Dynamic relationships between gross primary production and energy partitioning in three different ecosystems based on eddy covariance time series analysis

Ecosystems are responsible for strong feedback processes that affect climate. The mechanisms and consequences of this feedback are uncertain and must be studied to evaluate their influence on global climate change. The main objective of this study is to assess the gross primary production (GPP) dynamics and the energy partitioning patterns in three different European forest ecosystems through time series analysis. The forest types are an Evergreen Needleleaf Forest in Finland (ENF_FI), a Deciduous Broadleaf Forest in Denmark (DBF_DK), and a Mediterranean Savanna Forest in Spain (SAV_SP). Buys-Ballot tables were used to study the intra-annual variability of meteorological data, energy fluxes, and GPP, whereas the autocorrelation function was used to assess the inter-annual dynamics. Finally, the causality of GPP and energy fluxes was studied with Granger causality tests. The autocorrelation function of the GPP, meteorological variables, and energy fluxes revealed that the Mediterranean ecosystem is more irregular and shows lower memory in the long term than in the short term. On the other hand, the Granger causality tests showed that the vegetation feedback to the atmosphere was more noticeable in the ENF_FI and the DBF_DK in the short term, influencing latent and sensible heat fluxes. In conclusion, the impact of the vegetation on the atmosphere influences the energy partitioning in a different way depending on the vegetation type, which makes the study of the vegetation dynamics essential at the local scale to parameterize these processes with more detail and build improved global models.14 página

Dynamic relationships between gross primary production and energy partitioning in three different ecosystems based on eddy covariance time series analysis

Ecosystems are responsible for strong feedback processes that affect climate. The mechanisms and consequences of this feedback are uncertain and must be studied to evaluate their influence on global climate change. The main objective of this study is to assess the gross primary production (GPP) dynamics and the energy partitioning patterns in three different European forest ecosystems through time series analysis. The forest types are an Evergreen Needleleaf Forest in Finland (ENF_FI), a Deciduous Broadleaf Forest in Denmark (DBF_DK), and a Mediterranean Savanna Forest in Spain (SAV_SP). Buys-Ballot tables were used to study the intra-annual variability of meteorological data, energy fluxes, and GPP, whereas the autocorrelation function was used to assess the inter-annual dynamics. Finally, the causality of GPP and energy fluxes was studied with Granger causality tests. The autocorrelation function of the GPP, meteorological variables, and energy fluxes revealed that the Mediterranean ecosystem is more irregular and shows lower memory in the long term than in the short term. On the other hand, the Granger causality tests showed that the vegetation feedback to the atmosphere was more noticeable in the ENF_FI and the DBF_DK in the short term, influencing latent and sensible heat fluxes. In conclusion, the impact of the vegetation on the atmosphere influences the energy partitioning in a different way depending on the vegetation type, which makes the study of the vegetation dynamics essential at the local scale to parameterize these processes with more detail and build improved global models

Assessment of different components of the Carbon flux in forest and agricultural ecosystems using remote sensing data and field measurements

La evaluación del ciclo del carbono en los ecosistemas es fundamental para el estudio del cambio climático. Los dos principales componentes del ciclo del carbono son la Producción Primaria Bruta (GPP) y la Respiración del suelo (Rs). El primero representa el carbono fijado por los ecosistemas a través de la fotosíntesis y es el flujo más grande del ciclo del carbono. El segundo es la fuente principal de CO2 en la mayoría de los ecosistemas. La alta variabilidad espacial y temporal de estos flujos hace que los ecosistemas forestales y agrícolas se puedan comportar como fuentes o sumideros de CO2 a lo largo de los años dependiendo de las interacciones con los factores meteorológicos y ecológicos. Por tanto, es necesario el desarrollo de métodos y técnicas adecuadas para estimar de manera precisa la GPP y la Rs. Esta tesis tiene como objetivo principal la evaluación de estos dos componentes del ciclo del carbono en ecosistemas forestales y agrícolas a través de técnicas de teledetección y medidas de campo. Este objetivo ha sido llevado a cabo a través de cuatro experimentos, dos que evalúan la Rs en agroecosistemas y dos que evalúan la GPP en ecosistemas forestales. En el primer estudio, la respiración total del suelo (Rs) y su componente autotrófico (Ra) fueron evaluadas mediante información espectral adquirida a través de espectro radiometría de campo en un cultivo de regadío de maíz (Zea mays L.) durante el periodo de crecimiento. Las relaciones entre Rs y Ra con el Índice de Área Foliar (IAF), los índices espectrales y los factores abióticos (temperatura y humedad del suelo) fueron evaluadas a través de modelos de regresión lineal. Los resultados mostraron que los índices espectrales contienen información funcional significativa, más allá de la meramente estructural, que puede estar relacionada con la Rs y la Ra. Sin embargo, deben aplicarse modelos específicos para cada una de las etapas fenológicas del cultivo y este aspecto se debe tener en cuenta a la hora de ampliar la escala al usar modelos de teledetección. El objetivo del segundo trabajo fue evaluar la Rs ligada a la fenología de un cultivo de secano de cebada durante dos periodos de crecimiento a través de índices espectrales calculados a partir de espectro-radiometría de campo. Las relaciones entre Rs, Índice de Área Foliar (IAF) e índices espectrales fueron evaluadas mediante modelos de regresión lineal con el coeficiente ajustado de determinación. Los resultados mostraron que la mayoría de índices espectrales proporcionaron mejor información que el IAF durante el periodo de estudio y que la humedad y la temperatura del suelo fueron importantes en periodos específicos. Durante los estadios vegetativos, los índices basados en la región del visible (VIS) mostraron la mejor relación con Rs. Por otro lado, durante los estadios reproductivos, los índices que contienen información de las regiones del infrarrojo cercano y del infrarrojo cercano de onda corta (NIR-SWIR) mostraron la mejor relación con la Rs. La variabilidad interanual encontrada en las regiones Mediterráneas fue observada también en la ratio de emisión-absorción de carbono. Nuestros resultados muestran la capacidad potencial de la información espectral para evaluar la respiración del suelo ligada a la fenología del cultivo a través de diferentes escalas espaciales y temporales. En el tercer trabajo, nuestro objetivo principal fue evaluar la dinámica de la GPP en una Dehesa situada en el centro de España mediante análisis de series de tiempo (2004-2008) en dos modelos: (1) La GPP proporcionada imágenes de teledetección del sensor MODIS (producto MOD17A2); y (2) La GPP estimada mediante la implementación local de un modelo de uso de eficiencia de la luz que tiene en cuenta los parámetros meteorológicos y ecológicos locales. Ambos modelos se compararon con la GPP de una torre de flujo Eddy situada en nuestra área de estudio. Nuestros resultados indican que los dos modelos de GPP mostraron la dinámica de una Dehesa en la que hay principalmente dos estratos, el arbóreo y el herbáceo. Sin embargo, el modelo MODIS infraestimó la GPP de la Dehesa Mediterránea debido a los diferentes parámetros ecológicos y meteorológicos que usa en su cálculo. Finalmente, los test de Causalidad de Granger indicaron que incluyendo la precipitación o el contenido de la humedad del suelo en los modelos se puede mejorar la predicción en los mismos. En el último trabajo, nuestro objetivo principal fue evaluar la dinámica de la GPP, de las variables meteorológicas y del comportamiento de los flujos de energía en tres ecosistemas forestales diferentes de Europa mediante el análisis de series de tiempo. Los resultados mostraron que la temperatura y la radiación solar fueron los factores limitantes in el bosque perennifolio de Finlandia, mientras que el contenido de la humedad del suelo fue el factor determinante para el crecimiento en la Dehesa Mediterránea. El bosque caducifolio de Dinamarca mostró un ciclo de la GPP diferente relacionado con la interacción de varios factores durante la época de crecimiento. En Finlandia, el calor latente estuvo acoplado a la GPP durante todo el periodo mientras que en Dinamarca empezó a estar fuertemente acoplado cuando se produjo la salida de la hoja. En España, el calor latente estuvo acoplado a la GPP durante el periodo de crecimiento, condicionado a la disponibilidad de agua en el suelo. La dinámica de la vegetación de los tres ecosistemas fue responsable directamente de la partición de los flujos de energía y la dinámica del flujo del agua proporcionando un feedback a la atmósfera influenciando esta partición de los flujos de energía de distinta manera. Los resultados de la tesis muestran la capacidad de nuevos métodos para la medición y la estimación de la Respiración del suelo y la Producción Primaria Bruta en distintos ecosistemas forestales y agrícolas a distintas escalas espacio-temporales. Se necesita de una mayor investigación para mejorar las estimaciones de estos dos componentes del ciclo del carbono y evaluar el papel que juegan los ecosistemas en el cambio climático. ----------ABSTRACT---------- The assessment of carbon cycle in the ecosystems is essential for studying climate change. The two main components of the carbon cycle are Gross Primary Production (GPP) and Soil Respiration (Rs). The first one represents the carbon uptake of ecosystems through photosynthesis and it is the largest flux of the global carbon balance. The second one is the most important source of CO2 in most ecosystems. The high spatial and temporal variability of these fluxes can make forest and agricultural ecosystems behave as a sink or as a source of CO2 over the years depending on the interaction of meteorological and ecological factors. Therefore, developing suitable methods and techniques for estimating GPP and Rs are crucial to obtain accurate estimations. The main objective of this thesis is to assess these two main components of the carbon cycle in agricultural and forest ecosystems by new remote sensing and field techniques. This objective has been carried out with four experiments, two assessing Rs in agroecosystems and two assessing GPP in forest ecosystems. In the first study total soil respiration (Rs) and its autotrophic component (Ra) were assessed through spectral information acquired by field spectroscopy in a row irrigated corn crop (Zea mays L.) throughout the growing period. The relationships between Rs and Ra with leaf area index (LAI), spectral indexes and abiotic factors (soil moisture and soil temperature) were assessed by linear regression models. Results showed that Spectral indexes contain significant functional information, beyond mere structural changes, that could be related to Rs and Ra. However, specific models should be applied for the different phenological stages and there is a need to be cautious when upscaling remote sensing models. The aim of the second study was to assess Rs linked to crop phenology of a rainfed barley crop throughout two seasons based on spectral indices calculated from field spectroscopy data. The relationships between Rs, Leaf Area Index (LAI) and spectral indices were assessed by linear regression models with the adjusted coefficient of determination. Results showed that most of the spectral indices provided better information than LAI throughout the studied period and that soil moisture and temperature were relevant variables in specific periods. During vegetative stages, indices based on the visible (VIS) region showed the best relationship with Rs. On the other hand, during reproductive stages indices containing the near infrared-shortwave infrared (NIR-SWIR) spectral region and those related to water content showed the highest relationship. The inter-annual variability found in Mediterranean regions was also observed in the estimated ratio of carbon emission to carbon fixation between years. Our results show the potential capability of spectral information to assess soil respiration linked to crop phenology across several temporal and spatial scales. In the third work, our overall objective was to assess the GPP dynamics of a Dehesa ecosystem in Central Spain by analysing the time series (2004–2008) of two models: (1) GPP provided by remote sensing images from the MODIS sensor (MOD17A2 product); and (2) GPP estimated by the implementation of a site-specific light use efficiency model taking into account local ecological and meteorological parameters. Both models were compared to the production provided by an eddy covariance flux tower located in our study area. Our results indicated that both models of GPP showed a typical Dehesa dynamic where there are primarily two layers, the arboreal and the herbaceous strata. However, MODIS underestimates the production of the dehesa in a Mediterranean climate due to the different ecological and meteorological parameters used in the MODIS model. Finally, the Granger causality tests indicate that GPP prediction can be improved by including precipitation or soil water in the models. In the last work, our overall objective was to assess the GPP dynamics and the energy partitioning patterns in three different European forest ecosystems by time series analysis. Results show that temperature and solar radiation were the main limiting factors in the Evergreen Needleleaf forest of Finland while water availability was determinant for growth in the Mediterranean Dehesa ecosystem. The Deciduous Broadleaf Forest in Denmark showed a different GPP cycle related with an interaction of various factors during all the growing season. In Finland, latent heat was coupled to GPP during all growing season due to the factor of temperature while in Denmark began to be strongly coupled when leaf emergence occurred. In Spain, latent heat was coupled to GPP during all growing season conditioned by water availability. The vegetation dynamics of the three ecosystems were directly responsible for the energy fluxes partitioning and water fluxes dynamics providing a feedback to atmosphere influencing the energy partitioning in a different way. Results from this thesis show the capacity of new methods to measure and estimate soil respiration and Gross Primary Production in different forest and agricultural ecosystems at different spatial and temporal scales. Further research is needed to improve the estimations of these two components of the carbon cycle and to assess the role of ecosystems in the climate change

Soil and Land Cover Interrelationships: An Analysis Based on the Jenny’s Equation

This research analyzes the relationships between “soil” and “organisms” within the framework of the Jenny equation, a fundamental expression in soil science that is the theoretical basis for modeling the complex occurrence of soils on landscapes. This analysis is based on the interpretation of the indeterminate function “f” of the equation as “statistical dependence between categorical variables”. The categories of the “soil” component of the equation have been defined as “diagnostic horizons”, and those of the “organisms” factor as synthetic types of “land cover”. After applying these criteria to 424 soil profiles studied in a region with an oceanic climate in northern Spain, a multiple correspondence analysis showed pedologically consistent groupings between diagnostic horizons and categories of climate, land cover, relief, and parent material factors. Subsequently, a bivariate analysis detailed pedologically consistent relationships between diagnostic horizons and land cover categories. In the context the scarcity of quantitative information on soil and forming factor relationships, this work provides criteria to statistically assess the role of land cover in such relationships. This soil forming factor is the one whose spatial representation is more generalized and detailed, hence its interest in the development of soil mapping models

Identification and Modeling Carbon and Energy Fluxes from Eddy Covariance Time Series Measurements in Rice and Rainfed Crops

Gross primary production (GPP) represents the carbon (C) uptake of ecosystems through photosynthesis and it is the largest flux of the global carbon balance. Our overall objective in this research is to identify and model GPP dynamics and its relationship with meteorological variables and energy fluxes based on time series analysis of eddy covariance (EC) data in two different agroecosystems, a Mediterranean rice crop in Spain and a rainfed cropland in Germany. Crops exerted an important influence on the energy and water fluxes dynamics existing a clear feedback between GPP, meteorological variables and energy fluxes in both type of crops

Soil and land cover interrelationships: an analysis based on the Jenny’s equation

This research analyzes the relationships between “soil” and “organisms” within the framework of the Jenny equation, a fundamental expression in soil science that is the theoretical basis for modeling the complex occurrence of soils on landscapes. This analysis is based on the interpretation of the indeterminate function “f” of the equation as “statistical dependence between categorical variables”. The categories of the “soil” component of the equation have been defined as “diagnostic horizons”, and those of the “organisms” factor as synthetic types of “land cover”. After applying these criteria to 424 soil profiles studied in a region with an oceanic climate in northern Spain, a multiple correspondence analysis showed pedologically consistent groupings between diagnostic horizons and categories of climate, land cover, relief, and parent material factors. Subsequently, a bivariate analysis detailed pedologically consistent relationships between diagnostic horizons and land cover categories. In the context the scarcity of quantitative information on soil and forming factor relationships, this work provides criteria to statistically assess the role of land cover in such relationships. This soil forming factor is the one whose spatial representation is more generalized and detailed, hence its interest in the development of soil mapping models.Ministerio de Ciencia e Innovación (España)Union EuropeaDepto. de Física de la Tierra y AstrofísicaFac. de Ciencias FísicasTRUEpu

Mapping Cropland Intensification in Ecuador through Spectral Analysis of MODIS NDVI Time Series

2022Descuento MDPIMultiple cropping systems constitute an essential agricultural practice that will ensure food security within the increasing demand of basic cereals as a consequence of global population growth and climate change effects. In this regard, there is a need to develop new methodologies to adequately monitor cropland intensification. The main objective of this research was to assess cropland intensification by means of spectral analysis of MODIS NDVI time series in a high cloudiness tropical area such as Ecuador. A surface of 89,225 ha of the main staple crops in this country, which are rice and maize crops, was monitored to assess the evolution of the number of crop cycles. The 20-year period of NDVI time series was used to calculate the periodograms across four subperiods (2001–2005, 2006–2010, 2011–2015, 2016–2020). The maximum ordinate value of each periodogram was used as an indicator of the number of growing crop cycles per year identifying single-, double-, and triple-cropping systems in each subperiod. Cropland intensification was assessed by comparing the cropping system between the subperiods. Results reveal that more than half of the studied croplands experienced changes in the cropping systems, and 40% showed positive trends in terms of the number of growing crop cycles, being principally located near the main rivers where irrigation facilitates crop development during the dry season. Therefore, the area under single cropping decreased from over 60,000 ha in the first subperiod to less than 50,000 ha in the last two subperiods. The cropland surface subjected to multi-cropping practices increased during the second decade of the study period, with a double-cropping system being more widely used than growing three crops per year, reaching surfaces of 24,400 ha and 10,450 ha in the last subperiod, respectively. The robust results obtained in this research show the great potential of the periodogram approach for the discrimination of cropping systems and for mapping intensification areas in tropical regions where dealing with noisy remote sensing time series as a consequence of high cloudiness is a great challenge.Ministerio de Ciencia, Innovación y UniversidadesEuropean CommissionUniversidad Politécnica de MadridSecretaría de Educación Superior, Ciencia, Tecnología e Innovación (Ecuador)Comunidad de MadridDepto. de Física de la Tierra y AstrofísicaFac. de Ciencias FísicasTRUEpubDescuento UC

Mapping Cropland Intensification in Ecuador through Spectral Analysis of MODIS NDVI Time Series

Multiple cropping systems constitute an essential agricultural practice that will ensure food security within the increasing demand of basic cereals as a consequence of global population growth and climate change effects. In this regard, there is a need to develop new methodologies to adequately monitor cropland intensification. The main objective of this research was to assess cropland intensification by means of spectral analysis of MODIS NDVI time series in a high cloudiness tropical area such as Ecuador. A surface of 89,225 ha of the main staple crops in this country, which are rice and maize crops, was monitored to assess the evolution of the number of crop cycles. The 20-year period of NDVI time series was used to calculate the periodograms across four subperiods (2001–2005, 2006–2010, 2011–2015, 2016–2020). The maximum ordinate value of each periodogram was used as an indicator of the number of growing crop cycles per year identifying single-, double-, and triple-cropping systems in each subperiod. Cropland intensification was assessed by comparing the cropping system between the subperiods. Results reveal that more than half of the studied croplands experienced changes in the cropping systems, and 40% showed positive trends in terms of the number of growing crop cycles, being principally located near the main rivers where irrigation facilitates crop development during the dry season. Therefore, the area under single cropping decreased from over 60,000 ha in the first subperiod to less than 50,000 ha in the last two subperiods. The cropland surface subjected to multi-cropping practices increased during the second decade of the study period, with a double-cropping system being more widely used than growing three crops per year, reaching surfaces of 24,400 ha and 10,450 ha in the last subperiod, respectively. The robust results obtained in this research show the great potential of the periodogram approach for the discrimination of cropping systems and for mapping intensification areas in tropical regions where dealing with noisy remote sensing time series as a consequence of high cloudiness is a great challenge

MCJ: A mitochondrial target for cardiac intervention in pulmonary hypertension

Pulmonary hypertension (PH) can affect both pulmonary arterial tree and cardiac function, often leading to right heart failure and death. Despite the urgency, the lack of understanding has limited the development of effective cardiac therapeutic strategies. Our research reveals that MCJ modulates mitochondrial response to chronic hypoxia. MCJ levels elevate under hypoxic conditions, as in lungs of patients affected by COPD, mice exposed to hypoxia, and myocardium from pigs subjected to right ventricular (RV) overload. The absence of MCJ preserves RV function, safeguarding against both cardiac and lung remodeling induced by chronic hypoxia. Cardiac-specific silencing is enough to protect against cardiac dysfunction despite the adverse pulmonary remodeling. Mechanistically, the absence of MCJ triggers a protective preconditioning state mediated by the ROS/mTOR/HIF-1α axis. As a result, it preserves RV systolic function following hypoxia exposure. These discoveries provide a potential avenue to alleviate chronic hypoxia-induced PH, highlighting MCJ as a promising target against this condition.MINECOComunidad de MadridSevero Ochoa CNICInstituto de Salud Carlos IIIFundación “La Caixa”Juan de la Cierva Incorporación GrantMICINNDepto. de Medicina y Cirugía AnimalFac. de VeterinariaTRUEpu