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This study aims to characterize at landscape level the spatio-temporal dynamics of a massive oak decline that is occurring in dehesas ecosystems, looking at its possibilities of matching with Phytophthora disease behavior and to interpret its implications within the context of the disease management. Affected spots from 2001, 2009 and 2016 identified through photo interpretation were analyzed with the inhomogeneous Ripley's K function to identify spatial patterns. The relationship between affected/healthy spots with a range of landscape descriptors was investigated via the Multivariate Adaptive Regression Splines (MARS), a non-parametric data mining method. Affected spots showed a strong clustering pattern that decreased over time. The reported spatial patterns align with the hypothesis of Phytophthora cinnamomi Rands being the main cause of oak decline in Mediterranean forests. Affected spots from different years were found to be dependent, suggesting the implication of a contagion process. MARS models from 2001, 2009 and 2016 reported Area Under the Curve (AUC) values of 0.707, 0.671 and 0.651, respectively. Slope

The mountain olive grove is an agroecosystem that, despite low yields and high costs, is recognised for its marked multifunctionality and its significant potential to provide ecosystem services. Due to the close relationship between ecosystem services and human well-being, advancement in the identification and assessment of potential benefits is of great interest. Thus, by using the multi-criteria decision-making technique Analytic Network Process (ANP), this study offers an approach to assessing mountain olive grove ecosystem services provision. Based on three possible scenarios or alternatives, ANP provides data to determine the management system that has the most impact to provide ecosystem services. The results could supply technical data to support policy decision-making for the development of rural areas.