Dissertations / Theses on the topic 'Suitability modelling'

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.

In this thesis a number of statistical methods have been developed and applied to habitat suitability modelling for rare and threatened species. Data available on these species are typically limited. Therefore, developing these models from these data can be problematic and may produce prediction biases. To address these problems there are three aims of this thesis. The _rst aim is to develop and implement frequentist and Bayesian statistical modelling approaches for these types of data. The second aim is develop and implement expert elicitation methods. The third aim is to apply these novel approaches to Australian rare and threatened species case studies with the intention of habitat suitability modelling. The _rst aim is ful_lled by investigating two innovative approaches for habitat suitability modelling and sensitivity analysis of the second approach to priors. The _rst approach is a new multilevel framework developed to model the species distribution at multiple scales and identify excess zeros (absences outside the species range). Applying a statistical modelling approach to the identi_cation of excess zeros has not previously been conducted. The second approach is an extension and application of Bayesian classi_cation trees to modelling the habitat suitability of a threatened species. This is the _rst `real' application of this approach in ecology. Lastly, sensitivity analysis of the priors in Bayesian classi_cation trees are examined for a real case study. Previously, sensitivity analysis of this approach to priors has not been examined. To address the second aim, expert elicitation methods are developed, extended and compared in this thesis. In particular, one elicitation approach is extended from previous research, there is a comparison of three elicitation methods, and one new elicitation approach is proposed. These approaches are illustrated for habitat suitability modelling of a rare species and the opinions of one or two experts are elicited. The _rst approach utilises a simple questionnaire, in which expert opinion is elicited on whether increasing values of a covariate either increases, decreases or does not substantively impact on a response. This approach is extended to express this information as a mixture of three normally distributed prior distributions, which are then combined with available presence/absence data in a logistic regression. This is one of the _rst elicitation approaches within the habitat suitability modelling literature that is appropriate for experts with limited statistical knowledge and can be used to elicit information from single or multiple experts. Three relatively new approaches to eliciting expert knowledge in a form suitable for Bayesian logistic regression are compared, one of which is the questionnaire approach. Included in this comparison of three elicitation methods are a summary of the advantages and disadvantages of these three methods, the results from elicitations and comparison of the prior and posterior distributions. An expert elicitation approach is developed for classi_cation trees, in which the size and structure of the tree is elicited. There have been numerous elicitation approaches proposed for logistic regression, however no approaches have been suggested for classi_cation trees. The last aim of this thesis is addressed in all chapters, since the statistical approaches proposed and extended in this thesis have been applied to real case studies. Two case studies have been examined in this thesis. The _rst is the rare native Australian thistle (Stemmacantha australis), in which the dataset contains a large number of absences distributed over the majority of Queensland, and a small number of presence sites that are only within South-East Queensland. This case study motivated the multilevel modelling framework. The second case study is the threatened Australian brush-tailed rock-wallaby (Petrogale penicillata). The application and sensitivity analysis of Bayesian classi_cation trees, and all expert elicitation approaches investigated in this thesis are applied to this case study. This work has several implications for conservation and management of rare and threatened species. Novel statistical approaches addressing the _rst aim provide extensions to currently existing methods, or propose a new approach, for identi _cation of current and potential habitat. We demonstrate that better model predictions can be achieved using each method, compared to standard techniques. Elicitation approaches addressing the second aim ensure expert knowledge in various forms can be harnessed for habitat modelling, a particular bene_t for rare and threatened species which typically have limited data. Throughout, innovations in statistical methodology are both motivated and illustrated via habitat modelling for two rare and threatened species: the native thistle Stemmacantha australis and the brush-tailed rock wallaby Petrogale penicillata.

In this thesis a number of statistical methods have been developed and applied to habitat suitability modelling for rare and threatened species. Data available on these species are typically limited. Therefore, developing these models from these data can be problematic and may produce prediction biases. To address these problems there are three aims of this thesis. The _rst aim is to develop and implement frequentist and Bayesian statistical modelling approaches for these types of data. The second aim is develop and implement expert elicitation methods. The third aim is to apply these novel approaches to Australian rare and threatened species case studies with the intention of habitat suitability modelling. The _rst aim is ful_lled by investigating two innovative approaches for habitat suitability modelling and sensitivity analysis of the second approach to priors. The _rst approach is a new multilevel framework developed to model the species distribution at multiple scales and identify excess zeros (absences outside the species range). Applying a statistical modelling approach to the identi_cation of excess zeros has not previously been conducted. The second approach is an extension and application of Bayesian classi_cation trees to modelling the habitat suitability of a threatened species. This is the _rst `real' application of this approach in ecology. Lastly, sensitivity analysis of the priors in Bayesian classi_cation trees are examined for a real case study. Previously, sensitivity analysis of this approach to priors has not been examined. To address the second aim, expert elicitation methods are developed, extended and compared in this thesis. In particular, one elicitation approach is extended from previous research, there is a comparison of three elicitation methods, and one new elicitation approach is proposed. These approaches are illustrated for habitat suitability modelling of a rare species and the opinions of one or two experts are elicited. The _rst approach utilises a simple questionnaire, in which expert opinion is elicited on whether increasing values of a covariate either increases, decreases or does not substantively impact on a response. This approach is extended to express this information as a mixture of three normally distributed prior distributions, which are then combined with available presence/absence data in a logistic regression. This is one of the _rst elicitation approaches within the habitat suitability modelling literature that is appropriate for experts with limited statistical knowledge and can be used to elicit information from single or multiple experts. Three relatively new approaches to eliciting expert knowledge in a form suitable for Bayesian logistic regression are compared, one of which is the questionnaire approach. Included in this comparison of three elicitation methods are a summary of the advantages and disadvantages of these three methods, the results from elicitations and comparison of the prior and posterior distributions. An expert elicitation approach is developed for classi_cation trees, in which the size and structure of the tree is elicited. There have been numerous elicitation approaches proposed for logistic regression, however no approaches have been suggested for classi_cation trees. The last aim of this thesis is addressed in all chapters, since the statistical approaches proposed and extended in this thesis have been applied to real case studies. Two case studies have been examined in this thesis. The _rst is the rare native Australian thistle (Stemmacantha australis), in which the dataset contains a large number of absences distributed over the majority of Queensland, and a small number of presence sites that are only within South-East Queensland. This case study motivated the multilevel modelling framework. The second case study is the threatened Australian brush-tailed rock-wallaby (Petrogale penicillata). The application and sensitivity analysis of Bayesian classi_cation trees, and all expert elicitation approaches investigated in this thesis are applied to this case study. This work has several implications for conservation and management of rare and threatened species. Novel statistical approaches addressing the _rst aim provide extensions to currently existing methods, or propose a new approach, for identi _cation of current and potential habitat. We demonstrate that better model predictions can be achieved using each method, compared to standard techniques. Elicitation approaches addressing the second aim ensure expert knowledge in various forms can be harnessed for habitat modelling, a particular bene_t for rare and threatened species which typically have limited data. Throughout, innovations in statistical methodology are both motivated and illustrated via habitat modelling for two rare and threatened species: the native thistle Stemmacantha australis and the brush-tailed rock wallaby Petrogale penicillata.

Bacillus anthracis is the causal agent of anthrax which primarily affects ungulates, occasionally carnivores and less frequently humans. The endospores of this soil-borne bacterium are highly resistant to extreme conditions, and under ideal conditions, anthrax spores can survive for many years in the soil. The bacterium is generally found in soil at sites where infected animals have died. When these spores are exposed, they have the potential to be ingested by a mammalian species which could lead to an anthrax outbreak. Anthrax is almost never transmitted directly from host to host, but is rather ingested by herbivores while drinking, grazing or browsing in a contaminated environment, with the exception of scavengers and carnivores consuming infected prey. Anthrax is known to be endemic in the northern part of Kruger National Park (KNP) in South Africa (SA), with occasional epidemics spreading southward into the non-endemic areas. The aim of this study is to identify and map areas that are ecologically suitable for the harbouring of B. anthracis spores within the KNP. Anthrax surveillance data and selected environmental variables were used as inputs to the maximum entropy (Maxent) species distribution modelling method. Five-hundred and ninety-seven anthrax occurrence records, dating from the year 1988 to 2011, were extracted from the Skukuza State Veterinary Office’s database. A total of 40 environmental variables were used and their relative contribution to predicting suitability for anthrax occurrence was evaluated using Maxent software (version 3.3.3k). Variables showing the highest gain were then used for subsequent, refined model iterations until the final model parameters were established. The environmental variables that contributed the most to the occurrence of anthrax were soil type, normalized difference vegetation index (NDVI), land type and precipitation. A map was created using a geographic information system (GIS) that illustrates the sites where anthrax spores are most likely to occur throughout the Park. This included the known endemic Pafuri region as well as the low lying soils along the Shingwedzi-Phugwane-Bubube rivers and the Letaba-Olifants river drainage area. The outputs of this study could guide future targeted surveillance efforts to focus on areas predicted to be highly suitable for anthrax, especially since the KNP uses passive surveillance to detect anthrax outbreaks. Knowing where to look can improve sampling efficiency and lead to increased understanding of the ecology of anthrax within the KNP.
Dissertation (MMedVet)--University of Pretoria, 2013.
Production Animal Studies
unrestricted

Thesis (MScEng)-- Stellenbosch University, 2013.
ENGLISH ABSTRACT: Organizations formally define and document their business processes in order to properly understand them and to subsequently enable their continuous development, improvement and management. In order to formally define and document their business processes, organizations can use Business Process Modelling, which represents the design of graphical models that portray the business processes of organizations. It is however noted that it is difficult to select a suitable Business Process Modelling Technique in support of a specific application of Business Process Modelling. This is due to the considerable amount of existing Business Process Modelling Techniques, the inherent impact of their varying capabilities and the lack of formal measures that are available to support evaluations regarding their suitability for specific modelling applications. It is therefore considered appropriate to execute a research study that is aimed at the development and validation of a measurement framework that can be used to evaluate the suitability of Business Process Modelling Techniques for specific modelling applications.
AFRIKAANSE OPSOMMING: Organisasies definieer en dokumenteer hulle besigheidsprosesse op ʼn formele wyse om hulle ordentlik te verstaan en gevolglik hulle deurlopende ontwikkeling, verbetering en bestuur te bemagtig. Ten einde die uitvoering van hierdie aktiwiteit aan te spreek, kan organisasies Besigheidsproses Modellering gebruik om grafiese modelle van hulle besigheidsprosesse te ontwerp. Daar word egter kennis geneem dat dit moeilik is om ʼn geskikte Besigheidsproses Modellering Tegniek te kies tes ondersteuning van ʼn spesifieke toepassing van Besigheidsproses Modellering. Dit is weens die groot hoeveelheid bestaande Besigheidsproses Modellering Tegnieke, die impak van hulle variërende vermoëns asook die gebrek aan formele maatstawwe wat gebruik kan word om hulle geskiktheid vir spesifieke modellering toepassings te evalueer. Dit lei tot die besluit om ‘n studie te voltooi wat gefokus is op die ontwikkeling en validasie van ʼn metings raamwerk wat gebruik kan word om die geskiktheid van Besigheidsproses Modellering Tegnieke vir spesifieke toepassings van Besigheidproses Modellering te evalueer.

Globally fish production has continued to increase during recent years at a rate exceeding that of human population growth. However the contribution from capture fisheries has remained largely static since the late 1980s with the increase in production being accounted for by dramatic growth in the aquaculture sector. As of 2012 aquaculture accounted for approximately 42% of total fisheries production and 78% of inland fish production. In view of these figures it is unsurprising that for a number of regions aquaculture represents an important source of both food security and income. The use of Geographical Information Systems (GIS) and spatial data have seen substantial developments in recent years with the help of increasingly affordable computing capacity. From an aquaculture perspective the use of GIS has shown significant potential as a means of combining varied data sources, including those acquired via remote sensing, into models to provide decision support in relation to site selection. A common theme amongst site suitability assessments is the incorporation of climate variables relating to temperature and water availability. These factors in turn can have a significant influence on aquaculture in terms of water availability and quality, and temperature modulated growth performance. There is now a strong consensus that during the 20th century, and especially during recent decades, the earth has experienced a significant warming trend. There is also strong agreement that this warming trend is at least partially a consequence of anthropogenic greenhouse gas emissions and that some degree of further warming is inevitable. While global warming is typically discussed in terms of degrees centigrade of average global temperature increase the full effects in terms of climate changes will be varied both in terms of location and season. The current project focuses on site suitability for aquaculture in relation to changing climate conditions. Significant use is made of GIS and a range of spatial data including remotely sensed data and output from a series of climate models. The project consists of a number of key components: 1. Vulnerability of aquaculture related livelihoods to climate change was assessed at the global scale based on the concept of vulnerability to climate related impacts as a function of sensitivity to climate change, exposure to climate change, and adaptive capacity. Use was made of national level statistics along with gridded climate and population data. Climate change scenarios were supplied using the MAGICC/SCENGEN climate modelling tools. Analysis was conducted for aquaculture in freshwater, brackish, and marine environments with outputs represented as a series of raster images. A number of Asian countries (Vietnam, Bangladesh, Laos, and China) were indicated as most vulnerable to impacts on freshwater production. Vietnam, Thailand, Egypt and Ecuador stood out in terms of brackish water production. Norway and Chile were considered most vulnerable to impacts on Marine production while a number of Asian countries (China, Vietnam, and the Philippines) also ranked highly. 2. Site suitability for pond-based aquaculture was modelled at the global scale using a 10 arcsecond grid. Data from an ensemble of 13 climate models was used to model pond temperature and water availability for rain fed ponds under late 20th century conditions and for a 2°C global warming scenario. Two methods are demonstrated for combining data with a focus on the culture of warm water species. Results suggest both positive and negative impacts in relation to the 2°C warming scenario depending on location and season. Some areas are projected to see negative effects from maximum temperatures during the warmest parts of the year while for many regions there are likely to be potential increases in growth performance during colder months with possible expansion into previously unsuitable areas. 3. Methods for detecting surface water using remotely sensed data were investigated for Bangladesh. Use was made of data from the Moderate-resolution Imaging Spectroradiometer (MODIS) and Landsat ETM+ instruments with accuracy assessed against ground truth data collected in the field. A time series was constructed using all available MODIS data (approximately 13 years with an 8 day temporal resolution) to show areas of: surface water, land, and mixed land and water. The time series was then analysed to produce a layer showing the percentage of the total time series where surface water is indicated thus providing a spatial representation of flood prevalence. 4. A land cover data set was produced using 9 Landsat ETM+ scenes to cover the majority of Bangladesh. 10 different classification routines were evaluated including a decision tree approach unique to the current study. Classification results were assessed against two sets of ground control points produced: one based on field collected ground truth data and the other using a stratified random sampling procedure in association with visual analysis of high resolution true colour satellite images and ETM+ composites. The most accurate classifications were provided by the decision tree method developed for the current study and a Multi-Layer Perceptron (MLP) neural network based classifier. 5. Site suitability for pond-based aquaculture within Bangladesh was assessed using a GIS in combination with the ETM+ based land cover data, the MODIS based surface water time series, and components of the global site suitability assessment including modelled pond temperature data. Assessments were made based on late 20th century conditions and a 2°C global warming scenario. The MODIS surface water time series was also used to show the effects of storm surge flooding in relation to cyclone Aila that struck Bangladesh on 25th May 2009. The south and east of the country were considered most suitable for aquaculture due to more favourable cold season temperatures and higher water balance values. The north west of the country was considered least favourable due to higher maximum modelled pond temperatures and lower water balance values. The effect of the 2°C warming scenario was to enhance these trends. To date the potential spatial implications of changing climate for aquaculture has been significantly under researched. In this respect the current study provides a highly useful indication of where aquaculture related livelihoods may be vulnerable. In addition valuable and unique insights are provided into the distribution of areas of both potential increased, as well as decreased, suitability for existing aquaculture and further aquaculture development.

There is growing global concern over the influence of road development on the conservation of biodiversity and on the functioning of ecosystems. Published reviews in the field of road ecology have identified that most research has examined the effects of roads linearly and have advocated for research at landscape scales. Among the many effects roads have, one of the most significant is the loss of animal life resulting from collisions with vehicles. Despite this, little is known of what toll this has on animal populations and how these impacts vary with scale. This stems from the perception that impacts are localised and that animals killed are typically considered common, and therefore not of great conservation concern. This thesis challenges this notion by showing that the impacts of fatalities can affect populations at landscape extents and that commonness is not a barrier to localised extinction risk. To achieve this I focus on the common wombat; an example of a common species for which road impacts have never been previously examined. Chapter 1 provides an overview of the importance of scale in quantifying road impacts and the debate surrounding common species persistence in road environments. Chapter 2 assesses habitat use of wombats in a road environment at a local scale. Results suggest that wombats select for roadside habitat and as a result populations could be under threat. Chapter 3 is a predictive model of wombat road fatalities which demonstrates the importance of incorporating habitat use in predictive fatality modelling. Through use of a spatially explicit population viability analysis, Chapter 4 demonstrates that roads, in conjunction with other threats can affect the persistence of a common species at a local scale. Chapter 5 is a landscape extent assessment of wombat habitat use, finding that increased effort should be employed in evaluating how reserves confer resilience to species from the impacts of roads and that habitat quality can dictate road-based fatality rates. Chapter 6 summarises the research presented in the thesis and suggests direction for future work, particularly the importance of evaluating the interplay between susceptibility and abundance on species vulnerability in road environments.

Land, water and natural resources are under increasing pressure due to rising demands for food and energy from the rapidly growing global population. Across a catchment there can be multiple stakeholders with conflicting opinions over how space and resources should be used and managed. Consequently, it is important to consider the suitability of a catchment for a particular purpose to optimise use of the area and minimise potential conflicts and impacts on the wider environment. Aquaculture is a significant contributor to world food supply and as fisheries are unlikely to increase it is expected that the industry will continue to grow and expand in the future to help meet food security requirements. As a result, it is essential that the sector aims for sustainable development within the most suitable locations. However, it can be difficult to assess the suitability of multiple large catchments and some issues may not be immediately apparent. This project aimed to show how spatial models could be used as decision support tools to evaluate the suitability of large catchments for sustainable aquaculture. Four large areas of importance to aquaculture were selected; covering 10,148km2, 26,225km2, 48,319km2 and 66,283km2 in Bangladesh, China, Thailand and Vietnam respectively. Asia is by far the most dominant aquaculture region in the world and each of the four study areas contribute to local, regional and global food supplies. The study area in Bangladesh was located in Khulna region in the south west of the country and the main species of focus were prawn and shrimp. The Chinese study area was located in the south eastern province of Guangdong and the main species covered were tilapia and shrimp. Similarly, in Thailand, the main species evaluated were tilapia and shrimp whilst the study area extended across the Central region. Finally, the largest study area was the Mekong Delta in Vietnam and the main species of focus in this area were pangasius catfish and shrimp. One of the challenges in modelling large catchments is model applicability and data availability. Often, the required data are not available (or accessible) and it would be difficult, time consuming and expensive to collect new information. Furthermore, when assessing multiple areas is it vital that a representative and unbiased approach is used where no one catchment is favoured over the other due to higher quality data. Therefore, this study used data that are available for almost any area in the world; allowing future application of the models and enabling effective and unbiased decision support. Four modelling stages were employed in this study to evaluate the suitability of large catchments for sustainable aquaculture development. The first stage was the classification of seasonal land use models from satellite imagery. This provides information on what the land is used for and how aquaculture could impact or be impacted by the wider environment. The second step was the development of seasonal models of site suitability using optimal values within a GIS-based multi-stage framework. These models identify which locations are best for culture and can also be used to estimate the availability of areas for food production. The next stage investigated the use of Maxent as a novel approach in site suitability modelling to evaluate the conditions experienced by existing farms. The information from Maxent can be used to identify trends, opportunities and concerns related to sustainable management and farm locations. Finally, qualitative models of non-point source pollution (NPSP) were developed which assess the risk of NPSP within a catchment. NPSP is an issue which can impact both aquaculture and the wider environment. Thus, it is important to understand the areas within a catchment where NPSP risk is higher enabling the establishment of monitoring and/or mitigation procedures. The models support the ecosystem approach to aquaculture (EAA) and enable objective planning and management strategies to enhance productivity across large catchments without negatively impacting the environment. In order to meet growing food requirements, large areas will need to be used for agriculture and aquaculture; therefore, analysis at a wider catchment level, which complements assessment at a local scale, is required as it allows a holistic view of the situation. The work presented here illustrates the potential use of spatial models across large catchments and considers the suitability of the areas for aquaculture development.

The amazon ecosystems have been compromised by historical forms of occupation and land-use causing habitat loss and forest fragmentation. These anthropogenic disturbances associated to climate changes have direct consequences on the distribution of species and their in situ persistence. Currently, 76 of 14.003 plants taxonomically identified in the Amazon have been listed by the Brasilian Ministry of the Environment as threatened species, though we believe this number to be much bigger in the reality. Among them, Amazon-nut (Bertholletia excelsa), a native tree species, national and internationally known for its cultural, social-economic and nutritional value has been classified as vulnerable. For developping of public policy turned to its management and conservation is fundamental to know the percentage of habitat available, as well as the nature and scale of threats to this environments. Species distribution modelling is an increasingly important tool for predicting habitat suitability and for understanding species environmental tolerances, but has been rarely used in Brazil, especially for Amazonian species. This study aimed to model the potential distribution of B. excelsa in the Amazon biome and to know the factors that control its distribution. To enhance our analysis, case studies were carried out with stakeholders aiming to know their perceptions about the main threats to the species and potential solutions.This research project was based on two hypotheses: (i) There is a suitable habitat to Amazon-nut which require different objectives for conservation and planting; (ii) If the local people are aware of the species vulnerability, they are able to point out the factors that cause this condition. In the chapter 1, habitat was investigated using MAXENT algoritm. We collected 3,325 Amazon-nut records and organized one hundred-and-two environmental variables into climatic, edaphic and geophysical categories at a spatial resolution of 30 arcs-second (~1km). Multi-colinearity between variables was dealt with multivariate statistics associated to expert\'s knowledge, and presence data biased with the spatial filtering. The best model was selected adopting quantitative metrics and visual examination. The most importante biophysic variables we identified were: altitude (m), coarse soil fragments (<2mm) and clay (%). Finaly, the best model indicated 2.3 million km2 i.e., 32% of the Amazon basin has potential for B. excelsa to grow. In the chapter 2, the factors that affect Amazon-nut conservation and planting were discussed with local communities, public managers and researchers, totalyzing 203 participants. Focus groups, individual interviews and questionaire techniques were used to gather information. Data were categorized and the perceptions among stakeholders compared using quali-quantitative analyses. We found that there are currently 36 problems responsible for the species vulnerability and 72% of them belong to environmental and political contexts. Deforestation was the main problem mentioned, followed by fruit depreciation, control failures and lack of organization in the communities. For three groups of stakeholders, the main solutions were related to political context. The results obtained in this study contribute to increase ecological knowledge on the species, to demonstrate the complexity of sustainable use in the Amazon and to guide decisions makers in the selection of priority areas for conservation and potential planting.
Os ecossistemas amazônicos vêm sendo impactados ao longo dos anos por diversos processos de uso e ocupação do território, os quais têm resultado em perdas de habitats e na fragmentação da paisagem nativa. Essas perturbações antrópicas, associadas às mudanças climáticas, têm consequências diretas sobre a distribuição e persistência das espécies in situ. Das 14.003 plantas da Amazônia reconhecidas taxonomicamente, somente 76 estão atualmente listadas pelo Ministério do Meio Ambiente brasileiro como espécies ameaçadas, embora acredita-se que esse número seja muito maior. Entre elas, a Castanha-da-Amazônia (Bertholletia excelsa), uma espécie de árvore nativa, reconhecida nacional e internacionalmente pela sua importância cultural, socioeconômica e nutricional, encontra-se classificada como vulnerável. Para nortear políticas públicas na conservação e no plantio dessa espécie, um profundo entendimento sobre o habitat disponível para ela, bem como a origem e escala das ameaças à esse ambiente, é necessário. A modelagem de distribuição de espécies é uma ferramenta que oferece predições espaciais robustas sobre a adequabilidade de habitat e tolerância das espécies, mas tem sido pouco utilizada no Brasil, sobretudo para espécies Amazônicas. Nesse contexto, esse estudo objetivou modelar a distribuição potencial da B. excelsa no bioma Amazônia, bem como conhecer os fatores que controlam sua distribuição. Para aprofundar essas análises, estudos de caso foram realizados com o objetivo de conhecer a percepção de atores sociais envolvidos com a espécie sobre as principais ameaças e potenciais soluções. Essa tese baseou-se em duas hipóteses: (i) existem áreas com maior adequabilidade para a ocorrência da Castanha-da-Amazônia que demandam diferentes objetivos, para conservação e para o plantio; (ii) se a população local é conciente da vulnerabilidade da espécie, ela pode indicar os fatores que geram essa condição. No capítulo 1, o habitat foi investigado por meio de simulações usando o algoritmo MAXENT. Um total de 3.325 ocorrências e 102 variáveis ambientais foram obtidas, e posteriormente organizadas por categorias climática, edáfica e geofísica. A resolução espacial escolhida foi de 30 arc-segundo (~1km). A multi-colinearidade entre as variáveis foi reduzida por meio da estatística multivariada associada ao conhecimento de especialistas, e as tendências nas ocorrência foram tratadas através da filtragem espacial. O melhor modelo foi selecionado usando métricas quantitativas e examinações visuais. As variáveis biofísicas mais importantes encontradas foram altitude (m), solos com fragmentos grosseiros (<2mm) e argila (%). Por fim, o modelo indicou que 2.3 million km2 i.e., 32% da região amazônica é apropriado para B. excelsa crescer. No capítulo 2, os fatores que afetam a conservação e o plantio da espécie foram discutidos com comunidades, gestores e pesquisadores locais, totalizando 203 participantes. As técnicas de discussão em grupo focal, entrevistas individuais e questionários foram utilizadas para a coleta das informações. Os dados foram categorizados e as opiniões entre os diferentes grupos comparadas utilizando análises quali-quantitativas. Concluiu-se que atualmente existem 36 problemas responsáveis pela vulnerabilidade da espécie, dos quais 72% encontram-se no contexto ambiental e político. O desmatamento foi a principal forçante apontada, seguida pela desvalorização do fruto, falhas na fiscalização e falta de organização nas comunidades. Para os três grupos, as principais soluções foram voltadas para o contexto político. Os resultados obtidos nesse estudo contribuiem para aumentar o conhecimento ecológico da espécie, para demostrar a complexidade do uso sustentável na Amazônia, e orientar tomadores de decisão na seleção de áreas prioritárias para conservação e potenciais para o plantio.

The Blanding's turtle, a semi-aquatic freshwater species found in North America, is listed as a species at risk in 17 of the 18 state/provincial jurisdictions across its range (NatureServe, 2009). Furthermore, approximately 20% of the global range of the Blanding's turtle is contained in Ontario (COSEWIC, 2005). The purpose of this study was to characterise the spatial ecology of Blanding's turtles in Ontario at multiple spatial scales, from a single island population to Ontario-wide habitat suitability modeling. I followed 38 Blanding's turtles (20 males, 13 gravid females, and 5 non-gravid females) in 2008 and 2009 on Grenadier Island in the St. Lawrence River, Ontario via radio-telemetry. Furthermore, I built habitat suitability models using historical Blanding's turtle records in Ontario and two machine learning algorithms: maximum entropy modeling (MAXENT) and boosted regression trees (BRTs). At the local scale, Blanding's turtles selected colder water with more submerged and floating vegetation and avoided open water. Reproductive class and month did not have a significant effect on the mean daily movement of turtles in May, July, and August. In June, however, gravid females moved significantly more than males. Gravid females also had significantly larger home ranges than both males and non-gravid females. At the landscape level, Blanding's turtle habitat suitability was best predicted by air temperature, wetland area, open water area, cropland area, and road density. Habitat suitability increased with increasing air temperature, wetland area, forested area, alvar area, bedrock outcrop area, and decreased with increasing cropland area, pastures and field area, precipitations, terrain ruggedness, and settlements and developed land. Mean area under the operating curve (AUC) values for habitat suitability models tested on independent data ranged from 0.878 to 0.912. My results highlight the importance of stratifying spatial analyses by reproductive class and time and of including terrestrial habitat in management plans for Blanding's turtles.

When maintaining the biodiversity and ecological integrity of forests is a goal of management, a primary requirement is to assess the status, condition, conservation value of each forest, and change in forest conditions over time. GIS procedures were used here to compare different map-based surveys and look in detail at changes in woodlands of the Snowdonia National Park, North Wales, from 1970 to 2000. The maps from the 1970s and 1980s generated by Silsoe College did not compare well with the map from the 1990s produced by the Forestry Commission and no meaningful changes could be measured. This was attributed to difficulties with comparison of different interpretations and classification schemes used by the two organisations. A series of landscape surveys using the same minimum mapping unit, classification scheme, and methodology in general is needed. The potential changes in broadleaved and scrub woodland area were modelled based on the two most extreme climate change scenarios, termed the Low and High scenarios. Temperature and rainfall models formed the basis for logistic regressions of woodland type and distribution. A declining trend in probability of presence for both woodland types from the present sites was shown under the UKCIP98 High climate change scenario. The results emphasized the conceptual difficulties in using fragments of woodland within the realised niche rather than the fundamental niche as the basis for environmental modelling of plant community distributions. GIS based models were generated to address the key question in the biodiversity action plan process of where should new woodland be created or plantations restored. Ecological criteria were developed to identify the priority areas for native woodland expansion taking into account of the requirements for successful woodland expansion from the nature point of view and specific policy aims. The results were interesting and suggested that there is ample land potentially suitable in Snowdonia for new native woodland. The models could be used to aid decision-making for new native woodland in the National Park. A further extension of GIS-based modelling was developed for the prediction of individual NVC types and BAP priority woodland types. The environmental spaces occupied by the fragments of NVC woodland types currently present in Snowdonia were defined and used as templates to produce maps of potentially suitable sites for the occurrence of each NVC type. The results were not as clear-cut as had been hoped because of overlaps in the predicted occurrences of various woodland types. Independent verification of the predictions using non-spatial data for 24 sites revealed that the model produced was very poor. This was not, however, a fault of the modelling but a reflection of the fact that some of the environmental data were at too coarse a scale and that NVC types are not solely determined by environmental factors. In spite of some weaknesses in the data, the use of GIS for modelling these scenarios proved useful. Nowadays, forest policies in Wales, Europe and elsewhere are changing rapidly to meet modified global, national, and local objectives. GIS is, and will increasingly be so, proving to be a useful and flexible tool for translating forest policy into practical application on the ground.

In order to achieve sustainable agriculture, decision makers require appropriate and fully detailed spatial information on land resources. Crop-land suitability analysis is a prerequisite to achieve optimum utilization of the available land resources for sustainable agriculture rural production (T.R. Nisar Ahamed et al., 2000). It is indeed of paramount importance to identify suitable land for cropping while causing minimum impact to the environment. The Food and Agriculture Organization (FAO, 1976), recommended an approach of land suitability evaluation for crops in terms of suitable land based on climatic and terrain data and soil properties. In this study, an attempt was made to identify suitable areas for massive crop production using remote sensing and GIS methodologies and the knowledge from extension officers. The primary method aims at generating land cover data using SPOT 5 satellite imagery and modeling with the existing land capability. The research purpose was to map the map the number hectares suitable areas for crop production number hectares suitable areas for crop production number hectares suitable areas for crop production number hectares suitable areas for crop production. Spatial modeling techniques were utilized to model land suitability model in an effective and efficiently way. The spatial modeling extension from ESRI product was used to model the crop suitability areas. The model run on ArcGIS platform and due to the fact that modeling only uses raster formats, all the data sets were projected and converted to raster format. The weighted overlay model was used to create land suitability map. The model results revealed that 4046251.79 hectares were suitable for cropping in the study area. The final outputs of suitable areas were calculated and each ward was given a value of suitable area as well as unsuitable area. The validation of the final maps compliments the 500 000 hectares that were mapped by Dept of Agriculture EC using 8% slope as the best potential areas. The method provides a cheap, effective and efficient way to map suitable areas over a large area and it also uses remote sensing data. It is hoped that decision makers will make use of the information produced in this paper as the whole world is in crisis of food security.

Large marine vertebrate species can exhibit vast movements, both horizontally and vertically, which challenges our ability to observe their behaviours at extended time-scales. There is a growing need to understand the intra- and inter-annual movements of mobile marine species of conservation concern in order to develop effective management strategies. The basking shark (Cetorhinus maximus) is the world's second largest fish species, however, a comprehensive understanding of this species’ ecology, biology and spatial behaviour in the north-east Atlantic is currently lacking. This thesis seeks to investigate the movement ecology of basking sharks using a suite of technologies to integrate biologging, biotelemetry, remotely sensed data, and ecological modelling techniques. I use satellite telemetry data from basking sharks tracked in 2012, 2013 and 2014 to quantify movements in coastal waters off the west coast of Scotland within the Sea of the Hebrides proposed MPA. Sharks exhibited seasonal residency to the proposed MPA, with three long-term tracked basking sharks demonstrating inter-annual site fidelity, returning to the same coastal waters in the year following tag deployment (Chapter 2). I reveal that sharks tracked into winter months exhibit one of three migration strategies spanning nine geo-political zones and the High Seas, demonstrating the need for multi-national cooperation in the management of this species across its range (Chapter 3). I examine the vertical space-use of basking sharks to improve an understanding of the processes that influence movements in all dimensions. Basking sharks exhibit seasonality in depth-use, conduct deep dives to over 1000 m, and alter their depth-use behaviour in order to remain within thermal niche of between 8 and 16 oC (Chapter 4). Finally, I combine contemporaneous data recorded by deployed satellite tags with remotely sensed environmental data to employ novel ecological modelling techniques to predict suitable habitat for basking sharks throughout the Atlantic Ocean (Chapter 5).

Abstract The protection of endangered species requires knowledge about the habitat requirements and the genetic issues related to the population viability. In this doctoral thesis, I defined the breeding habitat features of the Finnish populations of the Golden Eagle (Aquila chrysaetos) and the Peregrine Falcon (Falco peregrinus) by applying habitat suitability modelling. Secondly, I studied the conservation genetic issues of the Finnish population of the White-tailed Eagle (Haliaeetus albicilla) and the two Reed Bunting subspecies Emberiza schoeniclus witherbyi and E.s. lusitanica met in the Iberian Peninsula. All study populations are classified as threatened according to IUCN classification and they have experienced declines in population sizes in recent history. My results from habitat suitability models showed that human-induced changes in habitat threaten the Golden Eagle in Finland. The relative suitability for the species presence dropped to zero when the proportion of human altered landscape (agricultural or urbanized areas) in the core of the breeding habitat (4 km2) was more than 5%. Models further showed that habitat structure influences breeding habitat selection of the Peregrine Falcon, as it favours well-connected areas of open peatlands. Therefore, fragmentation (i.e., decreasing the connectivity) of open peatlands decreases the habitat quality for the species. The White-tailed Eagle has recovered mainly through local growth, but my results suggest that gene flow from neighbouring populations has had an impact as well, and has enhanced the genetic viability of the Finnish population. The current structure of the two subpopulations (one along the Baltic Sea coast line and another inland in Northern Finland) results mainly from the species’ ecology (i.e., philopatric behaviour), not from the recent population bottlenecks. The effective population size estimate of the coastal subpopulation of White-tailed Eagle was below the critical size needed to maintain evolutionary potential. The estimates of the effective population sizes for E.s. lusitanica and E.s. witherbyi and inland subpopulation of White-tailed Eagle were close or below the critical level of 50, which makes them prone to losing fitness due to inbreeding depression in the short term. Therefore, these study populations need to increase in size in order to secure population viability in the future
Tiivistelmä Ihmisen aiheuttamat elinympäristöjen muutokset uhkaavat biodiversiteettiä kasvattamalla yhä useampien eliölajien sukupuuttoriskiä. Tehokkaat suojelutoimenpiteet edellyttävät tietoa uhanalaisten lajien elinympäristövaatimuksista sekä populaation elinkyvylle keskeisistä geneettisistä tekijöistä. Tarkastelen väitöskirjatyössäni maakotkan (Aquila chrysaetos) sekä muuttohaukan (Falco peregrinus) Suomen populaatioiden pesimäympäristön piirteitä maisemaekologisen mallinnuksen avulla. Toiseksi tarkastelen Suomen merikotkapopulaation (Haliaeetus albicilla) sekä Iberian niemimaalla esiintyvien pajusirkun alalajien Emberiza schoeniclus witherbyin ja E.s. lusitanican suojelun kannalta tärkeitä geneettisiä tekijöitä. Kaikki tutkimuspopulaatiot ovat uhanalaisia ja ne ovat kärsineet voimakkaista kannan pienenemisistä. Maisemaekologiset mallit osoittivat maakotkan välttävän ihmisen muokkaamaa ympäristöä (maatalousalueet ja rakennetut alueet). Lajin esiintymistodennäköisyys laski nopeasti nollaan, kun ihmisen muokkaaman ympäristön osuus nousi yli 5 prosenttiin pesimäympäristön ydinalueella (4 km2). Mallit osoittivat maiseman rakenteen vaikuttavan muuttohaukan habitaatinvalintaan, sillä se suosi pesimäympäristönään kytkeytyneitä avosoita. Avosoiden pirstoutuminen (l. kytkeytyneisyyden väheneminen) vähentää näin ollen muuttohaukan pesimäympäristön laatua. Merikotkapopulaatio on toipunut pääosin paikallisen kasvun myötä, mutta tulokseni viittaavat myös siihen, että geenivirta naapurimaiden populaatioista on lisännyt Suomen populaation geneettistä muuntelua. Nykyinen rakenne (rannikon ja Lapin alapopulaatiot) on seurausta lajin synnyinpaikkauskollisuudesta, ei niinkään populaatiokoon romahduksista. Rannikon merikotkapopulaation efektiivinen koko jäi alle kriittisen rajan, joka tarvitaan evolutiivisen potentiaalin säilymiselle. Pajusirkun alalajien sekä Lapin merikotkapopulaation efektiiviset populaatiokoot olivat lähellä kriittisenä pidettyä 50:tä tai jäivät alle, joten ne ovat vaarassa menettää kelpoisuutta sukusiitosdepression seurauksena lyhyellä aikavälillä. Sekä pajusirkun alalajien että merikotkapopulaatioiden tulee sen vuoksi kasvaa säilyäkseen elinvoimaisina tulevaisuudessa

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Pesquisas em campo voltadas para conservação de espécies são necessárias, porém muitas vezes são limitadas, onerosas e trabalhosas. Uma ferramenta que pode ser utilizada para minimizar estes problemas é a Modelagem Preditiva de Distribuição Potencial de Espécies (MPDPE), que permite estimar áreas potenciais de ocorrência atuais e futuras e que vem recebendo destaque em estudos conservacionistas, pois pode ser utilizada com espécies raras ou que estão sofrendo algum grau de ameaça. No presente estudo, a MPDPE foi utilizada para conhecer a distribuição e prever o efeito potencial de mudanças climáticas sobre a distribuição da perereca Phyllomedusa centralis, que possui distribuição conhecida restrita a poucas localidades no estado de Mato Grosso, Brasil. Os modelos foram desenvolvidos com o método de entropia máxima com o auxilio do programa MaxEnt, utilizando variáveis bioclimáticas atuais e futuras. Os modelos de predição de distribuição atual e de cenários futuros obtiveram elevados valores da área sob a curva operador-receptor e a validação apontou alta precisão na qualidade do modelo. Em todos os modelos, a variável ambiental com maior porcentagem de contribuição foi a precipitação. Todos os modelos apresentaram previsão de aumento nas áreas de distribuição potencial em comparação com o modelo atual de distribuição. Apesar de apresentar limitações, o modelo de distribuição potencial é relevante e pode ajudar no planejamento e gestão de reservas, descoberta de novas populações e manejo de espécies, identificação de áreas prioritárias para conservação e definição de onde é necessária a restauração de habitats.
Field surveys aimed at the conservation of species are necessary, but are often limited, costly and onerous. A tool that can be used to minimize these problems is the Predictive Modeling of Potential Species Distribution (PMPSD), which allows estimating current and future areas of potential occurrence and has received attention from conservationists studies, because it can be used with rare species or who are suffering some degree of threat. In the present study PMPSD was used to determine the distribution and predict the potential effect of climate change on the distribution of tree frog Phyllomedusa centralis, which has restricted distribution to a few localities in the state of Mato Grosso, Brazil. The models were developed with maximum entropy method with the aid of the MaxEnt program using current and future bioclimatic variables. The prediction models of current distribution and future scenarios had higher Area Under the receiver-operator Curve values and the validation showed high accuracy of the model quality. In all models the environmental variable with highest percentage of contribution was precipitation. All models showed increased areas of potential distribution compared with the current distribution model. Despite the limitations, the model of potential distribution is important and can help in planning and management of reserves, discovery of new populations, identification of priority areas for conservation, and definitions of regions to habitat restoration.

Aquaculture is one of the fastest growing activities worldwide. In 2006, it already accounted for around 40% of total fish consumption, and since 2012, aquaculture is the main source of marine food supplies. However, this strong and fast development of the sector tends to be reflected in significant environmental impacts and new challenges in the management and planning of the coastal areas. In this context, this work intends to contribute to the sustainability of the sector, by identifying preferential locations to ensure aquaculture expansion and proper operation in a sustainable manner and with minimal environmental impact under optimal hydrodynamic and water quality conditions in Ria de Aveiro (Portugal) and Rias Baixas (Spain). This study is particularly relevant because the mapping of the most suitable areas for aquaculture exploitation has never been performed in any of the study areas, proving to be crucial, not only to demonstrate the potential in this commercial activity and to encourage investment by companies, but mainly to enable an adequate targeting of investments. To achieve this objective, a multidisciplinary methodology was applied, which comprised the following steps: 1 - characterization of hydrodynamic, physical, chemical and biological variables governing aquaculture activities; 2 - implementation, calibration, validation and exploitation of hydrodynamic and water quality models; 3 - development of a habitat model integrating the numerical model results into an exploitation index; 4 - application of a habitat model and mapping of the suitable and unsuitable areas for fish and shellfish exploitation in Ria de Aveiro and Rias Baixas. The results show that 22% of Ria de Aveiro is suitable for fish production (axis of the main channels, from the inlet to the middle of the channels), while the production of pelagic fish in the Rias Baixas is not recommended due to vertical gradients of water temperature and dissolved oxygen. Concerning to bivalves, the habitat model predicts that 31% of Ria de Aveiro is suitable for production. In the Rias Baixas, except for some marginal areas and upstream areas, the suitability for bivalve production is almost complete, confirming the high exploitation of the region. The definition of suitable areas for aquaculture exploitation is highly related with the different geomorphological, hydrological and biogeochemical processes of Ria de Aveiro and Rias Baixas, but also with the vertical structure of the estuarine systems: homogeneous water column (Ria de Aveiro) in opposition to a partially mixed estuarine system (Rias Baixas). Results of Ria de Aveiro indicate that the upstream areas of the lagoon are the most vulnerable from the water quality point of view, highlighting the importance of the advective processes in the lagoon’s water quality, in opposition to Rias Baixas dynamics, where stratification is more relevant. In Rias Baixas, the strong vertical gradient of water temperature and dissolved oxygen disallows fish from having sustainable growth rates. The numerical modelling approach combined with a habitat model allowed to consider a large number of variables, integrating them in order to generate results that are very useful for coastal managers and investors. Therefore, this work shows that the methodology developed here is effective for the identification of favorable areas for the exploitation of species with economic interest, generating a tool that can be replicated and/or adapted in future studies in other coastal systems. Finally, this work demonstrated the potential of hydrodynamic and biogeochemical modelling to support the decision making process in future coastal plans.
A aquacultura é uma das atividades económicas com maior taxa de crescimento. Em 2006, já era responsável por cerca de 40% do consumo total de peixe, e em 2012, consolidou-se como a principal fonte de alimentos de origem marinha. Contudo, este forte e rápido desenvolvimento do setor tende a refletir-se em significativos impactos ambientais, e em novos desafios na gestão e planeamento das zonas costeiras. Neste contexto, este trabalho pretende contribuir para a sustentabilidade do sector, identificando locais preferenciais para a exploração aquícola de forma sustentável, com um impacto ambiental mínimo e um custo relativamente baixo, sob condições ideais de hidrodinâmica e qualidade da água na Ria de Aveiro (Portugal) e Rias Baixas (Espanha), os dois sistemas com maior exploração no NW da Península Ibérica. Este estudo torna-se particularmente relevante porque o mapeamento das localizações mais adequadas à exploração aquícola nunca foi efetuado em nenhuma das áreas de estudo, revelando-se fulcral, não só para demonstrar o potencial da atividade comercial e incentivar o investimento das empresas, mas principalmente para permitir um direcionamento adequado dos investimentos, e contribuir para a sustentabilidade do setor. Para alcançar este objetivo foi aplicada uma metodologia multidisciplinar que compreendeu a realização dos seguintes passos: 1 - caracterização das variáveis hidrodinâmicas, físicas, químicas e biológicas importantes para a aquacultura; 2 - implementação, calibração, validação e aplicação de modelos hidrodinâmicos e de qualidade da água; 3 - desenvolvimento de um modelo de habitat, para transformação dos resultados dos modelos numéricos, num índice de exploração; 4 - aplicação do modelo de habitat, e mapeamento das zonas mais adequados à exploração de peixes e bivalves na Ria de Aveiro e Rias Baixas. Os resultados evidenciam que 22% da Ria de Aveiro é adequada para a produção de peixes (eixo dos principais canais, desde a embocadura até à zona intermédia dos canais), enquanto que a produção de peixes pelágicos nas Rias Baixas não é aconselhável, devido aos gradientes verticais de temperatura da água e de oxigénio dissolvido. Relativamente aos bivalves, o modelo de habitat prevê que 31% da Ria de Aveiro é adequada à sua produção. Nas Rias Baixas, exceptuando algumas zonas marginais e perto das cabeceiras, a adequabilidade para a produção de bivalves é quase total, confirmando a elevada exploração que se verifica na região. A definição das áreas propícias para a exploração aquícola está altamente relacionada com os diferentes processos geomorfológicos, hidrológicos e biogeoquímicos que ocorrem na Ria de Aveiro e nas Rias Baixas, mas também com a estrutura vertical dos sistemas estuarinos: uma coluna de água homogénea (Ria de Aveiro) em oposição a um sistema estuarino parcialmente estratificado (Rias Baixas). Os resultados para a Ria de Aveiro indicam que as cabeceiras dos principais canais são as áreas mais vulneráveis do ponto de vista da qualidade da água, evidenciando a importância da adveção nos processos ecológicos, em oposição à dinâmica das Rias Baixas, onde a estratificação adquire maior relevância. Nestes estuários, o forte gradiente vertical da temperatura da água e do oxigénio dissolvido impede que os peixes possuam taxas de crescimento sustentáveis. A abordagem de modelação numérica combinada com um modelo de habitat permitiu considerar um elevado número de variáveis, integrando-as de forma a gerar resultados de grande utilidade para gestores e investidores do setor aquícola. Consequentemente, este trabalho mostra que a metodologia aqui desenvolvida é eficaz para a identificação de locais propícios para a exploração de espécies de interesse económico, gerando uma ferramenta que pode ser replicada e/ou adaptada em estudos futuros a realizar noutros sistemas costeiros. Finalmente, este trabalho demonstrou o potencial da modelação hidrodinâmica e biogeoquímica no suporte ao processo de tomada de decisão em futuros planos de ordenamento das zonas costeiras.
Programa Doutoral em Ciência, Tecnologia e Gestão do Mar

Human activities have fundamentally shaped ecosystems across the globe. While this is often associated with degradation, cultures with alternative philosophies can leave a different kind of legacy. First Nations in the temperate rainforest of coastal British Columbia, like the Heiltsuk and Wuikinuxv, have inhabited the land for over 14,000 years, leaving behind tangible legacies in the plant communities we see today. From fine-scale effects of enriched plant leaves to landscape-level species distributions, this research investigates the ecological legacies of human land use and management—both past and present. In one chapter, I test if plants growing on ancient, human-modified soils are enriched in nutrients. I find that plants growing on these sites contain more phosphorus and sodium, which generally benefit fruit production and overall growth. This aligns with oral histories that describe fertilized shrubs as having berries that are bigger, healthier, tastier, and more productive. In the following chapter, I create models that predict the distribution of culturally important plants. With the Heiltsuk Integrated Resource Management Department, I develop a framework for habitat suitability modelling that can be used as a tool for aiding their resource management decisions. All models performed well (AUC = 0.9 overall), and offer insight into suitable habitat across a 3,600 km2 area. Out of five predictor variables, distance to shore, site series (a vegetation index), and human influence contributed the most to model performance. This research contributes a practical tool for resource management and adds to the growing body of interdisciplinary knowledge that uses scientific methods to answer questions of cultural significance. In a time of overlapping environmental crises—like climate change and biodiversity loss—it is important to be aware of the positive influence humans can have on the environment, and how this can offer a hopeful direction for resource management into the future.
Graduate

博士
國立臺灣師範大學
生命科學研究所
101
Studies on the animal space use and habitat selection are required for the conservation and management of large herbivores. In Taiwan, the Formosan sambar deer (Rusa unicolor swinhoii) is listed as a protected species under the wildlife conservation law because of human overexploitation. However, its population status and life history remains unclear. In this study, we used 2 approaches to investigate habitat selection and space use of sambar deer. In the study on geographical-range scale habitat selection, we used habitat suitability modelling to identify key habitat variables and to predict potential distribution of this species throughout Taiwan. In the studies on space use and habitat selections at home-range scale, within-home-range scale, and temporal scale, we tracked the deer by using global positioning system telemetry. The habitat suitability models indicated the presence of 7,865 km2 suitable habitats for the sambar deer in Taiwan. The deer preferentially used areas that were over 1,500 m in elevation and were distant from roads. The results predicted that deer habitats are mainly located in the Central Mountain Range and Xue Mountain Range of Taiwan. However, the predicted habitats were divided into 5 regions, which were separated by 3 major mountain highways. We recommend that deer hotspots close to the highways should be monitored for the future establishment of connections among different Formosan sambar deer sub-populations. Furthermore, we collected location data from 12 collared deer (6 males and 6 females) between December 2009 and July 2013. The collared deer used higher elevation areas in hot/wet season (mean: 2,984 ± 222 m; from May to October) than in cold/dry season (mean: 2,483 ± 406 m; from November to April), which indicated a seasonal movement behavior. At the home-range scale, the deer preferred broadleaf forest, mixed forest, open habitat, and hemlock forest in the cold/dry season, and preferred fir forest, grassland, and hemlock forest in the hot/wet season. We suggested that sambar deer is a habitat generalist. In addition, the deer preferred to use areas with flatter slopes and mesic aspects (338-67°) at home-range scale, and selected areas with higher solar duration at within-home range scale in the cold/dry season. Habitat selection also occurred at temporal scale. The deer was usually closer to forested habitat in daytime than at night, highlighting its requirement of forest as shelter and cover. Moreover, the mean annual 100% minimum convex polygon home ranges were 1,078 ± 501 ha for males and 1,001 ± 346 ha for females. Overlap in home ranges of sambar deer could be as high as 80.2%, which suggested that the sambar deer did not establish exclusive territory. The mean daily displacements were 268 ± 90 m for males and 317 ± 135 m for females, with a maximum distance of 6,435 m for male and 4,422 m for female. No significant differences of home range size and daily displacement were detected between two sexes and between two seasons. In conclusion, we comprehensively studied the space use and habitat selection of sambar deer at multi-scales. The human-related disturbance would be the main factor affecting sambar deer population expansion in the future.

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies
The prediction of species' distribution is fundamental to many applications in ecology, wildlife conservation and the science of evolution. Variations in the abundance within a species' geographic range provide the connection between the disciplines of ecology, geostatistics and biogeography. Species predictive modelling is quite intricate considering the spatial and aspatial variables that both play interactive roles in predicting a species' occurrence. Like many primates across Africa, Pan troglodytes ellioti has both the least geographic distribution and population relative to the other chimpanzee subspecies continent wide. With the proposed Mount Cameroon National Park as the study area, predictions displayed as maps further enhance spatial visualisation. Predictions in Maxent had an estimated accuracy assessment of approximately 0.7 and 67.41% being currently suitable respectively. The observed shift in the habitat suitability from lower to higher altitudes suggests climatic conditions prevailing in the suitable range will likely be attainable only at much higher altitudes in the future. A likely consequence on species shall be to ascend towards the summit in order to meet their needs both physiologically and resource wise.