Kylie L Scales

Marine wildlife bycatch is a persistent and pervasive issue limiting sustainable fisheries management. Key gaps in knowledge include the spatio-temporal dynamics of where fisheries and marine wildlife overlap, and what drives interactions between them. The Critically Endangered Western Pacific subpopulation of leatherback turtles (Dermochelys coriacea) migrate and forage along the east coast of Australia, where they interact with a pelagic longline fishery. This region is characterised by a western boundary current system with a highly dynamic seascape, yet little is known about how leatherback turtles use this pelagic habitat or the drivers of fisheries interaction risk. Here, we use Ensemble Random Forests to examine the influence of surface and subsurface conditions derived from outputs of an openly available data-assimilative ocean model, season, and lunar illumination, on fisheries interactions with leatherback turtles. We found the highest risk areas for leatherback interactions were also the most oceanographically dynamic. Persistent links between leatherback turtle interactions and dynamic ocean features, particularly those associated with the East Australian Current, are explored. We hypothesise that turtles are likely using these features to forage and conserve thermal energy. The risk of interaction also increased during brighter periods of the lunar cycle; a finding likely driven by foraging ecology. These findings provide new information of value to industry and managers and a foundation for testing the utility of data-assimilative ocean models as the basis of decision-support tools for bycatch avoidance.

Climate change manifests in the ocean as chronic stressors, including warming, acidification and deoxygenation, and as acute stressors such as marine heatwaves. While marine protected areas (MPAs) are often designed to mitigate local stressors such as fishing and mining, their design seldom considers climate change. Using the Australian marine estate as a case study, we use projections from 11 CMIP6 Earth System Models to assess the climate exposure of Australian waters, and implications for the MPA network. We find that, under scenarios that exceed 1.8°C of global surface warming this century, ocean climate is projected to surpass recent variability (1995–2014) from mid-century. This results in the disappearance of climate analogs—where future ocean conditions remain within recent variability—and of climate refugia—regions with slowest rates of environmental change, most likely to retain biodiversity—by 2040. Australian MPAs and unprotected areas exhibit similar patterns of exposure to warming, acidification, deoxygenation, and marine heatwaves, suggesting that MPA placement with respect to future climate is no better than random. Despite potential re-emergence of climate refugia after 2060 under lower-emissions scenarios, continued emissions under current Nationally Determined Contributions (SSP2–4.5) risk ecosystem collapse from chronic and acute thermal stress across protected and unprotected waters. While cutting emissions can partially cap or delay climate impacts, even under lower-emissions scenarios, effective conservation requires adaptive strategies that protect biodiversity in place and on the move.

Anthropogenic climate change is driving rapid changes in marine ecosystems across the global ocean. The spatiotemporal footprints of other anthropogenic threats, such as infrastructure development, shipping, and fisheries, will also inevitably shift under climate change, but we find that these shifts are not yet accounted for in most projections of climate futures in marine systems. We summarise what is known about threat-shifting in response to climate change, and identify sources of predictability that have implications for ecological forecasting. We recommend that, where possible, the dynamics of anthropogenic threats are accounted for in nowcasts, forecasts, and projections designed for spatial management and conservation planning, and highlight key themes for future research into threat dynamics in a changing ocean.

Fisheries bycatch is a major threat to many marine predators and a global barrier to fisheries sustainability. Conservation and management strategies can be informed by identifying zones of overlap between fishing efforts and threatened, endangered or protected species, or existing bycatch hotspots. However, few studies have incorporated ocean data when considering such overlap, and even fewer have considered separate juvenile and adult life stages. Here, we characterise the biophysical conditions (i.e., thermal-front frequency, Finite-Size Lyapunov Exponents and eddy kinetic energy) underlying hotspots of interaction risk for an endangered seabird, the Antipodean albatross (Diomedea antipodensis antipodensis). Underlying data include a large (n = 192), high-resolution tracking data set covering all life-history stages, complemented by Automatic Identification System (AIS) vessel-tracking data. Overall, interaction risk was significantly higher during the Austral autumn and winter (May-August) and among juveniles. Over broad, climatological scales, the likelihood of interaction is spatially structured by zones in which thermal fronts occur frequently. At finer scales, interaction risk was intensified in association with aggregative Lagrangian Coherent Structures. Our findings show that immediate steps could be taken by Regional Fisheries Management Organisations, e.g., extending mitigation measures in addition to the current obligation between 25 – 30°S, to reduce bycatch risk for this endangered seabird. Our study also illustrates that incorporating measures of mesoscale ocean dynamics in delineating zones of interaction risk for species of conservation concern provides a potential step forward for dynamic threat management.

Ocean and climate drivers affect the distribution and abundance of marine life on a global scale. Marine ecological forecasting seeks to predict how living marine resources respond to physical variability and change, enabling proactive decision making to support climate adaptation. However, the skill of ecological forecasts is constrained by the skill of underlying models of both ocean state and species environment relationships. As a test of the skill of data driven forecasts for fisheries, we developed predictive models of catch per unit effort (CPUE) of tuna and billfish across the southwest Pacific Ocean, using a 12 year time series of catch data and a large ensemble climate reanalysis. Descriptors of water column structure, particularly temperature at depth and upper ocean heat content, emerged as useful predictors of CPUE across species. Enhancing forecast skill over sub seasonal to multi year timescales in any system is likely to require the inclusion of sub surface ocean data and explicit consideration of regional physical dynamics.