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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.

Hydrological connectivity describes the physical coupling (linkages) of different elements within a landscape regarding (sub-) surface flows. A firm understanding of hydrological connectivity is important for catchment management applications, for example, habitat and species protection, and for flood resistance and resilience improvement. Thinking about (geomorphological) systems as networks can lead to new insights, which has also been recognized within the scientific community, seeing the recent increase in the use of network (graph) theory within the geosciences. Network theory supports the analysis and understanding of complex systems by providing data structures for modelling objects and their linkages, and a versatile toolbox to quantitatively appraise network structure and properties. The objective of this study was to characterize and quantify overland flow connectivity dynamics on hillslopes in a humid sub-Mediterranean environment by using a combination of high-resolution digital-terrain models, overland flow sensors and a network approach. Results showed that there are significant differences between overland flow connectivity on agricultural areas and semi-natural shrubs areas. Significant positive correlations between connectivity and precipitation characteristics were found. Significant negative correlations between connectivity and soil moisture were found, most likely because of soil water repellency and/or soil surface crusting. The combination of structural networks and dynamic networks for determining potential connectivity and actual connectivity proved a powerful tool for analysing overland flow connectivity.

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

Knowledge about connectivity and what affects it, through space and time, is needed for taking appropriate action at the right place and/or time by stakeholders. Various conceptual frameworks for hydrological and sediment connectivity have been developed in recent years. For most of these frameworks, the objective was to conceptualise connectivity, not necessarily to infer it from measurements. Studies focussing on measurements of connectivity have so far not been done often. Because of lack of data on connectivity, few real-world data have been used in recent connectivity modelling studies. The aim of this study was to demonstrate that existing data can be used to assess governing factors of connectivity, and how these change over time. Data from three catchments in Navarre, Northern Spain, were used to assess factors that influence hydrologic and sediment connectivity. These factors were used as components in a linear model for discharge and suspended-sediment yield. Three components of connectivity were distinguished: topographical, biological and soil. Changes in the topographical component for the studied periods were considered relatively small, and, therefore, kept constant. Changes in the biological component were determined using the Normalised Difference Vegetation Index. Changes in the soil component were assessed using an Antecedent Precipitation Index. Nash-Sutcliffe model efficiency coefficients were between 0·49 through 0·62 for the discharge models and between 0·23 through 0·3 for the sediment-yield models. We recommend applying the model at smaller spatial scales than catchment scale to minimise the lumping of spatial variability in the components.

Natural damming of upland river systems, such as landslide or lava damming, occurs worldwide. Many dams fail shortly after their creation, while other dams are long-lived and therefore have a long-term impact on fluvial and landscape evolution. This long-term impact is still poorly understood and landscape evolution modelling (LEM) can increase our understanding of different aspects of this response. Our objective was to simulate fluvial response to damming, by monitoring sediment redistribution and river profile evolution for a range of geomorphic settings. We used LEM LAPSUS, which calculates runoff erosion and deposition and can deal with non-spurious sinks, such as dam-impounded areas. Because fluvial dynamics under detachment-limited and transport-limited conditions are different, we mimicked these conditions using low and high erodibility settings, respectively. To compare the relative impact of different dam types, we evaluated five scenarios for each landscape condition: one scenario without a dam and four scenarios with dams of increasing erodibility. Results showed that dam-related sediment storage persisted at least until 15 000years for all dam scenarios. Incision and knickpoint retreat occurred faster in the detachment-limited landscape than in the transport-limited landscape. Furthermore, in the transport-limited landscape, knickpoint persistence decreased with increasing dam erodibility. Stream capture occurred only in the transport-limited landscape due to a persisting floodplain behind the dam and headward erosion of adjacent channels. Changes in sediment yield variation due to stream captures did occur but cannot be distinguished from other changes in variation of sediment yield. Comparison of the model results with field examples indicates that the model reproduces several key phenomena of damming response in both transport-limited and detachment-limited landscapes. We conclude that a damming event which occurred 15 000years ago can influence present-day sediment yield, profile evolution and stream patterns. Copyright (c) 2014 John Wiley & Sons, Ltd.

International audience

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