Morphometrics of seagrasses at species level, Moreton Bay, Australia determined from core samples collected in 2012-2013

Seagrass meadows are important marine carbon sinks, yet they are threatened and declining worldwide. Seagrass management and conservation requires adequate understanding of the physical and biological factors determining carbon content in seagrass sediments. Here, we identified key factors that influence carbon content in seagrass meadows across several environmental gradients in Moreton Bay, SE Queensland. Sampling was conducted in two regions: (1) Canopy Complexity, 98 sites on the Eastern Banks, where seagrass canopy structure and species composition varied while turbidity was consistently low; and (2) Turbidity Gradient, 11 locations across the entire bay, where turbidity varied among sampling locations. Sediment organic carbon content and seagrass structural complexity (shoot density, leaf area, and species specific characteristics) were measured from shallow sediment and seagrass biomass cores at each location, respectively. Environmental data were obtained from empirical measurements (water quality) and models (wave height). The key factors influencing carbon content in seagrass sediments were seagrass structural complexity, turbidity, water depth, and wave height. In the Canopy Complexity region, carbon content was higher for shallower sites and those with higher seagrass structural complexity. When turbidity varied along the Turbidity Gradient, carbon content was higher at sites with high turbidity. In both regions carbon content was consistently higher in sheltered areas with lower wave height. Seagrass canopy structure, water depth, turbidity, and hydrodynamic setting of seagrass meadows should therefore be considered in conservation and management strategies that aim to maximize sediment carbon content.

Results of wave modelling for Moreton Bay, Southeast Queensland, and a reef lagoon off Lizard Island, Great Barrier Reef, Australia

The distribution, abundance, behaviour, and morphology of marine species is affected by spatial variability in the wave environment. Maps of wave metrics (e.g. significant wave height Hs, peak energy wave period Tp, and benthic wave orbital velocity URMS) are therefore useful for predictive ecological models of marine species and ecosystems. A number of techniques are available to generate maps of wave metrics, with varying levels of complexity in terms of input data requirements, operator knowledge, and computation time. Relatively simple "fetch-based" models are generated using geographic information system (GIS) layers of bathymetry and dominant wind speed and direction. More complex, but computationally expensive, "process-based" models are generated using numerical models such as the Simulating Waves Nearshore (SWAN) model. We generated maps of wave metrics based on both fetch-based and process-based models and asked whether predictive performance in models of benthic marine habitats differed. Predictive models of seagrass distribution for Moreton Bay, Southeast Queensland, and Lizard Island, Great Barrier Reef, Australia, were generated using maps based on each type of wave model. For Lizard Island, performance of the process-based wave maps was significantly better for describing the presence of seagrass, based on Hs, Tp, and URMS. Conversely, for the predictive model of seagrass in Moreton Bay, based on benthic light availability and Hs, there was no difference in performance using the maps of the different wave metrics. For predictive models where wave metrics are the dominant factor determining ecological processes it is recommended that process-based models be used. Our results suggest that for models where wave metrics provide secondarily useful information, either fetch- or process-based models may be equally useful.

Geochemistry on ferromanganese crusts and nodules from Green Bay, Lake Michigan

The differential solubility of ferromanganese oxides can lead to stratigraphic separation of iron and manganese. Results of chemical analysis of a sequence of ferromanganese nodules overlying iron-rich crusts in northern Green Bay show that selec¬tive ion transport is important in concentrating manganese and associated trace elements near the oxygenated water-sediment interface. Manganese carbonate, which cements ferromanganese nodules, occurs in dark-gray silty sands that are located adjacent to the organic-rich muds of southern Green Bay. These muds contain an average of approximately 3.5 ppm (6x10-5M) interstitial Mn with 2.8 meq/l carbonate alkalinity. Thermodynamic calculation shows that interstitial water approaches equilibrium with MnCO3 in the upper 10 cm of sediment. This carbonate has a composition (Mn73Ca22Fe5)CO3 and has been identified as rhodochrosite.

Ecological assessment data of the marine flora and fauna of Point Lookout in 2014 (PLEA)

In 2014, UniDive (The University of Queensland Underwater Club) conducted an ecological assessment of the Point Lookout Dive sites for comparison with similar surveys conducted in 2001. Involvement in the project was voluntary. Members of UniDive who were marine experts conducted training for other club members who had no, or limited, experience in identifying marine organisms and mapping habitats. Since the 2001 detailed baseline study, no similar seasonal survey has been conducted. The 2014 data is particularly important given that numerous changes have taken place in relation to the management of, and potential impacts on, these reef sites. In 2009, Moreton Bay Marine Park was re-zoned, and Flat Rock was converted to a marine national park zone (Green zone) with no fishing or anchoring. In 2012, four permanent moorings were installed at Flat Rock. Additionally, the entire area was exposed to the potential effects of the 2011 and 2013 Queensland floods, including flood plumes which carried large quantities of sediment into Moreton Bay and surrounding waters. The population of South East Queensland has increased from 2.49 million in 2001 to 3.18 million in 2011 (BITRE, 2013). This rapidly expanding coastal population has increased the frequency and intensity of both commercial and recreational activities around Point Lookout dive sites (EPA 2008). Methodology used for the PLEA project was based on the 2001 survey protocols, Reef Check Australia protocols and Coral Watch methods. This hybrid methodology was used to monitor substrate and benthos, invertebrates, fish, and reef health impacts. Additional analyses were conducted with georeferenced photo transects. The PLEA marine surveys were conducted over six weekends in 2014 totaling 535 dives and 376 hours underwater. Two training weekends (February and March) were attended by 44 divers, whilst biological surveys were conducted on seasonal weekends (February, May, July and October). Three reefs were surveyed, with two semi-permanent transects at Flat Rock, two at Shag Rock, and one at Manta Ray Bommie. Each transect was sampled once every survey weekend, with the transect tapes deployed at a depth of 10 m below chart datum. Fish populations were assessed using a visual census along 3 x 20 m transects. Each transect was 5 m wide (2.5 m either side of the transect tape), 5 m high and 20 m in length. Fish families and species were chosen that are commonly targeted by recreational or commercial fishers, or targeted by aquarium collectors, and that were easily identified by their body shape. Rare or otherwise unusual species were also recorded. Target invertebrate populations were assessed using visual census along 3 x 20 m transects. Each transect was 5 m wide (2.5 m either side of the transect tape) and 20 m in length. The diver surveying invertebrates conducted a 'U-shaped' search pattern, covering 2.5 m on either side of the transect tape. Target impacts were assessed using a visual census along the 3 x 20 m transects. Each transect was 5 m wide (2.5 m either side of the transect tape) and 20 m in length. The transect was surveyed via a 'U-shaped' search pattern, covering 2.5 m on either side of the transect tape. Substrate surveys were conducted using the point sampling method, enabling percentage cover of substrate types and benthic organisms to be calculated. The substrate or benthos under the transect line was identified at 0.5m intervals, with a 5m gap between each of the three 20m segments. Categories recorded included various growth forms of hard and soft coral, key species/growth forms of algae, other living organisms (i.e. sponges), recently killed coral, and, non-living substrate types (i.e. bare rock, sand, rubble, silt/clay).

Body sizes and dive characteristics of narwhals (Monodon monoceros) from Kakiak Point and Melville Bay (2005-2007)

We report on wintertime data collected from Baffin Bay and northern Davis Strait, a major gateway linking the Arctic with the subpolar North Atlantic, using narwhals (Monodon monoceros) as an oceanographic sampling platform. Fourteen narwhals were instrumented with satellite-linked time-depth-temperature recorders between 2005 and 2007. Transmitters collected and transmitted water column temperature profiles from each dive between December and April, where >90% of maximum daily dive depths reached the bottom. Temperature measurements were combined with 15 helicopter-based conductivity-temperature-depth (CTD) casts taken in April 2007 across central Baffin Bay and compared with hydrographic climatology values used for the region in Arctic climate models. Winter temperature maxima for whale and CTD data were in good agreement, ranging between 4.0°C and 4.6°C in inshore and offshore Baffin Bay and in Davis Strait. The warm Irminger Water was identified between 57°W and 59°W (at 68°N) between 200 and 400 m depths. Whale data correlated well with climatological temperature maxima; however, they were on average 0.9°C warmer ±0.6°C (P < 0.001). Furthermore, climatology data overestimated the winter surface isothermal layer thickness by 50-80 m. Our results suggest the previously documented warming in Baffin Bay has continued through 2007 and is associated with a warmer West Greenland Current in both of its constituent water masses. This research demonstrates the feasibility of using narwhals as ocean observation platforms in inaccessible Arctic areas where dense sea ice prevents regular oceanographic measurements and where innate site fidelity, affinity for winter pack ice, and multiple daily dives to >1700 m offer a useful opportunity to sample the area.

Probability inundation map for a scenario combining storm surge and sea-level rise

Coastal managers require reliable spatial data on the extent and timing of potential coastal inundation, particularly in a changing climate. Most sea level rise (SLR) vulnerability assessments are undertaken using the easily implemented bathtub approach, where areas adjacent to the sea and below a given elevation are mapped using a deterministic line dividing potentially inundated from dry areas. This method only requires elevation data usually in the form of a digital elevation model (DEM). However, inherent errors in the DEM and spatial analysis of the bathtub model propagate into the inundation mapping. The aim of this study was to assess the impacts of spatially variable and spatially correlated elevation errors in high-spatial resolution DEMs for mapping coastal inundation. Elevation errors were best modelled using regression-kriging. This geostatistical model takes the spatial correlation in elevation errors into account, which has a significant impact on analyses that include spatial interactions, such as inundation modelling. The spatial variability of elevation errors was partially explained by land cover and terrain variables. Elevation errors were simulated using sequential Gaussian simulation, a Monte Carlo probabilistic approach. 1,000 error simulations were added to the original DEM and reclassified using a hydrologically correct bathtub method. The probability of inundation to a scenario combining a 1 in 100 year storm event over a 1 m SLR was calculated by counting the proportion of times from the 1,000 simulations that a location was inundated. This probabilistic approach can be used in a risk-aversive decision making process by planning for scenarios with different probabilities of occurrence. For example, results showed that when considering a 1% probability exceedance, the inundated area was approximately 11% larger than mapped using the deterministic bathtub approach. The probabilistic approach provides visually intuitive maps that convey uncertainties inherent to spatial data and analysis.