The current state of the art in water quality profiling is reviewed to lay a foundation in addressing concerns over poor data in developing countries which has not been adequately covered by previous models. A particular focus is made on Ogbese River, southwest Nigeria as a case study. A process-based model with data-filling capability is projected which transforms processes into an event as a reasonably easy way for assessing and predicting river-water quality in the event of constraints in data collection. The structure of the study involves: (i) hydrologic modelling, (ii) hydraulic load modelling and (iii) instream water quality modelling. The hydrologic modelling assesses and makes use of satellite based rainfall estimates subject to processing and reliability tests. A modification to the conceptual relationship of rainfall distribution frequency which makes the model output sensitive to the season was derived. The hydraulic load modelling integrates diffuse sources of pollutant as spatial data in combination with the catchment runoff. A distance decay weighing factor was introduced into the export coefficient to better determine the effective load delivered into the stream. The utility of the model, implemented on WASP platform, was demonstrated by showing how it can be used for scenario testing. Different modelling concepts were evaluated in view of their ability to produce predictions under changing circumstances using the predictions as guide to management. This study promotes a knowledge base in water quality processes by evaluation of the processes which lead to the end product rather than using data monitoring. The study structures understanding of the phenomena that characterises river water quality and tailors it towards regulatory applications and catchment planning. It, also, provides a sustainable strategy to predict the river water quality, evaluate the risks, and take proactive action in setting up an early warning system, for data-poor regions.

This dissertation work presents a novel method for addressing system uncertainty to improve management of a small-scale fishery in St. Croix, United States Virgin Islands. Using fishers' ecological knowledge (FEK), this research examines existing perspectives and biases through the Q-Method to identify regulatory inefficiencies in the management framework and strengthen the rationale for including fishers into the management process, develops a coupled behavior-economics model to predict the likelihood of fishing the preferred grounds under a range of physical and regulatory conditions, establishes a baseline assessment of a spawning aggregation of mutton snapper following sixteen years of protection through a no-take marine protected area, and conducts a discrete choice method test to examine likely public support for FEK-based proposed regulatory alternatives. This work contributes to an under-studied and much-needed area of fisheries management, that of incorporating socioeconomic motivations within an ecosystem-based framework. As fisheries management efforts begin to embrace ecosystem-based approaches, the need for understanding and incorporating the knowledge and behavior of fishers into management has never been greater. Ecological goals of fishery sustainability and continued habitat function cannot be achieved without first understanding how fishers view and respond to any regulatory environment and then developing a framework that achieves the greatest support for those regulations. The time has come for incorporating FEK into ecosystem-based fisheries management.

Modeling is an important tool in watershed management. In much of the world, data needed for modeling, both for model inputs and for model evaluation, are very limited or non-existent. The overall objective of this research was to enable development of watershed management plans for agricultural dominated systems under situations where data are scarce. First, uncertainty of the SWAT model's outputs due to input parameters, specifically soils and high resolution digital elevation models, which are likely to be lacking in data-poor environments, was quantified using Monte Carlo simulation. Two sources of soil parameter values (SSURGO and STATSGO) were investigated, as well as three levels of DEM resolution (10, 30, and 90 m). Uncertainty increased as the input data became coarser for individual soil parameters. The combination of SSURGO and the 30 m DEM proved to adequately balance the level of uncertainty and the quality of input datasets. Second, methods were developed to generate appropriate soils information and DEM resolution for data-poor environments. The soils map was generated based on lithology and slope class, while the soil attributes were generated by linking surface soil texture to soils characterized in the SWAT soils database. A 30 m resolution DEM was generated by resampling a 90 m DEM, the resolution that is readily available around the world, by direct projection using a cubic convolution method. The effect of the generated DEM and soils data on model predictions was evaluated in a data-rich environment. When all soil parameters were varied at the same time, predictions based on the derived soil map were comparable to the predictions based on the SSURGO map. Finally, the methodology was tested in a data-poor watershed in Bolivia. The proposed methodologies for generating input data showed how available knowledge can be employed to generate data for modeling purposes and give the opportunity to incorporate uncertainty in the decision making process in data-poor environments. / Ph. D.

Spatial analysis of species for which there is limited quantity of data, termed as the data-poor species, has been challenging due to limited information, especially lack of spatially explicit information. However, these species are frequently of high ecological, conservation and management interest. In this study, I used two empirical examples to demonstrate spatial analysis for two kinds of data-poor species. One example was seabird bycatch from the U.S. Atlantic pelagic longline fishery, which focused on rare events/species for which data are generally characterized by a high percentage of zero observations. The other example was endangered white abalone off the California coast, which focused on endangered species whose data are very limited. With the seabird bycatch example, I adopted a spatial filtering technique to incorporate spatial patterns and to improve model performance. The model modified with spatial filters showed superior performance over other candidate models. I also applied the geographically weighted approach to explore spatial nonstationarity in seabird bycatch, i.e., spatial variation in the parameters that describe relationships between biological processes and environmental factors. Estimates of parameters exhibited high spatial variation. With the white abalone example, I demonstrated the spatially explicit hierarchical demographic model and conducted a risk assessment to evaluate the efficacy of hypothetical restoration strategies. The model allowed for the Allee effect (i.e., density-dependent fertilization success) by using spatial explicit density estimates. Restoration efforts directed at larger-size individuals may be more effective in increasing population density than efforts focusing on juveniles. I also explored the spatial nonstationarity in white abalone catch data. I estimated the spatially explicit decline rate and linked the decline rate to environmental factors including water depth, distance to California coast, distance to land, sea surface temperature and chlorophyll concentration. The decline rate showed spatial variation. I did not detect any significant associations between decline rate and these five environmental factors. Through such a study, I am hoping to provide insights on applying or adapting existing methods to model spatial dynamics of data-poor species, and on utilizing information from such analyses to aid in their conservation and management. / Ph. D.

Understanding long-term trends in highly migratory pelagic stocks in the Pacific Ocean is extremely important as fishing in the Western and Central Pacific is vital to both local economies and the global food supply, accounting for 14% of global seafood. The Pacific is considered “data poor” due to a lack of substantive data, poor quality data, and little fishery-independent assessment. Fishing vessels are nearly exclusively foreign-flagged with virtually all landings exported to Asia and Europe, whereas the GDPs of these island nations are wholly supported by sale of licensures to these fleets. The first chapter examines the validity of using best-available data for ecologically important reconstruction, as well as an overview of approaches used to overcome the encumbrances of such data: self-reporting and profit-maximization. We also examine current methods for handling data-poor situations in marine environments, which provide unique challenges to surveying, patrolling, and enforcement. We applied two modeling approaches to investigate the population dynamics and sustainability of seven species of large predators in the families Xiphiidae, Istiophoridae, and Scombridae comprising the Western and Central Pacific Fisheries Commission Aggregated Catch/Effort database from 1950-present. The entire management region was examined, with the Exclusive Economic Zone of Kiribati explored in detail. This collection of islands and seamounts covers 3.5 million square kilometers including several areas of conservation interest and variable bathymetry. The first, a “traditional” autoregressive integrated moving average (ARIMA) model, revealed shifts in effort, Catch Per Unit Effort (CPUE), catch, abundance, and morphology in all populations, regions, and management area. Second, Catch-MSY identified the Maximum Sustainable Yield (a common metric for fisheries management) for each species by region and the basin. This approach is unique, depending completely on non-reliable self-reported landings data to construct population models useful for management in the absence of costly surveys; often the best available data outside of North America and the EU. This body of work provides the foundation for cost-effective sustainable management of key high-profit open-ocean market species. It identified greatly reduced CPUE of targeted species, increasing CPUE of likely bycatch. Finally, we established catch limits for every reported species in the basin and subregion.

The conventional battery for genotoxicity testing is not well-suited to assessing the large number of chemicals needing evaluation. Traditional in vitro tests lack throughput capacity, provide little mechanistic information, and have poor specificity in predicting in vivo genotoxicity. The Health Canada GeneTox21 research program is developing a multi-endpoint platform for modernized in vitro genotoxicity assessment. The GeneTox21 assays include the TGx-DDI transcriptomic biomarker (i.e., 64-gene expression signature to identify DNA damage-inducing (DDI) substances), the MicroFlow® assay (i.e., a flow cytometry-based micronucleus (MN) test), and the MultiFlow® assay (i.e., a multiplexed flow cytometry-based reporter assay that yields mechanism-of-action (MoA) information). As part of GeneTox21 development, the objective of this study was to investigate the utility of the TGx-DDI transcriptomic biomarker, multiplexed with the MicroFlow® and MultiFlow® assays, as an integrated testing strategy for screening data-poor substances prioritized by Health Canada’s New Substances Assessment and Control Bureau. Human lymphoblastoid TK6 cells were exposed to 3 control and 10 data-poor substances, using a 6-point concentration range. Cells were exposed for 4 hours with or without exogenous metabolic activation. Gene expression profiling was conducted using the targeted TempO-SeqTM assay, and the TGx-DDI classifier was applied to the dataset. Classifications were compared with those based on the MicroFlow® and MultiFlow® assays. Benchmark Concentration (BMC) modeling was used for potency ranking. The results of the integrated hazard calls indicate that five data-poor compounds are genotoxic in vitro, causing DNA damage via a clastogenic MoA, and one is positive via a pan-genotoxic MoA. Two compounds are likely irrelevant positives in the MN test; two are considered possibly genotoxic causing DNA damage via an ambiguous MoA. From quantitative analyses of concentration-response data, we observed nearly identical potency rankings for each assay with two main potency groups being observed. This ranking was maintained when all endpoint BMCs were converted into a single score using the Toxicological Prioritization (ToxPi) approach. Overall, this study contributes to the establishment of a modernized approach for effective genotoxicity assessment and chemical prioritization for further regulatory scrutiny. We conclude that integration of the TGx-DDI biomarker with other GeneTox21 assays is an effective NAM-based strategy for genotoxicity assessment of data-poor compounds.

Management strategies to prevent overfishing while achieving optimum yield vary according to the available data and life history of the fished stock. I evaluated two sets of management strategies for Pacific coast rockfish: strategies to set harvest limits for data-poor stocks, and strategies intended to protect the age structure of fished stocks. Setting Harvest Limits for Data-poor Stocks - The collapse of canary rockfish, Sebastes pinniger, in the northeast Pacific began more than two decades before the stock was officially declared overfished. The 2006 reauthorization of the Magnuson-Stevens Fishery Conservation and Management Act requires a scientifically-based harvest limit for all fished stocks, including those with data limited to catch. Two such "data-poor" methods are currently in use for the management of west coast stocks, depletion-corrected average catch (DCAC) and depletion-based stock reduction analysis (DB-SRA). To evaluate the performance of each method when challenged with catch and biological uncertainty, I retrospectively applied the methods to the catch and biological data available at the time of the first and second canary rockfish stock assessments in 1984 and 1990. In 1980 canary rockfish would be classified as "data-poor", and in 1990 as "data-rich". To evaluate the sensitivity of DCAC and DB-SRA to error in the catch data, harvest limits were estimated using both the historic catch data from each assessment, and the reconstructed catch data from the most recent stock assessment. In addition, harvest limits were estimated using simulated catch data sets for the years 1916 to 1983 with increasing variability around the true catch. DCAC and DB-SRA estimated harvest limits were significantly lower than the catch recommended in both the data-poor and data-rich stock assessments, but higher than the "true" overfishing limit. Use of current catch data improved the estimated harvest limit when the stock was data-poor, but not when the stock was data-rich. The simple methods responded to increasing error in the catch time series with decreasing mean estimates of the harvest limit, indicating that these methods are highly precautionary for this species, when the catch time series is the only source of error. Age Structure Management Strategies - In a variable oceanographic environment, a population with many reproductive age classes benefits not only from the increased fecundity of older fish; but also, in some species, an increase in larval fitness. Older females may also spawn at different times or over longer periods than younger females, increasing the probability of larvae encountering favorable environmental conditions. Despite the accumulating evidence for the importance of age structure to long-term population viability in harvested fish populations, long-lived west coast rockfish (Genus Sebastes) are managed with a biomass-based harvest control rule. I compared three strategies for age structure management, and evaluated the strategies relative to the status quo, biomass-based harvest control rules, across three rockfish life histories. I examined the tradeoff between yield and traditional management reference points, as well as performance measures that could serve as management reference points for age structure. Yield was reduced by strategies that maintain "old growth" age structure, but annual variation in the catch and the probability of becoming overfished were also reduced. The longest-lived rockfish benefited the most from strategies that maintained older fish in the population through dome-shaped selectivity. The shorter-lived rockfish benefited from adjustments in the catch limit based on the age composition of the catch one year previous. Achieving "pretty good yield" with management strategies that also decrease the potential for overexploitation is an important goal for stocks that are well-studied and those that are poorly understood; these investigations contribute to a growing literature on alternative approaches to sustainable fisheries management. / Graduation date: 2012

Alterações no ecossistema marinho e nos estoques pesqueiros devido à pressão da pesca podem ser detectadas por meio de indicadores multiespecíficos. Geralmente, esses indicadores são aplicados a séries temporais de capturas aliados a dados bio-ecológicos dos recursos. Entretanto, abordagens alternativas baseadas em dados de comercialização do pescado podem ser utilizadas. Neste estudo foram aplicados vários indicadores multiespecíficos aos dados disponíveis da região Sudeste/Sul do Brasil, integrando aspectos ecológicos e econômicos de forma inédita para essa região. Para isto, utilizaram-se dados da estatística pesqueira e dados de comercialização de pescado entre 1968-2007, além de dados bio-ecológicos dos recursos (nível trófico, comprimento máximo, longevidade e profundidade). Foram analisadas as tendências desses parâmetros em relação aos desembarques, às quantidades comercializadas e aos preços de mercado. Os indicadores Índice Trófico Marinho, Fishing-in-Balance e Índice de Preço Relativo Logaritmizado também foram explorados. Foi realizada uma análise inferencial das tendências de preço e quantidade das principais categorias de mercado e de suas correlações. A avaliação ecológico-econômica evidencia uma tendência de escassez das espécies-alvo da pesca e de algumas espécies de nível trófico, longevidade e comprimento máximo altos, além do fenômeno \"pricing down the food web\". Portanto, a base de dados do mercado provou ser valiosa para compreender a dinâmica da pesca numa perspectiva ecossistêmica. / Changes in marine ecosystems and fisheries resources due to the fishing pressure can be detected by multispecies indicators. These are, usually, applied to catch or landing time series, jointly the resources bio-ecological data. However, there is an alternative approach, based on market data that could be used. In this study, several multispecies indicators were applied to data from Southeastern/Southern Brazil, integrating ecological and economics aspects to this region in an unprecedented way. Fishery landings and market values for the period 1968-2007 were used, besides bio-ecological classification of seafood categories (trophic level, longevity, maximum length and depth). Trends of these parameters by landings and market quantities and prices were analysed. The Marine Trophic Index, Fishing-in-Balance and the Logarithm Relative Price Index were also applied. Moreover, an inferential analysis of individual categories statistical trends in market prices and quantities and their correlations were done. The joint ecological-economic analysis provided evidence of the scarcity of most higher trophic level, longevity and maximum length categories and fisheries target species, besides the \"pricing down the food web\" phenomenon. Therefore, the market database proved to be priceless to understand the fishery dynamic in an ecosystem perspective.

Alterações no ecossistema marinho e nos estoques pesqueiros devido à pressão da pesca podem ser detectadas por meio de indicadores multiespecíficos. Geralmente, esses indicadores são aplicados a séries temporais de capturas aliados a dados bio-ecológicos dos recursos. Entretanto, abordagens alternativas baseadas em dados de comercialização do pescado podem ser utilizadas. Neste estudo foram aplicados vários indicadores multiespecíficos aos dados disponíveis da região Sudeste/Sul do Brasil, integrando aspectos ecológicos e econômicos de forma inédita para essa região. Para isto, utilizaram-se dados da estatística pesqueira e dados de comercialização de pescado entre 1968-2007, além de dados bio-ecológicos dos recursos (nível trófico, comprimento máximo, longevidade e profundidade). Foram analisadas as tendências desses parâmetros em relação aos desembarques, às quantidades comercializadas e aos preços de mercado. Os indicadores Índice Trófico Marinho, Fishing-in-Balance e Índice de Preço Relativo Logaritmizado também foram explorados. Foi realizada uma análise inferencial das tendências de preço e quantidade das principais categorias de mercado e de suas correlações. A avaliação ecológico-econômica evidencia uma tendência de escassez das espécies-alvo da pesca e de algumas espécies de nível trófico, longevidade e comprimento máximo altos, além do fenômeno \"pricing down the food web\". Portanto, a base de dados do mercado provou ser valiosa para compreender a dinâmica da pesca numa perspectiva ecossistêmica. / Changes in marine ecosystems and fisheries resources due to the fishing pressure can be detected by multispecies indicators. These are, usually, applied to catch or landing time series, jointly the resources bio-ecological data. However, there is an alternative approach, based on market data that could be used. In this study, several multispecies indicators were applied to data from Southeastern/Southern Brazil, integrating ecological and economics aspects to this region in an unprecedented way. Fishery landings and market values for the period 1968-2007 were used, besides bio-ecological classification of seafood categories (trophic level, longevity, maximum length and depth). Trends of these parameters by landings and market quantities and prices were analysed. The Marine Trophic Index, Fishing-in-Balance and the Logarithm Relative Price Index were also applied. Moreover, an inferential analysis of individual categories statistical trends in market prices and quantities and their correlations were done. The joint ecological-economic analysis provided evidence of the scarcity of most higher trophic level, longevity and maximum length categories and fisheries target species, besides the \"pricing down the food web\" phenomenon. Therefore, the market database proved to be priceless to understand the fishery dynamic in an ecosystem perspective.