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.

Modeling the viability of the free-ranging cheetah population in Namibia : an object-oriented Bayesian network approach

Conservation of free-ranging cheetah (Acinonyx jubatus) populations is multi faceted and needs to be addressed from an ecological, biological and management perspective. There is a wealth of published research, each focusing on a particular aspect of cheetah conservation. Identifying the most important factors, making sense of various (and sometimes contrasting) findings, and taking decisions when little or no empirical data is available, are everyday challenges facing conservationists. Bayesian networks (BN) provide a statistical modeling framework that enables analysis and integration of information addressing different aspects of conservation. There has been an increased interest in the use of BNs to model conservation issues, however the development of more sophisticated BNs, utilizing object-oriented (OO) features, is still at the frontier of ecological research. We describe an integrated, parallel modeling process followed during a BN modeling workshop held in Namibia to combine expert knowledge and data about free-ranging cheetahs. The aim of the workshop was to obtain a more comprehensive view of the current viability of the free-ranging cheetah population in Namibia, and to predict the effect different scenarios may have on the future viability of this free-ranging cheetah population. Furthermore, a complementary aim was to identify influential parameters of the model to more effectively target those parameters having the greatest impact on population viability. The BN was developed by aggregating diverse perspectives from local and independent scientists, agents from the national ministry, conservation agency members and local fieldworkers. This integrated BN approach facilitates OO modeling in a multi-expert context which lends itself to a series of integrated, yet independent, subnetworks describing different scientific and management components. We created three subnetworks in parallel: a biological, ecological and human factors network, which were then combined to create a complete representation of free-ranging cheetah population viability. Such OOBNs have widespread relevance to the effective and targeted conservation management of vulnerable and endangered species.

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.

A preliminary study on the mechanism of harmful algal bloom mitigation by use of sophorolipid treatment

in order to investigate a new method of mitigating the deleterious effect of harmful algal blooms (HABs), the inhibition of the glycolipid biosurfactant sophorolipid on three common harmful algae Alexandrium tamarense, Heterosigma akashiwo and Cochlodinium polykrikoides was studied. The optimum preparation condition for sophorolipid, the inhibition capability of sophorolipid and the interaction mechanism of sophorolipid on the three algal species were investigated. Results showed that sophorolipid prepared by extraction with ethyl acetate exhibited the most prominent inhibition effect and that storage time of one year had little influence on the inhibition effect of sophorolipid. The optimum concentration of 10-20 mg/l sophorolipid inhibited the motility of about 90% of the tested harmful algal cells without recovery. Investigation of the algicidal process revealed that sophorolipid induced ecdysis of A. tamarense, quick lysis of H. akashiwo and swelling of C. polykrikoides in a relatively short time. Investigation of the nucleotides showed that more than 15% of the nucleotides were released from the cytoplasm under the effect of 10-20 mg/l sophorolipid, indicating the irreversible damage on the cellular membrane, which resulted in the disintegration of the harmful algal cells. (C) 2004 Elsevier B.V. All rights reserved.

Vulnerability of coastal ecosystems to changes in harmful algal bloom distribution in response to climate change: projections based on model analysis

Harmful algal blooms (HABs), those proliferations of algae that can cause fish kills, contaminate seafood with toxins, form unsightly scums, or detrimentally alter ecosystem function have been increasing in frequency, magnitude, and duration worldwide. Here, using a global modeling approach, we show, for three regions of the globe, the potential effects of nutrient loading and climate change for two HAB genera, pelagic Prorocentrum and Karenia, each with differing physiological characteristics for growth. The projections (end of century, 2090-2100) are based on climate change resulting from the A1B scenario of the Intergovernmental Panel on Climate Change Institut Pierre Simon Laplace Climate Model (IPCC, IPSL-CM4), applied in a coupled oceanographic-biogeochemical model, combined with a suite of assumed physiological 'rules' for genera-specific bloom development. Based on these models, an expansion in area and/or number of months annually conducive to development of these HABs along the NW European Shelf-Baltic Sea system and NE Asia was projected for both HAB genera, but no expansion (Prorocentrum spp.), or actual contraction in area and months conducive for blooms (Karenia spp.), was projected in the SE Asian domain. The implications of these projections, especially for Northern Europe, are shifts in vulnerability of coastal systems to HAB events, increased regional HAB impacts to aquaculture, increased risks to human health and ecosystems, and economic consequences of these events due to losses to fisheries and ecosystem services.

Design and implementation of sensor networks for the observation and research of harmful algal blooms in southern California coastal waters

Harmful Algal Blooms (HABs) have become an important environmental concern along the western coast of the United States. Toxic and noxious blooms adversely impact the economies of coastal communities in the region, pose risks to human health, and cause mortality events that have resulted in the deaths of thousands of fish, marine mammals and seabirds. One goal of field-based research efforts on this topic is the development of predictive models of HABs that would enable rapid response, mitigation and ultimately prevention of these events. In turn, these objectives are predicated on understanding the environmental conditions that stimulate these transient phenomena. An embedded sensor network (Fig. 1), under development in the San Pedro Shelf region off the Southern California coast, is providing tools for acquiring chemical, physical and biological data at high temporal and spatial resolution to help document the emergence and persistence of HAB events, supporting the design and testing of predictive models, and providing contextual information for experimental studies designed to reveal the environmental conditions promoting HABs. The sensor platforms contained within this network include pier-based sensor arrays, ocean moorings, HF radar stations, along with mobile sensor nodes in the form of surface and subsurface autonomous vehicles. FreewaveTM radio modems facilitate network communication and form a minimally-intrusive, wireless communication infrastructure throughout the Southern California coastal region, allowing rapid and cost-effective data transfer. An emerging focus of this project is the incorporation of a predictive ocean model that assimilates near-real time, in situ data from deployed Autonomous Underwater Vehicles (AUVs). The model then assimilates the data to increase the skill of both nowcasts and forecasts, thus providing insight into bloom initiation as well as the movement of blooms or other oceanic features of interest (e.g., thermoclines, fronts, river discharge, etc.). From these predictions, deployed mobile sensors can be tasked to track a designated feature. This focus has led to the creation of a technology chain in which algorithms are being implemented for the innovative trajectory design for AUVs. Such intelligent mission planning is required to maneuver a vehicle to precise depths and locations that are the sites of active blooms, or physical/chemical features that might be sources of bloom initiation or persistence. The embedded network yields high-resolution, temporal and spatial measurements of pertinent environmental parameters and resulting biology (see Fig. 1). Supplementing this with ocean current information and remotely sensed imagery and meteorological data, we obtain a comprehensive foundation for developing a fundamental understanding of HAB events. This then directs labor- intensive and costly sampling efforts and analyses. Additionally, we provide coastal municipalities, managers and state agencies with detailed information to aid their efforts in providing responsible environmental stewardship of their coastal waters.

Harmful algal bloom management and response: assessment and plan

This report, "Harmful Algal Bloom Management and Response: Assessment and Plan" reviews and evaluates Harmful Algal Bloom (HAB) management and response efforts, identifies current prevention, control, and mitigation programs for HABs, and presents an innovative research, event response, and infrastructure development plan for advancing the response to HABs. In December 2004, Congress enacted and the President signed into law the Harmful Algal Bloom and Hypoxia Amendments Act of 2004, (HABHRCA 2004). The reauthorization of HABHRCA acknowledged that HABs are one of the most scientifically complex and economically damaging coastal issues challenging our ability to safeguard the health of our Nation’s coastal ecosystems. The Administration further recognized the importance of HABs as a high priority national issue by specifically calling for the implementation of HABHRCA in the President’s U.S. Ocean Action Plan. HABHRCA 2004 requires four reports to assess and recommend research programs on HABs in U.S. waters. This document comprises two linked reports specifically aimed at improving HAB management and response: the Prediction and Response Report and the follow-up plan, the National Scientific Research, Development, Demonstration, and Technology Transfer (RDDTT) Plan on Reducing Impacts from Harmful Algal Blooms. This document was prepared by the Interagency Working Group on Harmful Algal Blooms, Hypoxia, and Human Health, which was chartered through the Joint Subcommittee on Ocean Science and Technology of the National Science and Technology Council and the Interagency Committee on Ocean Science and Resource Management Integration. This report complements and expands upon HAB-related priorities identified in Charting the Course for Ocean Science in the United States for the Next Decade: An Ocean Research Priorities Plan and Implementation Strategy, recently released by the Joint Subcommittee on Ocean Science and Technology. It draws from the contributions of numerous experts and stakeholders from federal, state, and local governments, academia, industry, and non-governmental organizations through direct contributions, previous reports and planning efforts, a public comment period, and a workshop convened to develop strategies for a HAB management and response plan. Given the importance of the Nation’s coastal ocean, estuaries, and inland waters to our quality of life, our culture, and the economy, it is imperative that we move forward to better understand and mitigate the impacts of HABs which threaten all of our coasts and inland waters. This report is an effort to assess the extent of federal, state and local efforts to predict and respond to HAB events and to identify opportunities for charting a way forward.

Food Consumption by In Situ Pen-Cultured Planktivorous Fishes and Effects on an Algal Bloom in Lake Taihu, China

Silver carp (Hypophthalmichthys molitrix) and bighead carp (Aristichthys nobilis) were used as a new pen-cultureed biomanipulation technique to control algal blooms in Meiliang Bay of Lake Taihu. In order to evaluate the capacity of these two fishes to decrease algal blooms, diel feeding samplings were carried out in May (without algal blooms) and September (with algal blooms) in 2005. Based on estimated food consumption by the Elliott-Persson model, silver carp increased daily food consumption from 2.07 g dry weight per 100 g wet body weight in May before the outbreak of algal blooms to 4.98 g dry weight per 100 g wet body weight in September during algal blooms outbreak. However, no obvious variation of food consumption was observed in bighead carp during the study period. This species 1.88 and 1.54 g dry weight of plankton per 100 g wet body weight in May and September, respectively. Silver carp had a higher feeding capacity for plankton than bighead carp. Biotic factors (i.e., fish size and conspecific competition with natural species in the lake) may affect the feeding behaviors of both carps as well as seasonal variation of plankton communities in the pen.

Modelling algal blooms in Lake Dianchi, China using neural networks

Lake Dianchi is one of the most extensively impacted freshwater lakes by algal blooms. To investigate the response of dominant algal genera, neural networks were applied to model the relationship between water quality parameters and the biomass of four dominant genera (Microcystic spp., Anabaena sp., Quadricauda (Turp.) Breb, Pediastrum Mey) in Dianchi. Results showed that the timing and magnitude of algal blooms of Microcystic spp., nabaena sp., Quadricauda (Turp.) Breb, and Pediastrum Mey in Dianchi could be successfully predicted. The evaluation of environmental factors showed that pH had more significant impact on concentrations of all the four dominant algal genera than the nutrient factors, such as total phosphorus and total nitrogen.

The dominant Ulva strain of the 2008 green algal bloom in the Yellow Sea was not detected in the coastal waters of Qingdao in the following winter

The region of Qingdao, China, experienced the world's largest green tide from May to July 2008. More than one million tons of fresh algal biomass of the green alga Ulva prolifera was harvested, while more was suspected to have sunk to the bottom. The original source of this seaweed was suspected to be from the south as revealed by satellite images. The floating biomass drifted with the water current northward and flourished in nearshore waters around Qingdao. However, direct biological evidence for "seed" source is lacking. It is still unclear whether this alga could survive the Qingdao local coastal environment and pose future danger of potential blooming. Systematic and seasonal sampling of waters in the intertidal zone at six collection sites along the Qingdao coast was conducted from December 2008 to April 2009. Forty-eight water samples were analyzed. From these, nine different morphotypes of Ulva were grown in the laboratory under standard temperature and light regimes. Growth of Ulva was observed in all water samples. However, molecular phylogenetic analyses revealed that the dominant U. prolifera strain of the 2008 bloom was absent in all the water-derived cultures during the sampling period. These results provide evidence that the dominant bloom-forming alga was unlikely able to survive the coastal waters (the minimal surface water temperature in February is 2A degrees C) in winter conditions in Qingdao, even though all the sampling locations were heavily covered by this alga in June 2008.

Environmental and health effects associated with Harmful Algal Bloom and marine algal toxins in China

The frequency and scale of Harmful Algal Bloom (HAB) and marine algal toxin incidents have been increasing and spreading in the past two decades, causing damages to the marine environment and threatening human life through contaminated seafood. To better understand the effect of HAB and marine algal toxins on marine environment and human health in China, this paper overviews HAB occurrence and marine algal toxin incidents, as well as their environmental and health effects in this country. HAB has been increasing rapidly along the Chinese coast since the 1970s, and at least 512 documented HAB events have occurred from 1952 to 2002 in the Chinese mainland. It has been found that PSP and DSP toxins are distributed widely along both the northern and southern Chinese coasts. The HAB and marine algal toxin events during the 1990s in China were summarized, showing that the HAB and algal toxins resulted in great damages to local fisheries, marine culture, quality of marine environment, and human health. Therefore, to protect the coastal environment and human health, attention to HAB and marine algal toxins is urgently needed from the environmental and epidemiological view.

The effect of the causative algae of large-scale HAB in the East China Sea on egg hatching of Argopecten irradians, and population growth of Brachionus plicatilis and Moina mongolica

The impacts of Prorocentrum donghaiense Lu and Alexandrium catenella Balech, causative species of the large-scale HAB in the East China Sea, were studied under laboratory conditions. According to bloom densities, the effects of monoculture and mixture of the two species were examined on the egg-hatching success of Argopecten irradians Lamarck, and the population growth of Brachionus plicatilis Muller and Moina mongolica Daday. The results showed that monoculture of A. catenella had a significant inhibition on the egg hatching success of A. irradians, and the population growth of B. plicatilis and M. mongolica. The median effective densities ( EDSo) inhibiting the egg hatching success of A. irradians for 24 h and the population growth of B. plicatilis and M. mongolica for 96 h were 800, 630, and 2 400 cells/cm(3), respectively. Monoculture of P. donghaiense has no such inhibitory effect on the egg hatching success of A. irradians; P. donghaiense at lower suitable densities could sustain the population growth of B. plicatilis (1 x 10(4) similar to 3 x 10(4)cells/cm(3)) and M. mongolica (2 x 10(4) similar to 5 x 10(4) cells/cm(3)); P. doaghaiense at higher densities had significantly adverse effect on the population growth of B. plicatilis (4 x 10(4) similar to 10 x 10(4) cells/cm(3)) and M. mongolica (10 x 10(4) cells/cm(3)). When the two algae were mixed according to bloom densities, P. donghaiense at suitable densities to some extent could decrease the toxicity of A. catenella to B. plicatilis and M. mongolica. The results indicated that the large-scale HAB in the East China Sea could have adverse effect on zooplankton, and might further influence the marine ecosystem, especially when there was also Alexandrium bloom.