El efecto del cambio climático sobre las distribuciones de los bosques ibérico: pasado, presente y futuro

Tesis doctoral inédita leída en la Universidad Autónoma de Madrid. Facultad de Ciencias. Departamento de Biología. Fecha de lectura: 13-07-200

Aplicación de modelos ecológicos para el análisis de la estructura y dinámica de bosques Ibéricos en respuesta al cambio climático

Los modelos son simplificaciones de la realidad, su uso en Ecología permite estudiar patrones y procesos en sistemas naturales complejos de manera objetiva y relativamente sencilla. Los ecosistemas forestales son especialmente complejos de estudiar al estar formados por especies longevas y de gran tamaño, donde la experimentación es difícil. La combinación de modelos y datos observacionales a escalas espaciales regionales y continentales es particularmente útil para analizar patrones y procesos en bosques. La distribución y abundancia de organismos a lo largo del espacio y el tiempo está determinada por factores ambientales, bióticos y antrópicos, como por ejemplo las condiciones climáticas, la competencia inter- e intra-específica, la adaptación local, la plasticidad fenotípica o la gestión forestal. Por lo tanto, para el estudio de la respuesta de los bosques frente al cambio global es aconsejable el uso de modelos que incluyan estos factores de cambio y su efecto en los patrones y procesos observados. De hecho, el uso de modelos apropiadas a escalas regionales supone un paso fundamental para estimar los posibles impactos, la vulnerabilidad de los bosques y establecer prioridades en las estrategias de mitigación y adaptación al cambio climático. En el presente capítulo presentamos brevemente las técnicas más utilizadas para la parametrización de modelos en Ecología, y la aplicación de ciertos modelos para analizar los impactos y la vulnerabilidad de los bosques frente al cambio global. Dentro de las aplicaciones, incluimos desde modelos estadísticos correlacionales para analizar patrones (e.g. Modelos de Distribución de Especies o modelos de procesos demográficos) hasta modelos dinámicos que incorporan procesos demográficos para explicar patrones de distribución. Finalmente, discutimos  el uso de estos modelos como herramientas para el diagnóstico de los impactos del cambio climático sobre los bosques Ibéricos y su importancia para el diseño de estrategias de adaptación

Injectable hydrogel-based drug delivery system for cartilage regeneration.

pre-print1650 K

Validation of rat brain MR image intensity non-uniformity correction using surface coil images

[Poster] 4th European Molecular Imaging Meeting, Barcelona, Spain, May 27 - 30, 2009Non-uniform intensity artifacts confound the quantitative analysis of magnetic resonance (Mr) images of animal studies, particularly when using surface coils and high-field magnets. The use of correction methods proposed and validated on human brain images such as the n3 algorithm has previously been reported only on mouse images acquired with a volume coil. here, we evaluate the performance of n3 specifically on Mr rat brain images acquired with a surface coilCdTeaM (CeniT-ingenio 2010), Ministerio de Ciencia e innovación, Ciber Cb07/09/0031 CiberSaM, Ministerio de Sanidad y ConsumoPublicad

A new generation of sensors and monitoring tools to support climate-smart forestry practices

Climate-smart forestry (CSF) is an emerging branch of sustainable adaptive forest management aimed at enhancing the potential of forests to adapt to and mitigate climate change. It relies on much higher data requirements than traditional forestry. These data requirements can be met by new devices that support continuous, in situ monitoring of forest conditions in real time. We propose a comprehensive network of sensors, i.e., a wireless sensor network (WSN), that can be part of a worldwide network of interconnected uniquely addressable objects, an Internet of Things (IoT), which can make data available in near real time to multiple stakeholders, including scientists, foresters, and forest managers, and may partially motivate citizens to participate in big data collection. The use of in situ sources of monitoring data as ground-truthed training data for remotely sensed data can boost forest monitoring by increasing the spatial and temporal scales of the monitoring, leading to a better understanding of forest processes and potential threats. Here, some of the key developments and applications of these sensors are outlined, together with guidelines for data management. Examples are given of their deployment to detect early warning signals (EWS) of ecosystem regime shifts in terms of forest productivity, health, and biodiversity. Analysis of the strategic use of these tools highlights the opportunities for engaging citizens and forest managers in this new generation of forest monitoring.Peer reviewe

A new generation of sensors and monitoring tools to support climate-smart forestry practices

Climate-smart forestry (CSF) is an emerging branch of sustainable adaptive forest management aimed at enhancing the potential of forests to adapt to and mitigate climate change. It relies on much higher data requirements than traditional forestry. These data requirements can be met by new devices that support continuous, in situ monitoring of forest conditions in real time. We propose a comprehensive network of sensors, i.e., a wireless sensor network (WSN), that can be part of a worldwide network of interconnected uniquely addressable objects, an Internet of Things (IoT), which can make data available in near real time to multiple stakeholders, including scientists, foresters, and forest managers, and may partially motivate citizens to participate in big data collection. The use of in situ sources of monitoring data as ground-truthed training data for remotely sensed data can boost forest monitoring by increasing the spatial and temporal scales of the monitoring, leading to a better understanding of forest processes and potential threats. Here, some of the key developments and applications of these sensors are outlined, together with guidelines for data management. Examples are given of their deployment to detect early warning signals (EWS) of ecosystem regime shifts in terms of forest productivity, health, and biodiversity. Analysis of the strategic use of these tools highlights the opportunities for engaging citizens and forest managers in this new generation of forest monitoring.Peer reviewe

Available and missing data to model impact of climate change on European forests

Climate change is expected to cause major changes in forest ecosystems during the 21st century and beyond. To assess forest impacts from climate change, the existing empirical information must be structured, harmonised and assimilated into a form suitable to develop and test state-of-the-art forest and ecosystem models. The combination of empirical data collected at large spatial and long temporal scales with suitable modelling approaches is key to understand forest dynamics under climate change. To facilitate data and model integration, we identified major climate change impacts observed on European forest functioning and summarised the data available for monitoring and predicting such impacts. Our analysis of c. 120 forest-related databases (including information from remote sensing, vegetation inventories, dendroecology, palaeoecology, eddy-flux sites, common garden experiments and genetic techniques) and 50 databases of environmental drivers highlights a substantial degree of data availability and accessibility. However, some critical variables relevant to predicting European forest responses to climate change are only available at relatively short time frames (up to 10-20 years), including intra-specific trait variability, defoliation patterns, tree mortality and recruitment. Moreover, we identified data gaps or lack of data integration particularly in variables related to local adaptation and phenotypic plasticity, dispersal capabilities and physiological responses. Overall, we conclude that forest data availability across Europe is improving, but further efforts are needed to integrate, harmonise and interpret this data (i.e. making data useable for non-experts). Continuation of existing monitoring and networks schemes together with the establishments of new networks to address data gaps is crucial to rigorously predict climate change impacts on European forests. © 2019 The Author(s

Available and missing data to model impact of climate change on European forests

Climate change is expected to cause major changes in forest ecosystems during the 21st century and beyond. To assess forest impacts from climate change, the existing empirical information must be structured, harmonised and assimilated into a form suitable to develop and test state-of-the-art forest and ecosystem models. The combination of empirical data collected at large spatial and long temporal scales with suitable modelling approaches is key to understand forest dynamics under climate change. To facilitate data and model integration, we identified major climate change impacts observed on European forest functioning and summarised the data available for monitoring and predicting such impacts. Our analysis of c. 120 forest-related databases (including information from remote sensing, vegetation inventories, dendroecology, palaeoecology, eddy-flux sites, common garden experiments and genetic techniques) and 50 databases of environmental drivers highlights a substantial degree of data availability and accessibility. However, some critical variables relevant to predicting European forest responses to climate change are only available at relatively short time frames (up to 10-20 years), including intra-specific trait variability, defoliation patterns, tree mortality and recruitment. Moreover, we identified data gaps or lack of data integration particularly in variables related to local adaptation and phenotypic plasticity, dispersal capabilities and physiological responses. Overall, we conclude that forest data availability across Europe is improving, but further efforts are needed to integrate, harmonise and interpret this data (i.e. making data useable for non-experts). Continuation of existing monitoring and networks schemes together with the establishments of new networks to address data gaps is crucial to rigorously predict climate change impacts on European forests.Peer reviewe