The role of dissolved organic matter bioavailability in promoting phytoplankton blooms in Florida Bay

The clear, shallow, oligotrophic waters of Florida Bay are characterized by low phytoplankton biomass, yet periodic cyanobacteria and diatom blooms do occur. We hypothesized that allochthonous dissolved organic matter (DOM) was providing a subsidy to the system in the form of bound nutrients. Water from four bay sites was incubated under natural light and dark conditions with enrichments of either DOM ( > 1 kD, 2×DOM) or inorganic nutrients (N+P). Samples were analyzed for bacterial numbers, bacterial production, phytoplankton biomass, phytoplankton community structure, and production, nutrients, and alkaline phosphatase (AP) activity. The influence of 2×DOM enrichment on phytoplankton biomass developed slowly during the incubations and was relatively small compared to nutrient additions. Inorganic nutrient additions resulted in an ephemeral bloom characterized initially as cyanobacterial and brown algae but which changed to dinoflagellate and/or brown algae by day six. The DIN:TP ratio decreased 10-fold in the N+P treatments as the system progressed towards N limitation. This ratio did not change significantly for 2×DOM treatments. In addition, these experiments indicated that both autotrophic and heterotrophic microbial populations in Florida Bay may fluctuate in their limitation by organic and inorganic nutrient availability. Both N+P and 2×DOM enrichments revealed significant and positive response in bioavailability of dissolved organic carbon (BDOC). Potential BDOC ranged from 1.1 to 35.5%, with the most labile forms occurring in Whipray Basin. BDOC at all sites was stimulated by the 2×DOM addition. Except for Duck Key, BDOC at all sites was also stimulated by the addition of N+P. BDOC was lower in the dry season than in the wet season (5.56% vs. 16.86%). This may be explained by the distinct chemical characteristics of the DOM produced at different times of year. Thus, both the heterotrophic and autotrophic microbial communities in Florida Bay are modulated by bioavailability of DOM. This has ramifications for the fate of DOM from the Everglades inputs, implicating DOM bioavailability as a contributing factor in regulating the onset, persistence, and composition of phytoplankton blooms.

Potential role of sponge communities in controlling phytoplankton blooms in Florida Bay

An unprecedented series of ecological disturbances have been recurring within Florida Bay since the summer of 1987. Persistent and widespread phytoplankton and cyanobacteria blooms have coincided with the large scale decimation of sponge communities. One hypothesis is that the large scale loss of suspension-feeding sponges has rendered the Florida Bay ecosystem susceptible to these recurring blooms. The primary objective of this study was to experimentally evaluate the potential for suspension-feeding sponges to control nuisance phytoplankton blooms within Florida Bay prior to a large sponge die-off event. To achieve this objective, we determined the extent and biomass of the surviving sponge community in the different basins of Florida Bay. Many areas within Florida Bay possessed sponge densities and biomasses of 1 to 3 ind. m–2 or 100 to 300 g m–2 respectively. The dominant species includedSpheciospongia vesparia, Chondrilla nucula, Cinachyra alloclada, Tedania ignis and Ircinia sp., which accounted for 68% of individual sponges observed and 88% of sponge biomass. Laboratory grazing rates of these dominant sponges were experimentally determined on 4 different algal food treatments: a monoculture of cyanobacteria Synechococcus elongatus, a monoculture of the diatom Cyclotella choctawhatcheeana, a monoculture of the dinoflagellate Prorocentrum hoffmanianum, and an equal volume of the 3 monocultures combined. To estimate the impact of a mass sponge mortality event on the system-wide filtration rate of Florida Bay, we combined estimates of the current sponge biomass and laboratory sponge filtration rates with estimates of mean volumes of the sub-basins of Florida Bay. This study implies that the current blooms occurring within the central region of Florida Bay can be explained by the loss of the dominant suspension feeder in this system, and there is no need to invoke a new addition of nutrients within this region for the blooms to occur.

Contribution of lipophilic secondary metabolites to the toxicity of strains of freshwater cyanobacterial harmful algal blooms, identified using the zebrafish (Danio rerio) embryo as a model for vertebrate development

Cyanobacteria ("blue-green algae") are known to produce a diverse repertoire of biologically active secondary metabolites. When associated with so-called "harmful algal blooms", particularly in freshwater systems, a number of these metabolites have been associated—as "toxins", or commonly "cyanotoxins"—with human and animal health concerns. In addition to the known water-soluble toxins from these genera (i.e. microcystins, cylindrospermopsin, and saxitoxins), our studies have shown that there are metabolites within the lipophilic extracts of these strains that inhibit vertebrate development in zebrafish embryos. Following these studies, the zebrafish embryo model was implemented in the bioassay-guided purification of four isolates of cyanobacterial harmful algal blooms, namely Aphanizomenon, two isolates of Cylindrospermopsis, and Microcystis, in order to identify and chemically characterize the bioactive lipophilic metabolites in these isolates. ^ We have recently isolated a group of polymethoxy-1-alkenes (PMAs), as potential toxins, based on the bioactivity observed in the zebrafish embryos. Although PMAs have been previously isolated from diverse cyanobacteria, they have not previously been associated with relevant toxicity. These compounds seem to be widespread across the different genera of cyanobacteria, and, according to our studies, suggested to be derived from the polyketide biosynthetic pathway which is a common synthetic route for cyanobacterial and other algal toxins. Thus, it can be argued that these metabolites are perhaps important contributors to the toxicity of cyanobacterial blooms. In addition to the PMAs, a set of bioactive glycosidic carotenoids were also isolated because of their inhibition of zebrafish embryonic development. These pigmented organic molecules are found in many photosynthetic organisms, including cyanobacteria, and they have been largely associated with the prevention of photooxidative damage. This is the first indication of these compounds as toxic metabolites and the hypothesized mode of action is via their biotransformation to retinoids, some of which are known to be teratogenic. Additional fractions within all four isolates have been shown to contain other uncharacterized lipophilic toxic metabolites. This apparent repertoire of lipophilic compounds may contribute to the toxicity of these cyanobacterial harmful algal blooms, which were previously attributed primarily to the presence of the known water-soluble toxins.^

Human-driven benthic jellyfish blooms: Causes and consequences for coastal marine ecosystems

Coastal marine ecosystems are among the most impacted globally, attributable to individual and cumulative effects of human disturbance. Anthropogenic nutrient loading is one stressor that commonly affects nearshore ecosystems, including seagrass beds, and has positive and negative effects on the structure and function of coastal systems. An additional, previously unexplored mechanistic pathway through which nutrients may indirectly influence nearshore systems is by driving blooms of benthic jellyfish. My dissertation research, conducted on Abaco Island, Bahamas, focused on elucidating the role that benthic jellyfish have in structuring systems in which they are common (i.e., seagrass beds), and explored mechanistic processes that may drive blooms of this taxa. ^ To establish that human disturbances (e.g., elevated nutrient availability) may drive increased abundance and size of benthic jellyfish, Cassiopea spp., I conducted surveys in human-impacted and unimpacted coastal sites. Jellyfish were more abundant (and larger) from human-impacted areas, positively correlated to elevated nutrient availability. In order to elucidate mechanisms linking Cassiopea spp. with elevated nutrients, I evaluated whether zooxanthellae from Cassiopea were higher from human-disturbed systems, and whether Cassiopea exhibited increased size following nutrient input. I demonstrated that zooxanthellae population densities were elevated in human-impacted sites, and that nutrients led to positive jellyfish growth. ^ As heightened densities of Cassiopea jellyfish may exert top-down and bottom-up controls on flora and fauna in impacted seagrass beds, I sought to examine ecological responses to Cassiopea. I evaluated whether there was a relationship between high Cassiopea densities and lower benthic fauna abundance and diversity in shallow seagrass beds. I found that Cassiopea have subtle effects on benthic fauna. However, through an experiment conducted in a seagrass bed in which nutrients and Cassiopea were added, I demonstrated that Cassiopea can result in seagrass habitat modification, with negative consequences for benthic fauna. ^ My dissertation research demonstrates that increased human-driven benthic jellyfish densities may have indirect and direct effects on flora and fauna of coastal marine systems. This knowledge will advance our understanding of how human disturbances shift species interactions in coastal ecosystems, and will be critical for effective management of jellyfish blooms.^

Human-driven Benthic Jellyfish Blooms: Causes and Consequences for Coastal Marine Ecosystems

Coastal marine ecosystems are among the most impacted globally, attributable to individual and cumulative effects of human disturbance. Anthropogenic nutrient loading is one stressor that commonly affects nearshore ecosystems, including seagrass beds, and has positive and negative effects on the structure and function of coastal systems. An additional, previously unexplored mechanistic pathway through which nutrients may indirectly influence nearshore systems is by driving blooms of benthic jellyfish. My dissertation research, conducted on Abaco Island, Bahamas, focused on elucidating the role that benthic jellyfish have in structuring systems in which they are common (i.e., seagrass beds), and explored mechanistic processes that may drive blooms of this taxa. To establish that human disturbances (e.g., elevated nutrient availability) may drive increased abundance and size of benthic jellyfish, Cassiopea spp., I conducted surveys in human-impacted and unimpacted coastal sites. Jellyfish were more abundant (and larger) from human-impacted areas, positively correlated to elevated nutrient availability. In order to elucidate mechanisms linking Cassiopea spp. with elevated nutrients, I evaluated whether zooxanthellae from Cassiopea were higher from human-disturbed systems, and whether Cassiopea exhibited increased size following nutrient input. I demonstrated that zooxanthellae population densities were elevated in human-impacted sites, and that nutrients led to positive jellyfish growth. As heightened densities of Cassiopea jellyfish may exert top-down and bottom-up controls on flora and fauna in impacted seagrass beds, I sought to examine ecological responses to Cassiopea. I evaluated whether there was a relationship between high Cassiopea densities and lower benthic fauna abundance and diversity in shallow seagrass beds. I found that Cassiopea have subtle effects on benthic fauna. However, through an experiment conducted in a seagrass bed in which nutrients and Cassiopea were added, I demonstrated that Cassiopea can result in seagrass habitat modification, with negative consequences for benthic fauna. My dissertation research demonstrates that increased human-driven benthic jellyfish densities may have indirect and direct effects on flora and fauna of coastal marine systems. This knowledge will advance our understanding of how human disturbances shift species interactions in coastal ecosystems, and will be critical for effective management of jellyfish blooms.

Changes in the annual harmful algal blooms of Alexandrium minutum : effects of environmental conditions and drainage basin inputs in the Rance estuary (Brittany, France)

Time series of physico-chemical data and concentrations (cell L-1) of the toxic dinoflagellate Alexandrium minutum collected in the Rance macrotidal estuary (Brittany, France) were analyzed to understand the physico-chemical processes of the estuary and their relation to changes in bloom development from 1996 to 2009. The construction of the tidal power plant in the north and the presence of a lock in the south have greatly altered hydrodynamics, blocking the zone of maximum turbidity upstream, in the narrowest part of the estuary. Alexandrium minutum occurs in the middle part of the estuary. Most physical and chemical parameters of the Rance estuary are similar to those observed elsewhere in Brittany with water temperatures between 15–18 °C, slightly lowered salinities (31.8–33.1 PSU), low river flow rates upstream and significant solar radiation (8 h day-1). A notable exception is phosphate input from the drainage basin which seems to limit bloom development: in recent years, bloom decline can be significantly correlated with the decrease in phosphate input. On the other hand, the chemical processes occurring in the freshwater-saltwater interface do not seem to have an influence on these occurrences. The other hypotheses for bloom declines are discussed, including the prevalence of parasitism, but remain to be verified in further studies.

Integrating science through Bayesian Belief Networks : case study of Lyngbya in Moreton Bay

Bayesian Belief Networks (BBNs) are emerging as valuable tools for investigating complex ecological problems. In a BBN, the important variables in a problem are identified and causal relationships are represented graphically. Underpinning this is the probabilistic framework in which variables can take on a finite range of mutually exclusive states. Associated with each variable is a conditional probability table (CPT), showing the probability of a variable attaining each of its possible states conditioned on all possible combinations of it parents. Whilst the variables (nodes) are connected, the CPT attached to each node can be quantified independently. This allows each variable to be populated with the best data available, including expert opinion, simulation results or observed data. It also allows the information to be easily updated as better data become available ----- ----- This paper reports on the process of developing a BBN to better understand the initial rapid growth phase (initiation) of a marine cyanobacterium, Lyngbya majuscula, in Moreton Bay, Queensland. Anecdotal evidence suggests that Lyngbya blooms in this region have increased in severity and extent over the past decade. Lyngbya has been associated with acute dermatitis and a range of other health problems in humans. Blooms have been linked to ecosystem degradation and have also damaged commercial and recreational fisheries. However, the causes of blooms are as yet poorly understood.

Bayesian model averaging for harmful algal bloom prediction

Harmful Algal Blooms (HABs) are a worldwide problem that have been increasing in frequency and extent over the past several decades. HABs severely damage aquatic ecosystems by destroying benthic habitat, reducing invertebrate and fish populations and affecting larger species such as dugong that rely on seagrasses for food. Few statistical models for predicting HAB occurrences have been developed, and in common with most predictive models in ecology, those that have been developed do not fully account for uncertainties in parameters and model structure. This makes management decisions based on these predictions more risky than might be supposed. We used a probit time series model and Bayesian Model Averaging (BMA) to predict occurrences of blooms of Lyngbya majuscula, a toxic cyanophyte, in Deception Bay, Queensland, Australia. We found a suite of useful predictors for HAB occurrence, with Temperature figuring prominently in models with the majority of posterior support, and a model consisting of the single covariate average monthly minimum temperature showed by far the greatest posterior support. A comparison of alternative model averaging strategies was made with one strategy using the full posterior distribution and a simpler approach that utilised the majority of the posterior distribution for predictions but with vastly fewer models. Both BMA approaches showed excellent predictive performance with little difference in their predictive capacity. Applications of BMA are still rare in ecology, particularly in management settings. This study demonstrates the power of BMA as an important management tool that is capable of high predictive performance while fully accounting for both parameter and model uncertainty.

An extended CDIO syllabus framework with preparatory engineering proficiencies

The CDIO Initiative has been globally recognised as an enabler for engineering education reform. With the CDIO process, the CDIO Standards and the CDIO Syllabus, many scholarly contributions have been made around cultural change, curriculum reform and learning environments. In the Australasian region, reform is gaining significant momentum within the engineering education community, the profession, and higher education institutions. This paper presents the CDIO Syllabus cast into the Australian context by mapping it to the Engineers Australia Graduate Attributes, the Washington Accord Graduate Attributes and the Queensland University of Technology Graduate Capabilities. Furthermore, in recognition that many secondary schools and technical training institutions offer introductory engineering technology subjects, this paper presents an extended self-rating framework suited for recognising developing levels of proficiency at a preparatory level. The framework is consistent with conventional application to undergraduate programs and professional practice, but adapted for the preparatory context. As with the original CDIO framework with proficiency levels, this extended framework is informed by Bloom’s Educational Objectives. A proficiency evaluation of Queensland Study Authority’s Engineering Technology senior syllabus is demonstrated indicating proficiency levels embedded within this secondary school subject within a preparatory scope. Through this extended CDIO framework, students and faculty have greater awareness and access to tools to promote (i) student engagement in their own graduate capability development, (ii) faculty engagement in course and program design, through greater transparency and utility of the continuum of graduate capability development with associate levels of proficiency, and the context in which they exist in terms of pre-tertiary engineering studies; and (iii) course maintenance and quality audit methodology for the purpose of continuous improvement processes and program accreditation.

Integrated Bayesian network frameworks for modelling complex ecological issues

Ecological problems are typically multi faceted and need to be addressed from a scientific and a management perspective. There is a wealth of modelling and simulation software available, each designed to address a particular aspect of the issue of concern. Choosing the appropriate tool, making sense of the disparate outputs, and taking decisions when little or no empirical data is available, are everyday challenges facing the ecologist and environmental manager. Bayesian Networks provide a statistical modelling framework that enables analysis and integration of information in its own right as well as integration of a variety of models addressing different aspects of a common overall problem. There has been increased interest in the use of BNs to model environmental systems and issues of concern. However, the development of more sophisticated BNs, utilising dynamic and object oriented (OO) features, is still at the frontier of ecological research. Such features are particularly appealing in an ecological context, since the underlying facts are often spatial and temporal in nature. This thesis focuses on an integrated BN approach which facilitates OO modelling. Our research devises a new heuristic method, the Iterative Bayesian Network Development Cycle (IBNDC), for the development of BN models within a multi-field and multi-expert context. Expert elicitation is a popular method used to quantify BNs when data is sparse, but expert knowledge is abundant. The resulting BNs need to be substantiated and validated taking this uncertainty into account. Our research demonstrates the application of the IBNDC approach to support these aspects of BN modelling. The complex nature of environmental issues makes them ideal case studies for the proposed integrated approach to modelling. Moreover, they lend themselves to a series of integrated sub-networks describing different scientific components, combining scientific and management perspectives, or pooling similar contributions developed in different locations by different research groups. In southern Africa the two largest free-ranging cheetah (Acinonyx jubatus) populations are in Namibia and Botswana, where the majority of cheetahs are located outside protected areas. Consequently, cheetah conservation in these two countries is focussed primarily on the free-ranging populations as well as the mitigation of conflict between humans and cheetahs. In contrast, in neighbouring South Africa, the majority of cheetahs are found in fenced reserves. Nonetheless, conflict between humans and cheetahs remains an issue here. Conservation effort in South Africa is also focussed on managing the geographically isolated cheetah populations as one large meta-population. Relocation is one option among a suite of tools used to resolve human-cheetah conflict in southern Africa. Successfully relocating captured problem cheetahs, and maintaining a viable free-ranging cheetah population, are two environmental issues in cheetah conservation forming the first case study in this thesis. The second case study involves the initiation of blooms of Lyngbya majuscula, a blue-green algae, in Deception Bay, Australia. L. majuscula is a toxic algal bloom which has severe health, ecological and economic impacts on the community located in the vicinity of this algal bloom. Deception Bay is an important tourist destination with its proximity to Brisbane, Australia’s third largest city. Lyngbya is one of several algae considered to be a Harmful Algal Bloom (HAB). This group of algae includes other widespread blooms such as red tides. The occurrence of Lyngbya blooms is not a local phenomenon, but blooms of this toxic weed occur in coastal waters worldwide. With the increase in frequency and extent of these HAB blooms, it is important to gain a better understanding of the underlying factors contributing to the initiation and sustenance of these blooms. This knowledge will contribute to better management practices and the identification of those management actions which could prevent or diminish the severity of these blooms.