No description available.

The aim in this study was to develop a model for the probability of finding active golden eagle nests during their breeding season. It was done by using environmental variables derived from expert models which were tested against empirical data. This resulted in a habitat suitability index (HSI), which in this case is assumed to indicate the probability of active nests of golden eagles. The study was conducted together with the County Administrative Board of Västernorrland with the purpose to improve golden eagle’s ecological status.To develop the model, different combinations of several explanatory variables were tested in a model selection process, where the most optimal and parsimonious model was chosen. The tested variables have earlier been shown to affect golden eagles, as slope, aspect, forest age, foraging habitat, suitable flight routes, human population density, roads, railways, power lines, wind power plants, hiking trails and clear cuts. The variables where applied in in ArcMAP at three different scales: nest scale (25 x 25 meter), proximate scale (a circle with the radius of 500 meter) and home range scale (a circle with the radius of 8253 meter). A preliminary test of the variables showed that all golden eagle nests were found in slopes with at least 5֯ degreesas well as in home ranges with human population density not more than 8 people/km2. Due to that a stratified analysis wasperformed. The variables where analysed by multiple logistic regression in R, where the occurrence of golden eagles’ nestswas compared towards random points in the landscape. All variables were also tested one by one by logistic regression. Afterperforming the multiple logistic regression, it was possible to apply its equation into ArcMap to obtain suitability maps withHSI values over Västernorrland’s county.The comparisons of different models show that it is better to combine different spatial scales in the model than only using one spatial scale. The result indicate that three different models might be the best, which all had different combinations of slope and aspect at nest scale and power lines at the proximate scale. Two of these models also include hiking trails and human population density, both at home range scale, in their equation. Since it was some unclarity about the causality between hiking trails and human population density, the conclusion was not to choose any of these as the final model. The final model was more parsimonious and had an additive effect from slope and southern aspect at the nest scale and an antagonistic effect from power lines at the proximate scale.This study clarifies that golden eagles’ habitat preferences for nesting sites during their breeding period is steep slopes (at minimum 5֯ degrees) in more southern aspects with few power lines in the proximate area surrounding the nest. Their homeranges are also situated in areas with less than 8 people/km2. The study also pinpoints a potential conflict between golden eagleand wind power planning, as golden eagles prefer steep slopes and remote areas, which also are valuable areas for wind powerplants. Golden eagles’ preference of remote areas also indicate that they might be affected by human persecution, why certainconservation effort should be focused into this issue. Out from the final model, you can find cluster in the landscape where youcan focus conservation management and restrict exploitation. Due to low number of wind power plants in the landscape, nothingcould be concluded about their effect on golden eagle in this study. An advice from the golden eagle’s perspective is to use theprecautionary principle and further plan wind power plants in areas which already have high disturbance, as for example closeto power lines or roads. The result also indicates that forest age from SLU Forest Map is not suitable for telling where to findgolden eagle nests. GIS-data over forest age would facilitate conservation management for plenty of species connected to theforest.Although good statistical results for the final model, cautions need to be taken in general, since neither population viability analysis have been included, nor changes over time in the landscape. Another issue is the low sample size, where a larger sample size would make it possible to perform profound calibration and validation of the data. To develop a more robust model, the advice is to include these into the model and use a larger sample size.

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The west coast of Taiwan is densely populated with frequently activities for industrial and economic developments. The area is also the site with the existence of Chinese White Dolphin (CWD). Because the arising of ecosystem conservation, the government has attempted to promote the west coast as the marine protected areas (MPAs) for the CWD. Nevertheless, it is required to assess changes of environmental condition and marine environmental quality around the area before the establishment of marine protected areas to the site. If ineffective monitoring is implemented, then the establishment of marine protected areas will be no use. This study was initiated to assess the marine environmental condition by collecting and surveying the long term monitoring data that were published under the government reports and documents to assess the temporal and spatial trends of environmental factors. The data consists of rivers, trench, and marine water or sediments. The study areas covered Taichung County to Yunlin County. The methods for assessing the environmental quality included the use of geographic information system (GIS) for the biological distribution, regression analysis for the trend monitoring of chemical contaminants and physical environmental factors between 2001 ¡V 2010 year surveys. The overall environmental quality within the studied sites were further evaluated for the river pollution index (RPI) and the habitat suitability index (HSI). The survey results of 10 years river monitoring from Taichung to Yunlin showed that Hsin-Huu-Wei River belong to serious pollution with RPI 6.67 value. Yuanlin drainage, one of the six drainages of Chang Hua Coast Industrial Park, belongs to serious pollution with RPI 6.08 value. The RPI results of Six trenches around the Chang-Hua Coast Industrial Park showed that Tien-Wei trench 2, Lun-Wei trench 1, and Ji-An trench belong to mid level of pollution (RPI 3.7~3.975). In the marine water survey, the results showed that the pH values were found lower at southern-ward monitoring station nearby the Formosa Petrochemical Corporation No. 6 Naphtha Cracking Industry site. The nitrogen-NH3 concentrations were found high in Jhuo-Shuei River and No. 6 Naphtha Cracking industry. The concentration of Chlorophyll-a was high in Chang-Hua Coast Industrial Park. In the survey of sediment, Hsin-Huu-Wei River arsenic concentration (As) was over the EPA guidelines, but the concentrations of Cr, Cu, Pb, Zn were within the level of required limits. In the biological survey, the results showed that abundance and species were not evenly distributed with non-comprehensive trends related to the environmental condition or changes. These indicated that biological monitoring survey displayed less important than physical and chemical monitoring for the assessment of man-made pollution or environmental impact from the industrial activities. Overall the monitor sites of river, drainage and trench were differed without a consistent sampling scheme. The offshore sites were sampled greatly in distance, i.e. the farthermost point at four sea miles that had caused difficulties for the comparison of data results collected in different time. It is very uneasy to evaluate the pollution monitoring results. Thus, it is required to develop a long-term environmental quality monitoring plan for the assessment of water quality and sediment of river and marine water with appropriate / consistency sampling method, monitor time and site scheme. Finally, the relevant authorities should implement river remediation to improve the pollution and thereby to maintain the sustainability of marine environment. It is required to establish an integral monitoring program consisting of water and sediment and bio-monitoring in rivers, estuary, and marine to better predict the marine environmental quality. Also the integral and long-term monitoring program should ensure to predict the changes of west coastal and to achieve the effectiveness of marine environment.

The west coast of Taiwan is enriched with biological resources. The areas are the economic development sites with highly industrialized activities and densely population. The government attempts to promote the sites for the establishment of marine protected areas (MPA) because of the existence of Chinese White Dolphin (Sousa Chinensis) which is the most important issues against the sustainable development of economy. Thus, the present study was initiated to assess the marine environmental quality (MEQ) in the west coast of Taiwan. The research consists of the integral monitoring assessments of rivers, estuaries and the marine areas. This work collected, reviewed and analyzed the environmental monitoring data from industrial environmental impact assessment reports and governmental documents for the evaluation of spatial and temporal trends of the west coast areas over the last ten year. The assessment is required to understand the possible interactive problems between the marine protected areas and the marine environmental quality prior to the establishment of MPA acts. The present work consists of the subsection of coastal areas ranging from Hsinchu Country to Taichung Harbour. Ten annual monitoring data including the water quality or sediments of rivers, estuaries, and marine were assessed for the spatial and temporal trends of physical, chemical and biological changes over the years. The approaches for assessing the sites included the geographic information system (GIS) spatial analysis method and linear regression of monitoring data. The levels of pollution were also evaluated by using the river pollution index (RPI). The effect of habitat suitability index (HSI) was also calculated. The results of river water quality assessment showed that the Ke-ya-si, Jhong-gang river, and Nan-gan river were seriously polluted with RPI¡Ö6. The river seiment contaminants (Cu¡BNi) were significantly increased in the Ke-ya-si and Jhong-gang river. The water quality of Taichung Port drainage showed serious pollution with low dissolved oxygen (DO), high concentrations of ammonia nitrogen, and high counts of coli-forms. The Taichung Port drainage sediment contaminants (As¡BCu¡BHg¡BZn) had higher than the average of EPA guidelines. This could be resulting from the significant point source of industries pollutants discharged into the river. The significant amounts of waste water discharged into ocean could cause the impacts to the marine environment. The present study demonstrated the impacts to the river monitoring site although the ocean water quality monitoring contaminants were found without signicant changes in all time. This suggests that the ocean water quality monitoring sites were inconsistently sampled at 4 nm away from the coast which caused the dilution of contaminant concentrations and affecting the monitoring effectiveness. The sediment contaminants in Taichung Port monitoring site showed with the exception of appearing unusual change. The results also showed that there is lack of bio-monitoring program carried out in rivers, estuary, and marine that are imperatively needed to resolve the ineffective sampling protocol implemented in the current coastal environmental monitoring. This is owing to the non unified for authorization between the municipality and environmental bureau. The Canada Ocean Acts on assessing the water and sediment and bio-monitoring in rivers, estuary, and marine as a whole concept were compared with the present study. Finally, the relevant authorities should implement river remediation to improve the pollution and thereby to maintain the sustainability of marine environment. It is needed to establish an integral monitoring program consisting of water and sediment and bio-monitoring in rivers, estuary, and marine to better predict the marine environmental quality. Also the integral and long-term monitoring program should ensure to predict the changes of west coastal and to achieve the effectiveness of marine management.

Habitat selection may be considered a behavioural consequence of an individual actively selecting where it lives or passively persisting in a certain habitat. There are a variety of approaches to assessing habitat selection, including relating densities to predefined habitats and the characteristics of these habitats, measuring the behaviour of animals within predefined habitats in order to assess the relative benefits to the animal and comparing these between habitats, and using optimality theory to allow the animal to provide measures of its preference for particular habitats or patches. Each approach provides different perspectives on an animal’s choice and use of habitat, with some approaches working more effectively with certain species or habitats than others. There have, however, been no attempts to apply all these approaches to a single species at a single site. The objective of this study was therefore to apply the three above-mentioned approaches to assess habitat use and quality to a single species, the springbok (Antidorcas marsupialis) at the Augrabies Falls National Park (AFNP), on the northern bank of the Orange River, in order to provide the basis for further work on comparing and integrating these approaches. The relative abundance of springbok in Augrabies Falls National park was used to develop a habitat suitability model for the park, and thus determine the habitat variables that influenced habitat suitability. Isodar analysis revealed information on the mechanisms underlying habitat preference. Behavioural models were developed to improve our understanding of how springbok behaviour changes in relation to the habitat, and incorporated the variables identified in the habitat suitability model. The different spatial and temporal scales influencing springbok habitat selection were determined using optimal foraging theory and giving-up densities. Springbok preferred open habitats providing high food quality. Springbok behaviour was related to the foraging and predation risk characteristics of the habitat, and springbok varied their temporal and spatial utilisation so as to minimise their risk of predation and maximise their food intake. The habitat suitability model, behaviour models and giving-up densities were compared for ease of use and applicability. Using giving-up densities to reveal habitat suitability had greater applicability and was both efficient and objective.

Cape St Francis, Eastern Cape, has been identified as one of four potential sites for establishing a mainland-based African penguin (Spheniscus demersus) colony. This thesis comprises three main components: a verification of a preparation method for stable isotope samples from penguin feathers; a dietary analysis of the penguins on Bird Island, Algoa Bay, though stable isotope analysis of whole blood and feathers (2012 and 2013); and an estimation of available fish surplus that could potentially support a colony of penguins at Cape St Francis. Each component contributes towards the next, all building towards answering the main research question: Will there be enough food around St Francis Bay to support a colony of penguins and sustain the already established fisheries industry within the bay? Stable isotope analysis of whole blood and feathers from breeding adults and whole blood from juveniles provided insight into the variability of African penguins’ diets at different stages in their life history. Stable isotope mixing models indicated that the predicted proportions that each prey species could potentially contribute to diet conflicted with published stomach sample data. This might arise from inaccurate trophic enrichment factors used in the model, or from systematic biases in the published stomach sampling techniques, or both. Dietary sexual dimorphism was not demonstrated by the isotope signatures of breeding penguins. Based on official catch data, the fisheries activity on the south coast, and especially around the potential colony site at St Francis, is much lower than around the west coast’s penguin colonies. The model provided a first-order estimate for fish supply around the potential colony site at St Francis both at a large coastal scale and a local small scale. At both scales the estimate indicated an ample availability of fish at current fishing levels. The model in Chapter 4 can also be applied to refining the assessments of other potential colony sites on the south coast. In conclusion, the south coast is a promising area for a new colony of penguins in terms of food availability. There is relatively low fishing activity in the area and, as suggested by the large-scale model in Chapter 4, an ample fish resource. The final chapter briefly discusses factors that need to be considered before attempting to establish a mainland-based colony of African penguins.

For the west coast of North America, from northern California to southern Washington, a habitat suitability prediction framework was developed to support wave energy device siting. Concern that wave energy devices may impact the seafloor and benthos has renewed research interest in the distribution of marine benthic invertebrates and factors influencing their distribution. A Bayesian belief network approach was employed for learning species-habitat associations for Rhabdus rectius, a tusk-shaped marine infaunal Mollusk. Environmental variables describing surficial geology and water depth were found to be most influential to the distribution of R. rectius. Water property variables, such as temperature and salinity, were less influential as distribution predictors. Species-habitat associations were used to predict habitat suitability probabilities for R. rectius, which were then mapped over an area of interest along the south-central Oregon coast. Habitat suitability prediction models tested well against data withheld for crossvalidation supporting our conclusion that Bayesian learning extracts useful information available in very small, incomplete data sets and identifies which variables drive habitat suitability for R. rectius. Additionally, Bayesian belief networks are easily updated with new information, quantitative or qualitative, which provides a flexible mechanism for multiple scenario analyses. The prediction framework presented here is a practical tool informing marine spatial planning assessment through visualization of habitat suitability. / Graduation date: 2012