Physiological performance measures and tolerance limits of estuarine indicator species in South Florida

Current water management practices in South Florida have negatively impacted many species inhabiting Florida Bay. Variable and high salinity has been identified as a key stressor in these estuaries. The comprehensive Everglades Restoration Plan (CERP) includes water redistribution projects that will restore natural freshwater flows to northeastern Florida Bay. My studies focused on the following central theme and hypotheses: Biological performance measures (i.e., growth, reproduction, survival), behavior (i.e., habitat preference and locomotor behavior) and diversity of estuarine fish will be controlled by changes in salinity and water quality that will occur as a result of the restoration of freshwater flow to the bay. A series of acute and subchronic physiological toxicity studies were conducted to determine the effects of salinity changes on the life stages (embryo/larval, juvenile, adult) and fecundity of four native estuarine fish (Cyprinodon variegatus, Floridichthys carpio, Poecilia latipinna, and Gambusia holbrooki). Fishe were exposed to a range of salinity concentrations (freshwater to hypersaline) based on salinity profiles in the study areas. Growth (length, weight) and survival were measured. Salinity trials included both rapid and gradual change events. Results show negative effects of acute, abrupt salinity changes on fish survival, development and reproductive success as a result of salinity stress. Other studies targeted reproduction and critical embryo-larval/neonate development as key areas for detecting long-term population effects of salinity change in Florida Bay. Adults of C. variegatus and P. latipinna were also examined for behavioral responses to pulsed salinity changes. These responses include changes in swimming performance, locomotor behavior and zone preference. Finally, an ecological risk assessment was conducted for adverse salinity conditions in northeastern Florida Bay. Using the U.S. EPA's framework, the risk to estuarine fish species diversity was assessed against regional salinity profiles from a 17-year database. Based on the risk assessment, target salinity profiles for these areas are recommended for managers.

Development of gene expression-based biomarkers of exposure to metals and pesticides in the freshwater amphipod Hyalella azteca

Ecological risk assessment (ERA) is a framework for monitoring risks of exposure and adverse effects of environmental stressors to populations or communities of interest. One tool of ERA is the biomarker, which is a characteristic of an organism that reliably indicates exposure to or effects of a stressor like chemical pollution. Traditional biomarkers which rely on characteristics at the tissue level and higher often detect only acute exposures to stressors. Sensitive molecular biomarkers may detect lower stressor levels than traditional biomarkers, which helps inform risk mitigation and restoration efforts before populations and communities are irreversibly affected. In this study I developed gene expression-based molecular biomarkers of exposure to metals and insecticides in the model toxicological freshwater amphipod Hyalella azteca. My goals were to not only create sensitive molecular biomarkers for these chemicals, but also to show the utility and versatility of H. azteca in molecular studies for toxicology and risk assessment. I sequenced and assembled the H. azteca transcriptome to identify reference and stress-response gene transcripts suitable for expression monitoring. I exposed H. azteca to sub-lethal concentrations of metals (cadmium and copper) and insecticides (DDT, permethrin, and imidacloprid). Reference genes used to create normalization factors were determined for each exposure using the programs BestKeeper, GeNorm, and NormFinder. Both metals increased expression of a nuclear transcription factor (Cnc), an ABC transporter (Mrp4), and a heat shock protein (Hsp90), giving evidence of general metal exposure signature. Cadmium uniquely increased expression of a DNA repair protein (Rad51) and increased Mrp4 expression more than copper (7-fold increase compared to 2-fold increase). Together these may be unique biomarkers distinguishing cadmium and copper exposures. DDT increased expression of Hsp90, Mrp4, and the immune response gene Lgbp. Permethrin increased expression of a cytochrome P450 (Cyp2j2) and decreased expression of the immune response gene Lectin-1. Imidacloprid did not affect gene expression. Unique biomarkers were seen for DDT and permethrin, but the genes studied were not sensitive enough to detect imidacloprid at the levels used here. I demonstrated that gene expression in H. azteca detects specific chemical exposures at sub-lethal concentrations, making expression monitoring using this amphipod a useful and sensitive biomarker for risk assessment of chemical exposure.

An ecological assessment of secondary poisoning risk in the Australian sugarcane industry

Rodenticide use in agriculture can lead to the secondary poisoning of avian predators. Currently the Australian sugarcane industry has two rodenticides, Racumin® and Rattoff®, available for in-crop use but, like many agricultural industries, it lacks an ecologically-based method of determining the potential secondary poisoning risk the use of these rodenticides poses to avian predators. The material presented in this thesis addresses this by: a. determining where predator/prey interactions take place in sugar producing districts; b. quantifying the amount of rodenticide available to avian predators and the probability of encounter; and c. developing a stochastic model that allows secondary poisoning risk under various rodenticide application scenarios to be investigated. Results demonstrate that predator/prey interactions are highly constrained by environmental structure. Rodents used crops that provided high levels of canopy cover and therefore predator protection and poorly utilised open canopy areas. In contrast, raptors over-utilised areas with low canopy cover and low rodent densities, but which provided high accessibility to prey. Given this pattern of habitat use, and that industry baiting protocols preclude rodenticide application in open canopy crops, these results indicate that secondary poisoning can only occur if poisoned rodents leave closed canopy crops and become available for predation in open canopy areas. Results further demonstrate that after in-crop rodenticide application, only a small proportion of rodents available in open areas are poisoned and that these rodents carry low levels of toxicant. Coupled with the low level of rodenticide use in the sugar industry, the high toxic threshold raptors have to these toxicants and the low probability of encountering poisoned rodents, results indicate that the risk of secondary poisoning events occurring is minimal. A stochastic model was developed to investigate the effect of manipulating factors that might influence secondary poisoning hazard in a sugarcane agro-ecosystem. These simulations further suggest that in all but extreme scenarios, the risk of secondary poisoning is also minimal. Collectively, these studies demonstrate that secondary poisoning of avian predators associated with the use of the currently available rodenticides in Australian sugar producing districts is minimal. Further, the ecologically-based method of assessing secondary poisoning risk developed in this thesis has broader applications in other agricultural systems where rodenticide use may pose risks to avian predators.

Assessing the distribution of social-ecological resilience and risk: Ireland as a case study of the uneven impact of famine

Explanations for the causes of famine and food insecurity often reside at a high level of aggregation or abstraction. Popular models within famine studies have often emphasised the role of prime movers such as population stress, or the political-economic structure of access channels, as key determinants of food security. Explanation typically resides at the macro level, obscuring the presence of substantial within-country differences in the manner in which such stressors operate. This study offers an alternative approach to analyse the uneven nature of food security, drawing on the Great Irish famine of 1845–1852. Ireland is often viewed as a classical case of Malthusian stress, whereby population outstripped food supply under a pre-famine demographic regime of expanded fertility. Many have also pointed to Ireland's integration with capitalist markets through its colonial relationship with the British state, and country-wide system of landlordism, as key determinants of local agricultural activity. Such models are misguided, ignoring both substantial complexities in regional demography, and the continuity of non-capitalistic, communal modes of land management long into the nineteenth century. Drawing on resilience ecology and complexity theory, this paper subjects a set of aggregate data on pre-famine Ireland to an optimisation clustering procedure, in order to discern the potential presence of distinctive social–ecological regimes. Based on measures of demography, social structure, geography, and land tenure, this typology reveals substantial internal variation in regional social–ecological structure, and vastly differing levels of distress during the peak famine months. This exercise calls into question the validity of accounts which emphasise uniformity of structure, by revealing a variety of regional regimes, which profoundly mediated local conditions of food security. Future research should therefore consider the potential presence of internal variations in resilience and risk exposure, rather than seeking to characterise cases based on singular macro-dynamics and stressors alone.

Anticipating future risk in social-ecological systems using fuzzy cognitive mapping: the case of wildfire in the Chiquitania, Bolivia

Understanding complex social-ecological systems, and anticipating how they may respond to rapid change, requires an approach that incorporates environmental, social, economic, and policy factors, usually in a context of fragmented data availability. We employed fuzzy cognitive mapping (FCM) to integrate these factors in the assessment of future wildfire risk in the Chiquitania region, Bolivia. In this region, dealing with wildfires is becoming increasingly challenging due to reinforcing feedbacks between multiple drivers. We conducted semi-structured interviews and constructed different FCMs in focus groups to understand the regional dynamics of wildfire from diverse perspectives. We used FCM modelling to evaluate possible adaptation scenarios in the context of future drier climatic conditions. Scenarios also considered possible failure to respond in time to the emergent risk. This approach proved of great potential to support decision-making for risk management. It helped identify key forcing variables and generate insights into potential risks and trade-offs of different strategies. All scenarios showed increased wildfire risk in the event of more droughts. The ‘Hands-off’ scenario resulted in amplified impacts driven by intensifying trends, affecting particularly the agricultural production. The ‘Fire management’ scenario, which adopted a bottom-up approach to improve controlled burning, showed less trade-offs between wildfire risk reduction and production compared to the ‘Fire suppression’ scenario. Findings highlighted the importance of considering strategies that involve all actors who use fire, and the need to nest these strategies for a more systemic approach to manage wildfire risk. The FCM model could be used as a decision-support tool and serve as a ‘boundary object’ to facilitate collaboration and integration of different forms of knowledge and perceptions of fire in the region. This approach has also the potential to support decisions in other dynamic frontier landscapes around the world that are facing increased risk of large wildfires.

Towards consistency, rigour and compatibility of risk assessments for ecosystems and ecological communities

Ecosystem-level conservation is increasingly important at global, national and local levels. Many jurisdictions have developed and apply their own protocols for assessing the threat status of ecosystems, often independently, leading to inconsistencies between and within countries which are problematic for cross-jurisdictional environmental reporting. Australia is a good example of these historic legacies, with different risk assessment methods applied nationally and in most states. The newly developed criteria for the International Union for the Conservation of Nature (IUCN) Red List of Ecosystems (RLE) provide a framework to compare and contrast apparently divergent protocols. We critically reviewed the Australian protocols and compared them with the IUCN RLE, based on the following components of a risk assessment protocol: (i) categories of threat; (ii) assessment units; (iii) underlying concepts and definitions; (iv) assessment criteria; (v) uncertainty methods; and (vi) assessment outcomes. Despite some differences in specific objectives, criteria and their expression, the protocols were structurally similar, included broadly similar types of criteria, and produced assessment outcomes that were generally concordant. Alignment with the IUCN RLE would not require extensive changes to existing protocols, but would improve consistency, rigour and robustness in ecosystem risk assessment across jurisdictions. To achieve this, we recommend: (i) more quantitative assessments of functional change; (ii) separation of management and policy considerations from risk assessment; and (iii) cross-referencing of assessment units in different jurisdictions. We argue that the focus on processes and ecological function, rather than only patterns, is key to robust risk assessment. © 2014 The Authors.

Use of calcium channel blockers and risk of suicide: ecological findings confirmed in population based cohort study

Objective: To investigate possible associations between use of cardiovascular drugs and suicide.

Screening for chlamydial infections and the risk of ectopic pregnancy in a county in Sweden: ecological analysis

Objectives: To analyse trends in rates of genital chlamydial infection and ectopic pregnancy between 1985 and 1995 in a county in Sweden.

Anticipating future risk in social-ecological systems using fuzzy cognitive mapping: the case of wildfire in the Chiquitania, Bolivia

Understanding complex social-ecological systems, and anticipating how they may respond to rapid change, requires an approach that incorporates environmental, social, economic, and policy factors, usually in a context of fragmented data availability. We employed fuzzy cognitive mapping (FCM) to integrate these factors in the assessment of future wildfire risk in the Chiquitania region, Bolivia. In this region, dealing with wildfires is becoming increasingly challenging because of reinforcing feedbacks between multiple drivers. We conducted semistructured interviews and constructed different FCMs in focus groups to understand the regional dynamics of wildfire from diverse perspectives. We used FCM modelling to evaluate possible adaptation scenarios in the context of future drier climatic conditions. Scenarios also considered possible failure to respond in time to the emergent risk. This approach proved of great potential to support decision making for risk management. It helped identify key forcing variables and generate insights into potential risks and trade-offs of different strategies. The “Hands-off” scenario resulted in amplified impacts driven by intensifying trends, affecting particularly the agricultural production under drought conditions. The “Fire management” scenario, which adopted a bottom-up approach to improve controlled burning, showed less trade-offs between wildfire risk reduction and production compared with the “Fire suppression” scenario. Findings highlighted the importance of considering strategies that involve all actors who use fire, and the need to nest these strategies for a more systemic approach to manage wildfire risk. The FCM model could be used as a decision-support tool and serve as a “boundary object” to facilitate collaboration and integration of different perceptions of fire in the region. This approach also has the potential to inform decisions in other dynamic frontier landscapes around the world that are facing increased risk of large wildfires.

Biosecurity threats : the design of surveillance systems, based on power and risk

We consider the problem of designing a surveillance system to detect a broad range of invasive species across a heterogeneous sampling frame. We present a model to detect a range of invertebrate invasives whilst addressing the challenges of multiple data sources, stratifying for differential risk, managing labour costs and providing sufficient power of detection.We determine the number of detection devices required and their allocation across the landscape within limiting resource constraints. The resulting plan will lead to reduced financial and ecological costs and an optimal surveillance system.

Addressing issues in sparseness, ecological bias and formulation of the adjacency matrix in Bayesian spatio-temporal analysis of disease counts

The main objective of this PhD was to further develop Bayesian spatio-temporal models (specifically the Conditional Autoregressive (CAR) class of models), for the analysis of sparse disease outcomes such as birth defects. The motivation for the thesis arose from problems encountered when analyzing a large birth defect registry in New South Wales. The specific components and related research objectives of the thesis were developed from gaps in the literature on current formulations of the CAR model, and health service planning requirements. Data from a large probabilistically-linked database from 1990 to 2004, consisting of fields from two separate registries: the Birth Defect Registry (BDR) and Midwives Data Collection (MDC) were used in the analyses in this thesis. The main objective was split into smaller goals. The first goal was to determine how the specification of the neighbourhood weight matrix will affect the smoothing properties of the CAR model, and this is the focus of chapter 6. Secondly, I hoped to evaluate the usefulness of incorporating a zero-inflated Poisson (ZIP) component as well as a shared-component model in terms of modeling a sparse outcome, and this is carried out in chapter 7. The third goal was to identify optimal sampling and sample size schemes designed to select individual level data for a hybrid ecological spatial model, and this is done in chapter 8. Finally, I wanted to put together the earlier improvements to the CAR model, and along with demographic projections, provide forecasts for birth defects at the SLA level. Chapter 9 describes how this is done. For the first objective, I examined a series of neighbourhood weight matrices, and showed how smoothing the relative risk estimates according to similarity by an important covariate (i.e. maternal age) helped improve the model’s ability to recover the underlying risk, as compared to the traditional adjacency (specifically the Queen) method of applying weights. Next, to address the sparseness and excess zeros commonly encountered in the analysis of rare outcomes such as birth defects, I compared a few models, including an extension of the usual Poisson model to encompass excess zeros in the data. This was achieved via a mixture model, which also encompassed the shared component model to improve on the estimation of sparse counts through borrowing strength across a shared component (e.g. latent risk factor/s) with the referent outcome (caesarean section was used in this example). Using the Deviance Information Criteria (DIC), I showed how the proposed model performed better than the usual models, but only when both outcomes shared a strong spatial correlation. The next objective involved identifying the optimal sampling and sample size strategy for incorporating individual-level data with areal covariates in a hybrid study design. I performed extensive simulation studies, evaluating thirteen different sampling schemes along with variations in sample size. This was done in the context of an ecological regression model that incorporated spatial correlation in the outcomes, as well as accommodating both individual and areal measures of covariates. Using the Average Mean Squared Error (AMSE), I showed how a simple random sample of 20% of the SLAs, followed by selecting all cases in the SLAs chosen, along with an equal number of controls, provided the lowest AMSE. The final objective involved combining the improved spatio-temporal CAR model with population (i.e. women) forecasts, to provide 30-year annual estimates of birth defects at the Statistical Local Area (SLA) level in New South Wales, Australia. The projections were illustrated using sixteen different SLAs, representing the various areal measures of socio-economic status and remoteness. A sensitivity analysis of the assumptions used in the projection was also undertaken. By the end of the thesis, I will show how challenges in the spatial analysis of rare diseases such as birth defects can be addressed, by specifically formulating the neighbourhood weight matrix to smooth according to a key covariate (i.e. maternal age), incorporating a ZIP component to model excess zeros in outcomes and borrowing strength from a referent outcome (i.e. caesarean counts). An efficient strategy to sample individual-level data and sample size considerations for rare disease will also be presented. Finally, projections in birth defect categories at the SLA level will be made.

Ecological aspects of biosecurity surveillance design for the detection of multiple invasive animal species

Complex surveillance problems are common in biosecurity, such as prioritizing detection among multiple invasive species, specifying risk over a heterogeneous landscape, combining multiple sources of surveillance data, designing for specified power to detect, resource management, and collateral effects on the environment. Moreover, when designing for multiple target species, inherent biological differences among species result in different ecological models underpinning the individual surveillance systems for each. Species are likely to have different habitat requirements, different introduction mechanisms and locations, require different methods of detection, have different levels of detectability, and vary in rates of movement and spread. Often there is a further challenge of a lack of knowledge, literature, or data, for any number of the above problems. Even so, governments and industry need to proceed with surveillance programs which aim to detect incursions in order to meet environmental, social and political requirements. We present an approach taken to meet these challenges in one comprehensive and statistically powerful surveillance design for non-indigenous terrestrial vertebrates on Barrow Island, a high conservation nature reserve off the Western Australian coast. Here, the possibility of incursions is increased due to construction and expanding industry on the island. The design, which includes mammals, amphibians and reptiles, provides a complete surveillance program for most potential terrestrial vertebrate invaders. Individual surveillance systems were developed for various potential invaders, and then integrated into an overall surveillance system which meets the above challenges using a statistical model and expert elicitation. We discuss the ecological basis for the design, the flexibility of the surveillance scheme, how it meets the above challenges, design limitations, and how it can be updated as data are collected as a basis for adaptive management.

Association between ambient ultraviolet radiation and risk of esophageal cancer

OBJECTIVES: Ecological studies have suggested an inverse relationship between latitude and risks of some cancers. However, associations between solar ultraviolet radiation (UVR) exposure and esophageal cancer risk have not been fully explored. We therefore investigated the association between nevi, freckles, and measures of ambient UVR over the life-course with risks of esophageal cancers. METHODS: We compared estimated lifetime residential ambient UVR among Australian patients with esophageal cancer (330 esophageal adenocarcinoma (EAC), 386 esophago-gastric junction adenocarcinoma (EGJAC), and 279 esophageal squamous cell carcinoma (ESCC)), and 1471 population controls. We asked people where they had lived at different periods of their life, and assigned ambient UVR to each location based on measurements from NASA's Total Ozone Mapping Spectrometer database. Freckling and nevus burden were self-reported. We used multivariable logistic regression models to estimate the magnitude of associations between phenotype, ambient UVR, and esophageal cancer risk. RESULTS: Compared with population controls, patients with EAC and EGJAC were less likely to have high levels of estimated cumulative lifetime ambient UVR (EAC odds ratio (OR) 0.59, 95% confidence interval (CI) 0.35-0.99, EGJAC OR 0.55, 0.34-0.90). We found no association between UVR and risk of ESCC (OR 0.91, 0.51-1.64). The associations were independent of age, sex, body mass index, education, state of recruitment, frequency of reflux, smoking status, alcohol consumption, and H. pylori serostatus. Cases with EAC were also significantly less likely to report high levels of nevi than controls. CONCLUSIONS: These data show an inverse association between ambient solar UVR at residential locations and risk of EAC and EGJAC, but not ESCC.

Impact of socio-ecological variability on the transmission of malaria in Yunnan Province, China

This thesis is a population-based epidemiological study to explore the spatial and temporal pattern of malaria, and to assess the relationship between socio-ecological factors and malaria in Yunnan, China. Geospatial and temporal approaches were applied; the high risk areas of the disease were identified; and socio-ecological drivers of malaria were assessed. These findings will provide important evidence for the control and prevention of malaria in China and other countries with a similar situation of endemic malaria.