Quantifying the effects of bycatch reduction devices in Queensland's (Australia) shallow water eastern king prawn (Penaeus plebejus) trawl fishery

This study presents results from an experimental 10-day research charter that was designed to quantify the effects of a) a turtle excluder device (TED) and b) a radial escape section bycatch reduction device (BRD) and c) both devices together, on prawn and bycatch catch rates in the Queensland shallow water eastern king prawn (Penaeus plebejus) trawl fishery. The bycatch was comprised of 250 taxa, mainly gurnards, whiting, lizard fish, flathead, dragonets, portunid crabs, turretfish and flounders. The observed mean catch rates of bycatch and marketable eastern king prawns from the standard trawl net (i.e., net with no TED or BRD) used during the charter were 11.06 (se 0.90) kg per hectare swept by the trawl gear (ha-1) and 0.94 kg ha-1, respectively. For the range of depths sampled (20.1-90.7 m), bycatch catch rates declined significantly at a rate of 0.14 kg ha-1 for every 1 m increase in depth, while prawn catch rates were unaffected. When both the TED and radial escape section BRD were used together they resulted in a 24% reduction in total bycatch catch rate compared to a standard net, but at a 20% reduction in marketable prawn catch rate. The largest reductions were achieved for stout whiting Sillago robusta (57% reduction) and yellowtail scad Trachurus novaezelandiae (32% reduction). Multidimensional scaling and analysis of similarities revealed that bycatch assemblages differed significantly between depths and latitude, but not between the different combinations of bycatch reduction devices. Despite the lowered prawn catch rates, the reduced bycatch catch rates are promising, particularly for S. robusta which is not permitted to be retained by the prawn trawl fleet and yet experiences considerable incidental fishing mortality, and because it is targeted in a separate licensed commercial fishery.

Productivity, carbon assimilation and intra-annual change in tropical reef platform seagrass communities of the Torres Strait, north-eastern Australia

Detailed data on seagrass distribution, abundance, growth rates and community structure information were collected at Orman Reefs in March 2004 to estimate the above-ground productivity and carbon assimilated by seagrass meadows. Seagrass meadows were re-examined in November 2004 for comparison at the seasonal extremes of seagrass abundance. Ten seagrass species were identified in the meadows on Orman Reefs. Extensive seagrass coverage was found in March (18,700 ha) and November (21,600 ha), with seagrass covering the majority of the intertidal reef-top areas and a large proportion of the subtidal areas examined. There were marked differences in seagrass above-ground biomass, distribution and species composition between the two surveys. Major changes between March and November included a substantial decline in biomass for intertidal meadows and an expansion in area of subtidal meadows. Changes were most likely a result of greater tidal exposure of intertidal meadows prior to November leading to desiccation and temperature-related stress. The Orman Reef seagrass meadows had a total above-ground productivity of 259.8 t DW day-1 and estimated carbon assimilation of 89.4 t C day-1 in March. The majority of this production came from the intertidal meadows which accounted for 81% of the total production. Intra-annual changes in seagrass species composition, shoot density and size of meadows measured in this study were likely to have a strong influence on the total above-ground production during the year. The net estimated above-ground productivity of Orman Reefs meadows in March 2004 (1.19 g C m-2 day-1) was high compared with other tropical seagrass areas that have been studied and also higher than many other marine, estuarine and terrestrial plant communities.

Spatial patterns of sub-tidal seagrasses and their tissue nutrients in the Torres Strait, northern Australia: Implications for management

The distribution and nutritional profiles of sub-tidal seagrasses from the Torres Strait were surveyed and mapped across an area of 31,000 km2. Benthic sediment composition, water depth, seagrass species type and nutrients were sampled at 168 points selected in a stratified representative pattern. Eleven species of seagrass were present at 56 (33.3%) of the sample points. Halophila spinulosa, Halophila ovalis, Cymodocea serrulata and Syringodium isoetifolium were the most common species and these were nutrient profiled. Sub-tidal seagrass distribution (and associated seagrass nutrient concentrations) was generally confined to northern-central and south-western regions of the survey area (shallow (approximately 13 m below MSL) and where sediments were comprised primarily muddy sand to gravelly sand. Seagrass nitrogen and starch content, the most important nutrients for marine herbivores, were significantly correlated with species and with the plant component (above or below ground). For all seagrass species, the above-ground component (shoots and leaves) possessed greater nitrogen concentrations than the below-ground component (roots and rhizomes), which possessed greater starch concentrations. S. isoetifolium had the highest total nitrogen concentrations (1.40±0.05% DW). However, it also had higher fibre concentrations (38.2±0.68% DW) relative to the other four species. H. ovalis possessed the highest starch concentrations (2.76±0.12% DW) and highest digestibility (83.24±0.66% DW) as well as the lowest fibre (27.2±0.66% DW). The high relative abundance (found at 55% of the sites that had seagrass) and nutrient quality characteristics of H. ovalis make it an important source of energy to marine herbivores that forage sub-tidally in the Torres Strait. There were two regions in Torres Strait (north-central and south-western) where sub-tidal seagrass meadows were prevalent and of relatively higher nutritional value. This spatial and nutritional information can be used by local agencies to manage and to protect the ecological, economic and cultural values of the sub-tidal seagrass ecosystems and associated fisheries of the Torres Strait.

Seagrass-Watch: Engaging Torres Strait Islanders in marine habitat monitoring

Involvement in scientifically structured habitat monitoring is a relatively new concept to the peoples of Torres Strait. The approach we used was to focus on awareness, and to build the capacity of groups to participate using Seagrass-Watch as the vehicle to provide education and training in monitoring marine ecosystems. The project successfully delivered quality scientifically rigorous baseline information on the seasonality of seagrasses in the Torres Strait-a first for this region. Eight seagrass species were identified across the monitoring sites. Seagrass cover varied within and between years. Preliminary evidence indicated that drivers for seagrass variability were climate related. Generally, seagrass abundance increased during the north-west monsoon (Kuki), possibly a consequence of elevated nutrients, lower tidal exposure times, less wind, and higher air temperatures. Low seagrass abundance coincided with the presence of greater winds and longer periods of exposure at low tides during the south-east trade wind season (Sager). No seasonal patterns were apparent when frequency of disturbance from high sedimentation and human impacts was high. Seagrass-Watch has been incorporated in to the Thursday Island High School's Marine Studies Unit ensuring continuity of monitoring. The students, teachers, and other interested individuals involved in Seagrass-Watch have mastered the necessary scientific procedures to monitor seagrass meadows, and developed skills in coordinating a monitoring program and skills in mentoring younger students. This has increased the participants' self-esteem and confidence, and given them an insight into how they may participate in the future management of their sea country.

Structuring of Indo-Pacific fish assemblages along the mangrove-seagrass continuum

Indo-Pacific mangrove swamps and seagrass beds are commonly located in close proximity to each other, often creating complex ecosystems linked by biological and physical processes. Although they are thought to provide important nursery habitats for fish, only limited information exists about their usage by fish outside of estuaries. The present study investigated fish assemblages in non-estuarine intertidal habitats where mangroves and seagrass overlap (the mangrove-seagrass continuum). Three habitats (mangrove, mangrove edge, seagrass) were sampled at 4 sites of the Wakatobi Marine National Park, Indonesia, using underwater visual census. Ninety-one species of fish were observed at a mean density of 130.1 +/- 37.2 ind. 1000 m(-2). Predatory fish (fish that feed on invertebrates and/or fish) were the most dominant feeding groups in the mangroves, whilst omnivores dominated on the mangrove edge and in the seagrass. Although the habitats along the mangrove-seagrass continuum were observed to be important for many fish, only 22 of the 942 coral reef species known within the area utilised mangroves as nursery habitat and only 15 utilised seagrass. Despite finding evidence that nursery grounds in mangroves and seagrass may not directly support high coral reef fish diversity, many of the coral reef nursery species found in this study are likely to be key herbivores or apex predators as adult fish on local coral reefs, and thus highly important to local fisheries. Although mangroves are not permanently inundated by the tide, this study highlights their importance as fish habitats, which at high tide support a greater abundance of fish than seagrass beds. In the light of the high rate of destruction of these habitats, their role in supporting fish assemblages requires consideration in marine resource management programs.

Impacts of a fuel oil spill on seagrass meadows in a subtropical port, Gladstone, Australia - The value of long-term marine habitat monitoring in high risk areas.

We used an established seagrass monitoring programme to examine the short and longer-term impacts of an oil spill event on intertidal seagrass meadows. Results for potentially impacted seagrass areas were compared with existing monitoring data and with control seagrass meadows located outside of the oil spill area. Seagrass meadows were not significantly affected by the oil spill. Declines in seagrass biomass and area 1 month post-spill were consistent between control and impact meadows. Eight months post-spill, seagrass density and area increased to be within historical ranges. The declines in seagrass meadows were likely attributable to natural seasonal variation and a combination of climatic and anthropogenic impacts. The lack of impact from the oil spill was due to several mitigating factors rather than a lack of toxic effects to seagrasses. The study demonstrates the value of long-term monitoring of critical habitats in high risk areas to effectively assess impacts.

Light thresholds derived from seagrass loss in the coastal zone of the northern Great Barrier Reef, Australia

There is a world-wide trend for deteriorating water quality and light levels in the coastal zone, and this has been linked to declines in seagrass abundance. Localized management of seagrass meadow health requires that water quality guidelines for meeting seagrass growth requirements are available. Tropical seagrass meadows are diverse and can be highly dynamic and we have used this dynamism to identify light thresholds in multi-specific meadows dominated by Halodule uninervis in the northern Great Barrier Reef, Australia. Seagrass cover was measured at similar to 3 month intervals from 2008 to 2011 at three sites: Magnetic Island (MI) Dunk Island (DI) and Green Island (GI). Photosynthetically active radiation was continuously measured within the seagrass canopy, and three light metrics were derived. Complete seagrass loss occurred at MI and DI and at these sites changes in seagrass cover were correlated with the three light metrics. Mean daily irradiance (I-d) above 5 and 8.4 mol m(-2) d(-1) was associated with gains in seagrass at MI and DI, however a significant correlation (R = 0.649, p < 0.05) only occurred at MI. The second metric, percent of days below 3 mol m(-2) d(-1), correlated the most strongly (MI, R = -0.714, p < 0.01 and DI, R = -0.859, p = <0.001) with change in seagrass cover with 16-18% of days below 3 mol m(-2) d(-1) being associated with more than 50% seagrass loss. The third metric, the number of hours of light saturated irradiance (H-sat) was calculated using literature-derived data on saturating irradiance (E-k). H-sat correlated well (R = 0.686, p <0.01; and DI, R = 0.704, p < 0.05) with change in seagrass abundance, and was very consistent between the two sites as 4 H-sat was associated with increases in seagrass abundance at both sites, and less than 4 H-sat with more than 50% loss. At the third site (GI), small seasonal losses of seagrass quickly recovered during the growth season and the light metrics did not correlate (p > 0.05) with change in percent cover, except for I-d which was always high, but correlated with change in seagrass cover. Although distinct light thresholds were observed, the departure from threshold values was also important. For example, light levels that are well below the thresholds resulted in more severe loss of seagrass than those just below the threshold. Environmental managers aiming to achieve optimal seagrass growth conditions can use these threshold light metrics as guidelines; however, other environmental conditions, including seasonally varying temperature and nutrient availability, will influence seagrass responses above and below these thresholds. (C) 2012 Published by Elsevier Ltd.

Spatial and temporal variability in midge (Nematocera) assemblages in shallow Finnish lakes (60−70 °N) : community-based modelling of past environmental change

Multi- and intralake datasets of fossil midge assemblages in surface sediments of small shallow lakes in Finland were studied to determine the most important environmental factors explaining trends in midge distribution and abundance. The aim was to develop palaeoenvironmental calibration models for the most important environmental variables for the purpose of reconstructing past environmental conditions. The developed models were applied to three high-resolution fossil midge stratigraphies from southern and eastern Finland to interpret environmental variability over the past 2000 years, with special focus on the Medieval Climate Anomaly (MCA), the Little Ice Age (LIA) and recent anthropogenic changes. The midge-based results were compared with physical properties of the sediment, historical evidence and environmental reconstructions based on diatoms (Bacillariophyta), cladocerans (Crustacea: Cladocera) and tree rings. The results showed that the most important environmental factor controlling midge distribution and abundance along a latitudinal gradient in Finland was the mean July air temperature (TJul). However, when the dataset was environmentally screened to include only pristine lakes, water depth at the sampling site became more important. Furthermore, when the dataset was geographically scaled to southern Finland, hypolimnetic oxygen conditions became the dominant environmental factor. The results from an intralake dataset from eastern Finland showed that the most important environmental factors controlling midge distribution within a lake basin were river contribution, water depth and submerged vegetation patterns. In addition, the results of the intralake dataset showed that the fossil midge assemblages represent fauna that lived in close proximity to the sampling sites, thus enabling the exploration of within-lake gradients in midge assemblages. Importantly, this within-lake heterogeneity in midge assemblages may have effects on midge-based temperature estimations, because samples taken from the deepest point of a lake basin may infer considerably colder temperatures than expected, as shown by the present test results. Therefore, it is suggested here that the samples in fossil midge studies involving shallow boreal lakes should be taken from the sublittoral, where the assemblages are most representative of the whole lake fauna. Transfer functions between midge assemblages and the environmental forcing factors that were significantly related with the assemblages, including mean air TJul, water depth, hypolimnetic oxygen, stream flow and distance to littoral vegetation, were developed using weighted averaging (WA) and weighted averaging-partial least squares (WA-PLS) techniques, which outperformed all the other tested numerical approaches. Application of the models in downcore studies showed mostly consistent trends. Based on the present results, which agreed with previous studies and historical evidence, the Medieval Climate Anomaly between ca. 800 and 1300 AD in eastern Finland was characterized by warm temperature conditions and dry summers, but probably humid winters. The Little Ice Age (LIA) prevailed in southern Finland from ca. 1550 to 1850 AD, with the coldest conditions occurring at ca. 1700 AD, whereas in eastern Finland the cold conditions prevailed over a longer time period, from ca. 1300 until 1900 AD. The recent climatic warming was clearly represented in all of the temperature reconstructions. In the terms of long-term climatology, the present results provide support for the concept that the North Atlantic Oscillation (NAO) index has a positive correlation with winter precipitation and annual temperature and a negative correlation with summer precipitation in eastern Finland. In general, the results indicate a relatively warm climate with dry summers but snowy winters during the MCA and a cool climate with rainy summers and dry winters during the LIA. The results of the present reconstructions and the forthcoming applications of the models can be used in assessments of long-term environmental dynamics to refine the understanding of past environmental reference conditions and natural variability required by environmental scientists, ecologists and policy makers to make decisions concerning the presently occurring global, regional and local changes. The developed midge-based models for temperature, hypolimnetic oxygen, water depth, littoral vegetation shift and stream flow, presented in this thesis, are open for scientific use on request.

Subspace intersection method of high-resolution bearing estimation in shallow ocean using acoustic vector sensors

The subspace intersection method (SIM) provides unbiased bearing estimates of multiple acoustic sources in a range-independent shallow ocean using a one-dimensional search without prior knowledge of source ranges and depths. The original formulation of this method is based on deployment of a horizontal linear array of hydrophones which measure acoustic pressure. In this paper, we extend SIM to an array of acoustic vector sensors which measure pressure as well as all components of particle velocity. Use of vector sensors reduces the minimum number of sensors required by a factor of 4, and also eliminates the constraint that the intersensor spacing should not exceed half wavelength. The additional information provided by the vector sensors leads to performance enhancement in the form of lower estimation error and higher resolution.

Predicting the temporal response of seagrass meadows to dredging using Dynamic Bayesian Networks

Predicting temporal responses of ecosystems to disturbances associated with industrial activities is critical for their management and conservation. However, prediction of ecosystem responses is challenging due to the complexity and potential non-linearities stemming from interactions between system components and multiple environmental drivers. Prediction is particularly difficult for marine ecosystems due to their often highly variable and complex natures and large uncertainties surrounding their dynamic responses. Consequently, current management of such systems often rely on expert judgement and/or complex quantitative models that consider only a subset of the relevant ecological processes. Hence there exists an urgent need for the development of whole-of-systems predictive models to support decision and policy makers in managing complex marine systems in the context of industry based disturbances. This paper presents Dynamic Bayesian Networks (DBNs) for predicting the temporal response of a marine ecosystem to anthropogenic disturbances. The DBN provides a visual representation of the problem domain in terms of factors (parts of the ecosystem) and their relationships. These relationships are quantified via Conditional Probability Tables (CPTs), which estimate the variability and uncertainty in the distribution of each factor. The combination of qualitative visual and quantitative elements in a DBN facilitates the integration of a wide array of data, published and expert knowledge and other models. Such multiple sources are often essential as one single source of information is rarely sufficient to cover the diverse range of factors relevant to a management task. Here, a DBN model is developed for tropical, annual Halophila and temperate, persistent Amphibolis seagrass meadows to inform dredging management and help meet environmental guidelines. Specifically, the impacts of capital (e.g. new port development) and maintenance (e.g. maintaining channel depths in established ports) dredging is evaluated with respect to the risk of permanent loss, defined as no recovery within 5 years (Environmental Protection Agency guidelines). The model is developed using expert knowledge, existing literature, statistical models of environmental light, and experimental data. The model is then demonstrated in a case study through the analysis of a variety of dredging, environmental and seagrass ecosystem recovery scenarios. In spatial zones significantly affected by dredging, such as the zone of moderate impact, shoot density has a very high probability of being driven to zero by capital dredging due to the duration of such dredging. Here, fast growing Halophila species can recover, however, the probability of recovery depends on the presence of seed banks. On the other hand, slow growing Amphibolis meadows have a high probability of suffering permanent loss. However, in the maintenance dredging scenario, due to the shorter duration of dredging, Amphibolis is better able to resist the impacts of dredging. For both types of seagrass meadows, the probability of loss was strongly dependent on the biological and ecological status of the meadow, as well as environmental conditions post-dredging. The ability to predict the ecosystem response under cumulative, non-linear interactions across a complex ecosystem highlights the utility of DBNs for decision support and environmental management.

A shallow water AUV for benthic and water column observations

Autonomous underwater vehicles (AUVs) are becoming commonplace in the study of inshore coastal marine habitats. Combined with shipboard systems, scientists are able to make in-situ measurements of water column and benthic properties. In CSIRO, autonomous gliders are used to collect water column data, while surface vessels are used to collect bathymetry information through the use of swath mapping, bottom grabs, and towed video systems. Although these methods have provided good data coverage for coastal and deep waters beyond 50m, there has been an increasing need for autonomous in-situ sampling in waters less than 50m deep. In addition, the collection of benthic and water column data has been conducted separately, requiring extensive post-processing to combine data streams. As such, a new AUV was developed for in-situ observations of both benthic habitat and water column properties in shallow waters. This paper provides an overview of the Starbug X AUV system, its operational characteristics including vision-based navigation and oceanographic sensor integration.

Support vector machine applied to settlement of shallow foundations on cohesionless soils

The determination of settlement of shallow foundations on cohesionless soil is an important task in geotechnical engineering. Available methods for the determination of settlement are not reliable. In this study, the support vector machine (SVM), a novel type of learning algorithm based on statistical theory, has been used to predict the settlement of shallow foundations on cohesionless soil. SVM uses a regression technique by introducing an ε – insensitive loss function. A thorough sensitive analysis has been made to ascertain which parameters are having maximum influence on settlement. The study shows that SVM has the potential to be a useful and practical tool for prediction of settlement of shallow foundation on cohesionless soil.

Eddy diffusivity: A single dispersion analysis of high resolution drifters in a tidal shallow estuary

In an estuary, mixing and dispersion resulting from turbulence and small scale fluctuation has strong spatio-temporal variability which cannot be resolved in conventional hydrodynamic models while some models employs parameterizations large water bodies. This paper presents small scale diffusivity estimates from high resolution drifters sampled at 10 Hz for periods of about 4 hours to resolve turbulence and shear diffusivity within a tidal shallow estuary (depth < 3 m). Taylor's diffusion theorem forms the basis of a first order estimate for the diffusivity scale. Diffusivity varied between 0.001 – 0.02 m2/s during the flood tide experiment. The diffusivity showed strong dependence (R2 > 0.9) on the horizontal mean velocity within the channel. Enhanced diffusivity caused by shear dispersion resulting from the interaction of large scale flow with the boundary geometries was observed. Turbulence within the shallow channel showed some similarities with the boundary layer flow which include consistency with slope of 5/3 predicted by Kolmogorov's similarity hypothesis within the inertial subrange. The diffusivities scale locally by 4/3 power law following Okubo's scaling and the length scale scales as 3/2 power law of the time scale. The diffusivity scaling herein suggests that the modelling of small scale mixing within tidal shallow estuaries can be approached from classical turbulence scaling upon identifying pertinent parameters.

Plumbing systems of shallow level intrusive complexes

We have come a long way from simple straw and balloon models of magma plumbing systems to a more detailed picture of shallow level intrusive complexes. In this chapter, the sub-volcanic plumbing system is considered in terms of how we can define the types and styles of magma networks from the deep to the shallow subsurface. We look at the plumbing system from large igneous provinces, through rifted systems to polygenetic volcanoes, with a view to characterising some of the key conceptual models. There is a focus on how ancient magmatic centres can help us better understand magmatic plumbing. New innovative ways to consider and quantify magma plumbing are also highlighted including 3D seismic, and using the crystal cargo to help fingerprint key magma plumbing events. Conclusions are drawn to our understanding of the 3D plumbing system and how these recent advances can be helpful when exploring the other chapters of this contribution.