An ArcGIS Tool for Modeling the Climate Envelope with Feed-Forward ANN

This paper is about the development and the application of an ESRI ArcGIS tool which implements multi-layer, feed-forward artificial neural network (ANN) to study the climate envelope of species. The supervised learning is achieved by backpropagation algorithm. Based on the distribution and the grids of the climate (and edaphic data) of the reference and future periods the tool predicts the future potential distribution of the studied species. The trained network can be saved and loaded. A modeling result based on the distribution of European larch (Larix decidua Mill.) is presented as a case study

Analysis and visualization of energy use for university campus

The reduction of greenhouse gas emissions is one of the big global challenges for the next decades due to its severe impact on the atmosphere that leads to a change in the climate and other environmental factors. One of the main sources of greenhouse gas is energy consumption, therefore a number of initiatives and calls for awareness and sustainability in energy use are issued among different types of institutional and organizations. The European Council adopted in 2007 energy and climate change objectives for 20% improvement until 2020. All European countries are required to use energy with more efficiency. Several steps could be conducted for energy reduction: understanding the buildings behavior through time, revealing the factors that influence the consumption, applying the right measurement for reduction and sustainability, visualizing the hidden connection between our daily habits impacts on the natural world and promoting to more sustainable life. Researchers have suggested that feedback visualization can effectively encourage conservation with energy reduction rate of 18%. Furthermore, researchers have contributed to the identification process of a set of factors which are very likely to influence consumption. Such as occupancy level, occupants behavior, environmental conditions, building thermal envelope, climate zones, etc. Nowadays, the amount of energy consumption at the university campuses are huge and it needs great effort to meet the reduction requested by European Council as well as the cost reduction. Thus, the present study was performed on the university buildings as a use case to: a. Investigate the most dynamic influence factors on energy consumption in campus; b. Implement prediction model for electricity consumption using different techniques, such as the traditional regression way and the alternative machine learning techniques; and c. Assist energy management by providing a real time energy feedback and visualization in campus for more awareness and better decision making. This methodology is implemented to the use case of University Jaume I (UJI), located in Castellon, Spain

Mapping priority marine habitats : knowledge of their ecosystem to underpin the marine planning process

Marine planners need to know about ecosystems, such as Priority Marine Habitats (PMHs) in order to manage and conserve them effectively. The overarching theme of this thesis is to contribute to this knowledge through the development of “marine planning tools”. The primary focus is on the PMH, Modiolus modiolus beds, although other PMHs and Marine Protected Areas (MPAs) were also considered. Four key studies were designed and conducted, i) Species Distribution Modelling (SDM) of M. modiolus in UK waters; ii) SDM of PMHs in Europe; iii) assessment of MPA management effort; and iv) the genetic connectivity of M. modiolus beds Overall, the research provided information and knowledge to contribute to implementation of a truly ecosystem-based approach to management and effective PMH management. It is now known: i) where Modiolus modiolus beds occur; ii) where they have the potential to occur, now and in the future; iii) that there is the potential for them to be lost/ hindered or lack-viability if ocean temperatures increase; iv) that they may become more important to conservation at northern latitudes in the future; v) that European nations will have to work towards integrated marine conservation policies and protection when considering all PMHs; vi) that some MPAs may require more effort to manage than others and that it may be possible to predict which ones they will be; vii) that cumulative human impacts may not be the driving force for management effort; and viii) that some M. modiolus beds in the UK are potentially connected. The data and discussion points generated within this thesis will enable effective PMH management through the selection of appropriate management strategies

Mid-Pleistocene and Holocene demographic fluctuation of Scots pine (Pinus sylvestris L.) in the Carpathian Mountains and the Pannonian Basin: Signs of historical expansions and contractions

Climate fluctuations of the Quaternary caused radical changes in distribution of tree species and resulted in large-scale range shifts, population contractions and expansions. Scots pine (Pinus sylvestris L.) a widely distributed conifer of the boreal regions underwent spatio-temporal changes, which shaped the modern-day genetic structure and phylogeographic pattern of the species. By applying independent approaches, including molecular genetic data and historical climate models we aimed to describe demography and past distribution patterns of Scots pine populations from the highly fragmented southern periphery, the Carpathians and the Pannonian Basin. We used Approximate Bayesian Computation (ABC) approach based on nuclear microsatellite markers (nSSRs) and Maximum Entropy distribution modelling (MaxEnt) with temperature- and precipitation-related bioclimatic data. ABC results indicated that from an ancestral Scots pine population two genetic lineages have diverged that in the Mid-Pleistocene due to the favourable climatic conditions underwent population expansion leading to an admixture event. The outcome of the hindcasting confirmed the expansion that leaded to the admixture event revealed by the ABC analysis. This can be dated to the Late Glacial period (14,160–11,800 yrs BP), in which widespread distribution of Scots pine in accordance with palynological proxies was detected. Predictions for the Mid-Holocene period have shown large-scale reduction in distribution of Scots pine and low probability of its occurrence, leading to disjunction and population fragmentation

INTEGRATED MODELING OF LAND USE AND CLIMATE CHANGE IMPACTS ON MULTISCALE ECOSYSTEMS OF CENTRAL AFRICAN WATERSHEDS

Assessment and management of ecosystem services demands diverse knowledge of the system components. Land use change occurring mainly through deforestation, expansion of agriculture and unregulated extraction of natural resources are the greatest challenges of the Congo basin and yet is central to supporting over 100 million people. This study undertook to implement an integrated modeling of multiscale ecosystems of central African watersheds and model the impact of anthropogenic factors on elephant population in Greater Virunga landscape. The study was conducted at varied scales, regional, landscape, and community. Regional study included watershed analysis and hydrological assessment using remotely sensed data implemented in Geographical information System. Species distribution modeling using generalized linear models using presence only and pseudo absence data was also done at regional scale. The major findings were that ecosystem services for the Congo basin are spatially varied and there are significant differences in their distribution of ecosystem services at a subwatershed level three and six and the distribution of endangered and threatened species is more concentrated in the central part of the basin and most of these species occur mainly inside protected areas. Poaching and sustained civil wars were the biggest threat to elephant conservation in the region. Improvement in law enforcement, monitoring, and increasing household incomes for communities living adjacent to protected areas would help to reduce the impact of poaching on elephant population dynamics. Climate change did not show immediate direct impacts on the elephant population, but thermal and latent heat effects could be occurring. A change in habitat, however, showed resulted in an upward trend in elephant population for all age classes. The local communities heavily depend on these ecosystem services for their livelihoods. It is therefore recommended that reasonable financing to strengthen law enforcement and monitoring is done, multiple policy options should be considered in order to maximize ecosystem benefits. Creation of partnerships and research networks need to be promoted. Existing transboundary collaboration initiatives should continue and be supported by the donor community in order to build peace and dram support for wildlife and wild habitat protection

Scale aware modeling and monitoring of the urban energy chain

With energy modeling at different complexity levels for smart cities and the concurrent data availability revolution from connected devices, a steady surge in demand for spatial knowledge has been observed in the energy sector. This transformation occurs in population centers focused on efficient energy use and quality of life. Energy-related services play an essential role in this mix, as they facilitate or interact with all other city services. This trend is primarily driven by the current age of the Ger.: Energiewende or energy transition, a worldwide push towards renewable energy sources, increased energy use efficiency, and local energy production that requires precise estimates of local energy demand and production. This shift in the energy market occurs as the world becomes aware of human-induced climate change, to which the building stock has a significant contribution (40% in the European Union). At the current rate of refurbishment and building replacement, of the buildings existing in 2050 in the European Union, 75% would not be classified as energy-efficient. That means that substantial structural change in the built environment and the energy chain is required to achieve EU-wide goals concerning environmental and energy policy. These objectives provide strong motivation for this thesis work and are generally made possible by energy monitoring and modeling activities that estimate the urban energy needs and quantify the impact of refurbishment measures. To this end, a modeling library called aEneAs was developed in the scope of this thesis that can perform city-wide building energy modeling. The library performs its tasks at the level of a single building and was a first in its field, using standardized spatial energy data structures that allow for portability from one city to another. For data input, extensive use was made of digital twins provided from CAD, BIM, GIS, architectural models, and a plethora of energy data sources. The library first quantifies primary thermal energy demand and then the impact of refurbishment measures. Lastly, it estimates the potential of renewable energy production from solar radiation. aEneAs also includes network modeling components that consider energy distribution in the given context, showing a path toward data modeling and simulation required for distributed energy production at the neighborhood and district level. In order to validate modeling activities in solar radiation and green façade and roof installations, six spatial models were coupled with sensor installations. These digital twins are included in three experiments that highlight this monitoring side of the energy chain and portray energy-related use cases that utilize the spatially enabled web services SOS-SES-WNS, SensorThingsAPI, and FIWARE. To this author\u27s knowledge, this is the first work that surveys the capabilities of these three solutions in a unifying context, each having its specific design mindset. The modeling and monitoring activity and their corresponding literature review indicated gaps in scientific knowledge concerning data science in urban energy modeling. First, a lack of standardization regarding the spatial scales at which data is stored and used in urban energy modeling was observed. In order to identify the appropriate spatial levels for modeling and data aggregation, scale is explored in-depth in the given context and defined as a byproduct of resolution and extent, with ranges provided for both parameters. To that end, a survey of the encountered spatial scales and actors in six different geographical and cultural settings was performed. The information from this survey was used to put forth a standardized spatial scales definition and create a scale-dependent ontology for use in urban energy modeling. The ontology also provides spatially enabled persistent identifiers that resolve issues encountered with object relationships in modeling for inheritance, dependency, and association. The same survey also reveals two significant issues with data in urban energy modeling. These are data consistency across spatial scales and urban fabric contiguity. The impact of these issues and different solutions such as data generalization are explored in the thesis. Further advancement of scientific knowledge is provided specifically with spatial standards and spatial data infrastructure in urban energy modeling. A review of use cases in the urban energy chain and a taxonomy of the standards were carried out. These provide fundamental input for another piece of this thesis: inclusive software architecture methods that promote data integration and allow for external connectivity to modern and legacy systems. In order to reduce time-costly extraction, transformation, and load processes, databases and web services to ferry data to and from separate data sources were used. As a result, the spatial models become central linking elements of the different types of energy-related data in a novel perspective that differs from the traditional one, where spatial data tends to be non-interoperable / not linked with other data types. These distinct data fusion approaches provide flexibility in an energy chain environment with inconsistent data structures and software. Furthermore, the knowledge gathered from the experiments presented in this thesis is provided as a synopsis of good practices