133 research outputs found
High-Order AFEM for the Laplace-Beltrami Operator: Convergence Rates
We present a new AFEM for the Laplace-Beltrami operator with arbitrary
polynomial degree on parametric surfaces, which are globally and
piecewise in a suitable Besov class embedded in with . The idea is to have the surface sufficiently well resolved in
relative to the current resolution of the PDE in . This gives
rise to a conditional contraction property of the PDE module. We present a
suitable approximation class and discuss its relation to Besov regularity of
the surface, solution, and forcing. We prove optimal convergence rates for AFEM
which are dictated by the worst decay rate of the surface error in
and PDE error in .Comment: 51 pages, the published version contains an additional glossar
On an adaptive stabilized mixed finite element method for the Oseen problem with mixed boundary conditions
[Abstract] We consider the Oseen problem with nonhomogeneous Dirichlet boundary conditions on a part of the boundary and a Neumann type boundary condition on the remaining part. Suitable least squares terms that arise from the constitutive law, the momentum equation and the Dirichlet boundary condition are added to a dual-mixed formulation based on the pseudostress-velocity variables. We prove that the new augmented variational formulation and the corresponding Galerkin scheme are well-posed, and a Céa estimate holds for any finite element subspaces. We also provide the rate of convergence when each row of the pseudostress is approximated by Raviart–Thomas elements and the velocity is approximated by continuous piecewise polynomials. We develop an a posteriori error analysis based on a Helmholtz-type decomposition, and derive a posteriori error indicators that consist of two residual terms per element except on those elements with a side on the Dirichlet boundary, where they both have two additional terms. We prove that these a posteriori error indicators are reliable and locally efficient. Finally, we provide several numerical experiments that support the theoretical results.Xunta de Galicia; ED431G 2019/01Universidad Católica de la Santísima Concepción (Chile); 1160578Ministerio de Economía y Competitividad; MTM2016-76497-RMinisterio de Ciencia, Innovación y Universidades; PRX19/00475Xunta de Galicia; GRC ED431C 2018-03
Evolución del comportamiento espectral y la composición química en el dosel arbóreo de una dehesa
Revista oficial de la Asociación Española de Teledetección[EN] In the context of the BIOSPEC and FLUXPEC projects (http://www.lineas.cchs.csic.es/fluxpec/), spectral and biophysical variables measurements at leaf level have been conducted in the tree canopy of a holm oak dehesa (Quercus ilex) ecosystem during four vegetative periods. Measurements of bi-conical reflectance factor of intact leaf (ASD Fieldspec 3® spectroradiometer), specific leaf mass (SLM), leaf water content (LWC), nutrient (N, P, K, Ca, Mg, Mn, Fe, and Zn) and chlorophyll concentration were performed. The spectral measurements have been related with the biophysical variables by stepwise and partial least squares regression analyses. These analyses allowed to identify the spectral bands and regions that best explain the evolution of the biophysical variables and to estimate the nutrient contents during the leaf maturation process. Statistically significant estimates of the majority of the variables studied were obtained. Wavelengths that had the highest contributions explaining the chemical composition of the forest canopy were located in spectral regions of the red edge, the green visible region, and the shortwave infrared.[ES] En el contexto de los proyectos BIOSPEC y FLUXPEC (http://www.lineas.cchs.csic.es/fluxpec/), se han rea-lizado mediciones espectrales y de variables biofísicas a nivel de hoja en el dosel arbóreo de una dehesa de encina (Quercus ilex) durante cuatro períodos vegetativos. Se han llevado a cabo mediciones de reflectividad bi-cónica de hoja intacta (ASD Fieldspec 3®spectroradiometer), masa foliar específica (SLM), contenido de agua (LWC), concen-traciones de nutrientes (N, P, K, Ca, Mg, Mn, Fe, y Zn) y clorofilas. Las mediciones espectrales se han relacionado con las variables biofísicas mediante análisis de regresión múltiple por pasos (SWR) y regresión de mínimos cuadrados parciales (PLSR). Estos análisis han permitido identificar las bandas y regiones espectrales que explican la evolución de las variables biofísicas y estimar los contenidos de nutrientes a lo largo del proceso de maduración de las hojas en la copa. Se han obtenido modelos estadísticamente significativos para la mayoría de las variables foliares estudiadas. Las longitudes de onda que aportan mayor información sobre la composición química del dosel, se encuentran en las regiones espectrales del límite del rojo, la región verde del visible y el infrarrojo medio de onda corta (SWIR).Este trabajo ha sido financiado por los proyectos BIOSPEC (CGL2008-02301/CLI, Ministerio de Ciencia e innovación) y FLUXPEC (CGL-2012 34383, Ministerio de Economía y Competitividad).González-Cascón, R.; Pacheco-Labrador, J.; Martín, MP. (2016). Evolution of spectral behavior and chemical composition in the tree canopy of a dehesa ecosystem. Revista de Teledetección. (46):31-43. https://doi.org/10.4995/raet.2016.5688SWORD31434
Climate warming triggers the emergence of native viruses in Iberian amphibians
The number of epizootics in amphibian populations caused by viruses of the genus Ranavirus is increasing worldwide. Yet, causes for pathogen emergence are poorly understood. Here, we confirmed that the Common midwife toad virus (CMTV) and Frog virus 3 (FV3) are responsible for mass mortalities in Iberia since the late 1980s. Our results illustrate the Iberian Peninsula as a diversity hotspot for the highly virulent CMTV. Although this pattern of diversity in Europe is consistent with spread by natural dispersal, the exact origin of the emergence of CMTV remains uncertain. Nevertheless, our data allow hypothesizing that the Iberian Peninsula might harbor the ancestral population of CMTVs that could have spread into the rest of Europe. In addition, we found that climate warming could be triggering the CMTV outbreaks, supporting its endemic status in the Iberian Peninsula.info:eu-repo/semantics/acceptedVersio
Surface representation impacts on turbulent heat fluxes in the Weather Research and Forecasting (WRF) model (v.4.1.3)
The water and energy transfers at the interface between the Earth's surface and the atmosphere should be correctly simulated in numerical weather and climate models. This implies the need for a realistic and accurate representation of land cover (LC), including appropriate parameters for each vegetation type. In some cases, the lack of information and crude representation of the surface lead to errors in the simulation of soil and atmospheric variables. This work investigates the ability of the Weather Research and Forecasting (WRF) model to simulate surface heat fluxes in a heterogeneous area of southern France using several possibilities for the surface representation. In the control experiments, we used the default LC database in WRF, which differed significantly from the actual LC. In addition, sub-grid variability was not taken into account since the model uses, by default, only the surface information from the dominant LC category in each pixel (dominant approach). To improve this surface simplification, we designed three new interconnected numerical experiments with three widely used land surface models (LSMs) in WRF. The first one consisted of using a more realistic and higher-resolution LC dataset over the area of analysis. The second experiment aimed at investigating the effect of using a mosaic approach; 30 m sub-grid surface information was used to calculate the final grid fluxes based on weighted averages from values obtained for each LC category. Finally, in the third experiment, we increased the model stomatal conductance for conifer forests due to the large flux errors associated with this vegetation type in some LSMs. The simulations were evaluated with gridded area-averaged fluxes calculated from five tower measurements obtained during the Boundary-Layer Late Afternoon and Sunset Turbulence (BLLAST) field campaign. The results from the experiments differed depending on the LSM and displayed a high dependency of the simulated fluxes on the specific LC definition within the grid cell, an effect that was enhanced with the dominant approach. The simulation of the fluxes improved using the more realistic LC dataset except for the LSMs that included extreme surface parameters for coniferous forest. The mosaic approach produced fluxes more similar to reality and served to particularly improve the latent heat flux simulation of each grid cell. Therefore, our findings stress the need to include an accurate surface representation in the model, including soil and vegetation sub-grid information with updated surface parameters for some vegetation types, as well as seasonal and man-made changes. This will improve the modelled heat fluxes and ultimately yield more realistic atmospheric processes in the model
A Bibliometric Overview of the International Journal of Interactive Multimedia and Artificial Intelligence
The International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI) published its first issue ten years ago. Currently, IJIMAI is indexed in the important database Emerging Sources Citation Index. This paper aims to identify, through a mapping of science, those most relevant aspects of the structure of publications made during the first 10 years of IJIMAI. Using VOSviewer software, the structural maps of the IJIMAI publications are analysed according to techniques such as bibliographic coupling, co-citations and cooccurrence of keywords. In addition, the evolution of the publications, citations and an analysis of the most cited papers of the journal are presented. The results show that IJIMAI has experienced a remarkable growth of both publications and citations in the last five years. We also observe that IJIMAI does not only capture the attention of the Spanish scientific community, but also of emerging countries such as India and Iran and emerging Latin American countries such as Colombia. With a such increasing behaviour, it is expected in the coming years that IJIMAI will position itself among the best journals with similar scientific scope
Local and regional characterisation of the diurnal mountain wind systems in the Guadarrama mountain range (Spain)
Póster presentado en: EGU General Assembly celebrada del 23 al 28 de abril de 2017 en Viena, Austria.This research has been partially funded by the Spanish Government (MINECO projects CGL2015-65627-C3-3-R and CGL2012-37416-C04-02) and by the GR3/14 program (supported by UCM and Banco Santander) through the Research Group “Micrometeorology and Climate Variability” (No.910437)
Novel DNMT3A Germline Variant in a Patient with Multiple Paragangliomas and Papillary Thyroid Carcinoma
Over the past few years, next generation technologies have been applied to unravel the genetics of rare inherited diseases, facilitating the discovery of new susceptibility genes. We recently found germline DNMT3A gain-of-function variants in two patients with head and neck paragangliomas causing a characteristic hypermethylated DNA profile. Here, whole-exome sequencing identifies a novel germline DNMT3A variant (p.Gly332Arg) in a patient with bilateral carotid paragangliomas, papillary thyroid carcinoma and idiopathic intellectual disability. The variant, located in the Pro-Trp-Trp-Pro (PWWP) domain of the protein involved in chromatin targeting, affects a residue mutated in papillary thyroid tumors and located between the two residues found mutated in microcephalic dwarfism patients. Structural modelling of the variant in the DNMT3A PWWP domain predicts that the interaction with H3K36me3 will be altered. An increased methylation of DNMT3A target genes, compatible with a gain-of-function effect of the alteration, was observed in saliva DNA from the proband and in one independent acute myeloid leukemia sample carrying the same p.Gly332Arg variant. Although further studies are needed to support a causal role of DNMT3A variants in paraganglioma, the description of a new DNMT3A alteration in a patient with multiple clinical features suggests a heterogeneous phenotypic spectrum related to DNMT3A germline variants
Estimation of essential vegetation variables in a dehesa ecosystem using reflectance factors simulated at different phenological stages
[ES] Los pastos arbolados y arbustivos son vitales para la producción ganadera extensiva y sostenible, la conservación de la biodiversidad y la provisión de servicios ecosistémicos y se localizan en áreas que serán previsiblemente más afectadas por el cambio climático. Sin embargo, las características estructurales, fenológicas, y las propiedades ópticas de la vegetación en estos ecosistemas mixtos, como los ecosistemas adehesados en la Península Ibérica que combinan un estrato herbáceo y/o arbustivo con un dosel arbóreo disperso, constituyen un serio desafío para su estudio mediante teledetección. Este trabajo combina métodos físicos y empíricos para la estimación de variables de la vegetación esenciales para la modelización de su funcionamiento: índice de área foliar (LAI, m2 /m2 ), contenido en clorofila a nivel de hoja (Cab,leaf, μg/cm2 ) y dosel (Cab,canopy, g/m2 ) y contenido en materia seca a nivel de hoja (Cm,leaf, g/cm2 ) y dosel (Cm,canopy, g/m2), en un ecosistema de dehesa. Para este propósito se construyó una base de datos espectral simulada considerando las cuatro principales etapas fenológicas del estrato herbáceo, el más dinámico del ecosistema, (rebrote otoñal, máximo verdor, inicio de la senescencia y senescencia estival) mediante la combinación de los modelos de transferencia radiativa PROSAIL y FLIGHT. Esta base de datos se empleó para ajustar diferentes modelos predictivos basados en índices de vegetación (IV) propuestos en la literatura y en Partial Least Squares Regression (PLSR). PLSR permitió obtener los modelos con mayor poder de predicción (R2 ≥ 0,93, RRMSE ≤ 10,77 %), tanto para las variables a nivel de hoja como a nivel de dosel. Los resultados sugieren que los efectos direccionales y geométricos controlan las relaciones entre los factores de reflectividad (R) simulados y los parámetros foliares. Se observa una alta variabilidad estacional en la relación entre variables biofísicas e IVs, especialmente para LAI y Cab que se confirma en el análisis PLSR. Los modelos desarrollados deben ser aún validados con datos espectrales medidos con sensores próximos o remotos.[EN] Mixed vegetation systems such as wood pastures and shrubby pastures are vital for extensive and sustainable livestock production as well as for the conservation of biodiversity and provision of ecosystem services, and are mostly located in areas that are expected to be more strongly affected by climate change. However, the structural characteristics, phenology, and the optical properties of the vegetation in these mixed -ecosystems such as savanna-like ecosystems in the Iberian Peninsula which combines herbaceous and/or shrubby understory with a low density tree cover, constitute a serious challenge for the remote sensing studies. This work combines physical and empirical methods to improve the estimation of essential vegetation variables: leaf area index (LAI, m2 / m2 ), leaf (Cab,leaf, μg / cm2 ) and canopy(Cab,canopy, g / m2 ) chlorophyll content, and leaf (Cm, leaf, g / cm2 ) and canopy (Cm,canopy, g / m2 ) dry matter content in a dehesa ecosystem. For this purpose, a spectral simulated database for the four main phenological stages of the highly dynamic herbaceous layer (summer senescence, autumn regrowth, greenness peak and beginning of senescence), was built by coupling PROSAIL and FLIGHT radiative transfer models. This database was used to calibrate different predictive models based on vegetation indices (VI) proposed in the literature which combine different spectral bands; as well as Partial Least Squares Regression (PLSR) using all bands in the simulated spectral range (400-2500 nm). PLSR models offered greater predictive power (R2 ≥ 0.93, RRMSE ≤ 10.77 %) both for the leaf and canopy- level variables. The results suggest that directional and geometric effects control the relationships between simulated reflectance factors and the foliar parameters. High seasonal variability is observed in the relationship between biophysical variables and IVs, especially for LAI and Cab, which is confirmed in the PLSR analysis. The models developed need to be validated with spectral data obtained either with proximal or remote sensors.ste estudio se ha llevado a cabo en el contexto de los proyectos FLUXPEC (CGL2012-34383) y SynerTGE (CGL2015-69095-R, MINECO/FEDER,UE) financiados por el Ministerio de Economía y Competitividad. Agradecemos el apoyo de los proyectos IB16185 de la Junta de Extremadura, MoReDEHESHyReS (No. 50EE1621, Agencia Espacial Alemana (DLR) y Ministerio Alemán de Asuntos Económicos y Energía) y el premio de la fundación Alexander von Humboldt vía Premio Max-Planck a Markus ReichsteinMartín, MP.; Pacheco-Labrador, J.; González-Cascón, R.; Moreno, G.; Migliavacca, M.; García, M.; Yebra, M.... (2020). Estimación de variables esenciales de la vegetación en un ecosistema de dehesa utilizando factores de reflectividad simulados estacionalmente. Revista de Teledetección. 0(55):31-48. https://doi.org/10.4995/raet.2020.13394OJS3148055Alonso, M., Rozados, M.J., Vega, J.A., Pérez- Gorostiaga, P., Cuiñas, P., Fontúrbel, M.T., Fernández, C. 2002. Biochemical Responses of Pinus pinaster Trees to Fire-Induced Trunk Girdling and Crown Scorch: Secondary Metabolites and Pigments as Needle Chemical Indicators. Journal of Chemical Ecology, 28(4), 687-700. https://doi.org/10.1023/A:1015276423880Armah, F., Odoi, J., Yengoh, G., Obiri, S., Yawson, D., Afrifa, E. 2011. Food security and climate change in drought-sensitive savanna zones of Ghana. Mitigation and Adaptation Strategies for Global Change, 16, 291-306. https://doi.org/10.1007/s11027-010-9263-9Baret, F., Weiss, M., Lacaze, R., Camacho, F., Makhmara, H., Pacholcyzk, P., Smets, B. 2013. GEOV1: LAI and FAPAR essential climate variables and FCOVER global time series capitalizing over existing products. Part1: Principles of development and production. Remote Sensing of Environment, 137, 299-309. https://doi.org/10.1016/j.rse.2012.12.027Béland, M., Widlowski, J.L., Fournier, R.A. 2014. A model for deriving voxel-level tree leaf area density estimates from ground-based LiDAR. Environmental Modelling & Software, 51(0), 184- 189. https://doi.org/10.1016/j.envsoft.2013.09.034Chadwick, K.D., Asner, G.P. 2016. Organismic- Scale Remote Sensing of Canopy Foliar Traits in Lowland Tropical Forests. Remote Sensing, 8(2), 87. https://doi.org/10.3390/rs8020087Cleugh, H.A., Leuning, R., Mu, Q., Running, S.W. 2007. Regional evaporation estimates from flux tower and MODIS satellite data. Remote Sensing of Environment, 106(3), 285-304. https://doi.org/10.1016/j.rse.2006.07.007Croft, H., Chen, J.M. 2017. Remote Sensing of Leaf Pigments. En S. Liang (Ed.), Comprehensive Remote Sensing (pp. 117-142). Oxford: Elsevier. https://doi.org/10.1016/B978-0-12-409548-9.10547-0Croft, H., Chen, J.M., Froelich, N.J., Chen, B., Staebler, R.M. 2015. Seasonal controls of canopy chlorophyll content on forest carbon uptake: Implications for GPP modeling. Journal of Geophysical Research: Biogeosciences, 120(8), 1576-1586. https://doi.org/10.1002/2015JG002980Croft, H., Chen, J.M., Luo, X., Bartlett, P., Chen, B., Staebler, R.M. 2017. Leaf chlorophyll content as a proxy for leaf photosynthetic capacity. Global Change Biology, 23(9), 3513-3524. https://doi.org/10.1111/gcb.13599Croft, H., Chen, J.M., Wang, R., Mo, G., Luo, S., Luo, X., He, L., Gonsamo, A., Arabian, J., Zhang, Y., Simic-Milas, A., Noland, T.L., He, Y., Homolová, L., Malenovský, Z., Yi, Q., Beringer, J., Amiri, R., Hutley, L., Arellano, P., Stahl, C., Bonal, D. 2020. The global distribution of leaf chlorophyll content. Remote Sensing of Environment, 236, 111479. https://doi.org/10.1016/j.rse.2019.111479Dash, J., Curran, P.J. 2007. Evaluation of the MERIS terrestrial chlorophyll index (MTCI). Advances in Space Research, 39(1), 100-104. https://doi.org/10.1016/j.asr.2006.02.034Dorigo, W.A., Zurita-Milla, R., de Wit, A.J.W., Brazile, J., Singh, R., Schaepman, M.E. 2007. A review on reflective remote sensing and data assimilation techniques for enhanced agroecosystem modeling. International Journal of Applied Earth Observation and Geoinformation, 9(2), 165-193. https://doi.org/10.1016/j.jag.2006.05.003Doughty, C.E., Goulden, M.L. 2008. Seasonal patterns of tropical forest leaf area index and CO2 exchange. Journal of Geophysical Research: Biogeosciences, 113(G1). https://doi.org/10.1029/2007JG000590Fan, L., Gao, Y., Brück, H., Bernhofer, C. 2009. Investigating the relationship between NDVI and LAI in semi-arid grassland in Inner Mongolia using in-situ measurements. Theoretical and Applied Climatology, 95(1), 151-156. https://doi.org/10.1007/s00704-007-0369-2Fava, F., Colombo, R., Bocchi, S., Meroni, M., Sitzia, M., Fois, N., Zucca, C. 2009. Identification of hyperspectral vegetation indices for Mediterranean pasture characterization. International Journal of Applied Earth Observation and Geoinformation, 11(4), 233-243. https://doi.org/10.1016/j.jag.2009.02.003Feret, J.-B., François, C., Asner, G.P., Gitelson, A.A., Martin, R.E., Bidel, L.P.R., Ustin, S.L., le Maire, G., Jacquemoud, S. 2008. PROSPECT-4 and 5: Advances in the leaf optical properties model separating photosynthetic pigments. Remote Sensing of Environment, 112(6), 3030-3043. https://doi.org/10.1016/j.rse.2008.02.012Fortunel, C., Garnier, E., Joffre, R., Kazakou, E., Quested, H., Grigulis, K., Lavorel, S., Ansquer, P., Castro, H., Cruz, P., DoleŽal, J., Eriksson, O., Freitas, H., Golodets, C., Jouany, C., Kigel, J., Kleyer, M., Lehsten, V., Lepš, J., Meier, T., Pakeman, R., Papadimitriou, M., Papanastasis, V.P., Quétier, F., Robson, M., Sternberg, M., Theau, J.P., Thébault, A., Zarovali, M. 2009. Leaf traits capture the effects of land use changes and climate on litter decomposability of grasslands across Europe. Ecology, 90(3), 598- 611. https://doi.org/10.1890/08-0418.1Fourty, T., Baret, F. 1997. Vegetation water and dry matter contents estimated from top-of-the-atmosphere reflectance data: A simulation study. Remote Sensing of Environment, 61(1), 34-45. https://doi.org/10.1016/S0034-4257(96)00238-6Galvão, L.S., Formaggio, A.R., Tisot, D.A. 2005. Discrimination of sugarcane varieties in Southeastern Brazil with EO-1 Hyperion data. Remote Sensing of Environment, 94(4), 523-534. https://doi.org/10.1016/j.rse.2004.11.012García, M., Popescu, S., Riaño, D., Zhao, K., Neuenschwander, A., Agca, M., Chuvieco, E. 2012. Characterization of canopy fuels using ICESat/ GLAS data. Remote Sensing of Environment, 123(0), 81-89. https://doi.org/10.1016/j.rse.2012.03.018Gitelson, A.A., Buschmann, C., Lichtenthaler, H.K. 1999. The Chlorophyll Fluorescence Ratio F735/F700 as an Accurate Measure of the Chlorophyll Content in Plants. Remote Sensing of Environment, 69(3), 296-302. https://doi.org/10.1016/S0034-4257(99)00023-1Gitelson, A.A., Peng, Y., Viña, A., Arkebauer, T., Schepers, J.S. 2016. Efficiency of chlorophyll in gross primary productivity: A proof of concept and application in crops. Journal of Plant Physiology, 201, 101-110. https://doi.org/10.1016/j.jplph.2016.05.019Gitelson, A.A., Viña, A., Arkebauer, T.J., Rundquist, D.C., Keydan, G., Leavitt, B. 2003. Remote estimation of leaf area index and green leaf biomass in maize canopies. Geophysical Research Letters, 30(5). https://doi.org/10.1029/2002GL016450González-Cascón, R., Martín, M.P. 2018. Protocol for pigment content quantification in herbaceous covers: sampling and analysis. https://doi.org/10.17504/protocols.io.qs6dwheGuillen-Climent, M., Zarco-Tejada, P., Berni, J.A.J., North, P.R.J., Villalobos, F. 2012. Mapping radiation interception in row-structured orchards using 3D simulation and high-resolution airborne imagery acquired from a UAV. Precision Agriculture, 13, 473-500. https://doi.org/10.1007/s11119-012-9263-8Haboudane, D., Miller, J.R., Tremblay, N., Zarco-Tejada, P.J., Dextraze, L. 2002. Integrated narrow-band vegetation indices for prediction of crop chlorophyll content for application to precision agriculture. Remote Sensing of Environment, 81(2), 416-426. https://doi.org/10.1016/S0034-4257(02)00018-4Haldimann, P., Gallé, A., Feller, U. 2008. Impact of an exceptionally hot dry summer on photosynthetic traits in oak (Quercus pubescens) leaves. Tree Physiology, 28(5), 785-795. https://doi.org/10.1093/ treephys/28.5.785Hernández-Clemente, R., Navarro-Cerrillo, R.M., Suárez, L., Morales, F., Zarco-Tejada, P.J. 2011. Assessing structural effects on PRI for stress detection in conifer forests. Remote Sensing of Environment, 115(9), 2360-2375. https://doi.org/10.1016/j.rse.2011.04.036Hernández-Clemente, R., North, P.R.J., Hornero, A., Zarco-Tejada, P.J. 2017. Assessing the effects of forest health on sun-induced chlorophyll fluorescence using the FluorFLIGHT 3-D radiative transfer model to account for forest structure. Remote Sensing of Environment, 193, 165-179. https://doi.org/10.1016/j.rse.2017.02.012Hill, M.J., Hanan, N.P., Hoffmann, W., Scholes, R., Prince, S., Ferwerda, J., Lucas, R.M., Baker, I., Arneth, A., Higgins, S.I., Barrett, D.J., Disney, M., Hutley, L. 2011. Remote sensing and modeling of savannas: The state of the dis-union.Inoue, Y., Guérif, M., Baret, F., Skidmore, A., Gitelson, A., Schlerf, M., Darvishzadeh, R., Olioso, A. 2016. Simple and robust methods for remote sensing of canopy chlorophyll content: a comparative analysis of hyperspectral data for different types of vegetation. Plant, Cell & Environment, 39(12), 2609-2623. https://doi.org/10.1111/pce.12815Inoue, Y., Peñuelas, J., Miyata, A., Mano, M. 2008. Normalized difference spectral indices for estimating photosynthetic efficiency and capacity at a canopy scale derived from hyperspectral and CO2 flux measurements in rice. Remote Sensing of Environment, 112(1), 156-172. https://doi.org/10.1016/j.rse.2007.04.011Jacquemoud, S., Baret, F. 1990. PROSPECT: A model of leaf optical properties spectra. Remote Sensing of Environment, 34(2), 75-91. https://doi.org/10.1016/0034-4257(90)90100-ZJacquemoud, S., Verhoef, W., Baret, F., Bacour, C., Zarco-Tejada, P.J., Asner, G.P., François, C., Ustin, S.L. 2009. PROSPECT+SAIL models: A review of use for vegetation characterization. Remote Sensing of Environment, 113, S56-S66. https://doi.org/10.1016/j.rse.2008.01.026Jin, J., Wang, Q. 2019. Evaluation of Informative Bands Used in Different PLS Regressions for Estimating Leaf Biochemical Contents from Hyperspectral Reflectance. Remote Sensing, 11(2), 197. https://doi.org/10.3390/rs11020197Korhonen, L., Korpela, I., Heiskanen, J., Maltamo, M. 2011. Airborne discrete-return LIDAR data in the estimation of vertical canopy cover, angular canopy closure and leaf area index. Remote Sensing of Environment, 115(4), 1065-1080. https://doi.org/10.1016/j.rse.2010.12.011le Maire, G., François, C., Dufrêne, E. 2004. Towards universal broad leaf chlorophyll indices using PROSPECT simulated database and hyperspectral reflectance measurements. Remote Sensing of Environment, 89(1), 1-28. https://doi.org/10.1016/j.rse.2003.09.004le Maire, G., François, C., Soudani, K., Berveiller, D., Pontailler, J.-Y., Bréda, N., Genet, H., Davi, H., Dufrêne, E. 2008. Calibration and validation of hyperspectral indices for the estimation of broadleaved forest leaf chlorophyll content, leaf mass per area, leaf area index and leaf canopy biomass. Remote Sensing of Environment, 112(10), 3846- 3864. https://doi.org/10.1016/j.rse.2008.06.005Leonenko, G., Los, S.O., North, P.R.J. 2013. Retrieval of leaf area index from MODIS surface reflectance by model inversion using different minimization criteria. Remote Sensing of Environment, 139, 257-270. https://doi.org/10.1016/j.rse.2013.07.012Li, Q., Lu, X., Wang, Y., Huang, X., Cox, P.M., Luo, Y. 2018. Leaf area index identified as a major source of variability in modeled CO2 fertilization. Biogeosciences, 15(22), 6909-6925. https://doi.org/10.5194/bg-15-6909-2018LI-COR. 2019. LAI 2200-C Plant Canopy Analyzer instruction manual. Último acceso 5 de Junio, 2020, de https://licor.app.boxenterprise.net/s/ fqjn5mlu8c1a7zir5qelLichtenthaler, H.K., Buschmann, C. 2001. Chlorophylls and Carotenoids: Measurement and Characterization by UV-VIS Spectroscopy. Current Protocols in Food Analytical Chemistry, 1(1), F4.3.1-F4.3.8. https://doi.org/10.1002/0471142913.faf0403s01Luo, T., Pan, Y., Ouyang, H., Shi, P., Ji, L., Yu, Z., Lu, Q. 2004. Leaf area index and net primary productivity along subtropical to alpine gradients in the Tibetan Plateau. Global Ecology and Biogeography, 13, 345-358. https://doi.org/10.1111/j.1466-822X.2004.00094.xMaccioni, A., Agati, G., Mazzinghi, P. 2001. New vegetation indices for remote measurement of chlorophylls based on leaf directional reflectance spectra. Journal of Photochemistry and Photobiology B: Biology, 61(1), 52-61. https://doi.org/10.1016/S1011-1344(01)00145-2Melendo-Vega, J.R., Martín, M.P., Pacheco- Labrador, J., González-Cascón, R., Moreno, G., Pérez, F., Migliavacca, M., García, M., North, P., Riaño, D. 2018. Improving the Performance of 3-D Radiative Transfer Model FLIGHT to Simulate Optical Properties of a Tree-Grass Ecosystem. Remote Sensing, 10(12), 2061. https://doi.org/10.3390/rs10122061Metternicht, G. 2003. Vegetation indices derived from high-resolution airborne videography for precision crop management. International Journal of Remote Sensing, 24(14), 2855-2877. https://doi.org/10.1080/01431160210163074Miraglio, T., Adeline, K., Huesca, M., Ustin, S., Briottet, X. 2020. Monitoring LAI, Chlorophylls, and Carotenoids Content of a Woodland Savanna Using Hyperspectral Imagery and 3D Radiative Transfer Modeling. Remote Sensing, 12(1), 28. https://doi.org/10.3390/rs12010028Moreno, G., Rolo, V. 2019. Agroforestry practices: silvopastorism. En M.R. Mosquera-Losada & R. Prabhu (Eds.), Agroforestry for sustainable agriculture (pp. 119-164): Burleigh Dodds Science Publishing Limited.Myneni, R.B., Hoffman, S., Knyazikhin, Y., Privette, J.L., Glassy, J., Tian, Y., Wang, Y., Song, X., Zhang, Y., Smith, G.R., Lotsch, A., Friedl, M., Morisette, J.T., Votava, P., Nemani, R.R., Running, S.W. 2002. Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data. Remote Sensing of Environment, 83(1), 214-231. https://doi.org/10.1016/S0034-4257(02)00074-3North, P.R.J. 1996. Three-dimensional forest light interaction model using a Monte Carlo method. IEEE Transactions on Geoscience and Remote Sensing, 34(4), 946-956. https://doi.org/10.1109/36.508411Novara, A., Rühl, J., La Mantia, T., Gristina, L., La Bella, S., Tuttolomondo, T. 2015. Litter contribution to soil organic carbon in the processes of agriculture abandon. Solid Earth, 6, 425-432. https://doi.org/10.5194/se-6-425-2015Pacheco-Labrador, J., El-Madany, T.S., van der Tol, C., Martín, M.P., Gonzalez-Cascon, R., Perez-Priego, O., Guan, J., Moreno, G., Carrara, A., Reichstein, M., Migliavacca, M. 2020. senSCOPE: Modeling radiative transfer and biochemical processes in mixed canopies combining green and senescent leaves with SCOPE. bioRxiv, 2020.2002.2005.935064. https://doi.org/10.1101/2020.02.05.935064Pacheco-Labrador, J., González-Cascón, R., Martín, M.P., Melendo-Vega, J.R., Hernández-Clemente, R., Zarco-Tejada, P. 2017. Impact of trichomes in the application of radiative transfer models in leaves of Quercus ilex. En: VII Congreso forestal español, Plasencia, España. 26-30 Junio 2017.Pacheco-Labrador, J., Martín, M., Riaño, D., Hilker, T., Carrara, A. 2016. New approaches in multi-angular proximal sensing of vegetation: Accounting for spatial heterogeneity and diffuse radiation in directional reflectance distribution models. Remote Sensing of Environment, 187. https://doi.org/10.1016/j.rse.2016.10.051Pacheco-Labrador, J., Perez-Priego, O., El-Madany, T.S., Julitta, T., Rossini, M., Guan, J., Moreno, G., Carvalhais, N., Martín, M.P., Gonzalez-Cascon, R., Kolle, O., Reischtein, M., van der Tol, C., Carrara, A., Martini, D., Hammer, T.W., Moossen, H., Migliavacca, M. 2019. Multiple-constraint inversion of SCOPE. Evaluating the potential of GPP and SIF for the retrieval of plant functional traits. Remote Sensing of Environment, 234, 111362. https://doi.org/10.1016/j.rse.2019.111362Polley, H.W., Yang, C., Wilsey, B.J., Fay, P.A. 2019. Spectrally derived values of community leaf dry matter content link shifts in grassland composition with change in biomass production. Remote Sensing in Ecology and Conservation, n/a(n/a). https://doi.org/10.1002/rse2.145Pulido, F., Picardo, A., Campos, P., Carranza, J., Coleto, J., Díaz, M., Diéguez, E., Escudero, A., Ezquerra, F., Fernández, P., Solla, A. 2010. Libro Verde de la Dehesa. Consejería de Medio Ambiente, Junta Castilla La Mancha.Qiao, K., Zhu, W., Zhiying, X., Li, P. 2019. Estimating the Seasonal Dynamics of the Leaf Area Index Using Piecewise LAI-VI Relationships Based on Phenophases. Remote Sensing, 11(6), 689. https://doi.org/10.3390/rs11060689Reichstein, M., Bahn, M., Mahecha, M.D., Kattge, J., Baldocchi, D.D. 2014. Linking plant and ecosystem functional biogeography. Proceedings of the National Academy of Sciences, 111(38), 13697- 13702. https://doi.org/10.1073/pnas.1216065111Riaño, D., Valladares, F., Condes, S., Chuvieco, E. 2004. Estimation of leaf area index and covered ground from airborne laser scanner (LiDAR) in two contrasting forests. Agricultural and Forest Meteorology, 124(3-4), 269-275. https://doi.org/10.1016/j.agrformet.2004.02.005Riaño, D., Vaughan, P., Chuvieco, E., Zarco-Tejada, P., Ustin, S.L. 2005. Estimation of fuel moisture content by inversion of radiative transfer models to simulate equivalent water thickness and dry matter content: analysis at leaf and canopy level. IEEE Transactions on Geoscience and Remote Sensing, 43(4), 819-8
Carbon dioxide fluxes across the Sierra de Guadarrama, Spain
Understanding the spatial and temporal variation in soil respiration within small geographic areas is essential to accurately assess the carbon budget on a global scale. In this study, we investigated the factors controlling soil respiration in an altitudinal gradient in a southern Mediterranean mixed pine–oak forest ecosystem in the north face of the Sierra de Guadarrama in Spain. Soil respiration was measured in five Pinus sylvestris L. plots over a period of 1 year by means of a closed dynamic system (LI-COR 6400). Soil temperature and water content were measured at the same time as soil respiration. Other soil physico-chemical and microbiological properties were measured during the study. Measured soil respiration ranged from 6.8 to 1.4 lmol m-2 s-1, showing the highest values at plots situated at higher elevation. Q10 values ranged between 1.30 and 2.04, while R10 values ranged between 2.0 and 3.6. The results indicate that the seasonal variation of soil respiration was mainly controlled by soil temperature and moisture. Among sites, soil carbon and nitrogen stocks regulate soil respiration in addition to soil temperature and moisture. Our results suggest that application of standard models to estimate soil respiration for small geographic areas may not be adequate unless other factors are considered in addition to soil temperature
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