Mountain landscapes provide multiple ecosystem services that are continually vulnerable to land-change. These complex variations over space and time need to be clustered and explained to develop efficient and sustainable land management processes. We completed a spatiotemporal analysis that describes how different patterns of 6 land-change dynamics impact on the supply of 7 ecosystem services over a period of 13 years and across 25 provinces in the central high-Andean Puna of Peru. The appraisal describes: (1) how clusters of land-change dynamics are linked to ecosystem service bundles; (2) which are the dominant land-change dynamics that influence changes in ecosystem service bundles and (3) how multiple ecosystem service provision and relationships vary over space and time. Our analysis addressed agricultural intensification, agricultural de-intensification, natural processes and deforestation as the most critical land-change dynamics across the central high-Andean region over time. Our results show that most of the provinces were mainly described by a small set of land-change dynamics that configured four types of ecosystem service bundles. Moreover, our study demonstrated that different patterns of land-change dynamics can have the same influence on the ecosystem service bundle development, and transformation of large areas are not necessarily equivalent to high variations in ecosystem service supply. Overall, this study provides an approach to facilitate the incorporation of ES at multiple scales allowing an easy interpretation of the region development that can contribute to land management actions and policy decisions.

The understanding of relationships between ecosystem services and the appropriate spatial scales for their analysis and characterization represent opportunities for sustainable land management. Bundles have appeared as an integrated method to assess and visualize consistent associations among multiple ecosystem services. Most of the bundle assessments focused on a static framework at a specific spatial scale. Here, we addressed the effects of applying two cluster analyses (static and dynamic) for assessing bundles of ecosystem services across four different scales of observation (two administrative boundaries and two sizes of grids) over 13 years (from 2000 to 2013). We used the ecosystem services matrix to model and map the potential supply of seven ecosystem services in a case study system in the central high-Andean Puna of Peru. We developed a sensitivity analysis to test the robustness of the matrix. The differences between the configuration, spatial patterns, and historical trajectories of bundles were measured and compared. We focused on two hypotheses: first, bundles of ecosystem services are mainly affected by the method applied for assessing them; second, these bundles are influenced by the scale of observation over time. For the first hypothesis, the results suggested that the selection of a method for assessing bundles have inferences on the interactions with land-use change. The diverse implications to management on ecosystem services support that static and dynamic assessments can be complementary to obtain better contributions for decision-making. For the second hypothesis, our study showed that municipality and grid-scales kept similar sensitivity in capturing the aspects of ecosystem service bundles. Then, in favorable research conditions, we recommend the combination of a municipal and a fine-grid scale to assure robustness and successfully land-use planning processes.