Remote submerged banks and mesophotic ecosystems can provide key habitat for endangered marine megafauna.

The importance of some ecosystems remains poorly understood. We showed that mesophotic ecosystems (30 to 150 m) are a key habitat for a critically endangered species, with strong evidence that a globally important population of adult hawksbill turtles (Eretmochelys imbricata) almost exclusively foraged at these depths on remote submerged banks. This discovery highlights the need for such areas to be included in conservation planning, for example, as part of the United Nations High Seas Treaty. We equipped nesting turtles with Fastloc-GPS (Global Positioning System) satellite tags at an Indian Ocean breeding area and they all traveled to deep foraging sites (6765 days of tracking data across 22 individuals including 183,921 dive-depth measurements) rather than shallow coral reef sites. Both chart depths and depth data relayed from the tags indicated that turtles foraged at mesophotic depths, the modal dive depths being between 35 and 40 m. We calculate that 55,554 km2 of the western Indian Ocean alone consists of submerged banks between 30 and 60 m.

Travel routes to remote ocean targets reveal the map sense resolution for a marine migrant.

How animals navigate across the ocean to isolated targets remains perplexing greater than 150 years since this question was considered by Charles Darwin. To help solve this long-standing enigma, we considered the likely resolution of any map sense used in migration, based on the navigational performance across different scales (tens to thousands of kilometres). We assessed navigational performance using a unique high-resolution Fastloc-GPS tracking dataset for post-breeding hawksbill turtles (Eretmochelys imbricata) migrating relatively short distances to remote, isolated targets on submerged banks in the Indian Ocean. Individuals often followed circuitous paths (mean straightness index = 0.54, range 0.14-0.93, s.d. = 0.23, n = 22), when migrating short distances (mean beeline distance to target = 106 km, range 68.7-178.2 km). For example, one turtle travelled 1306.2 km when the beeline distance to the target was only 176.4 km. When off the beeline to their target, turtles sometimes corrected their course both in the open ocean and when encountering shallow water. Our results provide compelling evidence that hawksbill turtles only have a relatively crude map sense in the open ocean. The existence of widespread foraging and breeding areas on isolated oceanic sites points to target searching in the final stages of migration being common in sea turtles.

High accuracy tracking reveals how small conservation areas can protect marine megafauna.

Space use estimates can inform conservation management but relaying high-accuracy locations is often not straightforward. We used Fastloc-GPS Argos satellite tags with the innovation of additional data relay via a ground station (termed a "Mote") to record high volumes (typically >20 locations per individual per day) of high accuracy tracking data. Tags were attached in the Chagos Archipelago (Indian Ocean) in 2018-2019 to 23 immature turtles of two species for which there have been long-standing conservation concerns: 21 hawksbill turtles (Eretmochelys imbricata) and two green turtles (Chelonia mydas). Over long tracking durations (mean 227.6 d per individual), most turtles moved very little. For example, 17 of 21 hawksbill turtles remained continuously in the lagoon where they were equipped, with 95% and 50% utilization distributions (UDs) averaging only 1.03 and 0.18 km2 , respectively. Many individuals, and both species, could use the same small spaces, i.e., individuals did not maintain unique home ranges. However, three hawksbill turtles travelled hundreds of kilometers from the tagging site. Our results show that, for some large marine vertebrates, even small protected areas of only a few square kilometers can encompass the movements of a large proportion of individuals over long periods. High accuracy tracking may likewise reveal the details of space use for many other animals that move little and/or use important focal areas and where previous low-accuracy tracking techniques have tended to overestimate space use.

Why do Argos satellite tags stop relaying data?

Satellite tracking of animals is very widespread across a range of marine, freshwater, and terrestrial taxa. Despite the high cost of tags and the advantages of long deployments, the reasons why tracking data from tags stop being received are rarely considered, but possibilities include shedding of the tag, damage to the tag (e.g., the aerial), biofouling, battery exhaustion, or animal mortality.We show how information relayed via satellite tags can be used to assess why tracking data stop being received. As a case study to illustrate general approaches that are broadly applicable across taxa, we examined data from Fastloc-GPS Argos tags deployed between 2012 and 2019 on 78 sea turtles of two species, the green turtle (Chelonia mydas) and the hawksbill turtle (Eretmochelys imbricata).Tags transmitted for a mean of 267 days (SD = 113 days, range: 26-687 days, median = 251 days). In 68 of 78 (87%) cases, battery failure was implicated as the reason why tracking data stopped being received. Some biofouling of the saltwater switches, which synchronize transmissions with surfacing, was evident in a few tags but never appeared to be the reason that data reception ceased.Objectively assessing why tags fail will direct improvements to tag design, setup, and deployment regardless of the study taxa. Assessing why satellite tags stop transmitting will also inform on the fate of tagged animals, for example, whether they are alive or dead at the end of the study, which may allow improved estimates of survival rates.

Open Ocean Reorientation and Challenges of Island Finding by Sea Turtles during Long-Distance Migration.

In 1873, Charles Darwin marveled at the ability of sea turtles to find isolated island breeding sites [1], but the details of how sea turtles and other taxa navigate during these migrations remains an open question [2]. Exploring this question using free-living individuals is difficult because, despite thousands of sea turtles being satellite tracked across hundreds of studies [3], most are tracked to mainland coasts where the navigational challenges are easiest. We overcame this problem by recording unique tracks of green turtles (Chelonia mydas) migrating long distances in the Indian Ocean to small oceanic islands. Our work provides some of the best evidence to date, from naturally migrating sea turtles, for an ability to reorient in the open ocean, but only at a crude level. Using individual-based models that incorporated ocean currents, we compared actual migration tracks against candidate navigational models to show that turtles do not reorient at fine scales (e.g., daily), but rather can travel several 100 km off the direct routes to their goal before reorienting, often in the open ocean. Frequently, turtles did not home to small islands with pinpoint accuracy, but rather overshot and/or searched for the target in the final stages of migration. These results from naturally migrating individuals support the suggestion from previous laboratory work [4-6] that turtles use a true navigation system in the open ocean, but their map sense is coarse scale.

Local and regional scale habitat heterogeneity contribute to genetic adaptation in a commercially important marine mollusc (Haliotis rubra) from southeastern Australia.

Characterising adaptive genetic divergence among conspecific populations is often achieved by studying genetic variation across defined environmental gradients. In marine systems this is challenging due to a paucity of information on habitat heterogeneity at local and regional scales and a dependency on sampling regimes that are typically limited to broad longitudinal and latitudinal environmental gradients. As a result, the spatial scales at which selection processes operate and the environmental factors that contribute to genetic adaptation in marine systems are likely to be unclear. In this study we explore patterns of adaptive genetic structuring in a commercially- harvested abalone species (Haliotis rubra) from southeastern Australia, using a panel of genome-wide SNP markers (5,239 SNPs), and a sampling regime informed by marine LiDAR bathymetric imagery and 20-year hindcasted oceanographic models. Despite a lack of overall genetic structure across the sampling distribution, significant genotype associations with heterogeneous habitat features were observed at local and regional spatial scales, including associations with wave energy, ocean current, sea surface temperature, and geology. These findings provide insights into the potential resilience of the species to changing marine climates and the role of migration and selection on recruitment processes, with implications for conservation and fisheries management. This study points to the spatial scales at which selection processes operate in marine systems and highlights the benefits of geospatially-informed sampling regimes for overcoming limitations associated with marine population genomic research.

Applications of unmanned aerial vehicles in intertidal reef monitoring.

Monitoring of intertidal reefs is traditionally undertaken by on-ground survey methods which have assisted in understanding these complex habitats; however, often only a small spatial footprint of the reef is observed. Recent developments in unmanned aerial vehicles (UAVs) provide new opportunities for monitoring broad scale coastal ecosystems through the ability to capture centimetre resolution imagery and topographic data not possible with conventional approaches. This study compares UAV remote sensing of intertidal reefs to traditional on-ground monitoring surveys, and investigates the role of UAV derived geomorphological variables in explaining observed intertidal algal and invertebrate assemblages. A multirotor UAV was used to capture <1 cm resolution data from intertidal reefs, with on-ground quadrat surveys of intertidal biotic data for comparison. UAV surveys provided reliable estimates of dominant canopy-forming algae, however, understorey species were obscured and often underestimated. UAV derived geomorphic variables showed elevation and distance to seaward reef edge explained 19.7% and 15.9% of the variation in algal and invertebrate assemblage structure respectively. The findings of this study demonstrate benefits of low-cost UAVs for intertidal monitoring through rapid data collection, full coverage census, identification of dominant canopy habitat and generation of geomorphic derivatives for explaining biological variation.

The effects of an invasive seaweed on native communities vary along a gradient of land-based human impacts.

The difficulty in teasing apart the effects of biological invasions from those of other anthropogenic perturbations has hampered our understanding of the mechanisms underpinning the global biodiversity crisis. The recent elaboration of global-scale maps of cumulative human impacts provides a unique opportunity to assess how the impact of invaders varies among areas exposed to different anthropogenic activities. A recent meta-analysis has shown that the effects of invasive seaweeds on native biota tend to be more negative in relatively pristine than in human-impacted environments. Here, we tested this hypothesis through the experimental removal of the invasive green seaweed, Caulerpa cylindracea, from rocky reefs across the Mediterranean Sea. More specifically, we assessed which out of land-based and sea-based cumulative impact scores was a better predictor of the direction and magnitude of the effects of this seaweed on extant and recovering native assemblages. Approximately 15 months after the start of the experiment, the removal of C. cylindracea from extant assemblages enhanced the cover of canopy-forming macroalgae at relatively pristine sites. This did not, however, result in major changes in total cover or species richness of native assemblages. Preventing C. cylindracea re-invasion of cleared plots at pristine sites promoted the recovery of canopy-forming and encrusting macroalgae and hampered that of algal turfs, ultimately resulting in increased species richness. These effects weakened progressively with increasing levels of land-based human impacts and, indeed, shifted in sign at the upper end of the gradient investigated. Thus, at sites exposed to intense disturbance from land-based human activities, the removal of C. cylindracea fostered the cover of algal turfs and decreased that of encrusting algae, with no net effect on species richness. Our results suggests that competition from C. cylindracea is an important determinant of benthic assemblage diversity in pristine environments, but less so in species-poor assemblages found at sites exposed to intense disturbance from land-based human activities, where either adverse physical factors or lack of propagules may constrain the number of potential native colonizers. Implementing measures to reduce the establishment and spread of C. cylindracea in areas little impacted by land-based human activities should be considered a priority for preserving the biodiversity of Mediterranean shallow rocky reefs.

Exploring Spatiotemporal Trends in Commercial Fishing Effort of an Abalone Fishing Zone: A GIS-Based Hotspot Model.

Assessing patterns of fisheries activity at a scale related to resource exploitation has received particular attention in recent times. However, acquiring data about the distribution and spatiotemporal allocation of catch and fishing effort in small scale benthic fisheries remains challenging. Here, we used GIS-based spatio-statistical models to investigate the footprint of commercial diving events on blacklip abalone (Haliotis rubra) stocks along the south-west coast of Victoria, Australia from 2008 to 2011. Using abalone catch data matched with GPS location we found catch per unit of fishing effort (CPUE) was not uniformly spatially and temporally distributed across the study area. Spatial autocorrelation and hotspot analysis revealed significant spatiotemporal clusters of CPUE (with distance thresholds of 100's of meters) among years, indicating the presence of CPUE hotspots focused on specific reefs. Cumulative hotspot maps indicated that certain reef complexes were consistently targeted across years but with varying intensity, however often a relatively small proportion of the full reef extent was targeted. Integrating CPUE with remotely-sensed light detection and ranging (LiDAR) derived bathymetry data using generalized additive mixed model corroborated that fishing pressure primarily coincided with shallow, rugose and complex components of reef structures. This study demonstrates that a geospatial approach is efficient in detecting patterns and trends in commercial fishing effort and its association with seafloor characteristics.

Are we predicting the actual or apparent distribution of temperate marine fishes?

Planning for resilience is the focus of many marine conservation programs and initiatives. These efforts aim to inform conservation strategies for marine regions to ensure they have inbuilt capacity to retain biological diversity and ecological function in the face of global environmental change--particularly changes in climate and resource exploitation. In the absence of direct biological and ecological information for many marine species, scientists are increasingly using spatially-explicit, predictive-modeling approaches. Through the improved access to multibeam sonar and underwater video technology these models provide spatial predictions of the most suitable regions for an organism at resolutions previously not possible. However, sensible-looking, well-performing models can provide very different predictions of distribution depending on which occurrence dataset is used. To examine this, we construct species distribution models for nine temperate marine sedentary fishes for a 25.7 km(2) study region off the coast of southeastern Australia. We use generalized linear model (GLM), generalized additive model (GAM) and maximum entropy (MAXENT) to build models based on co-located occurrence datasets derived from two underwater video methods (i.e. baited and towed video) and fine-scale multibeam sonar based seafloor habitat variables. Overall, this study found that the choice of modeling approach did not considerably influence the prediction of distributions based on the same occurrence dataset. However, greater dissimilarity between model predictions was observed across the nine fish taxa when the two occurrence datasets were compared (relative to models based on the same dataset). Based on these results it is difficult to draw any general trends in regards to which video method provides more reliable occurrence datasets. Nonetheless, we suggest predictions reflecting the species apparent distribution (i.e. a combination of species distribution and the probability of detecting it). Consequently, we also encourage researchers and marine managers to carefully interpret model predictions.