Artículos destacados
El fruto de nuestro trabajo
Modeling water vapor impacts on the solar irradiance reaching the receiver of a solar tower plant by means of artificial neural networks. Solar Energy, 169, 34-39 (2018)
Gabriel López, Christian A. Gueymard, Juan Luis Bosch, Igor Rapp Arrarás, Joaquín Alonso Montesinos, Inmaculada Pulido Calvo, Jesús Ballestrín, Jesús Polo, Javier Barbero
This work analyses the influence of water vapor on the atmospheric transmission loss of solar radiation between heliostats and the receiver of solar power tower plants. To this purpose, an atmospheric transmission code (MODTRAN) is used to generate values of direct normal irradiance (DNI) reaching the mirror and the receiver under different geometries (including sun position, tower height, and mirror-to-receiver slant range) and atmospheric conditions related to water vapor and aerosols. These variables are then used as inputs to an artificial neural network (ANN), which is trained to calculate the corresponding DNI attenuation. Two different aerosol scenarios are simulated: an ideal aerosol-free atmosphere, and a widely different one corresponding to semi-hazy conditions. The developed ANN model is then able to provide the DNI attenuation over a wide range of the input variables considered here, with root mean square differences of only 0.8%. The transmission loss due to water vapor is found to decrease with sun elevation. This is explained by the saturation effect in the incident irradiance at the mirror. The simplicity and accuracy of the algorithm are its great strengths, allowing its anticipated inclusion into the actual energy simulation codes currently used for solar tower plant design.
Is it possible to differentiate between environmental and fishery effects on abundance-biomass variation? A case study of blackspot seabream (Pagellus bogaraveo) in the Strait of Gibraltar. Fisheries Oceanography, 26(4), 455-475 (2017)
Juan Carlos Gutiérrez Estrada, Juan Gil Herrera, Inmaculada Pulido Calvo, Ivonne Alejandra Czerwinski
We assessed the potential for simulation and modelling of the blackspot seabream (Pagellus bogaraveo) population in the Strait of Gibraltar to discriminate the environmental effects of fishery impacts. A discrete biomass–abundance dynamic model was implemented to obtain a simulated monthly time series of blackspot seabream biomass. On this simulated time series, autoregressive integrated moving average (ARIMA) models were fitted. The best ARIMA fit provided a significant correlation of 0.76 and persistence index higher than 0.85. The proportion of variance non-explained by the ARIMA models was correlated with a time series of sea surface temperature (SST) and North Atlantic Oscillation (NAO). The analysis of global, annual and winter correlation between the proportion of variance not explained by the ARIMA models and environmental variables showed that significant associations were not detected over the full time series. Our analysis therefore suggests that overexploitation is the main factor responsible for the commercial depletion of blackspot seabream in the Strait of Gibraltar.
Is the relationship between mast-seeding and weather in oaks related to their life-history or phylogeny? Ecology, 97, 2603-2615 (2016)
Walter D Koenig, Reyes Alejano, María Dolores Carbonero, Pilar FernándezRebollo, Johannes M H Knops, Teodoro Maranon, Carmen M Padilla-Díaz, Ian S Pearse, Ignacio M Pérez-Ramos, Javier Vázquez-Piqué, Mario B Pesendorfer
Although the functional basis of variable and synchronous seed production (masting behavior) has been extensively investigated, only recently has attention been focused on the proximate mechanisms driving this phenomenon. We analyzed the relationship between weather and acorn production in 15 species of oaks (genus Quercus) from three geographic regions on two continents with the goals of determining the extent to which similar sets of weather factors affect masting behavior across species and to explore the ecological basis for the similarities detected. Lag-1 temporal autocorrelations were predominantly negative, supporting the hypothesis that stored resources play a role in masting behavior across this genus, and we were able to determine environmental variables correlating with acorn production in all but one of the species. Standard weather variables outperformed “differential-cue” variables based on the difference between successive years in a majority of species, consistent with the hypothesis that weather is linked directly to the proximate mechanism driving seed production and that masting in these species is likely to be sensitive to climate change. Based on the correlations between weather variables and acorn production, cluster analysis failed to generate any obvious groups of species corresponding to phylogeny or life-history. Discriminant function analyses were, however, able to identify the phylogenetic section to which the species belonged and, controlling for phylogeny, the length of time species required to mature acorns, whether they were evergreen or deciduous, and, to a lesser extent, the geographic region to which they are endemic. These results indicate that similar proximate mechanisms are driving acorn production in these species of oaks, that the environmental factors driving seed production in oaks are to some extent phylogenetically conserved, and that the shared mechanisms driving acorn production result in some degree of synchrony among coexisting species in a way that potentially enhances predator satiation, at least when they have acorns requiring the same length of time to mature.
Effects of mesh size and towing speed on the multispecies catch ratesof historical swept area surveys. Fisheries Research, 164, 143-152 (2015)
Luis María Manjarrés Martínez, Juan Carlos Gutiérrez Estrada, José Antonio Hernando
The use of different trawl nets is a factor to be considered when analysing historical swept-area researchsurveys aimed to characterize temporal variations in the relative abundance of demersal resources. Iffactors that may affect the performance of the bottom trawls were considered, more reliable temporaltrends could be established. Due to the high species diversity that characterizes tropical areas, this kind ofanalysis is often carried out at the multispecies level. Therefore, the objective of this study was to establishthe effect of two technical factors, mesh size and towing speed on the multispecies catch rates obtained indifferent demersal surveys carried out in the Colombian Caribbean Sea between 1988 and 2001, using twogeneralized linear models: one covering the entire study area and another restricted to one eco-region.For the global model, the effect of the mesh size on the multispecies catch rates was marginally significant(p < 0.10), unlike the towing speed, whose effect was not significant (p > 0.10). In contrast, for the eco-region model, the effect of mesh size was not significant (p > 0.10), while towing speed had a significanteffect (p < 0.05). Size structure analysis showed escapement mainly through the codend meshes for thelarger mesh size evaluated (50.8 mm), confirming the appropriateness of considering mesh size whenanalyzing historical data of swept area surveys. The effect of the towing speed, beyond the clear incidenceon the area actually swept, point to the complexity of the relationship between speed and catch rates.In brief, the results showed that, when assessing historical databases, indices of relative abundance oftropical demersal resources can be improved by including mesh size and towing speed factors.
Is the Atlantic surface temperature a good proxy for forecasting
the recruitment of European eel in the Guadalquivir estuary? Progress in Oceanography, 130, 112-124 (2015)
Juan Carlos Gutiérrez-Estrada, Inmaculada Pulido-Calvo
This study analysed the possibility of using the sea surface temperature (SST) of the Atlantic Ocean to predict the recruitment of European eels in one of the most important estuaries of the south of Europe. For this purpose, two different time series concerning glass eel in the Guadalquivir estuary (the first obtained from a set of fishery-independent experimental samplings in this estuary and the second from an unofficial database on commercial catches provided by one of the main local marketer-buyers) were standardised to obtain a single time series on a monthly scale. This series was correlated with a total of 368 SST time series for 368 sectors of 1.95º x 1.95º of the Atlantic Ocean covering the possible migration routes of adult eels and leptocephalous larvae. The significant sectors were clustered and selected as inputs for artificial neural network models (ANNs) with the objective of obtaining a model to forecast glass eel recruitment. Globally, the best result was given by an ANN with only 12 clusters as input variables and 35 neurons in the hidden layer. For this configuration, the explained variance in the test phase was slightly higher than 79%. These results were significantly better than those obtained with classical methods. The strong correlation between predicted and observed glass eel abundance suggests that: (a) there is a marked non-linear relationship between SST and glass eel recruitment in the Guadalquivir estuary; (b) SST is a good proxy for predicting glass eel recruitment and; (c) one of the main factors responsible for the changes in abundance of this species is changes in the ocean conditions.
Assisted management of water exchange in traditional semi-intensive aquaculture ponds. Computers and Electronics in Agriculture, 101, 128-134 (2014)
Inmaculada Pulido-Calvo, Juan Carlos GutiérrezEstrada, Estefanía Díaz Rubio, Ignacio de la Rosa
Grid gates with multiple sharp-crested rectangular orifices are used to control manually water discharge from branch channels to semi-intensive aquaculture ponds. Experimental and analytical analysis related to the discharge characteristics of these grid gates under submerged flow conditions have been presented in this paper with the objective to integrate the results in an support system to control the water exchange management. Experimental analysis was carried out in the laboratory using a scaled model. Steady-state hydraulic data were measured and collected for each tested grid gate considering different orifices number and flow rates. Multiple linear regression (MLR), factorial regression (FR), polynomial regression (PR), hybrid model (PR + FR) and generalized linear model (GLM) were evaluated to determine the relationship between the coefficient of discharge Cd and the non-dimensional parameters x=h2 1, b/h1and h3/h1 (x is the total cross section of discharge; h1 is the upstream water level of the grid gate; h3 is the downstream water level of the grid gate; and b is the width of the channel) which were obtained by the analysis dimensional. Of all these approaches, the best fits were obtained using a FR + PR hybrid model and a GLM model with only two non-dimensional parameters x=h2 1 and h3/h1 as independent variables. These models produced errors not higher than ±3%. The best GLM model and the aquaculturist knowledge in relation to the management of water exchange were integrated in a computer program namely ‘Gate management’ which was implemented in the ACUIGES system.
Deriving data mining and regression based water-salinity production functions for spring wheat (Triticum aestivum). Computers and Electronics in Agriculture, 101, 68-75 (2014)
Amir Haghverdi, Bijan Ghahraman, Brian G. Leib, Inmaculada Pulido Calvo, Mohammad Kaf, Kamran Davary, Behrang Ashorun
Production functions (PFs) are practical tools for not only irrigation scheduling but also in economic analysis as a mathematical relationship between relative grain yield and factors like evapotranspiration, irrigation water and salinity. This study was carried out in the Mashhad region of Iran during cropping years 2010 and 2011 to evaluate the performances of two data mining methods, decision tree and neural network, for deriving PFs of spring wheat under simultaneous drought and salinity stress compared with four well known regression-based PFs. The four well known PFs were: Jensen-PF (Jensen, 1968), MinhasPF (Minhas et al., 1974), modified Stewart-PF (Stewart et al., 1977; Stegman et al., 1980), and Nairizi-PF (Nairizi and Rydzewski, 1977). Heading and flowering were the most sensitive growth stages followed by the stem elongation and booting. Salinity stress also affected grain yield and therefore was an important parameter for deriving PFs. In general, all the PFs were in agreement concerning the sensitivity of spring wheat to water stress. The neural network-based PF performed the best with a root mean square error equal to 44.27 g m2 while the decision tree-based PF ranked fourth out of six in terms of accuracy. The most important advantage of the neural network-based PF was the flexible number of input parameters.
Spring drought prediction based on winter NAO and global SST in Portugal. Hydrological Processes, 28, 1009-2024 (2014)
João Filipe Santos, Maria Manuela Portela, Inmaculada Pulido Calvo
The aim of this paper is to test the ability of neural network approaches to hindcast the spring standardized precipitation index on a 6-month time scale (SPI6) in Portugal, based on winter large-scale climatic indices. For this purpose, the linkage of the spring SPI time series with the winter North Atlantic Oscillation (NAO) and the sea surface temperature (SST) was investigated by means of maps of the correlation coefficient for the period from October 1910 to September 2004. The results indicate that the winter NAO is a good predictor for the SPI6 of the spring (SPI6 finishing in April, May and June, SPI6April, SPI6May and SPI6June, respectively) for the northern, central and southern regions of Portugal. The winter SST1 (area of the Mediterranean Sea) must only be considered for the northern region, and the winter SST3 (area of the North Atlantic between Iberia and North America) only for the southern region. Spatial maps of predictive SPI6 for April, May and June were created and validated. The neural models explained more than 81% of the total variance for the SPI6April and SPI6May and more than 64% of the total variance for the SPI6June. Probability maps were also developed considering the values predicted by the neural methods for the spring months and all drought categories (moderate, severe and extreme). These maps indicating the probability of droughts can provide valuable support for the integrated planning and management of water resources throughout Portugal.
Dimensionality reduction in drought modelling. Hydrological Processes, 27, 1399-1410 (2013)
João Filipe Santos, Maria Manuela Portela, Inmaculada Pulido Calvo
For monitoring hydrological events characterized by high spatial and temporal variability, the number and location of recording stations must be carefully selected to ensure that the necessary information is collected. Depending on the characteristics of each natural process, certain stations may be spurious or redundant, whereas others may provide most of the relevant data. With the objective of reducing the costs of the monitoring system and, at the same time, improving its operational effectiveness, three procedures were applied to identify the minimum network of rain gauge stations able to capture the characteristics of droughts in mainland Portugal. Drought severity is characterized by the standardized precipitation index applied to the timescales of 1, 3, 6 and 12 consecutive months. The three techniques used to reduce the dimensionality of the network of rain gauges were as follows: (i) artificial neural networks with sensitivity analysis, (ii) application of the mutual information criterion and (iii) K-means cluster analysis using Euclidean distances. The results demonstrated that the best dimensionality reduction method was case dependent in the three regions of Portugal (northern, central and southern) previously identified by cluster analysis. All the reduction techniques lead to the selection of a subset of rain gauges capable of reproducing the original temporal patterns of drought. For specific severe drought events in Portugal in the past, the comparison between drought spatial patterns obtained with the original stations and the selected subset indicated that the subset produced statistically satisfactory results (correlation coefficients higher than 0.6 and efficiency coefficients higher than 0.5).
Consistency of fuzzy rules in an ecological context. Ecological Modelling, 251, 187-198 (2013)
Juan Carlos Gutiérrez Estrada, Inmaculada Pulido Calvo, David T. Bilton
In this paper, we assess the performance of fuzzy inference systems (FISs) and the consistency of fuzzy rules generated from a meta-analysis exploring diversity–environment relationships, in a system of temporary and fluctuating ponds located in two regions of southern England. The analyses focus on aquatic coleopteran assemblages, which act as excellent surrogates of wider freshwater macroinvertebrate diversity. Evaluated FISs were calibrated using evolutionary algorithms and the consistency of the rules examined using a consistency index specifically developed in this work. The best fit accounted for 76% of observed variability in the Shannon diversity index across ponds in the validation phase, which was 56 points better than the benchmark value established by a generalized additive model (GAM). The analysis of fuzzy rules indicated that the basic dynamics of this system are controlled by 8 rules. Another 10 complementary rules were detected, suggesting that more than a single dimension controlled the dynamics of the system. Therefore, water beetle diversity appears to be driven by a relatively short set of rules which relate diversity and environmentalfactors in a non-linear manner. These rules can be grouped according to their consistency levels, which reflect differences in coleopteran community composition.
2018
Sanz-Fernández, V., Gutiérrez-Estrada, J.C., Pulido-Calvo, I., Gil-Herrera, J., Benchoucha, S., el Arraf, S. Environment or catches? Assessment of the decline in blackspot seabream (Pagellus bogaraveo) abundance in the Strait of Gibraltar. Journal of Marine Systems, https://doi.org/10.1016/j.jmarsys.2018.08.005
Ballestrín, J., Monterreal, R., Carra, M.E., Fernández-Reche, J., Polo, J., Enrique, R., Rodríguez, J., Casanova, M., Barbero, F.J., Alonso-Montesinos, J., López, G., Bosch, J.L., Batlles, F.J., Marzo, A. Solar extinction measurement system based on digital cameras. Application to solar tower plants. Renewable Energy 125, 648-654.
López, G., Gueymard, C.A., Bosch, J.L., Rapp-Arrarás, I., Alonso-Montesinos, J., Pulido-Calvo, I., Ballestríne, J., Polo, J., Barbero, J. Modeling water vapor impacts on the solar irradiance reaching the receiver of a solar tower plant by means of artificial neural networks. Solar Energy 169, 34–39.
Fernández, M., , Alaejos, J., Andivia, E., Vázquez-Piqué, J., Ruiz, F., López, F., Tapias, R. Eucalyptus x urograndis biomass production for energy purposes exposed to a Mediterranean climate under different irrigation and fertilisation regimes. Biomass and Bioenergy, 111: 22-30.
2017
Gutiérrez-Estrada, J.C., Gil-Herrera, J., Pulido-Calvo, I., Czerwinski, I.A. Is it possible to differenciate between environmental and fishery effects on abundance-biomas variation? A case study of blackspot seabream (Pagellus bogaraveo) in the Strait of Gibraltar. Fisheries Oceanography, 26(4): 455-475.
León, I., García, J.J., Fernández, M., Vázquez-Piqué, J., Tapias,R. Differences in root growth of Quercus ilex and Quercus suber seedlings infected with Phytophthora cinnamomi. Silva Fennica, 51(4): 1-12.
2016
Madejon, P., Alaejos, J., García-Albala, J., Fernandez, M., Madejon, E. Three-year study of fast-growing trees in degraded soils amended with composts: Effects on soil fertility and productivity. Journal of Environmental Management, 169: 18-26.
2015
Manjarrés-Martínez, L.M., Gutiérrez-Estrada, J.C., Hernando-Casal, J.A. Effects of mesh size and towing speed on the multispecies catch rates of Historical swept area surveys. Fisheries Research, 164: 143-152.
Gutiérrez-Estrada, J.C., Pulido-Calvo, I. Is the Atlantic surface temperature a good proxy for forecasting the recruitment of European eel in the Guadalquivir Estuary? Progress in Oceanography, 130: 112-124.
Fernandez, M., García-Albala, J., Andivia, E., Alaejos, J., Tapias, R., Menendez, J. Sickle bush (Dichrostachys cinerea L.) field performance and physicalechemical property assessment for energy purposes. Biomass and Bioenergy, 81: 483-489.
2014
Pulido-Calvo, I., Gutiérrez-Estrada, J.C., Díaz-Rubio, E., De la Rosa, I. Assisted management of water exchange in traditional semi-intensive aquaculture ponds. Computers and Electronics in Agriculture, 101: 128-134.
2013
Gutiérrez-Estrada, J.C., Pulido-Calvo, I., Bilton, D.T. Consistency of fuzzy rules in an ecological context. Ecological Modelling, 251: 187-198.