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Following earlier studies across 2115 → 33 m2 scales (Barnes and Laurie, 2018), patchiness of macrobenthic abundance in intertidal Queensland seagrass was assessed by dispersion indices, spatial autocorrelation and hotspot analysis across a hierarchically-nested series of smaller scales (5.75 → 0.09 m2). Overall patterns of distribution and abundance over larger extents and with greater lag were mirrored across these smaller ones. Assemblage abundance per station varied by a factor of >10, but all three approaches showed effective constancy of total assemblage patchiness across all sub-2115 m2 scales (across-scales-mean Lloyd's IP of 1.06 and global Moran's I of 0.13). Equivalent constancy was also shown by most numerically-dominant species (scaling exponent β = 0.93-1.15). Decreasing patchiness of some species with decreasing scale, however, resulted in two no longer being patchily dispersed across small scales. Significant hotspots of abundance occurred at a constant proportion of stations across scales, against a background of randomly scattered peak-abundance points.

Surface elevation dynamics have always responded to disturbance regimes. Creating Digital Elevation Models (DEMs) to detect surface dynamics has led to the development of several methods, devices and data clouds. DEMs can provide accurate and quick results with cost efficiency, in comparison to the inherited geomatics survey techniques. Nowadays, remote sensing datasets have become a primary source to create DEMs, including LiDAR point clouds with GIS analytic tools. However, these data need to be tested for error detection and correction. This paper evaluates various DEMs from different data sources over time for Apple Orchard Island, a coastal site in southeastern Australia, in order to detect surface dynamics. Subsequently, 30 chosen locations were examined in the field to test the error of the DEMs surface detection using high resolution global positioning systems (GPSs). Results show significant surface elevation changes on Apple Orchard Island. Accretion occurred on most of the island while surface elevation loss due to erosion is limited to the northern and southern parts. Concurrently, the projected differential correction and validation method aimed to identify errors in the dataset. The resultant DEMs demonstrated a small error ratio (≤ 3%) from the gathered datasets when compared with the fieldwork survey using RTK-GPS. As modern modelling approaches need to become more effective and accurate, applying several tools to create different DEMs on a multi-temporal scale would allow easy predictions in time-cost-frames with more comprehensive coverage and greater accuracy. With a DEM technique for the eco-geomorphic context, such insights about the ecosystem dynamic detection, at such a coastal intertidal system, would be valuable to assess the accuracy of the predicted eco-geomorphic risk for the conservation management sustainability. Demonstrating this framework to evaluate the historical and current anthropogenic and environmental stressors on coastal surface elevation dynamism could be profitably applied worldwide., {"references":["Aarts, B.G.W. and P.H. Nienhuis, Ecological sustainability and biodiversity. International journal of sustainable development and world ecology, 1999. 6(2): p. 89-102.","Al-Nasrawi, A.K., B.G. Jones, and S.M. Hamylton, GIS-based modelling of vulnerability of coastal wetland ecosystems to environmental changes: Comerong Island, southeastern Australia. Journal of Coastal Research, 2016b(75): p. 75, 33-37.","Alyazichi, Y.M., et al., Risk Assessment of Trace Element Pollution in Gymea Bay, NSW, Australia. 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