Exploring strategic farming choices to respond to mitigation and adaptation to climate change

Las alteraciones del sistema climático debido al aumento de concentraciones de gases de efecto invernadero (GEI) en la atmósfera, tendrán implicaciones importantes para la agricultura, el medio ambiente y la sociedad. La agricultura es una fuente importante de emisiones de gases de efecto invernadero (globalmente contribuye al 12% del total de GEI), y al mismo tiempo puede ser parte de la solución para mitigar las emisiones y adaptarse al cambio climático. Las acciones frente al desafío del cambio climático deben priorizar estrategias de adaptación y mitigación en la agricultura dentro de la agenda para el desarrollo de políticas. La agricultura es por tanto crucial para la conservación y el uso sostenible de los recursos naturales, que ya están sometidos a impactos del cambio climático, al mismo tiempo que debe suministrar alimentos para una población creciente. Por tanto, es necesaria una coordinación entre las actuales estrategias de política climática y agrícola. El concepto de agricultura climáticamente inteligente ha surgido para integrar todos estos servicios de la producción agraria. Al evaluar opciones para reducir las amenazas del cambio climático para la agricultura y el medio ambiente, surgen dos preguntas de investigación: • ¿Qué información es necesaria para definir prácticas agrarias inteligentes? • ¿Qué factores influyen en la implementación de las prácticas agrarias inteligentes? Esta Tesis trata de proporcionar información relevante sobre estas cuestiones generales con el fin de apoyar el desarrollo de la política climática. Se centra en sistemas agrícolas Mediterráneos. Esta Tesis integra diferentes métodos y herramientas para evaluar las alternativas de gestión agrícola y políticas con potencial para responder a las necesidades de mitigación y adaptación al cambio climático. La investigación incluye enfoques cuantitativos y cualitativos e integra variables agronómicas, de clima y socioeconómicas a escala local y regional. La investigación aporta una recopilación de datos sobre evidencia experimental existente, y un estudio integrado sobre el comportamiento de los agricultores y las posibles alternativas de cambio (por ejemplo, la tecnología, la gestión agrícola y la política climática). Los casos de estudio de esta Tesis - el humedal de Doñana (S España) y la región de Aragón (NE España) - permiten ilustrar dos sistemas Mediterráneos representativos, donde el uso intensivo de la agricultura y las condiciones semiáridas son ya una preocupación. Por este motivo, la adopción de estrategias de mitigación y adaptación puede desempeñar un papel muy importante a la hora de encontrar un equilibrio entre la equidad, la seguridad económica y el medio ambiente en los escenarios de cambio climático. La metodología multidisciplinar de esta tesis incluye una amplia gama de enfoques y métodos para la recopilación y el análisis de datos. La toma de datos se apoya en la revisión bibliográfica de evidencia experimental, bases de datos públicas nacionales e internacionales y datos primarios recopilados mediante entrevistas semi-estructuradas con los grupos de interés (administraciones públicas, responsables políticos, asesores agrícolas, científicos y agricultores) y encuestas con agricultores. Los métodos de análisis incluyen: meta-análisis, modelos de gestión de recursos hídricos (modelo WAAPA), análisis multicriterio para la toma de decisiones, métodos estadísticos (modelos de regresión logística y de Poisson) y herramientas para el desarrollo de políticas basadas en la ciencia. El meta-análisis identifica los umbrales críticos de temperatura que repercuten en el crecimiento y el desarrollo de los tres cultivos principales para la seguridad alimentaria (arroz, maíz y trigo). El modelo WAAPA evalúa el efecto del cambio climático en la gestión del agua para la agricultura de acuerdo a diferentes alternativas políticas y escenarios climáticos. El análisis multicriterio evalúa la viabilidad de las prácticas agrícolas de mitigación en dos escenarios climáticos de acuerdo a la percepción de diferentes expertos. Los métodos estadísticos analizan los determinantes y las barreras para la adopción de prácticas agrícolas de mitigación. Las herramientas para el desarrollo de políticas basadas en la ciencia muestran el potencial y el coste para reducir GEI mediante las prácticas agrícolas. En general, los resultados de esta Tesis proporcionan información sobre la adaptación y la mitigación del cambio climático a nivel de explotación para desarrollar una política climática más integrada y ayudar a los agricultores en la toma de decisiones. Los resultados muestran las temperaturas umbral y la respuesta del arroz, el maíz y el trigo a temperaturas extremas, siendo estos valores de gran utilidad para futuros estudios de impacto y adaptación. Los resultados obtenidos también aportan una serie de estrategias flexibles para la adaptación y la mitigación a escala local, proporcionando a su vez una mejor comprensión sobre las barreras y los incentivos para su adopción. La capacidad de mejorar la disponibilidad de agua y el potencial y el coste de reducción de GEI se han estimado para estas estrategias en los casos de estudio. Estos resultados podrían ayudar en el desarrollo de planes locales de adaptación y políticas regionales de mitigación, especialmente en las regiones Mediterráneas. ABSTRACT Alterations in the climatic system due to increased atmospheric concentrations of greenhouse gas emissions (GHG) are expected to have important implications for agriculture, the environment and society. Agriculture is an important source of GHG emissions (12 % of global anthropogenic GHG), but it is also part of the solution to mitigate emissions and to adapt to climate change. Responses to face the challenge of climate change should place agricultural adaptation and mitigation strategies at the heart of the climate change agenda. Agriculture is crucial for the conservation and sustainable use of natural resources, which already stand under pressure due to climate change impacts, increased population, pollution and fragmented and uncoordinated climate policy strategies. The concept of climate smart agriculture has emerged to encompass all these issues as a whole. When assessing choices aimed at reducing threats to agriculture and the environment under climate change, two research questions arise: • What information defines smart farming choices? • What drives the implementation of smart farming choices? This Thesis aims to provide information on these broad questions in order to support climate policy development focusing in some Mediterranean agricultural systems. This Thesis integrates methods and tools to evaluate potential farming and policy choices to respond to mitigation and adaptation to climate change. The assessment involves both quantitative and qualitative approaches and integrates agronomic, climate and socioeconomic variables at local and regional scale. The assessment includes the collection of data on previous experimental evidence, and the integration of farmer behaviour and policy choices (e.g., technology, agricultural management and climate policy). The case study areas -- the Doñana coastal wetland (S Spain) and the Aragón region (NE Spain) – illustrate two representative Mediterranean regions where the intensive use of agriculture and the semi-arid conditions are already a concern. Thus the adoption of mitigation and adaptation measures can play a significant role for reaching a balance among equity, economic security and the environment under climate change scenarios. The multidisciplinary methodology of this Thesis includes a wide range of approaches for collecting and analysing data. The data collection process include revision of existing experimental evidence, public databases and the contribution of primary data gathering by semi-structured interviews with relevant stakeholders (i.e., public administrations, policy makers, agricultural advisors, scientist and farmers among others) and surveys given to farmers. The analytical methods include meta-analysis, water availability models (WAAPA model), decision making analysis (MCA, multi-criteria analysis), statistical approaches (Logistic and Poisson regression models) and science-base policy tools (MACC, marginal abatement cost curves and SOC abatement wedges). The meta-analysis identifies the critical temperature thresholds which impact on the growth and development of three major crops (i.e., rice, maize and wheat). The WAAPA model assesses the effect of climate change for agricultural water management under different policy choices and climate scenarios. The multi-criteria analysis evaluates the feasibility of mitigation farming practices under two climate scenarios according to the expert views. The statistical approaches analyses the drivers and the barriers for the adoption of mitigation farming practices. The science-base policy tools illustrate the mitigation potential and cost effectiveness of the farming practices. Overall, the results of this Thesis provide information to adapt to, and mitigate of, climate change at farm level to support the development of a comprehensive climate policy and to assist farmers. The findings show the key temperature thresholds and response to extreme temperature effects for rice, maize and wheat, so such responses can be included into crop impact and adaptation models. A portfolio of flexible adaptation and mitigation choices at local scale are identified. The results also provide a better understanding of the stakeholders oppose or support to adopt the choices which could be used to incorporate in local adaptation plans and mitigation regional policy. The findings include estimations for the farming and policy choices on the capacity to improve water supply reliability, abatement potential and cost-effective in Mediterranean regions.

Adaptation of a Task-oriented Training Environment to its Users

The problem of adapting teaching systems to the teacher has not been extensively covered in the specialised literature. The authors present the server-client architecture of a Task-Oriented Environment for Design of Virtual Labs (TOEDVL). The paper focuses on the computational models supporting its base of tasks (BT) and on two groups of behavioural tutor’s models for planning training sessions. Detailed examples are presented.

Multi-agent systems for modeling high penetration photovoltaic system impacts in distribution networks

This paper reviews the use of multi-agent systems to model the impacts of high levels of photovoltaic (PV) system penetration in distribution networks and presents some preliminary data obtained from the Perth Solar City high penetration PV trial. The Perth Solar City trial consists of a low voltage distribution feeder supplying 75 customers where 29 consumers have roof top photovoltaic systems. Data is collected from smart meters at each consumer premises, from data loggers at the transformer low voltage (LV) side and from a nearby distribution network SCADA measurement point on the high voltage side (HV) side of the transformer. The data will be used to progressively develop MAS models.

Modelos de resposta à interação entre fármacos anestésicos : análise de regressão e análise de Clusters

Os avanços tecnológicos e científicos, na área da saúde, têm vindo a aliar áreas como a Medicina e a Matemática, cabendo à ciência adequar de forma mais eficaz os meios de investigação, diagnóstico, monitorização e terapêutica. Os métodos desenvolvidos e os estudos apresentados nesta dissertação resultam da necessidade de encontrar respostas e soluções para os diferentes desafios identificados na área da anestesia. A índole destes problemas conduz, necessariamente, à aplicação, adaptação e conjugação de diferentes métodos e modelos das diversas áreas da matemática. A capacidade para induzir a anestesia em pacientes, de forma segura e confiável, conduz a uma enorme variedade de situações que devem ser levadas em conta, exigindo, por isso, intensivos estudos. Assim, métodos e modelos de previsão, que permitam uma melhor personalização da dosagem a administrar ao paciente e por monitorizar, o efeito induzido pela administração de cada fármaco, com sinais mais fiáveis, são fundamentais para a investigação e progresso neste campo. Neste contexto, com o objetivo de clarificar a utilização em estudos na área da anestesia de um ajustado tratamento estatístico, proponho-me abordar diferentes análises estatísticas para desenvolver um modelo de previsão sobre a resposta cerebral a dois fármacos durante sedação. Dados obtidos de voluntários serão utilizados para estudar a interação farmacodinâmica entre dois fármacos anestésicos. Numa primeira fase são explorados modelos de regressão lineares que permitam modelar o efeito dos fármacos no sinal cerebral BIS (índice bispectral do EEG – indicador da profundidade de anestesia); ou seja estimar o efeito que as concentrações de fármacos têm na depressão do eletroencefalograma (avaliada pelo BIS). Na segunda fase deste trabalho, pretende-se a identificação de diferentes interações com Análise de Clusters bem como a validação do respetivo modelo com Análise Discriminante, identificando grupos homogéneos na amostra obtida através das técnicas de agrupamento. O número de grupos existentes na amostra foi, numa fase exploratória, obtido pelas técnicas de agrupamento hierárquicas, e a caracterização dos grupos identificados foi obtida pelas técnicas de agrupamento k-means. A reprodutibilidade dos modelos de agrupamento obtidos foi testada através da análise discriminante. As principais conclusões apontam que o teste de significância da equação de Regressão Linear indicou que o modelo é altamente significativo. As variáveis propofol e remifentanil influenciam significativamente o BIS e o modelo melhora com a inclusão do remifentanil. Este trabalho demonstra ainda ser possível construir um modelo que permite agrupar as concentrações dos fármacos, com base no efeito no sinal cerebral BIS, com o apoio de técnicas de agrupamento e discriminantes. Os resultados desmontram claramente a interacção farmacodinâmica dos dois fármacos, quando analisamos o Cluster 1 e o Cluster 3. Para concentrações semelhantes de propofol o efeito no BIS é claramente diferente dependendo da grandeza da concentração de remifentanil. Em suma, o estudo demostra claramente, que quando o remifentanil é administrado com o propofol (um hipnótico) o efeito deste último é potenciado, levando o sinal BIS a valores bastante baixos.

MODULARITY, NOISE, AND NATURAL SELECTION

Most biological systems are formed by component parts that are to some degree interrelated. Groups of parts that are more associated among themselves and are relatively autonomous from others are called modules. One of the consequences of modularity is that biological systems usually present an unequal distribution of the genetic variation among traits. Estimating the covariance matrix that describes these systems is a difficult problem due to a number of factors such as poor sample sizes and measurement errors. We show that this problem will be exacerbated whenever matrix inversion is required, as in directional selection reconstruction analysis. We explore the consequences of varying degrees of modularity and signal-to-noise ratio on selection reconstruction. We then present and test the efficiency of available methods for controlling noise in matrix estimates. In our simulations, controlling matrices for noise vastly improves the reconstruction of selection gradients. We also perform an analysis of selection gradients reconstruction over a New World Monkeys skull database to illustrate the impact of noise on such analyses. Noise-controlled estimates render far more plausible interpretations that are in full agreement with previous results.

A service-oriented user interaction analysis framework supporting adaptive applications

A comprehensive user model, built by monitoring a user's current use of applications, can be an excellent starting point for building adaptive user-centred applications. The BaranC framework monitors all user interaction with a digital device (e.g. smartphone), and also collects all available context data (such as from sensors in the digital device itself, in a smart watch, or in smart appliances) in order to build a full model of user application behaviour. The model built from the collected data, called the UDI (User Digital Imprint), is further augmented by analysis services, for example, a service to produce activity profiles from smartphone sensor data. The enhanced UDI model can then be the basis for building an appropriate adaptive application that is user-centred as it is based on an individual user model. As BaranC supports continuous user monitoring, an application can be dynamically adaptive in real-time to the current context (e.g. time, location or activity). Furthermore, since BaranC is continuously augmenting the user model with more monitored data, over time the user model changes, and the adaptive application can adapt gradually over time to changing user behaviour patterns. BaranC has been implemented as a service-oriented framework where the collection of data for the UDI and all sharing of the UDI data are kept strictly under the user's control. In addition, being service-oriented allows (with the user's permission) its monitoring and analysis services to be easily used by 3rd parties in order to provide 3rd party adaptive assistant services. An example 3rd party service demonstrator, built on top of BaranC, proactively assists a user by dynamic predication, based on the current context, what apps and contacts the user is likely to need. BaranC introduces an innovative user-controlled unified service model of monitoring and use of personal digital activity data in order to provide adaptive user-centred applications. This aims to improve on the current situation where the diversity of adaptive applications results in a proliferation of applications monitoring and using personal data, resulting in a lack of clarity, a dispersal of data, and a diminution of user control.

Cultural adaptation and resilience: Controversies, issues and emerging models

What enables people to bounce back from stressful experiences? How do certain individuals maintain a sense of purpose and direction over the long term, even in the face of adversity? This is the first book to move beyond childhood and adolescence to explore resilience across the lifespan. Coverage ranges from genetic and physiological factors through personal, family, organizational, and community processes. Contributors examine how resilience contributes to health and well-being across the adult life cycle; why—and what happens when—resilience processes fail; ethnic and cultural dimensions of resilience; and ways to enhance adult resilience, including reviews of exemplary programs.

Models of advertising standardisation and adaptation: it's time to move the debate forward

Advertising standardisation versus adaptation has been discussed in some detail in the marketing literature. Despite previous attempts, there is still no widely-used decision-making model available that has been accepted by marketing practitioners and academics. This paper examines the development of this important area by reviewing six prominent models in the advertising standardisation/adaptation literature. It shows why there has been a lack of development in the current literature and why it is crucial to address this problem. Important areas for future research are suggested in order to find a solution

Scalable black-box prediction models for multi-dimensional adaptation on NUMA multi-cores

This paper presents a scalable, statistical ‘black-box’ model for predicting the performance of parallel programs on multi-core non-uniform memory access (NUMA) systems. We derive a model with low overhead, by reducing data collection and model training time. The model can accurately predict the behaviour of parallel applications in response to changes in their concurrency, thread layout on NUMA nodes, and core voltage and frequency. We present a framework that applies the model to achieve significant energy and energy-delay-square (ED2) savings (9% and 25%, respectively) along with performance improvement (10% mean) on an actual 16-core NUMA system running realistic application workloads. Our prediction model proves substantially more accurate than previous efforts.

Mutual Information and Perplexity based Clustering of Dialogue Information for Dynamic Adaptation of Language Models

We present two approaches to cluster dialogue-based information obtained by the speech understanding module and the dialogue manager of a spoken dialogue system. The purpose is to estimate a language model related to each cluster, and use them to dynamically modify the model of the speech recognizer at each dialogue turn. In the first approach we build the cluster tree using local decisions based on a Maximum Normalized Mutual Information criterion. In the second one we take global decisions, based on the optimization of the global perplexity of the combination of the cluster-related LMs. Our experiments show a relative reduction of the word error rate of 15.17%, which helps to improve the performance of the understanding and the dialogue manager modules.

Development of mathematical models to elaborate strategies, select alternatives and development of plans for adaptation of communities to climate change in different geographical areas including costs to implement it.

There is evidence that the climate changes and that now, the change is influenced and accelerated by the CO2 augmentation in atmosphere due to combustion by humans. Such ?Climate change? is on the policy agenda at the global level, with the aim of understanding and reducing its causes and to mitigate its consequences. In most countries and international organisms UNO (e.g. Rio de Janeiro 1992), OECD, EC, etc . . . the efforts and debates have been directed to know the possible causes, to predict the future evolution of some variable conditioners, and trying to make studies to fight against the effects or to delay the negative evolution of such. The Protocol of Kyoto 1997 set international efforts about CO2 emissions, but it was partial and not followed e.g. by USA and China . . . , and in Durban 2011 the ineffectiveness of humanity on such global real challenges was set as evident. Among all that, the elaboration of a global model was not boarded that can help to choose the best alternative between the feasible ones, to elaborate the strategies and to evaluate the costs, and the authors propose to enter in that frame for study. As in all natural, technological and social changes, the best-prepared countries will have the best bear and the more rapid recover. In all the geographic areas the alternative will not be the same one, but the model must help us to make the appropriated decision. It is essential to know those areas that are more sensitive to the negative effects of climate change, the parameters to take into account for its evaluation, and comprehensive plans to deal with it. The objective of this paper is to elaborate a mathematical model support of decisions, which will allow to develop and to evaluate alternatives of adaptation to the climatic change of different communities in Europe and Latin-America, mainly in especially vulnerable areas to the climatic change, considering in them all the intervening factors. The models will consider criteria of physical type (meteorological, edaphic, water resources), of use of the ground (agriculturist, forest, mining, industrial, urban, tourist, cattle dealer), economic (income, costs, benefits, infrastructures), social (population), politician (implementation, legislation), educative (Educational programs, diffusion) and environmental, at the present moment and the future. The intention is to obtain tools for aiding to get a realistic position for these challenges, which are an important part of the future problems of humanity in next decades.

Development of mathematical models to elaborate strategies, to select alternatives and the development of plans for the adaptation of communities to climate change in different geographical areas including costs to implement it

Climate change is on the policy agenda at the global level, with the aim of understanding and reducing its causes and to mitigate its consequences. In most of the countries and international organisms UNO, OECD, EC, etc … the efforts and debates have been directed to know the possible causes, to predict the future evolution of some variable conditioners, and trying to make studies to fight against the effects or to delay the negative evolution of such. Nevertheless, the elaboration of a global model was not boarded that can help to choose the best alternative between the feasible ones, to elaborate the strategies and to evaluate the costs. As in all natural, technological and social changes, the best-prepared countries will have the best bear and the more rapid recover. In all the geographic areas the alternative will not be the same one, but the model should help us to make the appropriated decision. It is essential to know those areas that are more sensitive to the negative effects of climate change, the parameters to take into account for its evaluation, and comprehensive plans to deal with it. The objective of this paper is to elaborate a mathematical model support of decisions, that will allow to develop and to evaluate alternatives of adaptation to the climatic change of different communities in Europe and Latin-America, mainly, in vulnerable areas to the climatic change, considering in them all the intervening factors. The models will take into consideration criteria of physical type (meteorological, edaphic, water resources), of use of the ground (agriculturist, forest, mining, industrial, urban, tourist, cattle dealer), economic (income, costs, benefits, infrastructures), social (population), politician (implementation, legislation), educative (Educational programs, diffusion), sanitary and environmental, at the present moment and the future.