Abstract
Fluvial disturbances, especially floods and droughts, are the main drivers of the successional patterns of riparian vegetation. Those disturbances control the riparian landscape dynamics through the direct interaction between flow and vegetation. The main aim of this work is to investigate the specific paths by which fluvial disturbances, distributed by its components of groundwater hydrology (grndh) and morphodynamic disturbance (mrphd), drive riparian landscape patterns as characterized by the location (position in the river corridor) and shape (physical form of the patch) of vegetation patches in Mediterranean rivers. Specifically, this work assesses how the different components of fluvial disturbances affect these features in general and particularly in each succession phase of riparian vegetation. grndh and mrphd were defined by time and intensity weighted indexes calculated, respectively, from the mean annual water table elevations and the annual maximum instantaneous discharge shear stresses of the previous decade. The interactions between riparian landscape features and fluvial disturbances were assessed by confirmatory factor analysis using structural equation modeling. Two hypothetical models for patch location and shape were conceptualized and tested against empirical data collected from 220 patches at four different study sites. Both models were successfully fitted, meaning that they adequately depicted the relationships between the variables. Furthermore, the models achieved a good adjustment for the observed data, based on the evaluation of several approximate fit indexes. The patch location model explained approximately 80% of the patch location variability, demonstrating that the location of the riparian patches is primarily driven by grndh, while the mrphd had very little effect on this feature. In a multigroup analysis regarding the succession phases of riparian vegetation, the fitted model explained more than 68% of the variance of the data, confirming the results of the general model. The patch shape model explained nearly 13% of the patch shape variability, in which the disturbances came to have less influence on driving this feature. However, grndh continues to be the primary driver of riparian vegetation between the two disturbance factors, despite the proportional increase of the mrphd effect to approximately a third of the grndh effect.
Highlights
Riparian ecosystems are dynamic systems found in flood-prone areas along rivers
This determines a physiological effect by water stress control on plant growth and survival, affecting species differently according to their greater or Abbreviations: CFI, comparative fit index; EF, established forest phase; ES, early successional woodland phase; Goodness of Fit Index (GFI), goodness of fit index; grndh, groundwater hydrology; GWDi, groundwater depth index; IP, initial phase; ku, kurtosis; MDi, morphodynamic disturbance index; MPFD, mean patch fractal dimension; mrphd, morphodynamic disturbance; PERIMTR, perimeter; phslc, patches location; phssh, patches shape; PP, pioneer phase; Root Mean Square Error of Approximation (RMSEA), root mean square error of approximation; SEM, structural equation modeling; sk, skewness; SRMR, standardized root mean square residual; THAD, distance to thalweg; the study sites were characterized by height (THAH), height to thalweg; TLI, Tucker-Lewis Index; VIF, variance inflation factor
This study aimed to investigate the effect of fluvial disturbances on two central elements of landscape ecology, the location and shape of riparian vegetation patches
Summary
Riparian ecosystems are dynamic systems found in flood-prone areas along rivers. They represent the transition between the aquatic and terrestrial ecosystems (Naiman and Décamps, 1997) and play a decisive role in riverine integrity (Van Looy et al, 2013). It fluctuates in the form of flood pulses (Junk et al, 1989) according to the hydraulic and hydrologic characteristics of the river This effects the succession dynamics of riparian vegetation both physically and physiologically (Blom and Voesenek, 1996; Poff et al, 1997; Kozlowski, 2002; Džubáková et al, 2015) due to flood-induced stress through vegetation entrainment, uprooting, burial or anoxia (e.g., Friedman and Auble, 1999; Bendix and Hupp, 2000; Edmaier et al, 2011; Bendix and Stella, 2013). This determines a physiological effect by water stress control on plant growth and survival, affecting species differently according to their greater or Abbreviations: CFI, comparative fit index; EF, established forest phase; ES, early successional woodland phase; GFI, goodness of fit index; grndh, groundwater hydrology; GWDi, groundwater depth index; IP, initial phase; ku, kurtosis; MDi, morphodynamic disturbance index; MPFD, mean patch fractal dimension; mrphd, morphodynamic disturbance; PERIMTR, perimeter; phslc, patches location; phssh, patches shape; PP, pioneer phase; RMSEA, root mean square error of approximation; SEM, structural equation modeling; sk, skewness; SRMR, standardized root mean square residual; THAD, distance to thalweg; THAH, height to thalweg; TLI, Tucker-Lewis Index; VIF, variance inflation factor
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