Abstract:The impacts of coastal erosion are expected to increase through the present century, and beyond, as accelerating global mean sea-level rise begins to enhance or dominate local shoreline dynamics. In many cases, beach (and shoreline) response to sea-level rise will not be limited to passive inundation, but may be amplified or moderated by sediment redistribution between the beach and the broader coastal sedimentary system. We describe a simple and scalable approach for estimating the potential for beach erosion and shoreline change on wave-dominated sandy beaches, using a coastal sediment compartments framework to parameterise the geomorphology and connectivity of sediment-sharing coastal systems. We apply the approach at regional and local scales in order to demonstrate the sensitivity of forecasts to the available data. The regional-scale application estimates potential present and future asset exposure to coastal erosion in New South Wales, Australia. The assessment suggests that shoreline recession due to sea-level rise could drive a steep increase in the number and distribution of asset exposure in the present century. The local-scale example demonstrates the potential sensitivity of erosion impacts to the distinctive coastal geomorphology of individual compartments. Our findings highlight that the benefits of applying a coastal sediment compartments framework increase with the coverage and detail of geomorphic data that is available to parameterise sediment-sharing systems and sediment budget principles. Such data is crucial to reducing uncertainty in forecasts by understanding the potential response of key sediment sources and sinks (e.g., the shoreface, estuaries) to sea-level rise in different settings.

Seascape variability may confound assessments on the effectiveness of no-take marine reserves (NTMRs) in conserving biodiversity. In most cases baseline data are lacking, resulting in evaluations of NTMR effectiveness being Control Impact (CI) assessments. Even with independent replicate areas among management zones, this approach can make it difficult to detect zone effects if seascape attributes, such as habitat structural complexity varies among experimental areas. To determine the importance of structural complexity in evaluations of NTMR effectiveness we performed assessments on the abundance of a targeted fish, yellowtail kingfish (Seriola lalandi), in the Lord Howe Island Marine Park (LHIMP). We compared assessments which did and did not account for structural complexity, quantified using high resolution multibeam bathymetry. Despite almost 3 times more S. lalandi in NTMRs, the traditional CI assessment explained only 3% of the variation in the abundance of S. lalandi and revealed no clear effect of protection. Incorporating structural complexity into the assessment increased the deviance explained to 65% and uncovered an important interaction between zone and structural complexity. Greater abundances of S. lalandi were detected in NTMRs compared to fished zones but only on highly complex reefs. By accounting for structural complexity, we demonstrate that the precision and accuracy of NTMR assessments can be improved, leading to a better understanding of ecological change in response to this conservation strategy. Consequently, where marine park zones vary greatly in structural complexity, we strongly advocate for quantifying and accounting for such variability in assessments of NTMR performance. HIGHLIGHTS 22 No-take marine reserve assessments were compared with and without habitat structure 23  Abundances of yellowtail kingfish were greater in NTMRs but only on complex reef 24  Including habitat structure increased deviance explained from 3% to 65% 25  This reduced the standard error of mean abundances in NTMRs by 40% 26  Assessment precision & accuracy improved, providing robust outcomes for 27 management 28 29 ABSTRACT 30Seascape variability may confound assessments on the effectiveness of no-take marine 31 reserves (NTMRs) in conserving biodiversity. In most cases baseline data are lacking, resulting in 32 evaluations of NTMR effectiveness being Control Impact (CI) assessments. Even with independent 33 replicate areas among management zones, this approach can make it difficult to detect zone effects if 34 seascape attributes, such as habitat structural complexity varies among experimental areas. To 35 determine the importance of structural complexity in evaluations of NTMR effectiveness we 36 performed assessments on the abundance of a targeted fish, yellowtail kingfish (Seriola lalandi), in 37 the Lord Howe Island Marine Park (LHIMP). We compared assessments which did and did not 38 account for structural complexity, quantified using high resolution multibeam bathymetry. Despite 39 almost 3 time...

[1] Coral reefs track sea level and are particularly sensitive to changes in climate. Reefs are threatened by global warming, with many experiencing increased coral bleaching. Warmer sea surface temperatures might enable reef expansion into mid latitudes. Here we report multibeam sonar and coring that reveal an extensive relict coral reef around Lord Howe Island, which is fringed by the southernmost reef in the Pacific Ocean. The relict reef, in water depths of 25-50 m, flourished in early Holocene and covered an area more than 20 times larger than the modern reef. Radiocarbon and uranium-series dating indicates that corals grew between 9000 and 7000 years ago. The reef was subsequently drowned, and backstepped to its modern limited extent. This relict reef, with localised re-establishment of corals in the past three millennia, could become a substrate for reef expansion in response to warmer temperatures, anticipated later this century and beyond, if corals are able to recolonise its surface.

Where biological datasets are spatially limited, abiotic surrogates have been advocated to inform objective planning for Marine Protected Areas. However, this approach assumes close correlation between abiotic and biotic patterns. The Solitary Islands Marine Park, northern NSW, Australia, currently uses a habitat classification system (HCS) to assist with planning, but this is based only on data for reefs. We used Baited Remote Underwater Videos (BRUVs) to survey fish assemblages of unconsolidated substrata at different depths, distances from shore, and across an along-shore spatial scale of 10 s of km (2 transects) to examine how well the HCS works for this dominant habitat. We used multivariate regression modelling to examine the importance of these, and other environmental factors (backscatter intensity, fine-scale bathymetric variation and rugosity), in structuring fish assemblages. There were significant differences in fish assemblages across depths, distance from shore, and over the medium spatial scale of the study: together, these factors generated the optimum model in multivariate regression. However, marginal tests suggested that backscatter intensity, which itself is a surrogate for sediment type and hardness, might also influence fish assemblages and needs further investigation. Species richness was significantly different across all factors: however, total MaxN only differed significantly between locations. This study demonstrates that the pre-existing abiotic HCS only partially represents the range of fish assemblages of unconsolidated habitats in the region.

In 2017, the New South Wales (NSW) Office of Environment and Heritage (OEH) initiated a state-wide mapping program, SeaBed NSW, which systematically acquires high-resolution (2–5 m cell size) multibeam echosounder (MBES) and marine LiDAR data along more than 2000 km of the subtropical-to-temperate southeast Australian continental shelf. This program considerably expands upon existing efforts by OEH to date, which have mapped approximately 15% of NSW waters with these technologies. The delivery of high volumes of new data, together with the vast repository of existing data, highlights the need for a standardised, automated approach to classify seabed data. Here we present a methodological approach with new procedures to semi-automate the classification of high-resolution bathymetry and intensity (backscatter and reflectivity) data into a suite of data products including classifications of seabed morphology (landforms) and composition (substrates, habitats, geomorphology). These methodologies are applied to two case study areas representing newer (Wollongong, NSW) and older (South Solitary Islands, NSW) MBES datasets to assess the transferability of classification techniques across input data of varied quality. The suite of seabed classifications produced by this study provide fundamental baseline data on seabed shape, complexity, and composition which will inform regional risk assessments and provide insights into biodiversity and geodiversity.