In recent years, parallel developments in disparate disciplines have focused on what has come to be termed connectivity; a concept used in understanding and describing complex systems. Conceptualisations and operationalisations of connectivity have evolved largely within their disciplinary boundaries, yet similarities in this concept and its application among disciplines are evident. However, any implementation of the concept of connectivity carries with it both ontological and epistemological constraints, which leads us to ask if there is one type or set of approach(es) to connectivity that might be applied to all disciplines. In this review we explore four ontological and epistemological challenges in using connectivity to understand complex systems from the standpoint of widely different disciplines. These are: (i) defining the fundamental unit for the study of connectivity; (ii) separating structural connectivity from functional connectivity; (iii) understanding emergent behaviour; and (iv) measuring connectivity. We draw upon discipline-specific insights from Computational Neuroscience, Ecology, Geomorphology, Neuroscience, Social Network Science and Systems Biology to explore the use of connectivity among these disciplines. We evaluate how a connectivity-based approach has generated new understanding of structural-functional relationships that characterise complex systems and propose a ‘common toolbox’ underpinned by network-based approaches that can advance connectivity studies by overcoming existing constraints.
Connectivity relates to the coupling of landforms (e.g. hillslopes and channels) and the transfer of water and sediment between them. The degree to which parts of a catchment are connected depends largely on the morphological complexity of the catchment's landscape. Landscapes can have very different and distinct morphologies, such as terraces, V‐shaped valleys or broad floodplains. The objective of this study is to better understand and quantify the relation between landscape complexity and catchment connectivity. We hypothesize that connectivity decreases with increasing landscape morphological complexity. To quantify the connectivity–complexity relationship virtual digital elevation models (DEMs) with distinct morphologies were used as inputs into the landscape evolution model LAPSUS to simulate the sediment connectivity of each landscape. Additionally, the hypothesis was tested on six common real DEMs with widely different morphologies. Finally, the effects of different rainfall time series on catchment response were explored. Simulation results confirm the hypothesis and quantify the non‐linear relation. Results from the exploration of sediment connectivity in response to sequences of rainfall events indicate that feedback between erosion and deposition are more important for certain landscape morphologies than for others: for a given rainfall input, a more effective sediment connectivity and erosion response may be expected from rolling or V‐shaped catchments than from dissected or stepped landscapes. Awareness of the differences in the behaviour and response of different morphologies to catchment processes provides valuable information for the effective management of landscapes and ecosystems through efficiently designed soil and water conservation measures. Copyright © 2013 John Wiley & Sons, Ltd.
ABSTRACT. Soil erosion from agricultural areas is a large problem, because of off-site effects like the rapid filling of reservoirs. To mitigate the problem of sediments from agricultural areas reaching the channel, reservoirs and other surface waters, it is important to understand hillslope-channel connectivity
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. Figure 4. Structural networks for all three years, with 2014 being subdivided in an east (with shrubs) and a west (only agriculture) part. The insets show the networks on the hillslope with their corresponding contributing areas 214 R. J. H. MASSELINK ET AL.
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