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Prediction of ecosystem response to global environmental change is a pressing scientific challenge of major societal relevance. Many ecosystems display nonlinear responses to environmental change, and may even undergo practically irreversible ‘regime shifts’ that initiate ecosystem collapse. Recently, early warning signals based on spatiotemporal metrics have been proposed for the identification of impending regime shifts. The rapidly increasing availability of remotely sensed data provides excellent opportunities to apply such model‐based spatial early warning signals in the real world, to assess ecosystem resilience and identify impending regime shifts induced by global change. Such information would allow land‐managers and policy makers to interfere and avoid catastrophic shifts, but also to induce regime shifts that move ecosystems to a desired state. Here, we show that the application of spatial early warning signals in real‐world landscapes presents unique and unexpected challenges, and may result in misleading conclusions when employed without careful consideration of the spatial data and processes at hand. We identify key practical and theoretical issues and provide guidelines for applying spatial early warning signals in heterogeneous, real‐world landscapes based on literature review and examples from real‐world data. Major identified issues include (1) spatial heterogeneity in real‐world landscapes may enhance reversibility of regime shifts and boost landscape‐level resilience to environmental change (2) ecosystem states are often difficult to define, while these definitions have great impact on spatial early warning signals and (3) spatial environmental variability and socio‐economic factors may affect spatial patterns, spatial early warning signals and associated regime shift predictions. We propose a novel framework, shifting from an ecosystem perspective towards a landscape approach. The framework can be used to identify conditions under which resilience assessment with spatial remotely sensed data may be successful, to support well‐informed application of spatial early warning signals, and to improve predictions of ecosystem responses to global environmental change., Ongoing global change steadily increases pressure on ecosystems, to the point where a small additional change may cause a sudden ecosystem state shift and drastically modify ecosystem functioning. Predicting such generally undesired ‘regime shifts’ is crucial for timely management intervention. A promising prediction method is the translation of spatial vegetation patterns observed with, for example, satellite imagery into ecosystem resilience indicators. While these spatial indicators perform well in theory, we show how application to real‐world landscapes presents unexpected challenges and may even lead to misleading conclusions. Our study identifies the conditions for successful application of spatial indicators to real‐world landscapes.

Combining field reconstruction and landscape evolution modelling can be useful to investigate the relative role of different drivers on catchment response. The Geren Catchment (~45 km2) in western Turkey is suitable for such a study, as it has been influenced by uplift, climate change and lava damming. Four Middle Pleistocene lava flows (40Ar/39Ar- dated from 310 to 175 ka) filled and dammed the Gediz River at the Gediz–Geren confluence, resulting in base-level fluctuations of the otherwise uplift-driven incising river. Field reconstruction and luminescence dating suggest fluvial terraces in the Geren Catchment are capped by Middle Pleistocene aggradational fills. This showed that incision of the Geren trunk stream has been delayed until the end of MIS 5. Subsequently, the catchment has responded to base-level lowering since MIS 4 by 30 m of stepped net incision. Field reconstruction left us with uncertainty on the main drivers of terrace formation. Therefore, we used landscape evolution modelling to investigate catchment response to three scenarios of base-level change: (i) uplift with climate change (rainfall and vegetation based on arboreal pollen); (ii) uplift, climate change and short-lived damming events; (iii) uplift, climate and long-lived damming events. Outputs were evaluated for erosion–aggradation evolution in trunk streams at two different distances from the catchment outlet. Climate influences erosion–aggradation activity in the catchment, although internal feedbacks influence timing and magnitude. Furthermore, lava damming events partly control if and where these climate-driven aggradations occur. Damming thus leaves a legacy on current landscape evolution. Catchment response to long-duration damming events corresponds best with field reconstruction and dating. The combination of climate and base level explains a significant part of the landscape evolution history of the Geren Catchment. By combining model results with fieldwork, additional conclusions on landscape evolution could be drawn

International audience; Land-use changes (LUCs) can be defined as the result of the direct action of the stakeholders in a particular area and natural or human driving forces. LUCs can influence various processes within the landscape and can have an impact on landscape functions. An analysis of the impact of LUCs on landscape processes can help to focus future rural policies. LUCs in Mediterranean areas particularly affect landscape functions because of their agro-pedoclimatical characteristics. The aims of this work are as follows: (i) to characterise LUCs in the last 11years in a typical Mediterranean area, the Trasubbie river basin (southern Tuscany, Italy); (ii) to extrapolate these changes and create spatially explicit LUC scenarios for the near future; and (iii) to simulate how and where the predicted LUCs may affect soil redistribution. We carried out an analysis of LUCs within the study area and used the trends to propose alternative scenarios for 2013. For these years, we spatially allocated land use (using the Conversions of Land Use and its Effects model) and used a landscape process model (landscape process modelling at multi-dimensions and scales) to assess soil redistribution patterns. Land use in the study area changed almost linearly between 1996 and 2007, with cereals and annual fodder crops decreasing, and vineyards, perennial pastures and land abandonment increasing. Our LUC scenario extrapolates these dynamics to make predictions for 2013. A comparison of LAPSUS results between LUC and baseline scenarios for 2013 showed an increase in terms of net soil loss and total erosion, and a decrease in terms of sediment delivery ratio