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Abstract Background Accurate predictions of animal occurrence in time and space are crucial for informing and implementing science-based management strategies for threatened species. Methods We compiled known, available satellite tracking data for pygmy blue whales in the Eastern Indian Ocean (n = 38), applied movement models to define low (foraging and reproduction) and high (migratory) move persistence underlying location estimates and matched these with environmental data. We then used machine learning models to identify the relationship between whale occurrence and environment, and predict foraging and migration habitat suitability in Australia and Southeast Asia. Results Our model predictions were validated by producing spatially varying accuracy metrics. We identified the shelf off the Bonney Coast, Great Australian Bight, and southern Western Australia as well as the slope off the Western Australian coast as suitable habitat for migration, with predicted foraging/reproduction suitable habitat in Southeast Asia region occurring on slope and in deep ocean waters. Suitable foraging habitat occurred primarily on slope and shelf break throughout most of Australia, with use of the continental shelf also occurring, predominanly in South West and Southern Australia. Depth of the water column (bathymetry) was consistently a top predictor of suitable habitat for most regions, however, dynamic environmental variables (sea surface temperature, surface height anomaly) influenced the probability of whale occurrence. Conclusions Our results indicate suitable habitat is related to dynamic, localised oceanic processes that may occur at fine temporal scales or seasonally. An increase in the sample size of tagged whales is required to move towards developing more dynamic distribution models at seasonal and monthly temporal scales. Our validation metrics also indicated areas where further data collection is needed to improve model accuracy. This is of particular importance for pygmy blue whale management, since threats (e.g., shipping, underwater noise and artificial structures) from the offshore energy and shipping industries will persist or may increase with the onset of an offshore renewable energy sector in Australia.

As the use of coastal and offshore environments expands, there is a need to better understand the exposure of marine megafauna to anthropogenic activities that potentially threaten their populations. Individual satellite telemetry studies are often hampered by small sample sizes, providing limited information on spatiotemporal distributions of migratory animals and their relationships to anthropogenic threats. We addressed this issue by synthesising satellite tracking data from 484 individuals of three taxonomic groups and six species; three marine turtle, two whale and one shark. The spatial overlap between taxa distributions and multiple anthropogenic activities was assessed as a proxy for the cumulative exposure of these taxa to anthropogenic threats (coastal modification, vessel strike, underwater noise, oil spill, bycatch, entanglement, and artificial light) across an area totalling 2,205,740 km2 off north-western Australia. Core exposure areas (top 50% of the distribution) encompassed ecologically important sites for all taxa, such as the Ningaloo and Pilbara regions, migratory routes for whales and sharks in offshore waters beyond Ningaloo Reef, and marine turtle nesting beaches at Barrow Island and Cape Lambert. Although areas of high exposure represented

Abstract Seafloor characteristics can help in the prediction of fish distribution, which is required for fisheries and conservation management. Despite this, only 5%–10% of the world's seafloor has been mapped at high resolution, as it is a time‐consuming and expensive process. Multibeam echo‐sounders (MBES) can produce high‐resolution bathymetry and a broad swath coverage of the seafloor, but require greater financial and technical resources for operation and data analysis than singlebeam echo‐sounders (SBES). In contrast, SBES provide comparatively limited spatial coverage, as only a single measurement is made from directly under the vessel. Thus, producing a continuous map requires interpolation to fill gaps between transects. This study assesses the performance of demersal fish species distribution models by comparing those derived from interpolated SBES data with full‐coverage MBES distribution models. A Random Forest classifier was used to model the distribution of Abalistes stellatus, Gymnocranius grandoculis, Lagocephalus sceleratus, Loxodon macrorhinus, Pristipomoides multidens, and Pristipomoides typus, with depth and depth derivatives (slope, aspect, standard deviation of depth, terrain ruggedness index, mean curvature, and topographic position index) as explanatory variables. The results indicated that distribution models for A. stellatus, G. grandoculis, L. sceleratus, and L. macrorhinus performed poorly for MBES and SBES data with area under the receiver operator curves (AUC) below 0.7. Consequently, the distribution of these species could not be predicted by seafloor characteristics produced from either echo‐sounder type. Distribution models for P. multidens and P. typus performed well for MBES and the SBES data with an AUC above 0.8. Depth was the most important variable explaining the distribution of P. multidens and P. typus in both MBES and SBES models. While further research is needed, this study shows that in resource‐limited scenarios, SBES can produce comparable results to MBES for use in demersal fish management and conservation.

Key ecological features (KEFs) are elements of Australia’s Commonwealth marine environment considered to be important for biodiversity or ecosystem function, yet many KEFs are poorly researched, which can impede effective decision-making about future development and conservation. This study investigates a KEF positioned over the Last Glacial Maximum (LGM) shoreline on the northwest shelf of Australia (known as the ‘Ancient Coastline at ~125m depth contour’; AC125). Seafloor bathymetry, sedimentology and benthic habitats were characterised within five study areas using multibeam sonar, sediment samples and towed video imagery. Direct evidence for the existence of a palaeoshoreline formed during the LGM was not found, however candidate areas to find palaeoshoreline material at or just below the modern seabed were discovered. Approximately 98% of the seabed surveyed was comprised of unconsolidated soft sediment habitat (mud/sand/silt) supporting negligible epibenthic biota. The prevalence of soft sediment suggests that post-glacial sediments have infilled parts of the palaeoshoreline, with cross-shelf, probably tidal currents in the northern section of the study area responsible for some of the sediment mobilisation and southern study areas more influenced by oceanic conditions. Within study areas, total biotic cover ranged from 0.02% to 1.07%. Of the biota encountered, most comprised filter feeder organisms (including gorgonians, sponges, and whip corals) whose distribution was associated with pockets of consolidated hard substrate. Benthic community composition varied with both study area and position in relation to the predicted AC125. In general, consolidated substrate was proportionally higher in water shallower than the AC125 compared to on the AC125 or deeper than the AC125. Spatially continuous maps of predicted benthic habitat classes (pre-determined benthic communities) in each study area were developed to characterise biodiversity. Spatial modelling corroborated depth and large-scale structural complexity of the seafloor as surrogates for predicting likely habitat class. This study provides an important assessment of the AC125 and shows that if a distinct coastline exists in the areas we surveyed, it is now largely buried and as such does not provide a unique hard substrate habitat. However, much work remains to fully locate and map the ancient coastline within the vast region of the AC125 and additional surveys in shallow waters adjacent to the AC125 may identify whether some sections lie outside the currently defined KEF.

Regional patterns of fish diversity, abundance, distribution, and assemblage composition are driven by a combination of biotic and abiotic conditions in the marine environment, but these conditions can be altered through anthropogenic activities, such as those associated with oil and gas extraction. The present study utilises data on fish relative abundance and diversity obtained from 1546 baited remote underwater video deployments conducted between 2004 – 2019 in depths of 9 – 170 m across 2000 km of coastline in north-west Australia on natural habitats and subsea pipelines to understand the influence of oil and gas infrastructure on fish assemblages. A total of 450 fish taxa from 56 families was observed, with populations dominated by generalist and invertebrate carnivore taxa. At the regional scale, subsea pipelines had lower diversity (lower taxonomic richness) than natural environments, but possessed a higher abundance of piscivorous and herbivorous fish taxa. Clear patterns in fish assemblage composition were observed in multivariate analyses, reflecting the proximity of oceanic shoals and banks, depth, and to a lesser extent, oil and gas infrastructure. Shallow-water and close to shoals assemblages were characterised by a diversity of site-attached (e.g., wrasses, tuskfish), reef-associated taxa (e.g., emperors). Mesophotic fish assemblages were characterised by commercially important (e.g., goldband snapper), wide-ranging (e.g., sharks) and sand-affiliated (e.g., toadfish, threadfin bream) taxa. Proximity to pipelines and platforms ranked low as predictors in the multivariate analyses suggesting a negligible regional influence of these structures on fish communities in comparison to depth and shoal habitats. Local-scale influences of subsea infrastructure, however, may be important for some fish species (infrastructure vs. immediate surrounds). Our study highlights the influence of abiotic factors on regional-scale patterns in fish assemblage structure across north-west Australia.

Demersal fishes constitute an essential component of the continental shelf ecosystem, and a significant element of fisheries catch around the world. However, collecting distribution and abundance data of demersal fish, necessary for their conservation and management, is usually expensive and logistically complex. The increasing availability of seafloor mapping technologies has led to the opportunity to exploit the strong relationship demersal fish exhibit with seafloor morphology to model their distribution. Multibeam echo-sounder (MBES) systems are a standard method to map seafloor morphology. The amount of acoustic energy reflected by the seafloor (backscatter) is used to estimate specific characteristics of the seafloor, including acoustic hardness and roughness. MBES data including bathymetry and depth derivatives were used to model the distribution of Abalistes stellatus, Gymnocranius grandoculis, Lagocephalus sceleratus, Lethrinus miniatus, Loxodon macrorhinus, Lutjanus sebae, and Scomberomorus queenslandicus. The possible improvement of model accuracy by adding the seafloor backscatter was tested in three different areas of the Ningaloo Marine Park off the west coast of Australia. For the majority of species, depth was a primary variable explaining their distribution in the three study sites. Backscatter was identified to be an important variable in the models, but did not necessarily lead to a significant improvement in the demersal fish distribution models’ accuracy. Possible reasons for this include: the depth and derivatives were capturing the significant changes in the habitat, or the acoustic data collected with a high-frequency MBES were not capturing accurately relevant seafloor characteristics associated with the species distribution. The improvement in the accuracy of the models for certain species using data already available is an encouraging result, which can have a direct impact in our ability to monitor these species.

Novel tools and methods for monitoring marine environments can improve efficiency but must not compromise long-term data records. Quantitative comparisons between new and existing methods are therefore required to assess their compatibility for monitoring. Monitoring of shallow water coral reefs is typically conducted using diver-based collection of benthic images along transects. Diverless systems for obtaining underwater images (e.g. towed-cameras, remotely operated vehicles, autonomous underwater vehicles) are increasingly used for mapping coral reefs. Of these imaging platforms, towed-cameras offer a practical, low cost and efficient method for surveys but their utility for repeated measures in monitoring studies has not been tested. We quantitatively compare a towed-camera approach to repeated surveys of shallow water coral reef benthic assemblages on fixed transects, relative to benchmark data from diver photo-transects. Differences in the percent cover detected by the two methods was partly explained by differences in the morphology of benthic groups. The reef habitat and physical descriptors of the site—slope, depth and structural complexity—also influenced the comparability of data, with differences between the tow-camera and the diver data increasing with structural complexity and slope. Differences between the methods decreased when a greater number of images were collected per tow-camera transect. We attribute lower image quality (variable perspective, exposure and focal distance) and lower spatial accuracy and precision of the towed-camera transects as the key reasons for differences in the data from the two methods and suggest changes to the sampling design to improve the application of tow-cameras to monitoring.

Mangroves are a globally important ecosystem experiencing significant anthropogenic and climate impacts. Two subtypes of mangrove are particularly vulnerable to climate-induced impacts (1): tidally submerged forests and (2) those that occur in arid and semi-arid regions. These mangroves are either susceptible to sea level rise or occur in conditions close to their physiological limits of temperature and freshwater availability. The spatial extent and impacts on these mangroves are poorly documented, because they have structural and environmental characteristics that affect their ability to be detected with remote sensing models. For example, tidally submerged mangroves occur in areas with large tidal ranges, which limits their visibility at high tide, and arid mangroves have sparse canopy cover and a shorter stature that occur in fringing and narrow stands parallel to the coastline. This study introduced the multi-dimensional space–time randomForest method (MSTRF) that increases the detectability of these mangroves and applies this on the North-west Australian coastline where both mangrove types are prevalent. MSTRF identified an optimal four-year period that produced the most accurate model (Accuracy of 80%, Kappa value 0.61). This model was able to detect an additional 32% (76,048 hectares) of mangroves that were previously undocumented in other datasets. We detected more mangrove cover using this timeseries combination of annual median composite Landsat images derived from scenes across the whole tidal cycle but also over climatic cycles such as EÑSO. The median composite images displayed less spectral differences in mangroves in the intertidal and arid zones compared to individual scenes where water was present during the tidal cycle or where the chlorophyll reflectance was low during hot and dry periods. We found that the MNDWI (Modified Normalised Water Index) and GCVI (Green Chlorophyll Vegetation Index) were the best predictors for deriving the mangrove layer using randomForest.

Increasing sea surface temperature and extreme heat events pose the greatest threat to coral reefs globally, with trends exceeding previous norms. The resultant mass bleaching events, such as those evidenced on the Great Barrier Reef in 2016, 2017, and 2020 have substantial ecological costs in addition to economic and social costs. Advancing remote (nanosatellites, rapid revisit traditional satellites) and in-field (drones) technological capabilities, cloud data processing, and analysis, coupled with existing infrastructure and in-field monitoring programs, have the potential to provide cost-effective and timely information to managers allowing them to better understand changes on reefs and apply effective remediation. Within a risk management framework for monitoring coral bleaching, we present an overview of how remote sensing can be used throughout the whole risk management cycle and highlight the role technological advancement has in earth observations of coral reefs for bleaching events.

In 2016 we reported evidence for associative learning in plants (Gagliano et al., 2016). In view of the far-reaching implications of this finding we welcome the attempt made by Markel to replicate our study (Markel, 2020). However, as we discuss here, the protocol employed by Markel was unsuitable for testing for associative learning.

There is a growing emphasis on formally recognizing the connection to the marine environment of Indigenous peoples and the traditional ecological knowledge (TEK) these strong connections cultivate. The potential for TEK to significantly enrich the scientific comprehension of the marine environment, whilst also celebrating the rich bio-cultural knowledge in its own right, is indisputable. Here, we present a scientifically robust and culturally appropriate participatory mapping methodology for the marine environment which can effectively achieve genuine cross-cultural ecological knowledge transfer between scientists and Indigenous Peoples. Through a case study working with the Anindilyakwa people of the Groote Eylandt Archipelago, we mapped the TEK of benthic habitats off Australia’s poorly surveyed northern coast. Representatives from 14 Anindilyakwa clan groups participated in the marine mapping (n = 53), resulting in 22 individual maps. Eleven broad-scale habitat classifications, predominately in the intertidal and nearshore marine environment, were described in both Anindilyakwa and English. The information gathered was then used to develop benthic habitat maps covering a combined area of ∼1800 km2 and was assessed for accuracy against in situ observations. We found that despite the difficulties in working across two different world views, through the application of this carefully refined methodology, scientists can effectively document the rich TEK of the marine environment in a manner suitable for conservation and management planning while also supporting the prioritization of Indigenous values within the decision-making process.

Marine protected area (MPA) designs are likely to require iterative refinement as new knowledge is gained. In particular, there is an increasing need to consider the effects of climate change, especially the ability of ecosystems to resist and/or recover from climate-related disturbances, within the MPA planning process. However, there has been limited research addressing the incorporation of climate change resilience into MPA design. This study used Marxan conservation planning software with fine-scale shallow water (

BACKGROUND: The Symbiodinium community associated with scleractinian corals is widely considered to be shaped by seawater temperature, as the coral's upper temperature tolerance is largely contingent on the Symbiodinium types harboured. Few studies have challenged this paradigm as knowledge of other environmental drivers on the distribution of Symbiodinium is limited. Here, we examine the influence of a range of environmental variables on the distribution of Symbiodinium associated with Acropora millepora collected from 47 coral reefs spanning 1,400 km on the Great Barrier Reef (GBR), Australia. METHODOLOGY/PRINCIPAL FINDINGS: The environmental data included Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data at 1 km spatial resolution from which a number of sea surface temperature (SST) and water quality metrics were derived. In addition, the carbonate and mud composition of sediments were incorporated into the analysis along with in situ water quality samples for a subset of locations. Analyses were conducted at three spatio-temporal scales [GBR (regional-scale), Whitsunday Islands (local-scale) and Keppel Islands/Trunk Reef (temporal)] to examine the effects of scale on the distribution patterns. While SST metrics were important drivers of the distribution of Symbiodinium types at regional and temporal scales, our results demonstrate that spatial variability in water quality correlates significantly with Symbiodinium distribution at local scales. Background levels of Symbiodinium types were greatest at turbid inshore locations of the Whitsunday Islands where SST predictors were not as important. This was not the case at regional scales where combinations of mud and carbonate sediment content coupled with SST anomalies and mean summer SST explained 51.3% of the variation in dominant Symbiodinium communities. CONCLUSIONS/SIGNIFICANCE: Reef corals may respond to global-scale stressors such as climate change through changes in their resident symbiont communities, however, management of local-scale stressors such as altered water quality is also necessary for maintenance of coral-Symbiodinium associations.

BackgroundLipids in reef building corals can be divided into two classes; non-polar storage lipids, e.g. wax esters and triglycerides, and polar structural lipids, e.g. phospholipids and cholesterol. Differences among algal endosymbiont types are known to have important influences on processes including growth and the photobiology of scleractinian corals yet very little is known about the role of symbiont types on lipid energy reserves.Methodology/principal findingsThe ratio of storage lipid and structural lipid fractions of Scott Reef corals were determined by thin layer chromatography. The lipid fraction ratio varied with depth and depended on symbiont type harboured by two corals (Seriatopora hystrix and Pachyseris speciosa). S. hystrix colonies associated with Symbiodinium C1 or C1/C# at deep depths (>23 m) had lower lipid fraction ratios (i.e. approximately equal parts of storage and structural lipids) than those with Symbiodinium D1 in shallow depths (Conclusions/significanceThis study has demonstrated that Symbiodinium exert significant controls over the quality of coral energy reserves over a large-scale depth gradient. We conclude that the competitive advantages and metabolic costs that arise from flexible associations with divergent symbiont types are offset by energetic trade-offs for the coral host.