Forest ecosystems provide a wide range of goods and services to society and host high levels of biodiversity. Nevertheless, forest ecosystem services (ES) are often quantified and assessed using simplified methodologies (e.g., proxy methods based exclusively on Land Use Land Cover maps) that introduce substantial uncertainty in the analysis by ignoring, for instance, the species composition and spatial configuration of the ecosystems studied. In this work we defined and calculated a set of 12 indicators of several ES for the forests of the highly populated region of Catalonia (North-eastern Iberian Peninsula). The indicators combined different sources of information such as forest surveys, ecological model predictions and official statistics, but also included additional land cover information. All ES indicators were aggregated at the municipality level to compare their values and distribution patterns. We assessed spatial trade-offs and synergies among ES, as well as their relationships with a set of socioeconomic, climatic and biodiversity variables using correlation analyses and mixed-effects models. The results suggest a clustering of provisioning and regulating ES in mountainous zones towards the North of the study area. These two types of services showed a high degree of spatial similarity and presented high positive correlations. In contrast, cultural ES showed a more scattered pattern, which included lower elevation areas in the South of the study region. Climatic conditions were the main determinants of the spatial variability in the supply of the different ES, with most indicators being positively associated with precipitation and negatively associated with temperature. In addition, biodiversity (particularly woody species richness) showed positive relations with most of these ES, while socioeconomic indicators (such as population density and the percentage employment in agriculture) showed negative associations with most of them. The combination of information from different data sources (including primary data) allowed for a detailed analysis of forest ES, likely removing some of the problems derived from approaches based only on proxy methods. In addition, the use of municipalities as study unit makes results directly relevant to management and planning strategies operating at this scale (e.g., forest management and planning).

The implementation of the Ecosystem Services (ES) framework (including supply and demand) should be based on accurate spatial assessments to make it useful for land planning or environmental management. Despite the inherent dependence of ES assessments on the spatial resolution at which they are conducted, the studies analyzing these effects on ES supply and their relationships are still scarce. To study the influence of the spatial level of analysis on ES patterns and on the relationships among different ES, we selected seven indicators representing ES supply and three variables that describe forest cover and biodiversity for Catalonia (NE Iberian Peninsula). These indicators were estimated at three different scales: local, municipality and county. Our results showed differences in the ES patterns among the levels of analysis. The higher levels (municipality/county) removed part of the local heterogeneity of the patterns observed at the local scale, particularly for ES indicators characterized by a finely grained, scattered distribution. The relationships between ES indicators were generally similar at the three levels. However, some negative relationships (potential trade-offs) that were detected at the local level changed to positive (and significant) relationships at municipality and county. Spatial autocorrelation showed similarities between patterns at local and municipality levels, but differences with county level. We conclude that the use of high-resolution spatial data is preferable whenever available, in particular when identifying hotspots or trade-offs/synergies is of primary interest. When the main objective is describing broad patterns of ES, intermediate levels (e.g., municipality) are also adequate, as they conserve many of the properties of assessments conducted at finer scales, allowing the integration of data sources and, usually, being more directly relevant for policy-making. In conclusion, our results warn against the uncritical use of coarse (aggregated) spatial ES data and indicators in strategies for land use planning and forest conservation.

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