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Wetland shorelines around the world are susceptible to wave erosion. Previous work has suggested that the lateral erosion rate of their cliff-like edges can be predicted as a function of intercepting waves, and yet numerous field studies have shown that other factors, for example, tidal currents or mass wasting of differing soil types, induce a wide range of variability. Our objective was to isolate the unique effects of wave heights, wavelengths, and water depths on lateral erosion rates and then synthesize a mechanistic understanding that can be applied globally. We found a potentially universal relationship, where the lateral erosion rates increase exponentially as waves increase in height but decrease exponentially as waves become longer in length. These findings suggest that wetlands and other sheltered coastlines likely experience outsized quantities of erosion, as compared to oceanic-facing coastlines. 

Abstract The spatial pattern of vegetation patchiness may follow universal characteristic rules when the system is close to critical transitions between alternative states, which improves the anticipation of ecosystem-level state changes which are currently difficult to detect in real systems. However, the spatial patterning of vegetation patches in temperature-driven ecosystems have not been investigated yet. Here, using high-resolution imagery from 1972 to 2013 and a stochastic cellular automata model, we show that in a North American coastal ecosystem where woody plant encroachment has been happening, the size distribution of woody patches follows a power law when the system approaches a critical transition, which is sustained by the local positive feedbacks between vegetation and the surrounding microclimate. Therefore, the observed power law distribution of woody vegetation patchiness may be suggestive of critical transitions associated with temperature-driven woody plant encroachment in coastal and potentially other ecosystems. 

In savannas, predicting how vegetation varies is a longstanding challenge. Spatial patterning in vegetation may structure that variability, mediated by spatial interactions, including competition and facilitation. Here, we use unique high-resolution, spatially extensive data of tree distributions in an African savanna, derived from airborne Light Detection and Ranging (LiDAR), to examine tree-clustering patterns. We show that tree cluster sizes were governed by power laws over two to three orders of magnitude in spatial scale and that the parameters on their distributions were invariant with respect to underlying environment. Concluding that some universal process governs spatial patterns in tree distributions may be premature. However, we can say that, although the tree layer may look unpredictable locally, at scales relevant to prediction in, e.g., global vegetation models, vegetation is instead strongly structured by regular statistical distributions.