Assessing agglomeration economies in the Yangzi River Delta, China : a bayesian spatial econometric approach

This paper estimates the elasticity of labor productivity with respect to employment density, a widely used measure of the agglomeration effect, in the Yangtze River Delta, China. A spatial Durbin model is presented that makes explicit the influences of spatial dependence and endogeneity bias in a very simple way. Results of Bayesian estimation using the data of the year 2009 indicate that the productivity is influenced by factors correlated with density rather than density itself and that spatial spillovers of these factors of agglomeration play a significant role. They are consistent with the findings of Ke (2010) and Artis, et al. (2011) that suggest the importance of taking into account spatial dependence and hitherto omitted variables.

Spatial spillovers from FDI agglomeration : evidence from the Yangtze River Delta in China

Foreign firms have clustered together in the Yangtze River Delta, and their impact on domestic firms is an important policy issue. This paper studies the spatial effect of FDI agglomeration on the regional productivity of domestic firms, using Chinese firm-level data. To identify local FDI spillovers, we estimate the causal impact of foreign firms on domestic firms in the same county and similar industries. We then estimate a spatial-autoregressive model to examine spatial spillovers from FDI clusters to other domestic firms in distant counties. Our results show that FDI agglomeration generates positive spillovers for domestic firms, which are stronger in nearby areas than in distant areas.

Spatial spillover effects in determining China's regional CO2 emission growth : 2007-2010

This paper proposes an alternative input-output based spatial-structural decomposition analysis to elucidate the role of domestic-regional heterogeneity and interregional spillover effects in determining China's regional CO2 emission growth. Our empirical results based on the 2007 and 2010 Chinese interregional input-output tables show that the changes in most regions' final demand scale, final expenditure structure and export scale give positive spatial spillover effects on other regions' CO2 emission growth, the changes in most regions' consumption and export preference help the reduction of other regions' CO2 emissions, the changes in production technology, and investment preference may give positive or negative impacts on other region's CO2 emission growth through domestic supply chains. For some regions, the aggregate spillover effect from other regions may be larger than the intra-regional effect in determining regional emission growth. All these facts can significantly help better and deeper understanding on the driving forces of China's regional CO2 emission growth, thus can enrich the policy implication concerning a narrow definition of "carbon leakage" through domestic-interregional trade, and relevant political consensus about the responsibility sharing between developed and developing regions inside China.

Modelling the Impact of Built Environment, Geographical Scales and Latent Constructs On Individual Travel Behaviour

La relación entre la estructura urbana y la movilidad ha sido estudiada desde hace más de 70 años. El entorno urbano incluye múltiples dimensiones como por ejemplo: la estructura urbana, los usos de suelo, la distribución de instalaciones diversas (comercios, escuelas y zonas de restauración, parking, etc.). Al realizar una revisión de la literatura existente en este contexto, se encuentran distintos análisis, metodologías, escalas geográficas y dimensiones, tanto de la movilidad como de la estructura urbana. En este sentido, se trata de una relación muy estudiada pero muy compleja, sobre la que no existe hasta el momento un consenso sobre qué dimensión del entorno urbano influye sobre qué dimensión de la movilidad, y cuál es la manera apropiada de representar esta relación. Con el propósito de contestar estas preguntas investigación, la presente tesis tiene los siguientes objetivos generales: (1) Contribuir al mejor entendimiento de la compleja relación estructura urbana y movilidad. y (2) Entender el rol de los atributos latentes en la relación entorno urbano y movilidad. El objetivo específico de la tesis es analizar la influencia del entorno urbano sobre dos dimensiones de la movilidad: número de viajes y tipo de tour. Vista la complejidad de la relación entorno urbano y movilidad, se pretende contribuir al mejor entendimiento de la relación a través de la utilización de 3 escalas geográficas de las variables y del análisis de la influencia de efectos inobservados en la movilidad. Para el análisis se utiliza una base de datos conformada por tres tipos de datos: (1) Una encuesta de movilidad realizada durante los años 2006 y 2007. Se obtuvo un total de 943 encuestas, en 3 barrios de Madrid: Chamberí, Pozuelo y Algete. (2) Información municipal del Instituto Nacional de Estadística: dicha información se encuentra enlazada con los orígenes y destinos de los viajes recogidos en la encuesta. Y (3) Información georeferenciada en Arc-GIS de los hogares participantes en la encuesta: la base de datos contiene información respecto a la estructura de las calles, localización de escuelas, parking, centros médicos y lugares de restauración. Se analizó la correlación entre e intra-grupos y se modelizaron 4 casos de atributos bajo la estructura ordinal logit. Posteriormente se evalúa la auto-selección a través de la estimación conjunta de las elecciones de tipo de barrio y número de viajes. La elección del tipo de barrio consta de 3 alternativas: CBD, Urban y Suburban, según la zona de residencia recogida en las encuestas. Mientras que la elección del número de viajes consta de 4 categorías ordinales: 0 viajes, 1-2 viajes, 3-4 viajes y 5 o más viajes. A partir de la mejor especificación del modelo ordinal logit. Se desarrolló un modelo joint mixed-ordinal conjunto. Los resultados indican que las variables exógenas requieren un análisis exhaustivo de correlaciones con el fin de evitar resultados sesgados. ha determinado que es importante medir los atributos del BE donde se realiza el viaje, pero también la información municipal es muy explicativa de la movilidad individual. Por tanto, la percepción de las zonas de destino a nivel municipal es considerada importante. En el contexto de la Auto-selección (self-selection) es importante modelizar conjuntamente las decisiones. La Auto-selección existe, puesto que los parámetros estimados conjuntamente son significativos. Sin embargo, sólo ciertos atributos del entorno urbano son igualmente importantes sobre la elección de la zona de residencia y frecuencia de viajes. Para analizar la Propensión al Viaje, se desarrolló un modelo híbrido, formado por: una variable latente, un indicador y un modelo de elección discreta. La variable latente se denomina “Propensión al Viaje”, cuyo indicador en ecuación de medida es el número de viajes; la elección discreta es el tipo de tour. El modelo de elección consiste en 5 alternativas, según la jerarquía de actividades establecida en la tesis: HOME, no realiza viajes durante el día de estudio, HWH tour cuya actividad principal es el trabajo o estudios, y no se realizan paradas intermedias; HWHs tour si el individuo reaiza paradas intermedias; HOH tour cuya actividad principal es distinta a trabajo y estudios, y no se realizan paradas intermedias; HOHs donde se realizan paradas intermedias. Para llegar a la mejor especificación del modelo, se realizó un trabajo importante considerando diferentes estructuras de modelos y tres tipos de estimaciones. De tal manera, se obtuvieron parámetros consistentes y eficientes. Los resultados muestran que la modelización de los tours, representa una ventaja sobre la modelización de los viajes, puesto que supera las limitaciones de espacio y tiempo, enlazando los viajes realizados por la misma persona en el día de estudio. La propensión al viaje (PT) existe y es específica para cada tipo de tour. Los parámetros estimados en el modelo híbrido resultaron significativos y distintos para cada alternativa de tipo de tour. Por último, en la tesis se verifica que los modelos híbridos representan una mejora sobre los modelos tradicionales de elección discreta, dando como resultado parámetros consistentes y más robustos. En cuanto a políticas de transporte, se ha demostrado que los atributos del entorno urbano son más importantes que los LOS (Level of Service) en la generación de tours multi-etapas. la presente tesis representa el primer análisis empírico de la relación entre los tipos de tours y la propensión al viaje. El concepto Propensity to Travel ha sido desarrollado exclusivamente para la tesis. Igualmente, el desarrollo de un modelo conjunto RC-Number of trips basado en tres escalas de medida representa innovación en cuanto a la comparación de las escalas geográficas, que no había sido hecha en la modelización de la self-selection. The relationship between built environment (BE) and travel behaviour (TB) has been studied in a number of cases, using several methods - aggregate and disaggregate approaches - and different focuses – trip frequency, automobile use, and vehicle miles travelled and so on. Definitely, travel is generated by the need to undertake activities and obtain services, and there is a general consensus that urban components affect TB. However researches are still needed to better understand which components of the travel behaviour are affected most and by which of the urban components. In order to fill the gap in the research, the present dissertation faced two main objectives: (1) To contribute to the better understanding of the relationship between travel demand and urban environment. And (2) To develop an econometric model for estimating travel demand with urban environment attributes. With this purpose, the present thesis faced an exhaustive research and computation of land-use variables in order to find the best representation of BE for modelling trip frequency. In particular two empirical analyses are carried out: 1. Estimation of three dimensions of travel demand using dimensions of urban environment. We compare different travel dimensions and geographical scales, and we measure self-selection contribution following the joint models. 2. Develop a hybrid model, integrated latent variable and discrete choice model. The implementation of hybrid models is new in the analysis of land-use and travel behaviour. BE and TB explicitly interact and allow richness information about a specific individual decision process For all empirical analysis is used a data-base from a survey conducted in 2006 and 2007 in Madrid. Spatial attributes describing neighbourhood environment are derived from different data sources: National Institute of Statistics-INE (Administrative: municipality and district) and GIS (circular units). INE provides raw data for such spatial units as: municipality and district. The construction of census units is trivial as the census bureau provides tables that readily define districts and municipalities. The construction of circular units requires us to determine the radius and associate the spatial information to our households. The first empirical part analyzes trip frequency by applying an ordered logit model. In this part is studied the effect of socio-economic, transport and land use characteristics on two travel dimensions: trip frequency and type of tour. In particular the land use is defined in terms of type of neighbourhoods and types of dwellers. Three neighbourhood representations are explored, and described three for constructing neighbourhood attributes. In particular administrative units are examined to represent neighbourhood and circular – unit representation. Ordered logit models are applied, while ordinal logit models are well-known, an intensive work for constructing a spatial attributes was carried out. On the other hand, the second empirical analysis consists of the development of an innovative econometric model that considers a latent variable called “propensity to travel”, and choice model is the choice of type of tour. The first two specifications of ordinal models help to estimate this latent variable. The latent variable is unobserved but the manifestation is called “indicators”, then the probability of choosing an alternative of tour is conditional to the probability of latent variable and type of tour. Since latent variable is unknown we fit the integral over its distribution. Four “sets of best variables” are specified, following the specification obtained from the correlation analysis. The results evidence that the relative importance of SE variables versus BE variables depends on how BE variables are measured. We found that each of these three spatial scales has its intangible qualities and drawbacks. Spatial scales play an important role on predicting travel demand due to the variability in measures at trip origin/destinations within the same administrative unit (municipality, district and so on). Larger units will produce less variation in data; but it does not affect certain variables, such as public transport supply, that are more significant at municipality level. By contrast, land-use measures are more efficient at district level. Self-selection in this context, is weak. Thus, the influence of BE attributes is true. The results of the hybrid model show that unobserved factors affect the choice of tour complexity. The latent variable used in this model is propensity to travel that is explained by socioeconomic aspects and neighbourhood attributes. The results show that neighbourhood attributes have indeed a significant impact on the choice of the type of tours either directly and through the propensity to travel. The propensity to travel has a different impact depending on the structure of each tour and increases the probability of choosing more complex tours, such as tours with many intermediate stops. The integration of choice and latent variable model shows that omitting important perception and attitudes leads to inconsistent estimates. The results also indicate that goodness of fit improves by adding the latent variable in both sequential and simultaneous estimation. There are significant differences in the sensitivity to the latent variable across alternatives. In general, as expected, the hybrid models show a major improvement into the goodness of fit of the model, compared to a classical discrete choice model that does not incorporate latent effects. The integrated model leads to a more detailed analysis of the behavioural process. Summarizing, the effect that built environment characteristics on trip frequency studied is deeply analyzed. In particular we tried to better understand how land use characteristics can be defined and measured and which of these measures do have really an impact on trip frequency. We also tried to test the superiority of HCM on this field. We can concluded that HCM shows a major improvement into the goodness of fit of the model, compared to classical discrete choice model that does not incorporate latent effects. And consequently, the application of HCM shows the importance of LV on the decision of tour complexity. People are more elastic to built environment attributes than level of services. Thus, policy implications must take place to develop more mixed areas, work-places in combination with commercial retails.

Social attitude toward sustainable development in 2025: A case for reinforcing scenario design

This paper shows the role that some foresight tools, such as scenario design, may play in exploring the future impacts of global challenges in our contemporary Society. Additionally, it provides some clues about how to reinforce scenario design so that it displays more in-depth analysis without losing its qualitative nature and communication advantages. Since its inception in the early seventies, scenario design has become one of the most popular foresight tools used in several fields of knowledge. Nevertheless, its wide acceptance has not been seconded by the urban planning academic and professional realm. In some instances, scenario design is just perceived as a story telling technique that generates oversimplified future visions without the support of rigorous and sound analysis. As a matter of fact, the potential of scenario design for providing more in-depth analysis and for connecting with quantitative methods has been generally missed, giving arguments away to its critics. Based on these premises, this document tries to prove the capability of scenario design to anticipate the impacts of complex global challenges and to do it in a more analytical way. These assumptions are tested through a scenario design exercise which explores the future evolution of the sustainable development paradigm (SD) and its implications in the Spanish urban development model. In order to reinforce the perception of scenario design as a useful and added value instrument to urban planners, three sets of implications –functional, parametric and spatial— are displayed to provide substantial and in-depth information for policy makers. This study shows some major findings. First, it is feasible to set up a systematic approach that provides anticipatory intelligence about future disruptive events that may affect the natural environment and socioeconomic fabric of a given territory. Second, there are opportunities for innovating in the Spanish urban planning processes and city governance models. Third, as a foresight tool, scenario design can be substantially reinforced if proper efforts are made to display functional, parametric and spatial implications generated by the scenarios. Fourth, the study confirms that foresight offers interesting opportunities for urban planners, such as anticipating changes, formulating visions, fostering participation and building networks

The PSE-3D instability analysis methodology for flows depending strongly on two and weakly on the third spatial dimension

The present contribution discusses the development of a PSE-3D instability analysis algorithm, in which a matrix forming and storing approach is followed. Alternatively to the typically used in stability calculations spectral methods, new stable high-order finitedifference-based numerical schemes for spatial discretization 1 are employed. Attention is paid to the issue of efficiency, which is critical for the success of the overall algorithm. To this end, use is made of a parallelizable sparse matrix linear algebra package which takes advantage of the sparsity offered by the finite-difference scheme and, as expected, is shown to perform substantially more efficiently than when spectral collocation methods are used. The building blocks of the algorithm have been implemented and extensively validated, focusing on classic PSE analysis of instability on the flow-plate boundary layer, temporal and spatial BiGlobal EVP solutions (the latter necessary for the initialization of the PSE-3D), as well as standard PSE in a cylindrical coordinates using the nonparallel Batchelor vortex basic flow model, such that comparisons between PSE and PSE-3D be possible; excellent agreement is shown in all aforementioned comparisons. Finally, the linear PSE-3D instability analysis is applied to a fully three-dimensional flow composed of a counter-rotating pair of nonparallel Batchelor vortices.

Balancing groundwater conservation and rural livelihoods under water and climate uncertainties: An integrated hydro-economic modeling framework

In arid countries worldwide, social conflicts between irrigation-based human development and the conservation of aquatic ecosystems are widespread and attract many public debates. This research focuses on the analysis of water and agricultural policies aimed at conserving groundwater resources and maintaining rurallivelihoods in a basin in Spain's central arid region. Intensive groundwater mining for irrigation has caused overexploitation of the basin's large aquifer, the degradation of reputed wetlands and has given rise to notable social conflicts over the years. With the aim of tackling the multifaceted socio-ecological interactions of complex water systems, the methodology used in this study consists in a novel integration into a common platform of an economic optimization model and a hydrology model WEAP (Water Evaluation And Planning system). This robust tool is used to analyze the spatial and temporal effects of different water and agricultural policies under different climate scenarios. It permits the prediction of different climate and policy outcomes across farm types (water stress impacts and adaptation), at basin's level (aquifer recovery), and along the policies’ implementation horizon (short and long run). Results show that the region's current quota-based water policies may contribute to reduce water consumption in the farms but will not be able to recover the aquifer and will inflict income losses to the rural communities. This situation would worsen in case of drought. Economies of scale and technology are evidenced as larger farms with cropping diversification and those equipped with modern irrigation will better adapt to water stress conditions. However, the long-term sustainability of the aquifer and the maintenance of rurallivelihoods will be attained only if additional policy measures are put in place such as the control of illegal abstractions and the establishing of a water bank. Within the policy domain, the research contributes to the new sustainable development strategy of the EU by concluding that, in water-scarce regions, effective integration of water and agricultural policies is essential for achieving the water protection objectives of the EU policies. Therefore, the design and enforcement of well-balanced region-specific polices is a major task faced by policy makers for achieving successful water management that will ensure nature protection and human development at tolerable social costs. From a methodological perspective, this research initiative contributes to better address hydrological questions as well as economic and social issues in complex water and human systems. Its integrated vision provides a valuable illustration to inform water policy and management decisions within contexts of water-related conflicts worldwide.

Impacts and adaptive capacity as drivers for prioritizing agricultural adaptation to climate change in Europe

In the face of likely climate change impacts policy makers at different spatial scales need access to assessment tools that enable informed policy instruments to be designed. Recent scientific advances have facilitated the development of improved climate projections, but it remains to be seen whether these are translated into effective adaptation strategies. This paper uses existing databases on climate impacts on European agriculture and combines them with an assessment of adaptive capacity to develop an interdisciplinary approach for prioritising policies. It proposes a method for identifying relevant policies for different EU countries that are representative of various agroclimatic zones. Our analysis presents a framework for integrating current knowledge of future climate impacts with an understanding of the underlying socio-economic, agricultural and environmental traits that determine a region’s capacity for adapting to climate change.

Territory and the governmentalisation of social reproduction: parliamentary enclosure and spatial rationalities in the transition from feudalism to capitalism

Recent applications of Foucauldian categories in geography, spatial history and the history of town planning have opened up interesting new perspectives, with respect to both the evolution of spatial knowledge and the genealogy of territorial techniques and their relation to larger socio-political projects, that would be enriched if combined with other discursive traditions. This article proposes to conceptualise English parliamentary enclosureea favourite episode for Marxist historiography, frequently read in a strictly materialist fashioneas a precedent of a new form of sociospatial governmentality, a political technology that inaugurates a strategic manipulation of territory for social change on the threshold between feudal and capitalist spatial rationalities. I analyse the sociospatial dimensions of parliamentary enclosure’s technical and legal innovations and compare them to the forms of communal self-regulation of land use customs and everyday regionalisations that preceded it. Through a systematic, replicable mechanism of reterritorialisation, enclosure acts normalised spatial regulations, blurred regional differences in the social organisation of agriculture and erased the modes of autonomous social reproduction linked to common land. Their exercise of dispossession of material resources, social capital and community representations is interpreted therefore as an inaugural logic that would pervade the emergent spatial rationality later known as planning.

Estrategias innovadoras para la gestión del riesgo de sequía en sistemas ganaderos extensivos

La vulnerabilidad de los sistemas ganaderos de pastoreo pone en evidencia la necesidad de herramientas para evaluar y mitigar los efectos de la sequía. El avance en la teledetección ha despertado el interés por explotar potenciales aplicaciones, y está dando lugar a un intenso desarrollo de innovaciones en distintos campos. Una de estas áreas es la gestión del riesgo climático, en donde la utilización de índices de vegetación permite la evaluación de la sequía. En esta investigación, se analiza el impacto de la sequía y se evalúa el potencial de nuevas tecnologías como la teledetección para la gestión del riesgo de sequía en sistemas de ganadería extensiva. Para ello, se desarrollan tres aplicaciones: (i) evaluar el impacto económico de la sequía en una explotación ganadera extensiva de la dehesa de Andalucía, (ii) elaborar mapas de vulnerabilidad a la sequía en pastos de Chile y (iii) diseñar y evaluar el potencial de un seguro indexado para sequía en pastos en la región de Coquimbo en Chile. En la primera aplicación, se diseña un modelo dinámico y estocástico que integra aspectos climáticos, ecológicos, agronómicos y socioeconómicos para evaluar el riesgo de sequía. El modelo simula una explotación ganadera tipo de la dehesa de Andalucía para el período 1999-2010. El método de Análisis Histórico y la simulación de MonteCarlo se utilizan para identificar los principales factores de riesgo de la explotación, entre los que destacan, los periodos de inicios del verano e inicios de invierno. Los resultados muestran la existencia de un desfase temporal entre el riesgo climático y riesgo económico, teniendo este último un periodo de duración más extenso en el tiempo. También, revelan que la intensidad, frecuencia y duración son tres atributos cruciales que determinan el impacto económico de la sequía. La estrategia de reducción de la carga ganadera permite aminorar el riesgo, pero conlleva una disminución en el margen bruto de la explotación. La segunda aplicación está dedicada a la elaboración de mapas de vulnerabilidad a la sequia en pastos de Chile. Para ello, se propone y desarrolla un índice de riesgo económico (IRESP) sencillo de interpretar y replicable, que integra factores de riesgo y estrategias de adaptación para obtener una medida del Valor en Riesgo, es decir, la máxima pérdida esperada en un año con un nivel de significación del 5%.La representación espacial del IRESP pone en evidencia patrones espaciales y diferencias significativas en la vulnerabilidad a la sequía a lo largo de Chile. Además, refleja que la vulnerabilidad no siempre esta correlacionada con el riesgo climático y demuestra la importancia de considerar las estrategias de adaptación. Las medidas de autocorrelación espacial revelan que el riesgo sistémico es considerablemente mayor en el sur que en el resto de zonas. Los resultados demuestran que el IRESP transmite información pertinente y, que los mapas de vulnerabilidad pueden ser una herramienta útil en el diseño de políticas y toma de decisiones para la gestión del riesgo de sequía. La tercera aplicación evalúa el potencial de un seguro indexado para sequía en pastos en la región de Coquimbo en Chile. Para lo cual, se desarrolla un modelo estocástico para estimar la prima actuarialmente justa del seguro y se proponen y evalúan pautas alternativas para mejorar el diseño del contrato. Se aborda el riesgo base, el principal problema de los seguros indexados identificado en la literatura y, que está referido a la correlación imperfecta del índice con las pérdidas de la explotación. Para ello, se sigue un enfoque bayesiano que permite evaluar el impacto en el riesgo base de las pautas de diseño propuestas: i) una zonificación por clúster que considera aspectos espacio-temporales, ii) un período de garantía acotado a los ciclos fenológicos del pasto y iii) umbral de garantía. Los resultados muestran que tanto la zonificación como el periodo de garantía reducen el riesgo base considerablemente. Sin embargo, el umbral de garantía tiene un efecto ambiguo sobre el riesgo base. Por otra parte, la zonificación por clúster contribuye a aminorar el riesgo sistémico que enfrentan las aseguradoras. Estos resultados han puesto de manifiesto que un buen diseño de contrato puede tener un doble dividendo, por un lado aumentar su utilidad y, por otro, reducir el coste del seguro. Un diseño de contrato eficiente junto con los avances en la teledetección y un adecuado marco institucional son los pilares básicos para el buen funcionamiento de un programa de seguro. Las nuevas tecnologías ofrecen un importante potencial para la innovación en la gestión del riesgo climático. Los avances en este campo pueden proporcionar importantes beneficios sociales en los países en desarrollo y regiones vulnerables, donde las herramientas para gestionar eficazmente los riesgos sistémicos como la sequía pueden ser de gran ayuda para el desarrollo. The vulnerability of grazing livestock systems highlights the need for tools to assess and mitigate the adverse impact of drought. The recent and rapid progress in remote sensing has awakened an interest for tapping into potential applications, triggering intensive efforts to develop innovations in a number of spheres. One of these areas is climate risk management, where the use of vegetation indices facilitates assessment of drought. This research analyzes drought impacts and evaluates the potential of new technologies such as remote sensing to manage drought risk in extensive livestock systems. Three essays in drought risk management are developed to: (i) assess the economic impact of drought on a livestock farm in the Andalusian Dehesa, (ii) build drought vulnerability maps in Chilean grazing lands, and (iii) design and evaluate the potential of an index insurance policy to address the risk of drought in grazing lands in Coquimbo, Chile. In the first essay, a dynamic and stochastic farm model is designed combining climate, agronomic, socio-economic and ecological aspects to assess drought risk. The model is developed to simulate a representative livestock farm in the Dehesa of Andalusia for the time period 1999-2010. Burn analysis and MonteCarlo simulation methods are used to identify the significance of various risk sources at the farm. Most notably, early summer and early winter are identified as periods of peak risk. Moreover, there is a significant time lag between climate and economic risk and this later last longer than the former. It is shown that intensity, frequency and duration of the drought are three crucial attributes that shape the economic impact of drought. Sensitivity analysis is conducted to assess the sustainability of farm management strategies and demonstrates that lowering the stocking rate reduces farmer exposure to drought risk but entails a reduction in the expected gross margin. The second essay, mapping drought vulnerability in Chilean grazing lands, proposes and builds an index of economic risk (IRESP) that is replicable and simple to interpret. This methodology integrates risk factors and adaptation strategies to deliver information on Value at Risk, maximum expected losses at 5% significance level. Mapping IRESP provides evidence about spatial patterns and significant differences in drought vulnerability across Chilean grazing lands. Spatial autocorrelation measures reveal that systemic risk is considerably larger in the South as compared to Northern or Central Regions. Furthermore, it is shown that vulnerability is not necessarily correlated with climate risk and that adaptation strategies do matter. These results show that IRESP conveys relevant information and that vulnerability maps may be useful tools to assess policy design and decision-making in drought risk management. The third essay develops a stochastic model to estimate the actuarially fair premium and evaluates the potential of an indexed insurance policy to manage drought risk in Coquimbo, a relevant livestock farming region of Chile. Basis risk refers to the imperfect correlation of the index and farmer loses and is identified in the literature as a main limitation of index insurance. A Bayesian approach is proposed to assess the impact on basis risk of alternative guidelines in contract design: i) A cluster zoning that considers space-time aspects, ii) A guarantee period bounded to fit phenological cycles, and iii) the triggering index threshold. Results show that both the proposed zoning and guarantee period considerably reduces basis risk. However, the triggering index threshold has an ambiguous effect on basis risk. On the other hand, cluster zoning contributes to ameliorate systemic risk faced by the insurer. These results highlighted that adequate contract design is important and may result in double dividend. On the one hand, increasing farmers’ utility and, secondly, reducing the cost of insurance. An efficient contract design coupled with advances in remote sensing and an appropriate institutional framework are the basis for an efficient operation of an insurance program. The new technologies offer significant potential for innovation in climate risk managements. Progress in this field is capturing increasing attention and may provide important social gains in developing countries and vulnerable regions where the tools to efficiently manage systemic risks, such as drought, may be a means to foster development.

Methodology for reconstructing early zebrafish development from in vivo multiphoton microscopy

Investigating cell dynamics during early zebrafish embryogenesis requires specific image acquisition and analysis strategies. Multiharmonic microscopy, i.e., second- and third-harmonic generations, allows imaging cell divisions and cell membranes in unstained zebrafish embryos from 1- to 1000-cell stage. This paper presents the design and implementation of a dedicated image processing pipeline (tracking and segmentation) for the reconstruction of cell dynamics during these developmental stages. This methodology allows the reconstruction of the cell lineage tree including division timings, spatial coordinates, and cell shape until the 1000-cell stage with minute temporal accuracy and micrometer spatial resolution. Data analysis of the digital embryos provides an extensive quantitative description of early zebrafish embryogenesis.

Spatial effects on rural commerce

Commerce in rural territories should not be considered as a needed service, but as a basic infrastructure, that impact not only existent population, but also tourism, and rural industrialization. So, the rural areas need not only agriculture but industry and services, to have a global and balanced development, including for the countryside and the population. In the work presented in this paper, we are considering the formulation of the direct relation between population and the endowment of commerce sites within a geographical territory, the ?area of commercial interactions?. These are the closer set of towns that can gravitate to each other to cover the required needs for the populations within the area. The products retailed, range from basic products for the daily lives, to all other products for industry, agriculture, and services. The econometric spatial model developed to evaluate the interactions and estimate the parameters, is based on the Spatial Error Model, which allows for other spatial hidden effects to be considered without direct interference to the commercial disposition. The data and territory used to test the model correspond to a rural area in the Spanish Palencia territory (NUTS-3 level). The parameters have dependence from population levels, local rent per head, local and regional government budgets, and particular spatial restrictions. Interesting results are emerging form the model. The more significant is that the spatial effects can replace some number of commerce sites in towns, given the right spatial distribution of the sites and the towns. This is equivalent to consider the area of commercial interactions as the unit of measurement for the basic infrastructure and not only the towns.

Emission inventories and modeling requirements for the development of air quality plans. Application to Madrid (Spain)

Modeling is an essential tool for the development of atmospheric emission abatement measures and air quality plans. Most often these plans are related to urban environments with high emission density and population exposure. However, air quality modeling in urban areas is a rather challenging task. As environmental standards become more stringent (e.g. European Directive 2008/50/EC), more reliable and sophisticated modeling tools are needed to simulate measures and plans that may effectively tackle air quality exceedances, common in large urban areas across Europe, particularly for NO2. This also implies that emission inventories must satisfy a number of conditions such as consistency across the spatial scales involved in the analysis, consistency with the emission inventories used for regulatory purposes and versatility to match the requirements of different air quality and emission projection models. This study reports the modeling activities carried out in Madrid (Spain) highlighting the atmospheric emission inventory development and preparation as an illustrative example of the combination of models and data needed to develop a consistent air quality plan at urban level. These included a series of source apportionment studies to define contributions from the international, national, regional and local sources in order to understand to what extent local authorities can enforce meaningful abatement measures. Moreover, source apportionment studies were conducted in order to define contributions from different sectors and to understand the maximum feasible air quality improvement that can be achieved by reducing emissions from those sectors, thus targeting emission reduction policies to the most relevant activities. Finally, an emission scenario reflecting the effect of such policies was developed and the associated air quality was modeled.

Urbanization, socio-economic changes and population growth in Brazil: dietary shifts and environmental implications.

Population growth, economic globalization, improving living standards and urbanization are causing important changes in the global food system and modifying the dietary habits in many parts of the world (Molden, 2007; Godfray et al., 2010). The nutritional transition (linked to the development of countries and the increasing wealth of its population) implies a shift away from traditional staple food such as roots and tuber vegetables and a rise in consumption of meat and milk products, refined and processed foods, as well as sugars, oils and fats (Ambler-Edwards et al., 2009). The contemporary food system puts significant pressure on natural resources, especially on land and water, because the growing food demand pushes the agricultural frontier beyond, causing large impacts on ecosystems (Ambler-Edwards et al. 2009: 11-18). Also, the trend towards richer diets in animal proteins and processed food adds further pressure on the environment, since it requires larger amount of water and land to be produced (Allan, 2011; Mekonnen and Hoekstra, 2012).

Supporting decision making under uncertainty: Development of a participatory integrated model for water management in the middle Guadiana river basin.

Following the Integrated Water Resources Management approach, the European Water Framework Directive demands Member States to develop water management plans at the catchment level. Those plans have to integrate the different interests and must be developed with stakeholder participation. To face these requirements, managers need tools to assess the impacts of possible management alternatives on natural and socio-economic systems. These tools should ideally be able to address the complexity and uncertainties of the water system, while serving as a platform for stakeholder participation. The objective of our research was to develop a participatory integrated assessment model, based on the combination of a crop model, an economic model and a participatory Bayesian network, with an application in the middle Guadiana sub-basin, in Spain. The methodology is intended to capture the complexity of water management problems, incorporating the relevant sectors, as well as the relevant scales involved in water management decision making. The integrated model has allowed us testing different management, market and climate change scenarios and assessing the impacts of such scenarios on the natural system (crops), on the socio-economic system (farms) and on the environment (water resources). Finally, this integrated assessment modelling process has allowed stakeholder participation, complying with the main requirements of current European water laws.