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Terrestrially breeding marine predators have experienced shifts in species distribution, prey availability, breeding phenology, and population dynamics due to climate change worldwide. These central-place foragers are restricted within proximity of their breeding colonies during the breeding season, making them highly susceptible to any changes in both marine and terrestrial environments. While ecologists have developed risk assessments to evaluate climate risk in various contexts, these often overlook critical breeding biology data. To address this knowledge gap, we developed a trait-based risk assessment framework, focusing on the breeding season and applying it to marine predators breeding in parts of Australian territory and Antarctica. Our objectives were to quantify climate change risk, identify specific threats, and establish an adaptable assessment framework. The assessment considered 25 criteria related to three risk components: vulnerability, exposure, and hazard, while accounting for uncertainty. We employed a scoring system that integrated a systematic literature review and expert elicitation for the hazard criteria. Monte Carlo sensitivity analysis was conducted to identify key factors contributing to overall risk. We identified shy albatross (Thalassarche cauta), southern rockhopper penguins (Eudyptes chrysocome), Australian fur seals (Arctocephalus pusillus doriferus), and Australian sea lions (Neophoca cinerea) with high climate urgency. Species breeding in lower latitudes, as well as certain eared seal, albatross, and penguin species, were particularly at risk. Hazard and exposure explained the most variation in relative risk, outweighing vulnerability. Key climate hazards affecting most species include extreme weather events, changes in habitat suitability, and prey availability. We emphasise the need for further research, focusing on at-risk species, and filling knowledge gaps (less-studied hazards, and/or species) to provide a more accurate and robust climate change risk assessment. Our findings offer valuable insights for conservation efforts, given that monitoring and implementing climate adaptation strategies for land-dependent marine predators is more feasible during their breeding season.
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Cambio Climático , Animales , Medición de Riesgo , Conducta Predatoria , Regiones Antárticas , Spheniscidae/fisiología , Cadena AlimentariaRESUMEN
We present a global wind wave climate model ensemble composed of eight spectral wave model simulations forced by 3-hourly surface wind speed and daily sea ice concentration from eight different CMIP6 GCMs. The spectral wave model uses ST6 physics parametrizations and a global three-grid structure for efficient Arctic and Antarctic wave modeling. The ensemble performance is evaluated against a reference global multi-mission satellite altimeter database and the recent ECMWF IFS Cy46r1 ERA5 wave hindcast, ERA5H. For each ensemble member three 30-year slices, one historical, and two future emission scenarios (SSP1-2.6 and SSP5-8.5) are available, and cover two distinct periods: 1985-2014 and 2071-2100. Two models extend to 140 years (1961-2100) of continuous wind wave climate simulations. The present ensemble outperforms a previous CMIP5-forced wind wave climate ensemble, showing improved performance across all ocean regions. This dataset is a valuable resource for future wind wave climate research and can find practical applications in offshore and coastal engineering projects, providing crucial insights into the uncertainties connected to wind wave climate future projections.
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The dataset consists of ocean surface wind speed and direction at 10 m height and 1 km spatial resolution around the wider Australian coastal areas, spanning 4 years (2017 to 2021) of measurements from Sentinel-1 A and B imaging Synthetic Aperture Radar (SAR) platforms. The winds have been derived using a consistent SAR wind retrieval algorithm, processing the full Sentinel-1 archive in this region. The data are appropriately quality controlled, flagged, and archived as NetCDF files representing SAR wind field maps aligned with satellite along-track direction. The data have been calibrated against Metop-A/B Scatterometer buoy-calibrated, wind measurements and examined for potential changes in calibration over the duration of the data. The calibrated data are further validated by comparisons against independent Altimeter (Cryosat-2, Jason-2, Jason-3, and SARAL) wind speeds. Several methods for data access are also listed. The database is potentially useful for offshore industries (oil and gas, fisheries, shipping, offshore wind energy), public recreational activities (fishing, sailing, surfing), and protection and management of coasts and natural habitats.
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Understanding uncertainties in extreme wind-wave events is essential for offshore/coastal risk and adaptation estimates. Despite this, uncertainties in contemporary extreme wave events have not been assessed, and projections are still limited. Here, we quantify, at global scale, the uncertainties in contemporary extreme wave estimates across an ensemble of widely used global wave reanalyses/hindcasts supported by observations. We find that contemporary uncertainties in 50-year return period wave heights ([Formula: see text]) reach (on average) ~2.5 m in regions adjacent to coastlines and are primarily driven by atmospheric forcing. Furthermore, we show that uncertainties in contemporary [Formula: see text] estimates dominate projected 21st-century changes in [Formula: see text] across ~80% of global ocean and coastlines. When translated into broad-scale coastal risk analysis, these uncertainties are comparable to those from storm surges and projected sea level rise. Thus, uncertainties in contemporary extreme wave events need to be combined with those of projections to fully assess potential impacts.
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Abstract: The ocean economy is experiencing rapid growth that will provide benefits but will also pose environmental and social risks. With limited space and degraded resources in coastal areas, offshore waters will be a particular focus of Blue Economy expansion over the next decade. When emerging and established economic sectors expand in offshore waters (within national Exclusive Economic Zones), different potential Blue Economy opportunities and challenges will arise. Following a series of interdisciplinary workshops, we imagine two technically possible futures for the offshore Blue Economy and we identify the actions required to achieve the more sustainable outcome. Under a business as usual scenario the focus will remain on economic growth, the commodification of nature, the dominance of private over public and cultural interests, and prioritisation of the interests of current over future generations. A more sustainable scenario would meet multiple UN Sustainable Development Goals and ensure inclusive economic developments, environmental sustainability, and fair and equitable access to resources and technologies across users, nations, and generations. Challenges to this more sustainable future are a lack of infrastructure and technology to support emerging offshore sectors, limited understanding of environmental impacts, inequitable outcomes, and a lack of planning and governmental oversight. Addressing these challenges will require a shift in societal values, a more balanced allocation of funding to offshore activities, transparency in information sharing between industries and across nations, and adjustment of international legal and institutional mechanisms. The sustainable and equitable offshore Blue Economy we envisage is achievable and provides a unique opportunity to build global capacity and partnership.
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Coastal studies of wave climate and evaluations of wave energy resources are mainly regional and based on the use of computationally very expensive models or a network of in-situ data. Considering the significant wave height, satellite radar altimetry provides an established global and relatively long-term source, whose coastal data are nevertheless typically flagged as unreliable within 30 km of the coast. This study exploits the reprocessing of the radar altimetry signals with a dedicated fitting algorithm to retrieve several years of significant wave height records in the coastal zone. We show significant variations in annual cycle amplitudes and mean state in the last 30 km from the coastline compared to offshore, in areas that were up to now not observable with standard radar altimetry. Consequently, a decrease in the average wave energy flux is observed. Globally, we found that the mean significant wave height at 3 km off the coast is on average 22% smaller than offshore, the amplitude of the annual cycle is reduced on average by 14% and the mean energy flux loses 38% of its offshore value.
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Interaction uncertainties between tidal energy devices and marine animals have the potential to impede the tidal energy industry as it moves closer towards commercial-scale array installations. Developing standardised environmental impact assessment (EIA) practices would allow for potential impact concerns to the marine environment to be identified and mitigated early during project development. In an effort to help formulate a standardised EIA framework that addresses knowledge gaps in fish-current interactions at tidal energy candidate sites, Scherelis et al. [1] presented a case study for investigating changes in fish aggregations in response to changing environmental conditions including tidal currents at a tidal energy candidate site in Australia prior to turbine installation. Here, we present the dataset utilised for this study titled "Investigating biophysical linkages at tidal energy candidate sites: a case study for combining environmental assessment and resource characterisation" [1]. The dataset includes tidal current information from an Acoustic Doppler Current Profiler (ADCP), volume backscattering measurements from a four-frequency biological echosounder (Acoustic Zooplankton and Fish Profiler - AZFP) as an indicator for fish biomass, and fish aggregation metrics calculated from volume backscatter in post-processing. ADCP and AZFP were installed on a bottom-mounted mooring and engaged in a concurrent sampling plan for â¼2.5 months from December 2018 to February 2019. The mooring was deployed in the Banks Strait, a tidal energy candidate site located in the northeast of Tasmania, Australia, at a location favourable for tidal turbine installations considering current speed, depth, substrate, sediment type and proximity to shore. The ADCP dataset includes current velocity and direction measurements at 1â¯m vertical and 1-min time intervals. The raw AZFP dataset includes volume backscattering strength collected in 4-s time intervals with a vertical resolution of 0.072â¯m in raw, and 0.1â¯m in pre-processed form. Several post-processing steps were implemented to mitigate changes in background noise due to current speed and wind stress, and to isolate acoustic fish returns from remaining scattering sources. Once isolated, volume backscatter containing fish targets underwent post-processing to determine fish aggregation metrics including density, abundance, centre of mass, dispersion,% water column occupied, evenness, and index for aggregation. Each aggregation metric was then binned by minute matched with corresponding environmental conditions for current speed, shear, temperature, diel stage, and tidal stage. Raw and processed datasets for the AZFP and ADCP are provided. Post-processed data includes the derived fish aggregation metrics along with corresponding environmental conditions. The described datasets are freely available on the Australian Ocean Data Network (AODN).
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We describe an innovative approach to estimate global changes in extreme wave conditions by 2100, as a result of projected climate change. We generate a synthetic dataset from an ensemble of wave models forced by independent climate simulation winds, enhancing statistical confidence associated with projected changes in extreme wave conditions. Under two IPCC representative greenhouse gas emission scenarios (RCP4.5 and RCP8.5), we find that the magnitude of a 1 in 100-year significant wave height (H s ) event increases by 5 to 15% over the Southern Ocean by the end of the 21st century, compared to the 1979-2005 period. The North Atlantic shows a decrease at low to mid latitudes (≈5 to 15%) and an increase at high latitudes (≈10%). The extreme significant wave height in the North Pacific increases at high latitudes by 5 to 10%. The ensemble approach used here allows statistical confidence in projected changes of extremes.
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This dataset, produced through the Coordinated Ocean Wave Climate Project (COWCLIP) phase 2, represents the first coordinated multivariate ensemble of 21st Century global wind-wave climate projections available (henceforth COWCLIP2.0). COWCLIP2.0 comprises general and extreme statistics of significant wave height (HS), mean wave period (Tm), and mean wave direction (θm) computed over time-slices 1979-2004 and 2081-2100, at different frequency resolutions (monthly, seasonally and annually). The full ensemble comprising 155 global wave climate simulations is obtained from ten CMIP5-based state-of-the-art wave climate studies and provides data derived from alternative wind-wave downscaling methods, and different climate-model forcing and future emissions scenarios. The data has been produced, and processed, under a specific framework for consistency and quality, and follows CMIP5 Data Reference Syntax, Directory structures, and Metadata requirements. Technical comparison of model skill against 26 years of global satellite measurements of significant wave height has been undertaken at global and regional scales. This new dataset provides support for future broad scale coastal hazard and vulnerability assessments and climate adaptation studies in many offshore and coastal engineering applications.
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Climate change (CC) is likely to affect the thousands of bar-built or barrier estuaries (here referred to as Small tidal inlets - STIs) around the world. Any such CC impacts on the stability of STIs, which governs the dynamics of STIs as well as that of the inlet-adjacent coastline, can result in significant socio-economic consequences due to the heavy human utilisation of these systems and their surrounds. This article demonstrates the application of a process based snap-shot modelling approach, using the coastal morphodynamic model Delft3D, to 3 case study sites representing the 3 main STI types; Permanently open, locationally stable inlets (Type 1), Permanently open, alongshore migrating inlets (Type 2) and Seasonally/Intermittently open, locationally stable inlets (Type 3). The 3 case study sites (Negombo lagoon - Type 1, Kalutara lagoon - Type 2, and Maha Oya river - Type 3) are all located along the southwest coast of Sri Lanka. After successful hydrodynamic and morphodynamic model validation at the 3 case study sites, CC impact assessment are undertaken for a high end greenhouse gas emission scenario. Future CC modified wave and riverflow conditions are derived from a regional scale application of spectral wave models (WaveWatch III and SWAN) and catchment scale applications of a hydrologic model (CLSM) respectively, both of which are forced with IPCC Global Climate Model output dynamically downscaled to ~ 50 km resolution over the study area with the stretched grid Conformal Cubic Atmospheric Model CCAM. Results show that while all 3 case study STIs will experience significant CC driven variations in their level of stability, none of them will change Type by the year 2100. Specifically, the level of stability of the Type 1 inlet will decrease from 'Good' to 'Fair to poor' by 2100, while the level of (locational) stability of the Type 2 inlet will also decrease with a doubling of the annual migration distance. Conversely, the stability of the Type 3 inlet will increase, with the time till inlet closure increasing by ~75%. The main contributor to the overall CC effect on the stability of all 3 STIs is CC driven variations in wave conditions and resulting changes in longshore sediment transport, not Sea level rise as commonly believed.