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Glucosinolates and their hydrolysis products as a sustainable strategy in the control of postharvest diseases in non-Brassicaceae fruits and vegetables
No full textProducción CientíficaPostharvest losses in fruits and vegetables represent a critical challenge for global food security and sustain-
ability, accounting for up to 28–55 % of total production in some regions. Conventional control strategies, largely
based on synthetic fungicides and physical treatments, face increasing limitations due to concerns over resistance
development, chemical residues and environmental impact. This review provides a comprehensive analysis of
glucosinolates (GSLs) and their hydrolysis products (GHPs) as promising biocidal agents for the management of
postharvest diseases in non-Brassicaceae fresh produce. We summarize current knowledge on the chemical na-
ture, biosynthesis and hydrolytic activation of GSLs, as well as their mechanisms of action against key post-
harvest pathogens, including fungi, oomycetes and bacteria. Furthermore, we critically examine application
strategies—such as biofumigation, plant extracts, volatile release, and the use of commercial or modified
GHPs—along with their reported efficacy in in vitro and in vivo studies. The review highlights knowledge gaps
related to mechanistic understanding, formulation stability, and industrial scalability, outlining future research
directions to translate these compounds into sustainable and commercially viable solutions for reducing post-
harvest losses
Deep feature representations and fusion strategies for speech emotion recognition from acoustic and linguistic modalities: A systematic review
No full textProducción CientíficaEmotion Recognition (ER) has gained significant attention due to its importance in advanced human-machine interaction and its widespread real-world applications. In recent years, research
on ER systems has focused on multiple key aspects, including the development of high-quality
emotional databases, the selection of robust feature representations, and the implementation
of advanced classifiers leveraging AI-based techniques. Despite this progress in research, ER
still faces significant challenges and gaps that must be addressed to develop accurate and
reliable systems. To systematically assess these critical aspects, particularly those centered on
AI-based techniques, we employed the PRISMA methodology. Thus, we include journal and
conference papers that provide essential insights into key parameters required for dataset
development, involving emotion modeling (categorical or dimensional), the type of speech
data (natural, acted, or elicited), the most common modalities integrated with acoustic and
linguistic data from speech and the technologies used. Similarly, following this methodology,
we identified the key representative features that serve as critical emotional information sources
in both modalities. For acoustic, this included those extracted from the time and frequency
domains, while for linguistic, earlier embeddings and the most common transformer models
were considered. In addition, Deep Learning (DL) and attention-based methods were analyzed
for both. Given the importance of effectively combining these diverse features for improving ER,
we then explore fusion techniques based on the level of abstraction. Specifically, we focus on
traditional approaches, including feature-, decision-, DL-, and attention-based fusion methods.
Next, we provide a comparative analysis to assess the performance of the approaches included
in our study. Our findings indicate that for the most commonly used datasets in the literature:
IEMOCAP and MELD, the integration of acoustic and linguistic features reached a weighted
accuracy (WA) of 85.71% and 63.80%, respectively. Finally, we discuss the main challenges
and propose future guidelines that could enhance the performance of ER systems using acoustic
and linguistic features from speech.Proyecto FrailAlert SBPLY/21/180501/000216 cofinanciado por la Junta de Comunidades de Castilla-La Mancha y la Unión Europea a través del Fondo Europeo de Desarrollo RegionalActiTracker TED2021-130867B-I00 financiado por MCIN/AEI/10.13039/501100011033 y por European Union NextGenerationEU/PRTRINDRI (PID2021-122642OB-C41 /AEI/10.13039/501100011033/ FEDER, UE)Ministerio de Ciencia e Innovación bajo el proyecto PID2023-146254OB-C4
Twelve-year oak seedling survival and growth in post-coal mining pastures of northern Spain: Combined effects of nurse shrubs and grazing exclusion
No full textProducción CientíficaFacilitative interactions among plants can support vegetation recovery in degraded environments, yet their
medium-term effectiveness in restoration remains insufficiently understood. We conducted a 12-year field
experiment in reclaimed open-cast coal mines in northern Spain to assess whether native colonizer legume shrubs
enhance the survival and growth of seedlings of two Quercus species. A total of 800 seedlings were planted under
four treatments combining the presence/absence of shrub and grazing, allowing us to disentangle biotic and
abiotic facilitation mechanisms. Shrubs enhanced seedling survival, particularly for Q. pyrenaica, by buffering
early mortality during summer droughts. Medium-term seedling survival under shrubs was markedly higher than
in shrub-free areas (13–25 % vs. 1–4 %). Herbivory had a limited effect on survival, with fencing providing
marginal benefits in specific years. Slow increments of Quercus seedling height and diameter over time were
found, being more pronounced for Q. petraea, and varying as the combined effect of shrubs and grazing exclu-
sion. Annual growth varied over time for both Quercus species, being greater under than outside shrubs for
Q. petraea, while for Q. pyrenaica, the shrub effect depended on the year. Q. pyrenaica seedlings exhibited higher
annual growth than Q. petraea. Differences in seedling annual growth with and without shrubs were smaller in
the driest years. We conclude that native shrubs play a key facilitative role in the medium-term restoration of
degraded oak ecosystems under sub-Mediterranean conditions. Their effectiveness varies by species and response
variable (survival vs. growth), and the underlying facilitation mechanisms differ over time.Ministerio de Ciencia, Innovación Universidades - MICIU/AEI/10.13039/501100011033/FEDER, UE (Proyecto RESTORMINE: PID2022–140127OB-I00)Junta de Castilla y León (Proyectos VA042A10–2 y VA035G18)Universidad de Valladolid - beca predoctoral UVa-2019 (113–2019PREUVA27) y postdoctoral UVa-María Zambrano (CONVREC-2021–11
Evaluación de la adherencia a psicofármacos: Estudio farmacoepidemiológico de registro en Castilla y León.
No full textINTRODUCTION: The use of antidepressants and anti-dementia drugs has increased in recent years. Patients with depression, anxiety, or dementia are more likely to not adhere to treatment. Non-adherence is associated with poorer health outcomes and increased morbidity and mortality. Additionally, nonadherence correlates with a considerable increase in healthcare costs.
OBJECTIVES: 1) Evaluate non-adherence to antidepressants and anti-dementia drugs and analyze predisposing factors. 2) Evaluate the economic impact of nonadherence to antidepressants.
METHODS: This was a population-based epidemiological registry study. Pharmaceutical consumption data was obtained from the pharmaceutical service information system in Castilla y León (CONCYLIA). An indirect method based on the medication possession ratio (MPR) was used to estimate adherence. Patients with an MPR<80% were considered non-adherent. Multivariate logistic regression was used to identify predictors of non-adherence while controlling for sociodemographic and clinical variables. Values of p < 0.05 were considered significant.
RESULTS: In 2021, 10.6% of Castilla y León's population (246,718 individuals) consumed antidepressants, costing ¿29 million. The most used antidepressants were selective serotonin reuptake inhibitors (SSRIs) (54.77%) and "other antidepressants" (46.82%). Antidepressants were primarily prescribed for depression (36.73%) and anxiety (29.24%).
The median annual cost of antidepressants per patient was ¿70.08. Patients' copayments accounted for 6.09% of the total cost, with a median of ¿2.78.
Non-adherence to antidepressants was more prevalent among men (20.56%) than women (19.59%), decreasing with age. Non-adherence accounted for 13.30% of costs.
Tricyclic antidepressants (TCAs) were associated with the highest prevalence of non-adherence (23.99%), followed by SSRIs (20.19%). Fluoxetine (23.53%) and fluvoxamine (22.42%) had the highest rates of non-adherence. Conversely, venlafaxine (14.64%) and citalopram (14.88%) had the lowest rates.
Predictors of non-adherence to antidepressants included living in an urban area, taking TCAs, and having a neuropathic pain diagnosis. Non-adherence decreases with age. Protective factors include being female, institutionalization, polypharmacy, and having a diagnosis of depression or anxiety alongside another psychiatric diagnosis.
In 2022, 6.12% of people over 80 years of age in Castile and León took anti-dementia drugs. The most used anti-dementia drugs were donepezil (43.49%) and rivastigmine (36.84%). Among this population, 14.7% used two or more different anti-dementia drugs. Most of these patients had multiple chronic conditions, including cardiovascular diseases (80%), depression/anxiety (60%), and psychotic disorders (39%).
A total of 16.77% of patients were non-adherent to these medications, particularly rivastigmine. Memantine had the lowest rate of non-adherence (13.23%). Having multiple prescribers and using rivastigmine were predictors of non-adherence. In contrast, being institutionalized, taking multiple medications, the combined use of medications, the use of memantine, and having concomitant diagnoses such as psychotic disorders, depression, and Parkinson's disease were protective factors against non-adherence.
CONCLUSIONS: MPR is a reliable indicator that helps clinicians identify non-adherent patients and take corrective action. Reducing nonadherence to psychotropic medications is essential for improving clinical and economic outcomes. There is an urgent need to implement standardized interventions and measures for the early detection of non-adherence, such as the indicator used in this study.INTRODUCCIÓN: El uso de antidepresivos y de los medicamentos antidemencia ha aumentado en los últimos años. Los propios síntomas de la depresión/ansiedad y de la demencia predisponen a la falta de adherencia al tratamiento. La falta de adherencia se asocia a peores resultados en salud, incrementando la morbilidad y mortalidad. Además, la no adherencia se correlaciona con un incremento considerable del gasto sanitario.
OBJETIVOS: 1) Evaluar la falta de adherencia a antidepresivos y medicamentos antidemencia y analizar los factores predisponentes. 2) Evaluar el impacto económico derivado de la falta de adherencia a antidepresivos.
METODOLOGÍA: Estudio epidemiológico de registro basado en la población. La fuente de datos de consumo farmacéutico ha sido el sistema de información para la prestación farmacéutica en Castilla y León (CONCYLIA). Para estimar la adherencia se ha utilizado un método indirecto basado en el índice de posesión de medicación (MPR). Los pacientes con un MPR<80% se consideraron no adherentes. Se ha utilizado una regresión logística multivariante para identificar predictores de no adherencia, considerando variables sociodemográficas y clínicas. Se consideraron significativos los valores de p<0,05.
RESULTADOS: En 2021, el 10,6% de la población de Castilla y León (246.718 pacientes) consumió antidepresivos, con un coste de 29 M ¿. Los antidperesivos más consumidos fueron los inhibidores selectivos de la recaptación de serotonina (ISRS) (54,77%) y “otros antidepresivos” (46,82%). Los antidepresivos se prescribieron principalmente para la depresión (36,73%) y la ansiedad (29,24%).
La mediana del coste de antidepresivos por paciente/año fue de 70,08¿. El copago realizado por el paciente representó el 6,09% del total, con una mediana 2,78 ¿.
La no adherencia a antidepresivos fue más frecuente en hombres (20,56%) que en mujeres (19,59%) y disminuyó con el aumento de edad. La falta de adherencia un 13,30% de los costes.
Los antidepresivos tricíclicos (ATC) se asociaron con la mayor prevalencia de falta de adherencia (23,99%), seguidos de los ISRS (20,19%). Los medicamentos con mayores tasas de no adherencia fueron la fluoxetina (23,53%) y la fluvoxamina (22,42%). Por otra parte, la venlafaxina (14,64%) y citalopram (14,88%) presentaron las tasas más bajas.
Los predictores de la falta de adherencia a antidepresivos fueron: vivir en zonas urbanas, usar ATC y el diagnóstico de dolor neuropático. La no adherencia a los antidepresivos disminuye con el envejecimiento. Ser mujer, la institucionalización, estar polimedicado y tener depresión/ansiedad junto a otro diagnóstico psiquiátrico son factores protectores.
En 2022, el 6,12% de la población mayor de 80 años de Castilla y León consumió medicamentos antidemencia. El donepezilo (43,49%) y la rivastigmina (36,84%) fueron los fármacos antidemencia más utilizados. El 14,7% de la población uso dos o más medicamentos antidemencia diferentes. Estos pacientes eran fundamentalmente pluripatológicos: enfermedades cardiovasculares (80%), depresión/ansiedad (60%) y trastornos psicóticos (39%).
El 16,77% fueron no adherentes a estos medicamentos, especialmente la rivastigmina. Por su parte, la memantina mostro la menor tasa de no adherencia (13,23%). Los predictores de falta de adherencia fueron: tener varios prescriptores y el uso de la rivastigmina. Estar institucionalizado, ser polimedicado, el uso combinado de medicamentos, el uso de memantina y diagnósticos concomitantes como los trastornos psicóticos, la depresión y el Parkinson resultaron como factores protectores frente a la no adherencia.
CONCLUSIONES: El MPR es un indicador sólido para que el clínico identifique a los pacientes no adherentes para su seguimiento, y adopte las medidas correctoras necesarias. Reducir la falta de adherencia a psicofármacos es fundamental para mejorar los resultados clínicos y económicos. Es urgente aplicar intervenciones y medidas estandarizadas, como puede ser el indicador utilizado en este estudio para la detección precoz de la falta de adherencia.Escuela de DoctoradoDoctorado en Investigación en Ciencias de la Salu
Functional dimensioning based on a 3D nominal model
No full textProducción CientíficaAbstract A part definition drawing must accurately assume the functional require-
ments of the mechanical system to which it belongs to enable correct functional
dimensioning. This dimensioning is essential for the methods office to define its
production and for metrology to define its verification. It should be noted that the
functional dimensioning process we propose simulates a professional exercise in an
academic environment. In this paper, a method that uses a 3D model of a mechan-
ical system is adopted and the nominal models of the components. It also relies on
analyzing the positioning of each part in the possible working states of the mechanical
system. The part functional dimensioning requires mastery of the ISO-GPS language
(International Organization for Standardization-Geometrical product specifications),
and a precise analysis of the operation and positioning of each component. This anal-
ysis of the part positioning will allow the definition of the necessary datum systems
and the definition of the initial GPS specifications of dimension, tolerance zone
and pattern (maximum or least material requirement). Both analyses should provide
us with the ISO-GPS functional dimensions in the functional definition drawings
according to ISO 16792:2021 and other GPS standards
Dynamics and Interaction of Solitons in the BPS Limit and their Internal Modes
No full textSolitons are special solutions of nonlinear classical field theories that behave like extended particle-like states. They are of considerable interest both in classical physics and quantum field theory, with applications ranging from condensed matter and nuclear physics to cosmology.
These non-perturbative objects can be classified as stable or unstable, depending on whether they display dispersive behaviour. Stable solitons fall into two broad categories. Topological solitons, such as kinks, vortices, and monopoles, derive their stability from topological invariants. Within the class of field theories that admit topological solitons, BPS theories (Bogomolny–Prasad–Sommerfield) are especially notable, since their solitons exhibit no static interactions, allowing multiple configurations to exist with the same energy. BPS solutions satisfy first-order differential equations that automatically solve the static Euler-Lagrange equations. In contrast, non-topological solitons —including Q-balls, soliton stars, and oscillons— are stabilised by conserved charges of global symmetries, by the integrability of the theory, or by specific adiabatic invariants. Finally, unstable solitons, such as sphalerons, represent metastable configurations.
Solitons also possess a rich internal structure, which can be understood in terms of collective excitations around the base configuration. These excitations may lead to fragmentation into more elementary entities, oscillations that modify the soliton’s size, or new dynamical behaviours during its evolution. Such modes may be triggered after a phase transition or during interactions with other solitons, impurities, or incoming radiation.
The main purpose of this thesis has been to examine soliton dynamics, with particular attention to the role of internal modes. The research has focused on one- and two-dimensional models, providing a foundation for extending the analysis to three-dimensional theories. Among the wide variety of solitons, this thesis concentrates on kinks, oscillons, vortices, and sphalerons. Nevertheless, field theories possess infinitely many degrees of freedom, which makes both analytic solutions and predictive modelling highly challenging. To address this, the work develops effective models that retain only the essential degrees of freedom, employing the well-established collective coordinate method. Additional tools, such as perturbative techniques, have also been applied.
Among the main contributions, it is worth highlighting, first, the incorporation—for the first time within the collective coordinate framework—of genuine radiation modes, which makes it possible to describe phenomena of radiation emission and interaction in solitonic systems. Secondly, a generalisation of Samols’ moduli space metric for local vortices in the Abelian–Higgs model has been achieved by incorporating vibrational degrees of freedom. This extension allows the construction of accurate initial conditions for effective models of vortex–vortex collisions. Moreover, a new class of sphalerons, termed semi-BPS sphalerons, has been identified and studied. These exhibit properties closely analogous to those of BPS solitons. Finally, the role of oscillatory internal modes in the decay process of sphalerons has been studied in detail, leading to the proposal of a dynamic stabilisation mechanism. This mechanism has been further explained and extended to more general models, demonstrating the robustness and potential applicability of this phenomenon to physically relevant theories.Los solitones son soluciones particulares de teorías de campos clásicos no lineales que se comportan como estados extendidos semejantes a partículas. Resultan de gran interés tanto en física clásica como en teoría cuántica de campos, además de tener aplicaciones en la materia condensada, la física nuclear y la cosmología.
Estos objetos no perturbativos pueden clasificarse en estables o inestables, según presenten o no comportamiento dispersivo. Entre los solitones estables existen dos grandes categorías. Los solitones topológicos, como los kinks, los vórtices y los monopolos, deben su estabilidad a invariantes topológicos. Dentro de la clase de teorías de campos que admiten solitones topológicos, destacan las teorías BPS (Bogomolny–Prasad–Sommerfield), cuyas soluciones no presentan interacciones estáticas, lo que permite la coexistencia de múltiples configuraciones con la misma energía. Además, las soluciones BPS satisfacen ecuaciones diferenciales de primer orden que resuelven automáticamente las ecuaciones de Euler–Lagrange estáticas. Por otro lado, los solitones no topológicos —como las Q-balls, las estrellas de solitones y los oscilones— se estabilizan gracias a cargas conservadas asociadas a simetrías globales, a la integrabilidad de la teoría o a ciertos invariantes adiabáticos. En cambio, los solitones inestables, como los esfalerones, representan configuraciones metaestables.
Los solitones poseen además una compleja estructura interna, que puede interpretarse en términos de excitaciones colectivas alrededor de la configuración base. Estas excitaciones pueden dar lugar a fenómenos como la fragmentación en entidades más elementales, oscilaciones que modifican el tamaño del solitón o comportamientos dinámicos durante su evolución. Dichos modos pueden originarse tras una transición de fase o bien surgir durante interacciones con otros solitones, impurezas o radiación incidente.
El objetivo principal de esta tesis ha sido analizar la dinámica de solitones, prestando especial atención al papel de los modos internos. La investigación se ha centrado en modelos unidimensionales y bidimensionales, con la finalidad de establecer una base sólida que permita extender el estudio a teorías tridimensionales. Entre la amplia variedad de solitones, este trabajo se concentra en kinks, oscilones, vórtices y esfalerones. Sin embargo, las teorías de campos presentan un número infinito de grados de libertad, lo que dificulta tanto la obtención de soluciones analíticas como la construcción de modelos predictivos. Para afrontar este desafío, la tesis desarrolla modelos efectivos que conservan únicamente los grados de libertad esenciales, utilizando el conocido método de coordenadas colectivas. Asimismo, se han empleado técnicas complementarias, como métodos perturbativos.
Entre las aportaciones principales destacan, en primer lugar, la incorporación —por primera vez en el marco de coordenadas colectivas— de modos de radiación genuinos, lo que permite describir fenómenos de emisión e interacción de radiación en sistemas solitónicos. En segundo lugar, se ha desarrollado una generalización de la métrica del espacio de módulos de Samols para vórtices locales en el modelo de Abeliano–Higgs, mediante la inclusión de grados de libertad vibracionales. Esta extensión proporciona condiciones iniciales adecuadas para modelar colisiones de vórtices en modelos efectivos. Además, se ha identificado y estudiado una nueva clase de esfalerones, denominados semi-BPS, que presentan propiedades análogas a las de los solitones BPS. Finalmente, se ha analizado en detalle el papel de los modos internos oscilatorios en el proceso de decaimiento de los esfalerones, lo que nos ha permitido proponer un mecanismo de estabilización dinámica que ha sido explicado y posteriormente extendido a otros modelos más generales, lo cual muestra la robustez y la posible aplicabilidad de este fenómeno a modelos de mayor interés físico.Escuela de DoctoradoDoctorado en Físic
Security practices and insider threats in Spanish healthcare centers: a survey-based risk assessment
No full textProducción CientíficaIntroduction: Insider threats pose a critical risk in healthcare environments, where Hospital Information Systems
(HIS) manage sensitive patients data. Authorized users may intentionally or accidentally compromise data
confidentiality, integrity, and availability. This study assessed information security practices from the perspec-
tive of healthcare professionals in Spanish medical centers.
Methods: A descriptive, analytical, cross-sectional study was conducted using a survey administered to 41
healthcare professionals with access to confidential data. The survey covered access control, encryption at rest
and in transit, communication channels, and data usage control. Descriptive statistics, Chi-square tests, and
Cram´er’s V were applied to identify significant associations. K-means clustering and Silhouette coefficient were
used to define user profiles. Principal Component Analysis (PCA) was used to visualize behavior patterns. A
Random Forest model identified the most relevant predictive variables.
Results: Critical security gaps were detected, 31.7 % reported no control over data usage. Only 29.3 % encrypted
data at rest and 36.6 % during transmission. Over 40 % used personal email or messaging apps to share sensitive
data, and 97.6 % relied solely on passwords for authentication. These practices are inadequate to mitigate insider
threats.
Conclusion: There is an urgent need to strengthen insider data protection. Security strategies should be tailored to
user risk profiles. Measures must include strong authentication, full encryption, and stricter control of data
transmission to reduce exposure to insider threats (intentionally or unintentionally) in healthcare settings.
Additionally, there is a need to promote continuous cybersecurity training.Instituto da Telecomunicações da Delegação da Covilhã, Portugal. This work is partially funded by Brazilian National Council for Scientific and Technological Development - CNPq, via Grant No. 306607/2023-9.Ministerio de Ciencia, Innovación y Universidades (MICINN), a la Agencia Estatal de Investigación (AEI), así como al Fondo Europeo de Desarrollo Regional (FEDER, UE) M0CIN/AEI/10.13039/501100011033 y “FEDER Una manera de hacer Europa” (grant number PID2021-122210OB-I00
Volumetric and viscosity data of 1-iodonaphthalene + n-alkane mixtures at (288.15-308.15) K
No full textProducción CientíficaDensity and viscosity measurements have been performed for the systems 1-iodonaphthalene + heptane, or + decane, or + dodecane, or + tetradecane over the temperature range (288.15-308.15) K and atmospheric pressure. At this end, a densitometer Anton-Paar DMA 602 and a Ubbelohde viscosimeter were used. Excess molar volumes are large and negative and decrease when the temperature is increased, which reveals that the main contribution to the excess molar volume arises from structural effects. The values of the deviations of dynamic viscosity from linear dependence on mole fraction are also large and negative, indicating that n-alkanes are good breakers of the interactions between 1-iodonaphthalene molecules. Different models were applied for describing viscosity data. McAllister's equation correlates well with kinematic viscosities. Results are similar when dynamic viscosities are correlated with the Grunberg-Nissan or Fang-He equations. This means that size effects are not relevant to the mentioned data. The adjustable parameter of the Grunberg-Nissan equation is negative for all the systems at any temperature, a typical feature of systems where dispersive interactions are dominant. This is in agreement with findings obtained in previous studies on similar n-alkane mixtures involving C6H5X (X = Cl, Br, I) or 1,2,4-trichlorobenzene or 1-chloronaphthalene. Free volume effects have little influence on the present dynamic viscosity results, well represented by the absolute rate model using residual molar Gibbs energies obtained from the DISQUAC model.This work was carried out under Project PID2022-137104NA-I00, funded by MICIN/AEI/10.13039/501100011033/ and by FEDER, UE. J. V. A.-L. would like to thank the Instituto de Corresponsabilidade pela Educação (ICE) – Brazil for his PhD scholarship. F. P. acknowledges the FPI grant PREP2022-000047 from MCIN/AEI/10.13039/501100011033/ and FEDER, UE
Nonautonomous modelling in energy balance models of climate. Limitations of averaging and climate sensitivity
No full textStarting from a classical Budyko-Sellers-Ghil energy balance model for the average surface temperature of the Earth, a nonautonomous version is designed by allowing the solar irradiance and the cloud cover coefficients to vary with time on a fast timescale, and to exhibit chaos in a precise sense. The dynamics of this model is described in terms of three existing nonautonomous equilibria, the upper one being attracting and representing the present temperature profile. The theory of averaging is used to compare the nonautonomous model and its time-averaged version. We analyse the influence of the qualitative properties of the time-dependent coefficients and obtain reasonable approximations close to the upper hyperbolic solution. Furthermore, previous concepts of two-point response and sensitivity functions are adapted to the nonautonomous context and used to value the increase in temperature when a forcing caused by CO_2 and other emissions intervenes.All authors were partly supported by MICIIN/FEDER project PID2021-125446NB I00 and by the University of Valladolid under project PIP-TCESC-2020. I.P. Longo was also partly supported by UKRI under the grant agreement EP/X027651/1
Assessment of spaceborne and airborne lidar metrics using Fay-Herriot models to support forest biomass estimation
No full textAccurate estimation of Aboveground Biomass Density (AGBD) is essential for understanding carbon cycling and informing forest management and climate mitigation strategies. This study evaluates the use of Fay-Herriot (FH) models to estimate AGBD by integrating metrics from spaceborne LiDAR (GEDI), airborne LiDAR (ALS), and their combination. We assessed predictive performance across two contrasting forest environments: eucalyptus plantations in Hawai‘i and Mediterranean pine forests in Spain. Four estimation methods were compared at each site: FH models using only ALS data, only GEDI data, both data sources combined, and direct estimation using only field data. A model selection process was employed to identify candidate predictors, and all models were rigorously evaluated. To assess the performance of each estimator, Root Mean Square Error (RMSE) and relative efficiency—compared to direct estimation—were used as indicators. The results demonstrate that FH models, regardless of the auxiliary variables used, consistently outperformed direct estimation methods, as evidenced by lower RMSE values. Relative improvements over direct estimations were 18 %, 19 %, and 21 % for ALS, GEDI, and their combination in Hawai‘i; and 31 %, 29 %, and 31 % for the respective auxiliary datasets in Spain. Combining ALS and GEDI yielded only marginal improvements over using each set individually. Furthermore, both datasets exhibited comparable performance. Regarding the predictors, structural metrics related to vertical complexity emerged as key drivers of performance. Together, these results demonstrate that both ALS and GEDI data substantially enhance AGBD estimation within FH frameworks, with GEDI providing a cost-effective alternative at operational scales where ALS data are unavailable