Improving runoff estimates from regional climate models: a performance analysis in Spain

An important step to assess water availability is to have monthly time series representative of the current situation. In this context, a simple methodology is presented for application in large-scale studies in regions where a properly calibrated hydrologic model is not available, using the output variables simulated by regional climate models (RCMs) of the European project PRUDENCE under current climate conditions (period 1961–1990). The methodology compares different interpolation methods and alternatives to generate annual times series that minimise the bias with respect to observed values. The objective is to identify the best alternative to obtain bias-corrected, monthly runoff time series from the output of RCM simulations. This study uses information from 338 basins in Spain that cover the entire mainland territory and whose observed values of natural runoff have been estimated by the distributed hydrological model SIMPA. Four interpolation methods for downscaling runoff to the basin scale from 10 RCMs are compared with emphasis on the ability of each method to reproduce the observed behaviour of this variable. The alternatives consider the use of the direct runoff of the RCMs and the mean annual runoff calculated using five functional forms of the aridity index, defined as the ratio between potential evapotranspiration and precipitation. In addition, the comparison with respect to the global runoff reference of the UNH/GRDC dataset is evaluated, as a contrast of the “best estimator” of current runoff on a large scale. Results show that the bias is minimised using the direct original interpolation method and the best alternative for bias correction of the monthly direct runoff time series of RCMs is the UNH/GRDC dataset, although the formula proposed by Schreiber (1904) also gives good results

Impacts of projected maximum temperature extremes for C21 by an ensemble of regional climate models on cereal cropping systems in the Iberian Peninsula

Crops growing in the Iberian Peninsula may be subjected to damagingly high temperatures during the sensitive development periods of flowering and grain filling. Such episodes are considered important hazards and farmers may take insurance to offset their impact. Increases in value and frequency of maximum temperature have been observed in the Iberian Peninsula during the 20th century, and studies on climate change indicate the possibility of further increase by the end of the 21st century. Here, impacts of current and future high temperatures on cereal cropping systems of the Iberian Peninsula are evaluated, focusing on vulnerable development periods of winter and summer crops. Climate change scenarios obtained from an ensemble of ten Regional Climate Models (multimodel ensemble) combined with crop simulation models were used for this purpose and related uncertainty was estimated. Results reveal that higher extremes of maximum temperature represent a threat to summer-grown but not to winter-grown crops in the Iberian Peninsula. The study highlights the different vulnerability of crops in the two growing seasons and the need to account for changes in extreme temperatures in developing adaptations in cereal cropping systems. Finally, this work contributes to clarifying the causes of high-uncertainty impact projections from previous studies.

Comparison of methods for downscaling runoff from regional climate models in Spanish basins

At present there is much literature that refers to the advantages and disadvantages of different methods of statistical and dynamical downscaling of climate variables projected by climate models. Less attention has been paid to other indirect variables, like runoff, which play a significant role in evaluating the impact of climate change on hydrological systems. Runoff presents a much greater bias in climate models than other climate variables, like temperature or precipitation. It is very important to identify the methods that minimize bias while downscaling runoff from the gridded results of climate models to the basin scale

Influence of climate change on the flowering of temperate fruit trees

It is well known that winter chilling is necessary for the flowering of temperate trees. The chilling requirement is a criterion for choosing a species or variety at a given location. Also chemistry products can be used for reducing the chilling-hours needs but make our production more expensive. This study first analysed the observed values of chilling hours for some representative agricultural locations in Spain for the last three decades and their projected changes under climate change scenarios. Usually the chilling is measured and calculated as chilling-hours, and different methods have been used to calculate them (e.g. Richarson et al., 1974 among others) according to the species considered. For our objective North Carolina method (Shaltout and Unrath, 1983) was applied for apples, Utah method (Richardson et al. 1974) for peach and grapevine and the approach used by De Melo-Abreu et al. (2004) for olive trees. The influence of climate change in temperate trees was studied by calculating projections of chilling-hours with climate data from Regional Climate Models (RCMs) at high resolution (25 km) from the European Project ENSEMBLES (http://www.ensembles-eu.org/). These projections will allow for analysing the modelled variations of chill-hours between 2nd half of 20C and 1st half of 21C at the study locations.

Evolution of extreme temperature events in short term climate projection for Iberian Peninsula

Extreme events of maximum and minimum temperatures are a main hazard for agricultural production in Iberian Peninsula. For this purpose, in this study we analyze projections of their evolution that could be valid for the next decade, represented in this study by the 30-year period 2004-2034 (target period). For this purpose two kinds of data were used in this study: 1) observations from the station network of AEMET (Spanish National Meteorological Agency) for five Spanish locations, and 2) simulated data at a resolution of 50 50 km horizontal grid derived from the outputs of twelve Regional Climate Models (RCMs) taken from project ENSEMBLES (van der Linden and Mitchell, 2009), with a bias correction (Dosio and Paruolo, 2011; Dosio et al., 2012) regarding the observational dataset Spain02 (Herrera et al., 2012). To validate the simulated climate, the available period of observations was compared to a baseline period (1964-1994) of simulated climate for all locations. Then, to analyze the changes for the present/very next future, probability of extreme temperature events for 2004-2034 were compared to that of the baseline period. Although only minor changes are expected, small variations in variability may have a significant impact in crop performance.

Strategies for adapting maize to climate change and extreme temperatures in Andalusia, Spain

Climate projections indicate that rising temperatures will affect summer crops in the southern Iberian Peninsula. The aim of this study was to obtain projections of the impacts of rising temperatures, and of higher frequency of extreme events on irrigated maize, and to evaluate some adaptation strategies. The study was conducted at several locations in Andalusia using the CERES-Maize crop model, previously calibrated/validated with local experimental datasets. The simulated climate consisted of projections from regional climate models from the ENSEMBLES project; these were corrected for daily temperature and precipitation with regard to the E-OBS observational dataset. These bias-corrected projections were used with the CERES-Maize model to generate future impacts. Crop model results showed a decrease in maize yield by the end of the 21st century from 6 to 20%, a decrease of up to 25% in irrigation water requirements, and an increase in irrigation water productivity of up to 22%, due to earlier maturity dates and stomatal closure caused by CO2 increase. When adaptation strategies combining earlier sowing dates and cultivar changes were considered, impacts were compensated, and maize yield increased up to 14%, compared with the baseline period (1981-2010), with similar reductions in crop irrigation water requirements. Effects of extreme maximum temperatures rose to 40% at the end of the 21st century, compared with the baseline. Adaptation resulted in an overall reduction in extreme Tmax damages in all locations, with the exception of Granada, where losses were limited to 8%.

Propuesta metodológica para la identificación de medidas de adaptación al cambio climático en sistemas de recursos hídricos

Esta tesis realiza una contribución metodológica en el estudio de medidas de adaptación potencialmente adecuadas a largo plazo, donde los sistemas de recursos hídricos experimentan fuertes presiones debido a los efectos del cambio climático. Esta metodología integra el análisis físico del sistema, basándose en el uso de indicadores que valoran el comportamiento de éste, y el análisis económico mediante el uso del valor del agua. El procedimiento metodológico inicia con la construcción de un conjunto de escenarios futuros, que capturan por un lado las características de variabilidad de las aportaciones de diversos modelos climáticos y, por otro, las características hidrológicas de la zona de estudio. Las zonas de estudio seleccionadas fueron las cuencas del Guadalquivir, Duero y Ebro y se utilizaron como datos observados las series de escorrentía en régimen natural estimadas por el modelo SIMPA que está calibrado en la totalidad del territorio español. Estas series observadas corresponden al periodo 1961-1990. Los escenarios futuros construidos representan el periodo 2071-2100. La identificación de medidas de adaptación se apoyó en el uso de indicadores que sean capaces de caracterizar el comportamiento de un sistema de recursos hídricos frente a los efectos del cambio climático. Para ello se seleccionaron los indicadores de calidad de servicio (I1) y de confiabilidad de la demanda (I2) propuestos por Martin-Carrasco et al. (2012). Estos indicadores valoran el comportamiento de un sistema mediante la identificación de los problemas de escasez de agua que presente, y requieren para su cuantificación el uso de un modelo de optimización. Para este estudio se ha trabajado con el modelo de optimización OPTIGES. La determinación de estos indicadores fue realizada para análisis a corto plazo donde los efectos del cambio climático no son de relevancia, por lo que fue necesario analizar su capacidad para ser usados en sistemas afectados por dichos efectos. Para este análisis se seleccionaron tres cuencas españolas: Guadalquivir, Duero y Ebro, determinándose que I2 no es adecuado para este tipo de escenarios. Por ello se propuso un nuevo indicador “Indicador de calidad de servicio bajo cambio climático” (I2p) que mantiene los mismos criterios de valoración que I2 pero que responde mejor bajo fuertes reducciones de aportaciones producto del cambio climático. La metodología propuesta para la identificación de medidas de adaptación se basa en un proceso iterativo en el cual se van afectando diversos elementos que conforman el esquema del sistema bajo acciones de gestión previamente identificadas, hasta llegar a un comportamiento óptimo dado por el gestor. Las mejoras de estas afectaciones son cuantificadas mediante los indicadores I1 e I2p, y de este conjunto de valores se selecciona la que se acerca más al comportamiento óptimo. Debido a la extensa cantidad de información manejada en este análisis, se desarrolló una herramienta de cálculo automatizada en Matlab. El proceso seguido por esta herramienta es: (i) Ejecución del modelo OPTIGES para las diferentes modificaciones por acciones de gestión; (ii) Cálculo de los valores de I1 e I2p para cada una de estas afectaciones; y (iii) Selección de la mejor opción. Este proceso se repite hasta llegar al comportamiento óptimo buscado, permitiendo la identificación de las medidas de adaptación mas adecuadas. La aplicación de la metodología para la identificación de medidas de adaptación se realizó en la cuenca del Guadalquivir, por ser de las tres cuencas analizadas bajo los indicadores I1 e I2p la que presenta los problemas más serios de escasez de agua. Para la identificación de medidas de adaptación se analizaron dos acciones de gestión: 1) incremento de los volúmenes de regulación y 2) reducción de las demandas de riego, primero bajo la valoración del comportamiento físico del sistema (análisis de sensibilidad) permitiendo identificar que la primera acción de gestión no genera cambios importantes en el comportamiento del sistema, que si se presentan bajo la segunda acción. Posteriormente, con la acción que genera cambios importantes en el comportamiento del sistema (segunda acción) se identificaron las medidas de adaptación más adecuadas, mediante el análisis físico y económico del sistema. Se concluyó que en la cuenca del Guadalquivir, la acción de reducción de las demandas de riego permite minimizar e incluso eliminar los problemas de escasez de agua que se presentarían a futuro bajo diferentes proyecciones hidrológicas, aunque estas mejoras implicarían fuertes reducciones en dichas demandas. Siendo las demandas más afectadas aquellas ubicadas en cabecera de cuenca. Los criterios para la reducción de las demandas se encuentran en función de las productividades y garantías con las que son atendidas dichas demandas. This thesis makes a methodological contribution to the study of potentially suitable adaptation measures in the long term, where water resource systems undergo strong pressure due to the effects of climate change. This methodology integrates the physical analysis of the system, by the use of indicators which assess its behavior, and the economic analysis by the use of the value of water. The methodological procedure begins with the building of a set of future scenarios that capture, by one hand, the characteristics and variability of the streamflow of various climate models and, on the other hand, the hydrological characteristics of the study area. The study areas chosen were the Guadalquivir, Ebro and Duero basins, and as observed data where used runoff series in natural regimen estimated by the SIMPA model, which is calibrated in the whole Spanish territory. The observed series are for the 1961-1990 period. The future scenarios built represent the 2071-2100 periods. The identification of adaptation measures relied on the use of indicators that were able of characterize the behavior of one water resource system facing the effects of climate change. Because of that, the Demand Satisfaction Index (I1) and the Demand Reliability Index (I2) proposed by Martin-Carrasco et al. (2012) were selected. These indicators assess the behavior of a system by identifying the water scarcity problems that it presents, and require in order to be quantified the use of one optimization model. For this study the OPTIGES optimization model has been used. The determination of the indicators was made for the short-term analysis where the climates change effect are not relevant, so it was necessary to analyze their capability to be used in systems affected by those these. For this analysis three Spanish basins were selected: Guadalquivir, Duero and Ebro. It was determined that the indicator I2 is not suitable for this type of scenario. It was proposed a new indicator called “Demand Reliability Index under climate change” (I2p), which keeps the same assessment criteria than I2, but responsive under heavy reductions of streamflow due to climate change. The proposed methodology for identifying adaptation measures is based on an iterative process, in which the different elements of the system´s schema are affected by previously defined management actions, until reach an optimal behavior given by the manager. The improvements of affectations are measured by indicators I1 e I2p, and from this set of values it is selected the affectation that is closer to the optimal behavior. Due to the large amount of information managed in this analysis, it was developed an automatic calculation tool in Matlab. The process followed by this tool is: Firstly, it executes the OPTIGES model for the different modifications by management actions; secondly, it calculates the values of I1 e I2p for each of these affectations; and finally it chooses the best option. This process is performed for the different iterations that are required until reach the optimal behavior, allowing to identify the most appropriate adaptation measured. The application of the methodology for the identification of adaptation measures was conducted in the Guadalquivir basin, due to this was from the three basins analyzed under the indicators I1 e I2p, which presents the most serious problems of water scarcity. For the identification of adaptation measures there were analyzed two management actions: 1) To increase the regulation volumes, and 2) to reduce the irrigation demands, first under the assessment of the physical behavior of the system (sensibility analysis), allowing to identify that the first management action does not generate significant changes in the system´s behavior, which there are present under the second management action. Afterwards, with the management action that generates significant changes in the system´s behavior (second management action), there were identified the most adequate adaptation measures, through the physical and economic analysis of the system. It was concluded that in the Guadalquivir basin, the action of reduction of irrigation demands allows to minimize or even eliminate the water scarcity problems that could exist in the future under different hydrologic projections, although this improvements should involve strong reductions of the irrigation demands. Being the most affected demands those located in basins head. The criteria for reducing the demands are based on the productivities and reliabilities with which such demands are meet.

Viticultura y Cambio Climático en España: Vulnerabilidad en las distintas regiones y estrategias de adaptación frente al desarrollo de nuevas políticas

El presente trabajo realiza un análisis de la vulnerabilidad de la viticultura en España ante el Cambio Climático que contribuya a la mejora de la capacidad de respuesta del sector vitivinícola a la hora de afrontar los retos de la globalización. Para ello se analiza el impacto que puede tener el Cambio Climático en primer lugar sobre determinados riesgos ocasionados por eventos climáticos adversos relacionados con extremos climáticos y en segundo lugar, sobre los principales índices agro-climáticos definidos en el Sistema de Clasificación Climática Multicriterio Geoviticultura (MCGG), que permiten clasificar las zonas desde un punto de vista de su potencial climático. Para el estudio de las condiciones climáticas se han utilizado los escenarios de Cambio Climático regionalizados del proyecto ESCENA, desarrollados dentro del Plan Nacional de Adaptación al Cambio Climático (PNACC) con el fin de promover iniciativas de anticipación y respuesta al Cambio Climático hasta el año 2050. Como parte clave del estudio de la vulnerabilidad, en segundo lugar se miden las necesidades de adaptación para 56 Denominaciones de Origen Protegidas, definidas por los impactos y de acuerdo con un análisis de sensibilidad desarrollado en este trabajo. De este análisis se desprende que los esfuerzos de adaptación se deberían centrar en el mantenimiento de la calidad sobre todo para mejorar las condiciones en la época de maduración en los viñedos de la mitad norte, mientras que en las zonas de la mitad sur y del arco mediterráneo, además deberían buscar mantener la productividad en la viticultura. Los esfuerzos deberían ser más intensos en esta zona sur y también estarían sujetos a más limitaciones, ya que por ejemplo el riego, que podría llegar a ser casi obligatorio para mantener el cultivo, se enfrentaría a un contexto de mayor competencia y escasez de recursos hídricos. La capacidad de afrontar estas necesidades de adaptación determinará la vulnerabilidad del viñedo en cada zona en el futuro. Esta capacidad está definida por las propias necesidades y una serie de condicionantes sociales y de limitaciones legales, como las impuestas por las propias Denominaciones de Origen, o medioambientales, como la limitación del uso de agua. El desarrollo de estrategias que aseguren una utilización sostenible de los recursos hídricos, así como el apoyo de las Administraciones dentro de la nueva Política Agraria Común (PAC) pueden mejorar esta capacidad de adaptación y con ello disminuir la vulnerabilidad. ABSTRACT This paper analyzes the vulnerability of viticulture in Spain on Climate Change in order to improve the adaptive capacity of the wine sector to meet the diverse challenges of globalization. The risks to quality and quantity are explored by considering bioclimatic indices with specific emphasis on the Protected Designation of Origin areas that produce the premium winegrapes. The Indices selected represents risks caused by adverse climatic events related to climate extremes, and requirements of varieties and vintage quality in the case of those used in the Multicriteria Climatic Classification System. (MCCS). To study the climatic conditions, an ensemble of Regional Climate Models (RCMs) of ESCENA project, developed in the framework of the Spanish Plan for Regional Climate Change Scenarios (PNACC-2012) have been used As a key part of the study of vulnerability risks and opportunities are linked to adaptation needs across the Spanish territory. Adaptation efforts are calculated as proportional to the magnitude of change and according to a sensitivity analysis for 56 protected designations of origin. This analysis shows that adaptation efforts should focus on improving conditions in the ripening period to maintain quality in the vineyards of the northern half of Iberian Peninsula, while in areas of the southern half and in the Mediterranean basin, also should seek to maintain productivity of viticulture. Therefore, efforts should be more intense in the Southern and Eastern part, and may also be subject to other limitations, such as irrigation, which could become almost mandatory to keep growing, would face a context of increased competition and lack of resources water. The ability to meet these needs will determine the vulnerability of the vineyard in each region in the future. This capability is defined also by a number of social factors and legal limitations such as environmental regulations, limited water resources or those imposed by their own Designation of Origin. The development of strategies to ensure sustainable use of water resources and the support schemes in the new Common Agricultural Policy (CAP) can improve the resilience and thus reduce vulnerability.

Desarrollo de un método estadístico para la generación de escenarios climáticos de alta resolución a partir de simulaciones de baja resolución de Modelos de Circulación General: aplicación a España

Esta tesis doctoral presenta el desarrollo, verificación y aplicación de un método original de regionalización estadística para generar escenarios locales de clima futuro de temperatura y precipitación diarias, que combina dos pasos. El primer paso es un método de análogos: los "n" días cuya configuración atmosférica de baja resolución es más parecida a la del día problema, se seleccionan de un banco de datos de referencia del pasado. En el segundo paso, se realiza un análisis de regresión múltiple sobre los "n" días más análogos para la temperatura, mientras que para la precipitación se utiliza la distribución de probabilidad de esos "n" días análogos para obtener la estima de precipitación. La verificación de este método se ha llevado a cabo para la España peninsular y las Islas Baleares. Los resultados muestran unas buenas prestaciones para temperatura (BIAS cerca de 0.1ºC y media de errores absolutos alrededor de 1.9ºC); y unas prestaciones aceptables para la precipitación (BIAS razonablemente bajo con una media de -18%; error medio absoluto menor que para una simulación de referencia (la persistencia); y una distribución de probabilidad simulada similar a la observada según dos test no-paramétricos de similitud). Para mostrar la aplicabilidad de la metodología desarrollada, se ha aplicado en detalle en un caso de estudio. El método se aplicó a cuatro modelos climáticos bajo diferentes escenarios futuros de emisiones de gases de efecto invernadero, para la región de Aragón, produciendo así proyecciones futuras de precipitación y temperaturas máximas y mínimas diarias. La fiabilidad de la técnica de regionalización fue evaluada de nuevo para el caso de estudio mediante un proceso de verificación. Para determinar la capacidad de los modelos climáticos para simular el clima real, sus simulaciones del pasado (la denominada salida 20C3M) se regionalizaron y luego se compararon con el clima observado (los resultados son bastante robustos para la temperatura y menos concluyentes para la precipitación). Las proyecciones futuras a escala local presentan un aumento significativo durante todo el siglo XXI de las temperaturas máximas y mínimas para todos los futuros escenarios de emisiones considerados. Las simulaciones de precipitación presentan mayores incertidumbres. Además, la aplicabilidad práctica del método se demostró también mediante su utilización para producir escenarios climáticos futuros para otros casos de estudio en los distintos sectores y regiones del mundo. Se ha prestado especial atención a una aplicación en Centroamérica, una región que ya está sufriendo importantes impactos del cambio climático y que tiene un clima muy diferente. ABSTRACT This doctoral thesis presents the development, verification and application of an original downscaling method for daily temperature and precipitation, which combines two statistical approaches. The first step is an analogue approach: the “n” days most similar to the day to be downscaled are selected. In the second step, a multiple regression analysis using the “n” most analogous days is performed for temperature, whereas for precipitation the probability distribution of the “n” analogous days is used to obtain the amount of precipitation. Verification of this method has been carried out for the Spanish Iberian Peninsula and the Balearic Islands. Results show good performance for temperature (BIAS close to 0.1ºC and Mean Absolute Errors around 1.9ºC); and an acceptable skill for precipitation (reasonably low BIAS with a mean of - 18%, Mean Absolute Error lower than for a reference simulation, i.e. persistence, and a well-simulated probability distribution according to two non-parametric tests of similarity). To show the applicability of the method, a study case has been analyzed. The method was applied to four climate models under different future emission scenarios for the region of Aragón, thus producing future projections of daily precipitation and maximum and minimum temperatures. The reliability of the downscaling technique was re-assessed for the study case by a verification process. To determine the ability of the climate models to simulate the real climate, their simulations of the past (the 20C3M output) were downscaled and then compared with the observed climate – the results are quite robust for temperature and less conclusive for the precipitation. The downscaled future projections exhibit a significant increase during the entire 21st century of the maximum and minimum temperatures for all the considered future emission scenarios. Precipitation simulations exhibit greater uncertainties. Furthermore, the practical applicability of the method was demonstrated also by using it to produce future climate scenarios for some other study cases in different sectors and regions of the world. Special attention was paid to an application of the method in Central America, a region that is already suffering from significant climate change impacts and that has a very different climate from others where the method was previously applied.

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.

How do various maize crop models vary in their responses to climate change factors?

Comments This article is a U.S. government work, and is not subject to copyright in the United States. Abstract Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly 0.5 Mg ha 1 per °C. Doubling [CO2] from 360 to 720 lmol mol 1 increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2] among models. Model responses to temperature and [CO2] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information.

Using ecological niche models to support tree species selection for forest restoration planning in largely deforested regions

Species selection for forest restoration is often supported by expert knowledge on local distribution patterns of native tree species. This approach is not applicable to largely deforested regions unless enough data on pre-human tree species distribution is available. In such regions, ecological niche models may provide essential information to support species selection in the framework of forest restoration planning. In this study we used ecological niche models to predict habitat suitability for native tree species in "Tierra de Campos" region, an almost totally deforested area of the Duero Basin (Spain). Previously available models provide habitat suitability predictions for dominant native tree species, but including non-dominant tree species in the forest restoration planning may be desirable to promote biodiversity, specially in largely deforested areas were near seed sources are not expected. We used the Forest Map of Spain as species occurrence data source to maximize the number of modeled tree species. Penalized logistic regression was used to train models using climate and lithological predictors. Using model predictions a set of tools were developed to support species selection in forest restoration planning. Model predictions were used to build ordered lists of suitable species for each cell of the study area. The suitable species lists were summarized drawing maps that showed the two most suitable species for each cell. Additionally, potential distribution maps of the suitable species for the study area were drawn. For a scenario with two dominant species, the models predicted a mixed forest (Quercus ilex and a coniferous tree species) for almost one half of the study area. According to the models, 22 non-dominant native tree species are suitable for the study area, with up to six suitable species per cell. The model predictions pointed to Crataegus monogyna, Juniperus communis, J.oxycedrus and J.phoenicea as the most suitable non-dominant native tree species in the study area. Our results encourage further use of ecological niche models for forest restoration planning in largely deforested regions.

Lesson from the habitat suitability models to evaluate the environmental of Pinus nigra Arnold and Pinus sylvesris L. in the Iberian Peninsula

PREDICT POTENTIAL DISTRIBUTION. Spatial and temporal evolution of the species under different climate scenarios. Generation of habitat suitability models (HSM)  high degree of uncertainty and limitations. The importance of their validation has been stressed. In this work we discuss the present potential distribution of P. sylvestris and P. nigra in the Iberian Peninsula by using MaxEnt, and evaluate the influence of the different environmental variables. Our intention is to select a set of environmental variables that explains better their current distribution, to achieve the most accurate and reliable models. Then we project them to the past climatic conditions (21 to 0 kyrs BP), to evaluate the outputs with existing palaeo-ecological data.

Refining predictions of iberian plant distribution: lessons from p. nigra and p. sylvestris palaeoecological-based habitat suitability models

In recent years, challenged by the climate scenarios put forward by the IPCC and its potential impact on plant distribution, numerous predictive techniques -including the so called habitat suitability models (HSM)- have been developed. Yet, as the output of the different methods produces different distribution areas, developing validation tools are strong needs to reduce uncertainties. Focused in the Iberian Peninsula, we propose a palaeo-based method to increase the robustness of the HSM, by developing an ecological approach to understand the mismatches between the palaeoecological information and the projections of the HSMs. Here, we present the result of (1) investigating causal relationships between environmental variables and presence of Pinus sylvestris L. and P. nigra Arn. available from the 3rd Spanish Forest Inventory, (2) developing present and past presence-predictions through the MaxEnt model for 6 and 21 kyr BP, and (3) assessing these models through comparisons with biomized palaeoecological data available from the European Pollen Database for the Iberian Peninsula.