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

Shifts in the suitable habitat available for brown trout (Salmo trutta L.) under short-term climate change scenarios

The impact of climate change on the habitat suitability for large brown trout (Salmo trutta L.) was studied in a segment of the Cabriel River (Iberian Peninsula). The future flow and water temperature patterns were simulated at a daily time step with M5 models' trees (NSE of 0.78 and 0.97 respectively) for two short-term scenarios (2011 2040) under the representative concentration pathways (RCP 4.5 and 8.5). An ensemble of five strongly regularized machine learning techniques (generalized additive models, multilayer perceptron ensembles, random forests, support vector machines and fuzzy rule base systems) was used to model the microhabitat suitability (depth, velocity and substrate) during summertime and to evaluate several flows simulated with River2D©. The simulated flow rate and water temperature were combined with the microhabitat assessment to infer bivariate habitat duration curves (BHDCs) under historical conditions and climate change scenarios using either the weighted usable area (WUA) or the Boolean-based suitable area (SA). The forecasts for both scenarios jointly predicted a significant reduction in the flow rate and an increase in water temperature (mean rate of change of ca. −25% and +4% respectively). The five techniques converged on the modelled suitability and habitat preferences; large brown trout selected relatively high flow velocity, large depth and coarse substrate. However, the model developed with support vector machines presented a significantly trimmed output range (max.: 0.38), and thus its predictions were banned from the WUA-based analyses. The BHDCs based on the WUA and the SA broadly matched, indicating an increase in the number of days with less suitable habitat available (WUA and SA) and/or with higher water temperature (trout will endure impoverished environmental conditions ca. 82% of the days). Finally, our results suggested the potential extirpation of the species from the study site during short time spans.The study has been partially funded by the IMPADAPT project (CGL2013-48424-C2-1-R) - Spanish MINECO (Ministerio de Economia y Competitividad) - and FEDER funds and by the Confederacion Hidrografica del Jucar (Spanish Ministry of Agriculture, Food and Environment). We are grateful to the colleagues who worked in the field and in the preliminary data analyses, especially Juan Diego Alcaraz-Henandez, David Argibay, Aina Hernandez and Marta Bargay. Thanks to Matthew J. Cashman for the academic review of English. Finally, the authors would also to thank the Direccion General del Agua and INFRAECO for the cession of the trout data. The authors thank AEMET and UC by the data provided for this work (dataset Spain02).Muñoz Mas, R.; López Nicolás, AF.; Martinez-Capel, F.; Pulido-Velazquez, M. (2016). Shifts in the suitable habitat available for brown trout (Salmo trutta L.) under short-term climate change scenarios. Science of the Total Environment. 544:686-700. https://doi.org/10.1016/j.scitotenv.2015.11.14768670054

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

Revisiting probabilistic neural networks: a comparative study with support vector machines and the microhabitat suitability for the Eastern Iberian chub (Squalius valentinus)

[EN] Probabilistic Neural Networks (PNNs) and Support Vector Machines (SVMs) are flexible classification techniques suited to render trustworthy species distribution and habitat suitability models. Although several alternatives to improve PNNs¿ reliability and performance and/or to reduce computational costs exist, PNNs are currently not well recognised as SVMs because the SVMs were compared with standard PNNs. To rule out this idea, the microhabitat suitability for the Eastern Iberian chub (Squalius valentinus Doadrio & Carmona, 2006) was modelled with SVMs and four types of PNNs (homoscedastic, heteroscedastic, cluster and enhanced PNNs); all of them optimised with differential evolution. The fitness function and several performance criteria (correctly classified instances, true skill statistic, specificity and sensitivity) and partial dependence plots were used to assess respectively the performance and reliability of each habitat suitability model. Heteroscedastic and enhanced PNNs achieved the highest performance in every index but specificity. However, these two PNNs rendered ecologically unreliable partial dependence plots. Conversely, homoscedastic and cluster PNNs rendered ecologically reliable partial dependence plots. Thus, Eastern Iberian chub proved to be a eurytopic species, presenting the highest suitability in microhabitats with cover present, low flow velocity (approx. 0.3 m/s), intermediate depth (approx. 0.6 m) and fine gravel (64¿256 mm). PNNs outperformed SVMs; thus, based on the results of the cluster PNN, which also showed high values of the performance criteria, we would advocate a combination of approaches (e.g., cluster & heteroscedastic or cluster & enhanced PNNs) to balance the trade-off between accuracy and reliability of habitat suitability models.The study has been partially funded by the national Research project IMPADAPT (CGL2013-48424-C2-1-R) with MINECO (Spanish Ministry of Economy) and Feder funds and by the Confederacion Hidrografica del Near (Spanish Ministry of Agriculture and Fisheries, Food and Environment). This study was also supported in part by the University Research Administration Center of the Tokyo University of Agriculture and Technology. Thanks to Maria Jose Felipe for reviewing the mathematical notation and to the two anonymous reviewers who helped to improve the manuscript.Muñoz Mas, R.; Fukuda, S.; Portolés, J.; Martinez-Capel, F. (2018). Revisiting probabilistic neural networks: a comparative study with support vector machines and the microhabitat suitability for the Eastern Iberian chub (Squalius valentinus). Ecological Informatics. 43:24-37. https://doi.org/10.1016/J.ECOINF.2017.10.008S24374

Comparison of approaches for the development of microhabitat suitability models based on fuzzy logic

[ES] La trucha comun (Salmo trutta L.) ha sido utilizada como indicador del estado ecológico. Los modelos de hábitat evaluan la idoneidad del hábitat en base a las condiciones físicas como por ejemplo la velocidad del flujo o el calado. Existen diversas metodologías para analizar la idoneidad y desarrollar modelos de idoneidad del hábitat no obstante el desarrollo de Curvas univariantes de Idoneidad del Hábitat (en terminología inglesa, HSCs) ha sido, de lejos, la metodología más habitual. Existen dos metodologías principales en el desarrollo de las HSCs. El primero considera solamente las condiciones observadas en los lugares donde aparecieron los peces (HSCs de Categoría II ½) mientras que la segunda también considera las condiciones observadas en el área circundante (HSCs de Categoría III). Diversos autores han sugerido que considerar las variables hidráulicas de forma independiente puede ser cuestionable. Por lo tanto el uso de metodologías multivariantes entre los investigadores se ha ido incrementado. Entre estas la lógica difusa es una de las que más veces ha sido aplicada exitosamente. La lógica difusa imita la forma de pensamiento humana, así usa una secuencia SI-ENTONCES. Si ciertas condiciones se dan entonces la idoneidad del hábitat es esta. Principalmente existen dos metodologías en el desarrollo de modelos de lógica difusa El basado en conocimiento de expertos (en terminología inglesa, Expert-knowledge) y el basado en datos (en terminología inglesa, Data-driven). El Expert-knowledge se basa en referencias bibliográficas y el consenso entre científicos mientras que el segundo es basa en la optimización de los elementos que componen el modelo en base a datos de campo. Este trabajo presenta una metodología para el desarrollo de modelos de lógica difusa Expert-knowledge basados en HSCs comparando los resultados con aquellos obtenidos mediente la metodología Data-driven. Específicamente tres modelos fueron desarrollados para las tres clases de talla consideradas, trucha común adulta-grande (> 20 cm), juvenil-median (20 - 10 cm) y alevín-pequeña (< 10 cm). Dos de los modelas se basaron en la metodología de Expert-knowledge pero diferían en las HSCs de base, un se basó en HSCs de Categoría II ½ y el otro en las de Categoria III, el modelo restante utilizó lametodología de Data-driven. Los 9 modelos desarrollados fueron validados de forma espacialmente explícita en un tramo de rio independiente y su desempeño fue comparado por medio del estadístico Kappa difuso (en terminología inglesa, fuzzy Kappa) La metodología de Expert-knowledge presentada en este trabajo ha devenido satisfactoria. Mostró un buen desempeño y no difirió substancialmente en comparación con la Data-driven a pesar del hecho que los modelos de Expert-knowledge basados en las HSCs de Categoría II ½ subestimaron la idoneidad en las zonas profundas para adultos y juveniles. Los modelos basados en las HSCs de Categoría III presentaron mejor desempeño que sus contrapartidas basadas en las HSCs de Categoría II ½ en el caso de los adultos y los alevines por lo que se recomendaron per a ulteriores análisis. No obstante los modelos de Expert-knowledge presentaron menor especificidad en comparación con los Data-driven. Por esta razón en el caso de los juveniles el modelo Data-driven fue el recomendado para futuros análisis. La comparativa entre modelos basada en el estadístico fuzzy Kappa no mostró similitudes entre modelos y la validación espacial se demostró fundamental en la selección del modelo más adecuado entre los modelos desarrollados.[EN] Brown trout (Salmo trutta L.) have been used as an indicator of ecological status. Habitat models assess habitat suitability based on physical conditions such flow velocity or water depth are. There are several methodologies to analyse the suitability and to develop habitat suitability models but, at the microscale, the development of continuous univariate Habitat Suitability Curves (HSCs) is by far the most common approach. Two main methodologies exist in the development of HSCs. The first one considers only the conditions observed at the fish locations (Category II ½ HSCs) whereas the second one considers also the conditions observed in the surrounding area (Category III HSCs) Several authors have suggested that considering each hydraulic variable independently may be questionable. Therefore the use of multivariate approaches among researches have increased. The Fuzzy logic is one of those who has most successfully been applied. The fuzzy logic approach mimics the human reasoning thus are presented in an IF-THEN sequence. If certain conditions are resent then the habitat suitability is that. There are two main approaches in the development of Fuzzy logic models; the Expert-knowledge and the Data-driven. The Expert-knowledge approach is based on the literature and the consensus of scientists whereas the Data-driven approach is based on the optimization of the elements of the model based on field data. This study presented a methodology to develop Expert-knowledge fuzzy models based on HSCs and compared the results with those derived from the Data-driven approach. Specifically Three habitat suitability models were develop for the three considered size classes; brown trout adult-large (> 20 cm), juvenile-medium (20 - 10 cm) and fry-small (< 10 cm). Two models based on the Expert-knowledge approach but differing on the HSCs, Category II ½ HSCs or Category III HSCs and another model was based on the Data-driven approach. The 9 developed models were spatially explicitly validated in an independent river reach and their performance was compared by means of the fuzzy Kappa statistic. The Expert-knowledge approach herein presented have demonstrated satisfactory. It showed generally a good performance and did not differed substantially in comparison with the Data-driven approach despite the Expert-knowledge models based on Category II ½ HSCs underrated the deep areas in the adult and juvenile. The Category III based models presented better performances that the Category II ½ counterparts and the models for adult and fry were recommended for further analysis. However the Expert-knowledge models presented lower specificity in comparison with the Data-driven approach. Then, in the juvenile case the Data-driven fuzzy model was de recommended for further analysis. The comparison between models based on the fuzzy Kappa did not showed any similarity and the spatially explicit validation have been demonstrated fundamental in the proper selection between the developed models.Muñoz Mas, R. (2013). Comparison of approaches for the development of microhabitat suitability models based on fuzzy logic. http://hdl.handle.net/10251/37128Archivo delegad

Microhabitat competition between Iberian fish species and the endangered Júcar nase (Parachondrostoma arrigonis; Steindachner, 1866)

"This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Ecohydraulics on 24-01-2017, available online: https://www.tandfonline.com/doi/full/10.1080/24705357.2016.1276417"[EN] Competition with invasive species is recognized as having a major impact on biodiversity conservation. The upper part of the Cabriel River (Eastern Iberian Peninsula) harbours the most important population of the Júcar nase (Parachondrostoma arrigonis; Steindachner, 1866), a fish species in imminent danger of extinction. Currently, this species cohabits with several non-native species, such as the Iberian nase (Pseudochondrostoma polylepis; Steindachner, 1864) and the bermejuela (Achondrostoma arcasii; Steindachner, 1866). The potential habitat competition with these species was studied by analysing the spatial and temporal overlapping of suitable microhabitats. Generalized Additive Mixed Models (GAMMs) were developed to model microhabitat selection and these GAMMs were used to assess the habitat suitability (i.e. probability of presence) under several flows simulated with River2D. The Júcar nase will compete, spatially and temporally, for the few suitable microhabitats with bermejuela and, to a lesser extent, with small Iberian nase; conversely, large Iberian nase was of minor concern, due to increased differences in habitat preferences. This study represents an important assessment of potential competition and, therefore, these results might assist to better define future management practices in the upper part of the Cabriel River.This study was funded by the Spanish Ministry of Economy and Competitiveness through the SCARCE project (Consolider Ingenio 2010 CSD2009 00065); the Universitat Politècnica de València, through the project UPPTE/2012/294 [PAID 06 12]; it was also partially funded by the IMPADAPT project (CGL2013-48424-C2-1-R) with Spanish MINECO (Ministerio de Economía y Competitividad) and FEDER funds. The authors would like to thank the help of the Conselleria de Territori i Vivenda (Generalitat Valenciana) and the Confederación Hidrográfica del Júcar (Spanish government), which provided environmental data to Alfredo Ollero, and the two anonymous reviewers who first suggested the submission of the paper to a regular journal. 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M., Alcaraz-Hernández, J. D., De Baets, B., Goethals, P. L. M., & Martínez-Capel, F. (2011). Data-driven fuzzy habitat suitability models for brown trout in Spanish Mediterranean rivers. Environmental Modelling & Software, 26(5), 615-622. doi:10.1016/j.envsoft.2010.12.001Mouton, A. M., De Baets, B., & Goethals, P. L. M. (2010). Ecological relevance of performance criteria for species distribution models. Ecological Modelling, 221(16), 1995-2002. doi:10.1016/j.ecolmodel.2010.04.017Muñoz-Mas, R., Fukuda, S., Vezza, P., & Martínez-Capel, F. (2016). Comparing four methods for decision-tree induction: A case study on the invasive Iberian gudgeon ( Gobio lozanoi ; Doadrio and Madeira, 2004). Ecological Informatics, 34, 22-34. doi:10.1016/j.ecoinf.2016.04.011Muñoz-Mas, R., Lopez-Nicolas, A., Martínez-Capel, F., & Pulido-Velazquez, M. (2016). Shifts in the suitable habitat available for brown trout (Salmo trutta L.) under short-term climate change scenarios. Science of The Total Environment, 544, 686-700. doi:10.1016/j.scitotenv.2015.11.147Muñoz-Mas, R., Martínez-Capel, F., Garófano-Gómez, V., & Mouton, A. M. (2014). Application of Probabilistic Neural Networks to microhabitat suitability modelling for adult brown trout (Salmo trutta L.) in Iberian rivers. Environmental Modelling & Software, 59, 30-43. doi:10.1016/j.envsoft.2014.05.003Muñoz-Mas, R., Martínez-Capel, F., Schneider, M., & Mouton, A. M. (2012). Assessment of brown trout habitat suitability in the Jucar River Basin (SPAIN): Comparison of data-driven approaches with fuzzy-logic models and univariate suitability curves. Science of The Total Environment, 440, 123-131. doi:10.1016/j.scitotenv.2012.07.074Muñoz-Mas, R., Papadaki, C., Martínez-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). 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Risk of invasion predicted with support vector machines: A case study on northern pike (Esox Lucius, L.) and bleak (Alburnus alburnus, L.)

The impacts of invasive species are recognised as a major threat to global freshwater biodiversity. The risk of invasion (probability of presence) of two avowed invasive species, the northern pike (Esox Lucius, L.) and bleak (Alburnus alburnus, L.), was evaluated in the upper part of the Cabriel River (eastern Iberian Peninsula). Habitat suitability models for these invasive species were developed with Support Vector Machines (SVMs), which were trained with data collected downstream the Contreras dam (the last barrier impeding the invasion of the upper river segment). Although SVMs gained visibility in habitat suitability modelling, they cannot be considered widespread in ecology. Thus, with this technique, there is certain controversy about the necessity of performing variable selection procedures. In this study, the parameters tuning and the variable selection for the SVMs was simultaneously performed with a genetic algorithm and, contradicting previous studies in freshwater ecology, the variable selection proved necessary to achieve almost perfect accuracy. Further, the development of partial dependence plots allowed unveiling the relationship between the selected input variables and the probability of presence. Results revealed the preference of northern pike for large and wide mesohabitats with vegetated shores and abundant prey whereas bleak preferred deep and slightly fast flow mesohabitats with fine substrate. Both species proved able to colonize the upper part of the Cabriel River but the habitat suitability for bleak indicated a slightly higher risk of invasion. Altogether may threaten the endemic species that actually inhabit that stretch, especially the Jucar nase (Parachondrostoma arrigonis; Steindachner), which is one of the most critically endangered Iberian freshwater fish species. (C) 2016 Elsevier B.V. All rights reserved.The study has been partially funded by the IMPADAPT project (CGL2013-48424-C2-1-R) with Spanish MINECO (Ministerio de Economia y Competitividad) and by the Confederacion Hidrografica del Jucar (Spanish Ministry of Agriculture, Food and Environment). We also want to thank all the colleagues who worked in the field data collection, especially Rui M. S. Costa and Aina Hernandez. Finally, we are especially grateful to Esther Lopez Fernandez who kindly and selflessly posed for the graphical abstract.Muñoz Mas, R.; Vezza, P.; Alcaraz-Hernández, JD.; Martinez-Capel, F. (2016). Risk of invasion predicted with support vector machines: A case study on northern pike (Esox Lucius, L.) and bleak (Alburnus alburnus, L.). Ecological Modelling. 342:123-134. https://doi.org/10.1016/j.ecolmodel.2016.10.006S12313434

Tree-based ensembles unveil the microhabitat suitability for the invasive bleak (Alburnus alburnus L.) and pumpkinseed (Lepomis gibbosus L.): Introducing XGBoost to eco-informatics

[EN] Random Forests (RFs) and Gradient Boosting Machines (GBMs) are popular approaches for habitat suitability modelling in environmental flow assessment. However, both present some limitations theoretically solved by alternative tree-based ensemble techniques (e.g. conditional RFs or oblique RFs). Among them, eXtreme Gradient Boosting machines (XGBoost) has proven to be another promising technique that mixes subroutines developed for RFs and GBMs. To inspect the capabilities of these alternative techniques, RFs and GBMs were compared with: conditional RFs, oblique RFs and XGBoost by modelling, at the micro-scale, the habitat suitability for the invasive bleak (Alburnus alburnus L.) and pumpkinseed (Lepomis gibbosus L). XGBoost outperformed the other approaches, particularly conditional and oblique RFs, although there were no statistical differences with standard RFs and GBMs. The partial dependence plots highlighted the lacustrine origins of pumpkinseed and the preference for lentic habitats of bleak. However, the latter depicted a larger tolerance for rapid microhabitats found in run-type river segments, which is likely to hinder the management of flow regimes to control its invasion. The difference in the computational burden and, especially, the characteristics of datasets on microhabitat use (low data prevalence and high overlapping between categories) led us to conclude that, in the short term, XGBoost is not destined to replace properly optimised RFs and GBMs in the process of habitat suitability modelling at the micro-scale.This project had the support of Fundacion Biodiversidad, of Spanish Ministry for Ecological Transition. We want to thank the volunteering students of the Universitat Politecnica de Valencia, Marina de Miguel, Carlos A. Puig-Mengual, Cristina Barea, Rares Hugianu, and Pau Rodriguez. R. Munoz-Mas benefitted from a postdoctoral Juan de la Cierva fellowship from the Spanish Ministry of Science, Innovation and Universities (ref. FJCI-2016-30829). This research was supported by the Government of Catalonia (ref. 2017 SGR 548).Muñoz-Mas, R.; Gil-Martínez, E.; Oliva-Paterna, FJ.; Belda, E.; Martinez-Capel, F. (2019). Tree-based ensembles unveil the microhabitat suitability for the invasive bleak (Alburnus alburnus L.) and pumpkinseed (Lepomis gibbosus L.): Introducing XGBoost to eco-informatics. Ecological Informatics. 53:1-12. https://doi.org/10.1016/j.ecoinf.2019.100974S1125

On species distribution modelling, spatial scales and environmental flow assessment with Multi Layer Perceptron Ensembles: A case study on the redfin barbel (Barbus haasi; Mertens, 1925)

Inconsistent performance of Species Distribution Models (SDMs), which may depend on several factors such as the initial conditions or the applied modelling technique, is one of the greatest challenges in ecological modelling. To overcome this problem, ensemble modelling combines the forecasts of several individual models. A commonly applied ensemble modelling technique is the Multi Layer Perceptron (MLP) Ensemble, which was envisaged in the 1990s. However, despite its potential for ecological modelling, it has received little attention in the development of SDMs for freshwater fish. Although this approach originally included all the developed MLPs, Genetic Algorithms (GA) now allow selection of the optimal subset of MLPs and thus substantial improvement of model performance. In this study, MLP Ensembles were used to develop SDMs for the redfin barbel (Barbus haasi; Mertens, 1925) at two different spatial scales: the micro scale and the meso scale. Finally, the potential of the MLP Ensembles for environmental flow (e flow) assessment was tested by linking model results to hydraulic simulation. MLP Ensembles with a candidate selection based on GA outperformed the optimal single MLP or the ensemble of the whole set of MLPs. The micro scale model complemented previous studies, showing high suitability of relatively deep areas with coarse substrate and corroborating the need for cover and the rheophilic nature of the redfin barbel. The meso scale model highlighted the advantages of using cross scale variables, since elevation (a macro scale variable) was selected in the optimal model. Although the meso scale model also demonstrated that redfin barbel selects deep areas, it partially contradicted the micro scale model because velocity had a clearer positive effect on habitat suitability and redfin barbel showed a preference for fine substrate in the meso scale model. Although the meso scale model suggested an overall higher habitat suitability of the test site, this did not result in a notable higher minimum environmental flow. Our results demonstrate that MLP Ensembles are a promising tool in the development of SDMs for freshwater fish species and proficient in e flow assessment.This study was funded by the Spanish Ministry of Economy and Competitiveness with the projects SCARCE (Consolider-Ingenio 2010 CSD2009-00065). We thank to Confederacion Hidrografica del Jucar (Spanish Ministry of Agriculture, Food and Environment), especially to the Office for Water Planning and Teodoro Estrela for the data provided to develop the SDMs. Finally we would like to thank TECNOMA S.A. for the development of the hydraulic model in the Mijares River and all the people who participated in the field data collection.Muñoz Mas, R.; Martinez-Capel, F.; Alcaraz-Hernández, JD.; Mouton, A. (2017). On species distribution modelling, spatial scales and environmental flow assessment with Multi Layer Perceptron Ensembles: A case study on the redfin barbel (Barbus haasi; Mertens, 1925). Limnologica. 62. https://doi.org/10.1016/j.limno.2016.09.004S6

Desarrollo de modelos de idoneidad de hábitat para la trucha balcánica (Salmo fariodes, Karaman) y estimación de caudales ecológicos en ríos de montaña de Grecia

[EN] Esta investigación, enmarcada en el proyecto ECOFLOW (Grecia), está enfocada a la estimación de caudales ecológicos en ríos de Grecia. La alteración hidrológica y la degradación de los hábitats fluviales han sido escasamente estudiados en este país, y permanecen aún fuera de su legislación. En este trabajo se aplicó el enfoque de la simulación del hábitat físico, basado en simulación hidráulica y del hábitat. Por primera vez para la trucha balcánica occidental (Salmo fariodes, Karaman) adulta, se realizó un modelo de idoneidad del hábitat multivariante (a escala de microhábitat) mediante modelos generalizados aditivos (GAM). Dichos adultos escogían principalmente los microhábitats con escasa corriente, profundos y con abundante refugio. Un tramo del río Acheloos se escogió para la simulación del hábitat físico. La falta de hábitats con abundante refugio y las pozas poco desarrolladas no llegaron a aportar una idoneidad alta. Esta primera aplicación en Grecia remarca la necesidad de ampliar y extender los enfoques de caudales ecológicos basados en estudios científicos locales y regionales, basados en hidrología y en eco-hidráulica. Estos métodos suponen avances importantes y son relevantes para mejorar el estado ecológico de los ríos y para la aplicación de las actuales políticas europeas sobre el agua.Este estudio se enmarca dentro del proyecto ECOFLOW patrocinado por la Secretaría General Griega para la investigación y la Tecnología en el marco de NSRF 2007-2013.Papadaki, C.; Muñoz Mas, R.; Ntoanidis, L.; Martínez Capel, F.; Zogaris, S.; Dimitriou, E. (2015). Desarrollo de modelos de idoneidad de hábitat para la trucha balcánica (Salmo fariodes, Karaman) y estimación de caudales ecológicos en ríos de montaña de Grecia. Cuadernos de la Sociedad Española de Ciencias Forestales. (41):253-268. http://hdl.handle.net/10251/60208S2532684