20 resultados para MARINE ECOSYSTEM

em Deakin Research Online - Australia


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Analysis of Permian-Triassic brachiopod diversity and body size changes from different water depths spanning the continental shelf to basinal facies in South China provides insights into the process of environmental deterioration. Comparison of the temporal changes of brachiopod diversity between deepwater and shallow-water facies demonstrates that deepwater brachiopods disappeared earlier than shallow-water brachiopods. This indicates that high environmental stress commenced first in deepwater settings and later extended to shallow waters. This environmental stress is attributed to major volcanic eruptions, which first led to formation of a stratified ocean and a chemocline in the outer shelf and deeper water environments, causing the disappearance of deep marine benthos including brachiopods. The chemocline then rapidly migrated upward and extended to shallow waters, causing widespread mass extinction of shallow marine benthos. We predict that the spatial and temporal patterns of earlier onset of disappearance/extinction and ecological crisis in deeper water ecosystems will be recorded during other episodes of rapid global warming.

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The objective of the work reported in this thesis was to design and implement an ecological effects environmental monitoring program which would: 1) Collect baseline biological information on sessile epibiotic fouling communities from an area adjacent to a petroleum refinery located on Corio Bay, Victoria, to allow comparison with results of future monitoring for the assessment of long term temporal water quality trends. 2) Detect and — if possible - estimate the magnitude of any influence on epibiotic fouling communities within the Corio Bay marine ecosystem attributable to operations at the Shell Petroleum Refinery. 3) Investigate the extent of thermal stratification and rate of dispersal of the petroleum refinery main cooling-water outfall plume (discharging up to 350,000 tonnes of warmed seawater per day), and its effect on epibiotic communities within the EPA-defined mixing zone. A major component of the work undertaken was the design and development of artificial-substrate biological sampling stations suitable for use under the conditions prevailing in Corio Bay, and the development of appropriate quantitative underwater photographic sampling techniques to fulfil the experimental criteria outlined above. Experimental and other constraints imposed on the design of the stations precluded the simple suspension of frames from jetties or pylons, a technique widely used in previous work of this type. Artificial substrate panels were deployed along three radial transects centred within and extending beyond the petroleum refinery main cooling-water mixing zone. Identical substrate panels were deployed at a number of control sites located throughout Corio Bay, each chosen for differences in their degree of exposure to such factors as water movement, depth, shipping traffic and/or comparable industrial activity. The rate of colonisation (space utilisation) and the development of epibiotic fouling communities on artificial substrate panels was monitored over two twelve-month sampling periods using quantitative underwater photographic sampling techniques. Sampling was conducted at 4-8 week intervals with the rate of panel colonisation and community structure determined via coverage measurements. Various species of marine algae, polychaete tubeworms, hydroids, barnacles, simple and colonial ascidians, sponges, bivalve molluscs and encrusting bryozoans were all detected growing on panels. Communities which established on panels within the cooling-water mixing-zone and those at control sites were compared using statistical procedures including agglomerative hierarchical cluster analysis. A photographic sample archive has been established to allow comparison with similar future studies.

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Monitoring marine object is important for understanding the marine ecosystem and evaluating impacts on different environmental changes. One prerequisite of monitoring is to identify targets of interest. Traditionally, the target objects are recognized by trained scientists through towed nets and human observation, which cause much cost and risk to operators and creatures. In comparison, a noninvasive way via setting up a camera and seeking objects in images is more promising. In this paper, a novel technique of object detection in images is presented, which is applicable to generic objects. A robust background modelling algorithm is proposed to extract foregrounds and then blob features are introduced to classify foregrounds. Particular marine objects, box jellyfish and sea snake, are successfully detected in our work. Experiments conducted on image datasets collected by the Australian Institute of Marine Science (AIMS) demonstrate the effectiveness of the proposed technique.

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This thesis is the first study to examine the interaction between estuarine discharge and coastal environments, for intermittent estuaries in Victoria. The study examined water quality, bacteria and seaweed communities and the diet of mussels, concluding that estuarine discharge is an important driver for the productivity of nearshore marine environments.

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Agricultural discharge of herbicides to the Great Barrier Reef (GBR) poses significant threat to the marine ecosystem. This study evaluates the performance of a hybrid treatment system consists of a membrane bioreactor (MBR), UV disinfection unit and a granular activated carbon (GAC) column in treating Ametryn which is one of the major herbicides in agricultural discharges. While the MBR alone removes only 40% of Ametryn at a hydraulic retention time of 7.8 hours, the hybrid system removed Ametryn to below detection levels.

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Agricultural discharge of herbicides to the Great Barrier Reef (GBR) poses significant threat to the marine ecosystem. This study evaluates the performance of a hybrid treatment system consists of a membrane bioreactor (MBR), UV disinfection unit and a granular activated carbon (GAC) column in treating ametryn which is one of the major herbicides in agricultural discharges. While the MBR alone removes only 40% of ametryn at a hydraulic retention time of 7.8 h, the hybrid system removed ametryn to below detection levels.

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Long-distance migrations are among the wonders of the natural world, but this multi-taxon review shows that the characteristics of species that undertake such movements appear to make them particularly vulnerable to detrimental impacts of climate change. Migrants are key components of biological systems in high latitude regions, where the speed and magnitude of climate change impacts are greatest. They also rely on highly productive seasonal habitats, including wetlands and ocean upwellings that, with climate change, may become less food-rich and predictable in space and time. While migrants are adapted to adjust their behaviour with annual changes in the weather, the decoupling of climatic variables between geographically separate breeding and non-breeding grounds is beginning to result in mistimed migration. Furthermore, human land-use and activity patterns will constrain the ability of many species to modify their migratory routes and may increase the stress induced by climate change. Adapting conservation strategies for migrants in the light of climate change will require substantial shifts in site designation policies, flexibility of management strategies and the integration of forward planning for both people and wildlife. While adaptation to changes may be feasible for some terrestrial systems, wildlife in the marine ecosystem may be more dependent on the degree of climate change mitigation that is achievable.

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 Changes in cellular structure in Antarctic Rock-cod signified biological impact of untreated human wastewater on the marine ecosystem at Davis Station, East Antarctica. Based on these alterations a Histological Health Index was developed to identify and compare changes in fish health correlated to the degree of wastewater exposure. The health index provides a risk assessment tool applicable for all Antarctic Treaty research stations.

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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 km2 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.

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The application of the 'ecosystem approach' to marine conservation management demands knowledge of the distribution patterns of the target species or communities. This information is commonly obtained from species distribution models (SDMs). This article explores an important but rarely acknowledged assumption in these models: almost all species may be present, but simply not detected by the particular survey method. However, nearly all of these SDM approaches neglect this important characteristic. This leads to the violation of a fundamental assumption of these models, which presuppose the detection of a species is equal to one (i.e. at each survey locality, a species is perfectly detected). In this article, the concept of imperfect detection is discussed, how it potentially influences the prediction of species' distributions is examined, and some statistical methods that could be used to incorporate the detection probability of species in estimates of their distribution are suggested. The approaches discussed here could improve the collection and interpretation of marine biological survey data and provide a coherent way to incorporate detection probability estimates in the modelling of species distributions. This will ultimately lead to an unbiased and more rigorous understanding of the distribution of species in the marine environment.

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Diel vertical migration (DVM) by zooplankton is a universal feature in all the World's oceans, as well as being common in freshwater environments. The normal pattern involves movement from shallow depths at night to greater depths during the day. For many herbivorous and omnivorous mesozooplankton that feed predominantly near the surface on phytoplankton and microzooplankton, minimising the risk of predation from fish seems to be the ultimate factor behind DVM. These migrants appear to use deep water as a dark daytime refuge where their probability of being detected and eaten is lower than if they remained near the surface. Associated with these vertical movements of mesozooplankton, predators at higher trophic levels, including invertebrates, fish, marine mammals, birds and reptiles, may modify their behaviour to optimise the exploitation of their vertically migrating prey. Recent advances in biotelemetry promise to allow the interaction between migrating zooplankton and diving air-breathing vertebrates to be explored in far more detail than hitherto.

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Marine diatoms and dinoflagellates play a variety of key ecosystem roles as important primary producers (diatoms and some dinoflagellates) and grazers (some dinoflagellates). Additionally some are harmful algal bloom (HAB) species and there is widespread concern that HAB species may be increasing accompanied by major negative socio-economic impacts, including threats to human health and marine harvesting1, 2. Using 92,263 samples from the Continuous Plankton Recorder survey, we generated a 50-year (1960–2009) time series of diatom and dinoflagellate occurrence in the northeast Atlantic and North Sea. Dinoflagellates, including both HAB taxa (for example, Prorocentrum spp.) and non-HAB taxa (for example, Ceratium furca), have declined in abundance, particularly since 2006. In contrast, diatom abundance has not shown this decline with some common diatoms, including both HAB (for example, Pseudo-nitzschia spp.) and non-HAB (for example, Thalassiosira spp.) taxa, increasing in abundance. Overall these changes have led to a marked increase in the relative abundance of diatoms versus dinoflagellates. Our analyses, including Granger tests to identify criteria of causality, indicate that this switch is driven by an interaction effect of both increasing sea surface temperatures combined with increasingly windy conditions in summer.

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Monitoring the abundance and distribution of taxa is essential to assess their contribution to ecosystem processes. For marine taxa that are difficult to study or have long been perceived of little ecological importance, quantitative information is often lacking. This is the case for jellyfish (medusae and other gelatinous plankton). In the present work, 4 years of scyphomedusae by-catch data from the 2007-2010 Irish Sea juvenile gadoid fish survey were analysed with three main objectives: (1) to provide quantitative and spatially-explicit species-specific biomass data, for a region known to have an increasing trend in jellyfish abundance; (2) to investigate whether year-to-year changes in catch-biomass are due to changes in the numbers or in the size of medusa (assessed as the mean mass per individual), and (3) to determine whether inter-annual variation patterns are consistent between species and water masses. Scyphomedusae were present in 97% of samples (N=306). Their overall annual median catch-biomass ranged from 0.19 to 0.92gm-3 (or 8.6 to 42.4gm-2). Aurelia aurita and Cyanea spp. (Cyanea lamarckii and Cyanea capillata) made up 77.7% and 21.5% of the total catch-biomass respectively, but species contributions varied greatly between sub-regions and years. No consistent pattern was detected between the distribution and inter-annual variations of the two genera, and contrasting inter-annual patterns emerged when considering abundance either as biomass or as density. Significantly, A.aurita medusae were heavier in stratified than in mixed waters, which we hypothesize may be linked to differences in timing and yield of primary and secondary productions between water masses. These results show the vulnerability of time-series from bycatch datasets to phenological changes and highlight the importance of taking species- and population-specific distribution patterns into account when integrating jellyfish into ecosystem models.

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Here, we evaluated the potential of using bathymetric Light Detection and Ranging (LiDAR) to characterise shallow water (<30 m) benthic habitats of high energy subtidal coastal environments. Habitat classification, quantifying benthic substrata and macroalgal communities, was achieved in this study with the application of LiDAR and underwater video groundtruth data using automated classification techniques. Bathymetry and reflectance datasets were used to produce secondary terrain derivative surfaces (e.g., rugosity, aspect) that were assumed to influence benthic patterns observed. An automated decision tree classification approach using the Quick Unbiased Efficient Statistical Tree (QUEST) was applied to produce substrata, biological and canopy structure habitat maps of the study area. Error assessment indicated that habitat maps produced were primarily accurate (>70%), with varying results for the classification of individual habitat classes; for instance, producer accuracy for mixed brown algae and sediment substrata, was 74% and 93%, respectively. LiDAR was also successful for differentiating canopy structure of macroalgae communities (i.e., canopy structure classification), such as canopy forming kelp versus erect fine branching algae. In conclusion, habitat characterisation using bathymetric LiDAR provides a unique potential to collect baseline information about biological assemblages and, hence, potential reef connectivity over large areas beyond the range of direct observation. This research contributes a new perspective for assessing the structure of subtidal coastal ecosystems, providing a novel tool for the research and management of such highly dynamic marine environments. © 2014 by the authors; licensee MDPI, Basel, Switzerland.