years. A database that represents the Tabacay catchment (Ecuador) as a set of land units with associated performance values was used as the input for BIOLP, which was then executed to determine the trajectories distribution that optimizes regional performance. The sensitivity of BIOLP to uncertainty in the input data, simulated through random variations on the performance values, was also tested. BIOLP showed a relative stability on its results under these conditions of stochastic, restricted changes. Additionally, the behaviour of BIOLP under different settings of its balancing and relative importance parameters was studied. Stronger variations on the outcomes were observed in this case, which indicate the influential role that such parameters play. Finally, the inclusion of performance thresholds in BIOLP was tested through the addition of sample constraints that required some of the criteria at stake to exceed predefined values. The outcome of the optimization exercises makes clear that the phenomenon of trade off between the provisioning service of the land (income) and the regulation and maintenance services (runoff, sediment, SOC) is crucial. BIOLP succeeds in accounting for this complex multi-dimensional phenomenon when determining the optimal spatio-temporal distributions of land use types. Despite this complexity, it is confirmed that the weights attributed to the provisioning or to the regulation and maintenance services are the main determinants for having the land use distributions dominated by either agriculture or forest.