Foram avaliados dois modelos para estimativa do potencial produtivo relativo de cana-de-açúcar. Utilizou-se dados de produtividade (t.ha -1 ) de experimentos, dados de campo da Usina Santa Rita, localizado no município de Santa Rita do Passa Quatro e das áreas de cana-de-açúcar da Usina Costa Pinto em Piracicaba, todas localizadas no Estado de São Paulo, Brasil, para realizar uma comparação entre a produtividade obtida em campo e a produtividade relativa (% da máxima produtividade) estimada pelo modelo matemático. As variáveis de entrada são o fósforo (P, mmolc/kg), potássio (K, mmolc/kg), capacidade de troca de cátions (T, mmolc/kg), saturação por bases (V%) e o teor de argila (Arg%). As avaliações mostraram que o modelo estimou de forma eficiente a produtividade relativa de cana-de-açúcar, com relações altamente significativas (P<0,001) entre produtividade medida no campo e produtividade relativa estimada. Verificou-se que o modelo ganha precisão quando se trabalha em escalas maiores (dados experimentais) em comparação com escalas menores (grandes fazendas). Uma análise de regressão linear múltipla, pelo método stepwise, foi utilizada para verificar quais foram os fatores que influenciaram a produtividade da cana-de-açúcar nos diferentes anos. Verificou-se forte influencia do número de cortes e das variedades, entretanto notou-se que as variáveis do solo utilizados como variáveis de entrada (P,K,T,V,Arg) nem sempre influenciaram a produtividade nos diferentes anos. Constatou-se então que as ferramentas estatísticas podem ser limitadas para elaboração de modelos. Consequentemente o modelo mostrou-se uma ferramenta útil para identificação da capacidade produtiva de áreas para a cana-de-açúcar de maneira holística e integrada em comparação aos métodos estatísticos. O modelo foi aplicado, numa escala regional, no o município de Piracicaba. Através de um sistema de informações geográficas (SIG) foram gerados um mapa de declividade, mapa de distância em relação a 4 usinas da região e uma mapa de produtividade relativa. Os mapas foram úteis na identificação da distribuição espacial da cana-de-açúcar no município. Utilizou-se o modelo climático da FAO para simular a produtividade da cana-de-açúcar mês a mês durante um ano. O mesmo não apresentou correlação com a produtividade média mensal obtida. Este modelo foi concebido para estudos em dimensões continentais com regiões climaticamente contrastantes. Em escala local se mostrou muito sensível ao déficit hídrico para estimar a produtividade da cana-de-açúcar adequado para realizar estimativas, principalmente porque esta cultura é tolerante a períodos de stress hídricos. / Two models of sugarcane were evaluated. The yield (t/ha) out of experimental data, and from fields of the Santa Rita Sugar Mill, located at Santa Rita do Passa Quatro, and from large farms of the Costa Pinto Sugar Mill, located at Piracicaba, all in the State of São Paulo – Brazil were compared to the estimated relative yield (% of the maximum yield) by a mathematical model having as input the soil fertility parameters: potassium content (K, in mol/kg), phosphorus content (P, in mol/kg), cation exchange capacity (T, in mol/kg), base saturation (V, in %) and clay content (Arg, in %), by linear regression. The high significance of the regressions (P<0,001) showed a closed relation between estimated and measured yield. The model gain precision with bigger scales (experimental data) compared to the smaller scales (larger farms). A linear multiple regression statistical analysis, by the stepwise method, were applied to select the soil parameter which most affected the yield. The ratton number and the sugarcane variety were the most important factors determining yield, overcoming the soil fertility parameters which not always affected yield according to this analysis. Consequently, the model was a better tool to identify soil capability for sugarcane yield, in a holistic and integrated manner, than the statistical analysis. The soil model to estimated relative yield were applied tin the regional scale on the Piracicaba county to generate maps of the distance of sugarcane field to the sugar mills, relative sugarcane yield of the fields, and land slopes of the sugarcane fields. The maps were useful to elucidate the sugarcane distribution within the county. An estimation of yield by the FAO model, using weather data as input parameters, showed a large month to month yield variation in discrepancy to the field observations. No significance regressions demonstrated that the yield estimated by FAO model is not related to the field data. This model was created for studies at continental level with contrasting weather differences, but is too sensitive for the water deficit to estimate sugarcane yield at local and regional scale, mainly because this crop is particularly tolerant do periodic water stress.

53 Abstract Application of MiFID directive on activities in universal bank MiFID or Markets on financial instruments Directive, is extensive and key European financial market regulation. Introduced into the laws of all the Member States many new applications and employed a large number of companies. The content of this work is to first clarify the concept of a universal bank, the bank and the reason why the Directive applies to them. Furthermore, analysis of specific activities and procedures, which are due to the introduction of the Directive into law occurred mainly by retail investors, the current clients of universal bank. Most attention is devoted to investor protection, mainly test the appropriateness and suitability, performance instructions for the customer. The following chapter is devoted to issues of organizational changes, the new rules required. Part of the text is devoted to the transposition process in individual countries and especially in the Czech Republic. Another chapter is concerned with problems that frequently appear in the application and in the last chapter outlines recent developments, particularly in the new draft directive, revising MiFID after almost five years of operation, which is just being born on the soil of the European Union. The conclusion is the finding that changes in...

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 use of a system of detention reservoirs distributed across a region has been gaining interest as an innovative way to manage riverine flooding. An open problem is the role played by the spatial configuration of detention projects in regulating the flow. Possible locations for reservoirs within a watershed are numerous, however methods used in literature to place reservoirs on real watersheds and couple them with realistic values of storage are not very detailed. This thesis presents a methodology for modeling dams and related reservoirs at high density, based on the analysis of a Digital Elevation Model (DEM) of the terrain, and extracting their geometric characteristics. Four indicators, based on the morphology of reservoirs and their position in the network, are proposed to classify them and identify which locations are more suitable for a detention project. These are the Horton order, the ratio between volume and extent of the reservoir, the ratio between volume and the expected inflow volume, and the volume itself. The study area of the analysis is the Turkey River watershed, in northeastern Iowa. The algorithm analyzed over 100,000 locations and successfully modeled more than 60%. Most of the failed attempts occurred in a region of the watershed where the terrain is generally flat and reservoirs, when feasible, tend to store water inundating a large area. Regional patterns of ratios are highlighted at the scale of the watershed, but no clear, recurring pattern is identified at the subwatershed level. The considered indicators have the purpose of narrowing down locations to a manageable number of candidates. Further criteria can also be adopted, based on land use and social and economic considerations. Selected reservoirs can be variously combined and entered, together with their geometric characteristics, in hydrological models and optimization processes to determine the best spatial configuration possible.

River barriers, such as dams, culverts and diversions are important for water conveyance, but disrupt river ecosystems and hydrologic processes. River barrier removal is increasingly used to restore and improve river habitat and connectivity. Most past barrier removal projects prioritized individual barriers using score-and-rank techniques, neglecting the spatial structure and cumulative change from multiple barrier removals. Similarly, most water demand models satisfy human water uses or, only prioritize aquatic habitat, failing to include both human and environmental water use benefits. In this study, a dual objective optimization model identified in-stream barriers that impede quality-weighted aquatic habitat connectivity for Bonneville cutthroat trout. Monthly streamflow, stream temperature, channel gradient and geomorphic condition were indicators of aquatic habitat suitability. Solutions to the dual objective problem quantify and graphically present tradeoffs between quality-weighted habitat connectivity and economic water demands. The optimization model is generalizable to other watersheds, but it was applied as a case study in Utah’s Weber Basin to prioritize removal of environmentally-harmful barriers, while maintaining human water uses. Modeled results suggest tradeoffs between economic costs of removing barriers and quality-weighted habitat gains. Removing 54 in-stream barriers increases quality-weighted habitat by about 160 km and costs approximately $10M, after which point the cost effectiveness of removing barriers to connect river habitat slows. In other words, there is decreasing benefit of removing barriers, so that after removing the first 54 barriers, it costs more to connect more high-quality habitat. Removing reservoirs or diversions that result in large economic losses did not substantially increase habitat. This suggests that removing numerous small barriers results in greater increases in habitat for the same removal costs, without significant water scarcity losses. The set of barriers prioritized for removal varied monthly depending on limiting habitat conditions for Bonneville cutthroat trout. The common barriers removed in the model were identified to communicate the most environmentally harmful barriers to local stakeholders and inform decision-making. Additionally, limiting the budget or number of barrier removal projects resulted in a different set of barriers removed. This research helps prioritize barrier removals and future restoration decisions in the Weber Basin although the model formulation is generalizable to other watersheds. Available data and a simplified approach limit the scope of this model. The modeling approach expands current barrier removal optimization methods by explicitly including economic and environmental water uses.

It is widely known that the world is losing biodiversity and primarily it is thought to be caused by anthropogenic activities. Many of these activities have been identified. However, we still lack a clear understanding of the causal relationships between human activities and the pressures they place on the environment and biodiversity. We need to know how ecosystems and individual species respond to changes in human activities and therefore how best to moderate our actions and reduce the rate of loss of biodiversity. One of the ways to detect these changes is to use indicators of ecosystem conditions. Indicators are statistics following changes in a particular factor usually over time. These indicators are used to summarise a complex set of data, and are seen as being representative of the wider situation in that field. So it can be assumed that if that particular factor is declining or improving, then the situation in general is also declining or improving. They are used to check the status and trends of biodiversity by both the public and policy makers. Indicators are also used to assess national performance and can be used to identify the actions required at the policy level. In this manner, they provide an important link between policy-makers and scientists collecting the data. The current thesis investigates the possibility of using bird species as indicators of biodiversity for better management of natural terrestrial ecosystems, by identifying their habitats according to various environmental factors. The study is established by drawing upon three main scientific areas: ecology, geographical information system (GIS), and statistical modelling. The Mornington Peninsula and Western Port Biosphere Reserve (MPWPBR) (Victoria, Australia) was chosen for the study area because of the combination of suburban and natural environments that made it optimum for this type of study. Once the study area was defined, the necessary data for the research were obtained from various sources. Birds Australia provided data on recorded observation of 271 bird species within the study area. Based on the nature of this study, seven species were selected for the study. The criteria for this selection are discussed in Chapter 3. Most literature state that the primary determinant for bird abundance is vegetation and land cover. Because of this, Ecological Vegetation Class (EVC) layer was used to determine which type(s) of vegetation have the greatest impact on habitat selection. Each species showed a relationship to a number of v vegetation types. These EVCs were combined to produce vegetation patches, and were considered as potentially suitable habitats of corresponding bird species. For each of the species, these habitat patches were analysed for the different aspects of patch characteristics (such as the level of patchiness, connectivity, size, shape, weighted distance between patches, etc.) by using the Landscape Context Tool (a GIS add-on). This process assisted the understanding of the importance of patch quality in habitat selection among different bird species by analysing the location of bird observation sites relative to habitat patches. In this way, the association between bird presence and the conditions of a habitat patch was identified by performing a discriminant function analysis. To investigate the probability of a species presence according to different environmental factors, a model of species distribution was created. Binary logistic regression was used to indicate the level of effect of each variable. The model was then successfully validated in the field. To define the indicators of environmental factors, it was essential to separate bird species based on their dependency on one or more of the studied variables. For this purpose, One-Way ANOVA was used. This analysis showed that some bird species can be considered as indicators of urban areas, while others could be good indicators of wellpreserved large forests. Finally, it must be mentioned that the type and quality of the datasets are crucial to this type of study, because some species have a higher degree of sensitivity to certain types of vegetation or land cover. Therefore, the vegetation data must be produced as detailed as possible. At the same time, the species data needs to be collected based on the presence and absence (versus presence-only) of the birds.

<p>This thesis was aimed at the development of a Geographical Information System (GIS) based model to support the Rwanda Land Use and Development Master Plan. Developing sustainable land management is the main task of this master plan. Stakeholder’s involvement was of key importance. Their demands should be analysed and visualised to support discussions and the decision-making process. Spatial Multicriteria Decision Analysis (MCDA) is a proven method for land-use planning purposes. However, most land-use planning applications focus on a specific theme, such as urban development. In addition, land-use planning is often limited to a relatively small area. This thesis focused at the development of a countrywide GIS model, containing all land-uses accommodated in three main land-use categories: urban, agriculture and conservation. The GIS model was largely based on the Land-Use Conflict Identification Strategy (LUCIS) model. Many of the goals, objectives, and subobjectives that described the earlier mentioned land-use categories were adopted from the original model. However, a significant number of them were dropped, and new were created to suit the Rwandan situation. Stakeholder’s involvement was realized by assigning weights to the goals and preference maps. The Analytical Hierarchy Process (AHP) was used as weighting method. ESRI’s ArcGIS ModelBuilder was used to give the model shape in the GIS. Firstly, suitability maps were created of all elements in the model. The suitability maps were then transformed into preference maps by weighting them. In the next step the preference maps were collapsed in three classes: low, medium and high preference. Finally, the preference maps of the three land-use categories were combined, in order to visualize conflict areas. Ortho photos proved to be useful when acting as reference for the suitability and preference maps. Despite a large number of missing datasets, the GIS model was executed to simplify the understanding. However, many of the obtained results were unreliable because of the incompleteness of datasets, and can therefore not be used for decision-making.  Unfortunately, due to the stage of the project it was not possible to obtain weights from the stakeholders, and should therefore be done when the time is right. Right Choice DSS, a very user-friendly decision support application, was proposed to use for calculating weights. To conclude, the developed GIS model integrated countrywide land-use suitability mapping and stakeholders’ wishes that can be used for discussions and decision making.</p>

The American alligator (Alligator mississippiensis) has been frequently studied in large reservoirs and coastal marshes. Large ontogenetic shifts in their diet and morphology have been linked with changes in habitat use, with adult males using deep, open water and juveniles and nesting females relying on vegetated marsh. In certain regions of the inland portion of the alligator’s range, these different aquatic habitats are represented by seasonal wetlands and riverine systems that are separated by a terrestrial matrix. Ontogenetic habitat shifts, therefore, would require overland movements between systems, which has important implications for conservation of the species. I tested several commonly used methods of surveying alligator populations to determine the most effective method of studying alligators in seasonal wetlands. I then used systematic trapping, nest surveys and radio telemetry to determine habitat use and overland movement rates by different sex and size classes. I found that seasonal wetlands provided nesting and nursery sites for these inland alligator populations, but that both juveniles undergoing an ontogenetic shift and nesting females move between the wetlands and riverine systems. Overland movements by alligators between the wetland and riverine habitats establish a level of functional connectivity between these aquatic ecosystems. I constructed a habitat suitability index of both the wetlands and the surrounding landscape to determine which patch and landscape characteristics were important to wetland use by alligators. I found that both descriptive wetland characteristics and the spatial relationships between wetlands were important predictors of alligator use. Overland movement was related to upland landuse as well as distance between aquatic habitats. Conserving a variety of wetland sizes and types within an intact upland matrix is critical to maintaining connectivity across the landscape. Furthermore, understanding how species may act as mobile links between ecosystems, particularly those with ontogenetic niche shifts, illustrates the importance of approaching conservation from a landscape perspective.

Human activities in the form of land use changes, urbanisation and infrastructure developments are major threats to biodiversity. The loss and fragmentation of natural habitats are great obstacles for the long term preservation of biodiversity and nature protection measures alone may not be sufficient to tackle the problem. Environmental impact assessment (EIA) and strategic environmental assessment (SEA) play a central role in identifying, predicting and managing the impacts of human activities on biodiversity. The review of current practice suggests that the complexity of the task is underestimated and that new methodological approaches encompassing the entire landscape are needed. Spatial aspects of the assessment and the lack of information on scale-related issues are particular problems affecting the appropriate assessment of cumulative effects. In parallel with the development and establishment of EIA and SEA, spatial modelling is an expanding field in ecology and many derived applications could be suitable for the prediction and assessment of biodiversity-related impacts. The diversity of modelling methods suggests that a strategy is needed to identify prediction methods appropriate for EIA and SEA. The relevance and potential limitations of GIS-based species distribution and habitat models in predicting impacts on biodiversity were examined in three studies in the greater Stockholm area. Distinct approaches to habitat suitability modelling were compared from the perspective of environmental assessment needs and requirements. The results showed that model performance, validity and ultimate suitability for planning applications were strongly dependent on empirical data and expert knowledge. The methods allowed visual, qualitative and quantitative assessment of habitat loss, thus improving decision support for assessment of impacts on biodiversity. The proposed methods allowed areas of high ecological value and the surrounding landscape to be considered in the same assessment, thereby contributing to better integration of biodiversity issues in physical planning. / QC 20100727

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