Microscale dispersion of intertidal seagrass macrofauna.

Previous studies of dispersion of intertidal seagrass-associated macrobenthos in subtropical Moreton Bay, Queensland, showed that patchiness characterised its assemblage abundance with scale-invariant magnitude across areas ranging from >8000 to 0.1 m2. Those studies were here continued across the smaller scales (down to 0.014 m2) arguably more relevant to the dominant 2-10 mm long animals, using 16 replicate blocks of 5x5 contiguous 0.0024 m2 cores nested within the previously studied site. At microscales ≥0.09 m2, the earlier congruence of conclusions derived from patchiness indices and spatial autocorrelation broke down. At >0.014 m2, adjacent points (cores) no longer together formed larger spatial units of related abundance (i.e. showed no autocorrelation), but point abundances were still highly disparate (as reflected in patchiness indices). Congruent indications of patchiness only manifested at 0.014 m2 spatial scales. Assemblage dispersion pattern was partly consequent on one microgastropod (Pseudoliotia) occurring superabundantly in scattered 0.0024 m2 hotspots.

Isometric scaling of faunal patchiness: Seagrass macrobenthic abundance across small spatial scales.

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 ß = 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.

An assessment of anthropogenic and climatic stressors on estuaries using a spatio-temporal GIS-modelling approach for sustainability: Towamba estuary, southeastern Australia.

Monitoring estuarine ecological-geomorphological dynamics has become a crucial aspect of studying the impacts of climate change and worldwide infrastructure development in coastal zones. Together, these factors have changed the natural eco-geomorphic processes that affect estuarine regimes and comprehensive modelling of coastal resources can assist managers to make appropriate decisions about their sustainable use. This study has utilised Towamba estuary (southeastern NSW, Australia), to demonstrate the value and priority of modelling estuarine dynamism as a measure of the rates and consequences of eco-geomorphic changes. This research employs several geoinformatic modelling approaches over time to investigate and assess how climate change and human activities have altered this estuarine eco-geomorphic setting. Multitemporal trend/change analysis of sediment delivery, shoreline positions and land cover, determined from fieldwork and GIS analysis of remote sensing datasets, shows significant spatio-temporal changes to the elevation and areal extent of sedimentary facies in the Towamba estuary over the past 65 years. Geomorphic growth (~ 2600 m2 annually) has stabilised the estuarine habitats, particularly within native vegetation, salt marsh and mangrove areas. Geomorphic changes have occurred because of a combination of sediment runoff from the mostly unmodified terrestrial catchment, nearshore processes (ocean dynamics) and human activities. The construction of GIS models, verified with water and sediment samples, can characterise physical processes and quantify changes within the estuarine ecosystem. Such robust models will allow resource managers to evaluate the potential effects of changes to the current coastal ecosystems.