Modelling fish habitat preference with a genetic algorithm-optimized Takagi-Sugeno model based on pairwise comparisons

Species-environment relationships are used for evaluating the current status of target species and the potential impact of natural or anthropogenic changes of their habitat. Recent researches reported that the results are strongly affected by the quality of a data set used. The present study attempted to apply pairwise comparisons to modelling fish habitat preference with Takagi-Sugeno-type fuzzy habitat preference models (FHPMs) optimized by a genetic algorithm (GA). The model was compared with the result obtained from the FHPM optimized based on mean squared error (MSE). Three independent data sets were used for training and testing of these models. The FHPMs based on pairwise comparison produced variable habitat preference curves from 20 different initial conditions in the GA. This could be partially ascribed to the optimization process and the regulations assigned. This case study demonstrates applicability and limitations of pairwise comparison-based optimization in an FHPM. Future research should focus on a more flexible learning process to make a good use of the advantages of pairwise comparisons

Flow management to control excessive growth of Macrophytes - An assessment based on habitat suitability modeling

Original ResearchMediterranean rivers in intensive agricultural watersheds usually display outgrowths of macrophytes – notably alien species – due to a combination of high concentrations of nutrients in the water runoff and low flows resulting from water abstraction for irrigation. Standard mechanical and chemical control is used to mitigate the problems associated with excessive growth of plant biomass: mainly less drainage capacity and higher flood risk. However, such control measures are cost and labor-intensive and do not present long-term efficiency. Although the high sensitivity of aquatic vegetation to instream hydraulic conditions is well known, management approaches based on flow management remain relatively unexplored. The aim of our study was therefore to apply physical habitat simulation techniques promoted by the Instream Flow Incremental Method (IFIM) to aquatic macrophytes – the first time it has been applied in this context – in order to model shifts in habitat suitability under different flow scenarios in the Sorraia river in central Portugal. We used this approach to test whether the risk of invasion and channel encroachment by nuisance species can be controlled by setting minimum annual flows. We used 960 randomly distributed survey points to analyze the habitat suitability for the most important aquatic species (including the invasive Brazilian milfoil Myriophyllum aquaticum, Sparganium erectum, and Potamogeton crispus) in regard to the physical parameters ‘flow velocity,’ ‘water depth,’ and ‘substrate size’. We chose the lowest discharge period of the year in order to assess the hydraulic conditions while disturbances were at a low-point, thus allowing aquatic vegetation establishment and subsistence. We then used the two-dimensional hydraulic River2D software to model the potential habitat availability for different flow conditions based on the site-specific habitat suitability index for each physical parameter and species. Our results show that the growth and distribution of macrophytes in the hydrologically stable vegetation period is primarily a function of the local physical instream condition. Using site-specific preference curves and a two-dimensional hydraulic model, it was possible to determine minimum annual flows that might prevent the excessive growth and channel encroachment caused by Myriophyllum aquaticuminfo:eu-repo/semantics/publishedVersio

Prediction of self-compacting concrete elastic modulus using two symbolic regression techniques

yesThis paper introduces a novel symbolic regression approach, namely biogeographical-based programming (BBP), for the prediction of elastic modulus of self-compacting concrete (SCC). The BBP model was constructed directly from a comprehensive dataset of experimental results of SCC available in the literature. For comparison purposes, another new symbolic regression model, namely artificial bee colony programming (ABCP), was also developed. Furthermore, several available formulas for predicting the elastic modulus of SCC were assessed using the collected database. The results show that the proposed BBP model provides slightly closer results to experiments than ABCP model and existing available formulas. A sensitivity analysis of BBP parameters also shows that the prediction by BBP model improves with the increase of habitat size, colony size and maximum tree depth. In addition, among all considered empirical and design code equations, Leemann and Hoffmann and ACI 318-08’s equations exhibit a reasonable performance but Persson and Felekoglu et al.’s equations are highly inaccurate for the prediction of SCC elastic modulus

Generalized additive models to predict adult and young brown trout (Salmo trutta Linnaeus, 1758) densities in Mediterranean rivers

Habitat suitability models (HSM) are concerned with the abundance or distribution of species as a consequence of interactions with the physical environment. Generalized Additive Models (GAMs) were used to model brown trout (Salmo trutta L.) density as a function of environmental variables at the scale of river reach and hydromorphological units (HMU) in the Jucar River Basin (Eastern Spain). After 4years of observations (2003-2006) the data representing trout density were split into two categories, young (<2years) and adult (2years), for modelling independently. The environmental descriptors at reach-scale described the geographical position, hydrological conditions, proportions and diversity of habitats. At the scale of HMUs (pool, glide, riffle or rapid), habitat descriptors representing dimensions, substrate, cover and velocity were used. The best and parsimonious GAM for each category was selected after a comprehensive trial of all possible combinations of input variables. The models explained 61% (adult) and 75% (young) of the variability of the data (R(2)adj). The results demonstrated the relevance of mean width, mean depth, cover index, mean velocity and slope for adult brown trout. Young trout densities were mainly related to maximum depths, cover index, mean velocity, elevation, average distance between rapids and number of slow water HMUs. This article shows the relevance of considering geographical and habitat-related requirements at different scales to describe the patterns of trout density. Furthermore, the importance of considering non-linear relationships with habitat variables was demonstrated. The results are useful for environmental managers to design effective and science-based restoration measures, and result in a more efficient management of brown trout populations.This study was partially funded by the Generalitat Valenciana (Conselleria de Territorio y Vivienda) and the Spanish Ministry of Economy and Competitiveness with the project SCARCE (Consolider-Ingenio 2010 CSD2009-00065). This work was also funded by the Universitat Politecnica de Valencia, through the project UPPTE/2012/294 (PAID-06-12). Authors also give thanks to the help of the Confederacion Hidrografica del Jucar (Gobierno de Espana), which provided environmental data, and to all colleagues who collaborated in the field data collection.Alcaraz-Hernández, JD.; Muñoz Mas, R.; Martinez-Capel, F.; Garófano-Gómez, V.; Vezza, P. (2016). Generalized additive models to predict adult and young brown trout (Salmo trutta Linnaeus, 1758) densities in Mediterranean rivers. Journal of Applied Ichthyology. 32(1):217-228. https://doi.org/10.1111/jai.13025S21722832

Generalized additive and fuzzy models in environmental flow assessment: A comparison employing the West Balkan trout (Salmo farioides; Karaman, 1938)

Human activities have altered flow regimes resulting in increased pressures and threats on river biota. Physical habitat simulation has been established as a standard approach among the methods for Environmental Flow Assessment (EFA). Traditionally, in EFA, univariate habitat suitability curves have been used to evaluate the habitat suitability at the microhabitat scale whereas Generalized Additive Models (GAMs) and fuzzy logic are considered the most common multivariate approaches to do so. The assessment of the habitat suitability for three size classes of the West Balkan trout (Salmo farioides; Karaman, 1938) inferred with these multivariate approaches was compared at three different levels. First the modelled patterns of habitat selection were compared by developing partial dependence plots. Then, the habitat assessment was spatially explicitly compared by calculating the fuzzy kappa statistic and finally, the habitat quantity and quality was compared broadly and at relevant flows under a hypothetical flow regulation, based on the Weighted Usable Area (WUA) vs. flow curves. The GAMs were slightly more accurate and the WUA-flow curves demonstrated that they were more optimistic in the habitat assessment with larger areas assessed with low to intermediate suitability (0.2 0.6). Nevertheless, both approaches coincided in the habitat assessment (the optimal areas were spatially coincident) and in the modelled patterns of habitat selection; large trout selected microhabitats with low flow velocity, large depth, coarse substrate and abundant cover. Medium sized trout selected microhabitats with low flow velocity, middle-to-large depth, any kind of substrate but bedrock and some elements of cover. Finally small trout selected microhabitats with low flow velocity, small depth, and light cover only avoiding bedrock substrate. Furthermore, both approaches also rendered similar WUA-flow curves and coincided in the predicted increases and decreases of the WUA under the hypothetical flow regulation. Although on an equal footing, GAMs performed slightly better, they do not automatically account for variables interactions. Conversely, fuzzy models do so and can be easily modified by experts to include new insights or to cover a wider range of environmental conditions. Therefore, as a consequence of the agreement between both approaches, we would advocate for combinations of GAMs and fuzzy models in fish-based EFA.This study was supported by the ECOFLOW project funded by the Hellenic General Secretariat of Research and Technology in the framework of the NSRF 2007-2013. We are grateful for field assistance of Dimitris Kommatas, Orfeas Triantafillou and Martin Palt and to Alcibiades N. Economou for assistance in discussions on trout biology and ecology.Muñoz Mas, R.; Papadaki, C.; Martinez-Capel, F.; Zogaris, S.; Ntoanidis, L.; Dimitriou, E. (2016). Generalized additive and fuzzy models in environmental flow assessment: A comparison employing the West Balkan trout (Salmo farioides; Karaman, 1938). Ecological Engineering. 91:365-377. doi:10.1016/j.ecoleng.2016.03.009S3653779

Random forests to evaluate interspecific interactions in fish distribution models

[EN] Previous research indicated that high predictive performance in species distribution modelling can be obtained by combining both biotic and abiotic habitat variables. However, models developed for fish often only address physical habitat characteristics, thus omitting potentially important biotic factors. Therefore, we assessed the impact of biotic variables on fish habitat preferences in four selected stretches of the upper Cabriel River (E Spain). The occurrence of Squalius pyrenaicus and Luciobarbus guiraonis was related to environmental variables describing biotic interactions (inferred by relationships among fish abundances) and channel hydro-morphological characteristics. Random Forests (RF) models were trained and then validated using independent datasets. To build RF models, the conditional variable importance was used together with the model improvement ratio technique. The procedure showed effectiveness in identifying a parsimonious set of not correlated variables, which minimize noise and improve model performance in both training and validation phases. Water depth, channel width, fine substrate and water-surface gradient were selected as most important habitat variables for both fish. Results showed clear habitat overlapping between fish species and suggest that competition is not a strong factor in the study area.This research has been developed in the framework of the HolRiverMed project (FP7-PEOPLE-2010-275577, Marie Curie Actions, Intra-European Fellowships) and the SCARCE project (Assessing and predicting effects on water quantity and quality in Iberian rivers caused by global change, Consolider-Ingenio 2010 CSD2009-00065). Data collection was partially funded by the Spanish Ministry of Environment, Rural and Marine Affairs, the Jucar River Basin District Authority and the Spanish Ministry of Education and Science (POTECOL, CGL2007-66412). We thank Juan Diego Alacaraz-Hernandez, Matias Peredo-Parada and Aina Hernandez-Mascarell for their help with field work and suggestions on data analysis.Vezza, P.; Muñoz Mas, R.; Martinez-Capel, F.; Mouton, A. (2015). Random forests to evaluate interspecific interactions in fish distribution models. Environmental Modelling and Software. 67:173-183. https://doi.org/10.1016/j.envsoft.2015.01.005S1731836

Application of Probabilistic Neural Networks to microhabitat suitability modelling for adult brown trout (Salmo trutta L.) in Iberian rivers

Probabilistic Neural Networks (PNN) have been tested for the first time in microhabitat suitability modelling for adult brown trout (Salmo trutta L.). The impact of data prevalence on PNN was studied. The PNN were evaluated in an independent river and the applicability of PNN to assess the environmental flow was analysed. Prevalence did not affect significantly the results. However PNN presented some limitations regarding the output range. Our results agreed previous studies because trout preferred deep microhabitats with medium-to-coarse substrate whereas velocity showed a wider suitable range. The 0.5 prevalence PNN showed similar classificatory capability than the 0.06 prevalence counterpart and the outputs covered the whole feasible range (from 0 to 1), but the 0.06 prevalence PNN showed higher generalisation because it performed better in the evaluation and it allowed a better modulation of the environmental flow. PNN has demonstrated to be a tool to be into consideration.The authors would like to thank the Spanish Ministry of Economy and Competitiveness for its financial support through the SCARCE project (Consolider-Ingenio 2010 CSD2009-00065). We are grateful to the colleagues who worked in the field and in the preliminary data analyses, especially Marta Bargay, Aina Hernandez and David Argibay. The works were partially funded by the Confederacion Hidrografica del Jucar (Spanish Ministry of Agriculture, Food and Environment), that also provided hydrological and environmental information about the study sites. The authors also thank the Direccion General del Agua and INFRAECO for the cession of the microhabitat data. Finally, we also thank Javier Ferrer, Teodoro Estrela and Onofre Gabaldo (Confederacion Hidrografica del Jucar) for their help and the data provided. Thanks to Grieg Davies for the academic review of English.Muñoz Mas, R.; Martinez-Capel, F.; Garófano-Gómez, V.; Mouton, A. (2014). Application of Probabilistic Neural Networks to microhabitat suitability modelling for adult brown trout (Salmo trutta L.) in Iberian rivers. Environmental Modelling and Software. 59:30-43. https://doi.org/10.1016/j.envsoft.2014.05.003S30435

Reliability-based topology optimization of bridge structures using first and second order reliability methods

Reliability-based topology optimization (RBTO) results in an optimal topology satisfying given constraints with consideration of uncertainties in the variables. Due to inherent uncertainties, including external loading, material properties, and the quality of construction, prototypes and products may not satisfy the essential functions required. In RBTO, each of these uncertain parameters are treated as random variables and reliability constraints are used in the formulation of the topology optimization problem to obtain a more reliable structure. In this article, RBTO was applied to obtain reliable topologies for two bridge structures using the Solid Isotropic Microstructure with Penalization (SIMP). The first and second order reliability methods are used as reliability analysis methods to take into account the uncertainties of the load, Young's modulus and thickness. It was found that in optimal topologies obtained by RBTO, the corresponding compliance values are higher than values obtained by deterministic topology optimization (DTO) and increase the number of uncertain parameters which results in softer structures with higher compliances

Progressive collapse analysis of offshore platforms

This thesis presents a study of the ultimate strength capacity of two offshore platforms located in the Gulf of Mexico. The objective of the study was to validate existing non-linear finite element models for estimating the loads and strength of offshore platforms.From August 24 to 26 1992, hurricane Andrew moved through the Gulf of Mexico with sustained winds of 140 miles per hour. Thirty-six major platforms suffered significant damage, of these, ten were completely toppled and twenty-six were leaning significantly or had significant topside damage.Structures "H" and "K" were bridge-connected platforms, located in the ST151 field of the South Timbalier area of the Gulf of Mexico, platform "H" collapsed during Andrew, while "K" survived undamaged. They were both designed, fabricated, and installed in the early 1960's.A push-over analysis, using the program USFOS was used to estimate the ultimate strength of the two structures in three direction: end-on, diagonal and broadside.In the first series of analyses, all the primary members such as legs, vertical and horizontal braces, piles, soil, conductors and deck structure were precisely defined with appropriate finite elements as well as secondary members such as conductors guides barge bumpers. In the second series of analyses it was assumed that there was no horizontal or vertical movements at the level of the mudmat. In the third series of analysis the model used in the first series of analysis was modified by increasing stiffness and resistance of the piles 10 times. Finally a fourth model was investigated in which the soil resistance of the mud-level horizontal members is modelled. (Abstract shortened by UMI.