Assessing the suitable habitat for reintroduction of brown trout (Salmo trutta forma fario) in a lowland river : a modeling approach

Huge efforts have been made during the past decades to improve the water quality and to restore the physical habitat of rivers and streams in western Europe. This has led to an improvement in biological water quality and an increase in fish stocks in many countries. However, several rheophilic fish species such as brown trout are still categorized as vulnerable in lowland streams in Flanders (Belgium). In order to support cost-efficient restoration programs, habitat suitability modeling can be used. In this study, we developed an ensemble of habitat suitability models using metaheuristic algorithms to explore the importance of a large number of environmental variables, including chemical, physical, and hydromorphological characteristics to determine the suitable habitat for reintroduction of brown trout in the Zwalm River basin (Flanders, Belgium), which is included in the Habitats Directive. Mean stream velocity, water temperature, hiding opportunities, and presence of pools or riffles were identified as the most important variables determining the habitat suitability. Brown trout mainly preferred streams with a relatively high mean reach stream velocity (0.2-1m/s), a low water temperature (7-15 degrees C), and the presence of pools. The ensemble of models indicated that most of the tributaries and headwaters were suitable for the species. Synthesis and applications. Our results indicate that this modeling approach can be used to support river management, not only for brown trout but also for other species in similar geographical regions. Specifically for the Zwalm River basin, future restoration of the physical habitat, removal of the remaining migration barriers and the development of suitable spawning grounds could promote the successful restoration of brown trout

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

Combining literature-based and data-driven fuzzy models to predict brown trout (salmo trutta l.) spawning habitat degradation induced by climate change

[EN] A fuzzy rule-based system combining empirical data on hydraulic preferences and literature information on temperature requirements was used to foresee the brown trout (Salmo trutta L.) spawning habitat degradation induced by climate change. The climatic scenarios for the Cabriel River (Eastern Iberian Peninsula) corresponded to two Representative Concentration Pathways (4.5 and 8.5) for the short (2011¿2040) and mid (2041¿2070) term horizons. The hydraulic and hydrologic modelling were undertaken with process-based numerical models (i.e., River2D© and HBV-light) while the water temperature was modelled by assembling the predictions of three machine learning techniques (M5, Multi-Adaptive Regression Splines and Support Vector Regression). The predicted rise in the water temperature will not be compensated by the more benign lower flows. Consequently, the suitable spawning habitat will be reduced between 15.4¿48.7%. The entire population shall suffer the effects of climate change and will probably be extirpated from the downstream segments of the river.The study has been partially funded by the IMPADAPT project (CGL2013-48424-C2-1-R) with Spanish MINECO (Ministerio de Economía y Competitividad) and FEDER funds and by the Confederación Hidrográfica del Júcar (Spanish Ministry of Agriculture, Food and Environment). The authors thank AEMET and UC for the data provided for this work (dataset Spain02). Finally, we are grateful to the colleagues who worked in the field and in preliminary data analyses; especially Marcello Minervini (funded by the EU programme of Erasmus Traineeships, at the Dept. of Hydraulic Engineering and Environment, Universitat Politècnica de València).Muñoz Mas, R.; Marcos-García, P.; Lopez-Nicolas, A.; Martínez-García, F.; Pulido-Velazquez, M.; Martinez-Capel, F. (2018). Combining literature-based and data-driven fuzzy models to predict brown trout (salmo trutta l.) spawning habitat degradation induced by climate change. Ecological Modelling. 386:98-114. https://doi.org/10.1016/j.ecolmodel.2018.08.012S9811438

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

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. Finally, we would like to thank TECNOMA S.A. for the development of the hydraulic model.Muñoz Mas, R.; Soares Costa, RM.; Alcaraz-Hernández, JD.; Martinez-Capel, F. (2017). Microhabitat competition between Iberian fish species and the endangered Júcar nase (Parachondrostoma arrigonis; Steindachner, 1866). Journal of Ecohydraulics. 2(1):3-15. https://doi.org/10.1080/24705357.2016.1276417S31521Alcaraz, C., Carmona-Catot, G., Risueño, P., Perea, S., Pérez, C., Doadrio, I., & Aparicio, E. (2014). Assessing population status of Parachondrostoma arrigonis (Steindachner, 1866), threats and conservation perspectives. Environmental Biology of Fishes, 98(1), 443-455. doi:10.1007/s10641-014-0274-3ALMEIDA, D., & GROSSMAN, G. D. (2012). Utility of direct observational methods for assessing competitive interactions between non-native and native freshwater fishes. Fisheries Management and Ecology, 19(2), 157-166. doi:10.1111/j.1365-2400.2012.00847.xAlmeida, D., Merino-Aguirre, R., Vilizzi, L., & Copp, G. H. (2014). Interspecific Aggressive Behaviour of Invasive Pumpkinseed Lepomis gibbosus in Iberian Fresh Waters. PLoS ONE, 9(2), e88038. doi:10.1371/journal.pone.0088038Anderson, D. R., Burnham, K. P., & Thompson, W. L. (2000). Null Hypothesis Testing: Problems, Prevalence, and an Alternative. The Journal of Wildlife Management, 64(4), 912. doi:10.2307/3803199Aparicio, E., Vargas, M. J., Olmo, J. M., & de Sostoa, A. (2000). Environmental Biology of Fishes, 59(1), 11-19. doi:10.1023/a:1007618517557Arlot, S., & Celisse, A. (2010). A survey of cross-validation procedures for model selection. Statistics Surveys, 4(0), 40-79. doi:10.1214/09-ss054Austin, M. (2007). Species distribution models and ecological theory: A critical assessment and some possible new approaches. Ecological Modelling, 200(1-2), 1-19. doi:10.1016/j.ecolmodel.2006.07.005Baltz, D. M., Vondracek, B., Brown, L. R., & Moyle, P. B. (1991). Seasonal Changes in Microhabitat Selection by Rainbow Trout in a Small Stream. Transactions of the American Fisheries Society, 120(2), 166-176. doi:10.1577/1548-8659(1991)1202.3.co;2Barbet-Massin, M., Jiguet, F., Albert, C. H., & Thuiller, W. (2012). Selecting pseudo-absences for species distribution models: how, where and how many? Methods in Ecology and Evolution, 3(2), 327-338. doi:10.1111/j.2041-210x.2011.00172.xBeakes, M. P., Moore, J. W., Retford, N., Brown, R., Merz, J. E., & Sogard, S. M. (2012). EVALUATING STATISTICAL APPROACHES TO QUANTIFYING JUVENILE CHINOOK SALMON HABITAT IN A REGULATED CALIFORNIA RIVER. River Research and Applications, 30(2), 180-191. doi:10.1002/rra.2632BROOK, B., SODHI, N., & BRADSHAW, C. (2008). Synergies among extinction drivers under global change. Trends in Ecology & Evolution, 23(8), 453-460. doi:10.1016/j.tree.2008.03.011Brosse, S., Laffaille, P., Gabas, S., & Lek, S. (2001). Is scuba sampling a relevant method to study fish microhabitat in lakes? Examples and comparisons for three European species. Ecology of Freshwater Fish, 10(3), 138-146. doi:10.1034/j.1600-0633.2001.100303.xCLAVERO, M. (2011). Assessing the risk of freshwater fish introductions into the Iberian Peninsula. Freshwater Biology, 56(10), 2145-2155. doi:10.1111/j.1365-2427.2011.02642.xCollares-Pereira, M. J., & Coelho, M. M. (1983). Biometrical analysis of Chondrostoma polylepis x Rutilus arcasi natural hybrids (Osteichthyes-Cypriniformes-Cyprinidae). Journal of Fish Biology, 23(5), 495-509. doi:10.1111/j.1095-8649.1983.tb02930.xCosta, R. M. S., Martínez-Capel, F., Muñoz-Mas, R., Alcaraz-Hernández, J. D., & Garófano-Gómez, V. (2011). HABITAT SUITABILITY MODELLING AT MESOHABITAT SCALE AND EFFECTS OF DAM OPERATION ON THE ENDANGERED JúCAR NASE, PARACHONDROSTOMA ARRIGONIS (RIVER CABRIEL, SPAIN). River Research and Applications, 28(6), 740-752. doi:10.1002/rra.1598Dal Pozzolo A, Caelen O, Bontempi G. 2015. unbalanced: Racing for unbalanced methods selection. R package version 2.0.Elith, J., & Leathwick, J. R. (2009). Species Distribution Models: Ecological Explanation and Prediction Across Space and Time. Annual Review of Ecology, Evolution, and Systematics, 40(1), 677-697. doi:10.1146/annurev.ecolsys.110308.120159Elvira, B., & Almodovar, A. (2001). Freshwater fish introductions in Spain: facts and figures at the beginning of the 21st century. Journal of Fish Biology, 59(sa), 323-331. doi:10.1111/j.1095-8649.2001.tb01393.xElvira, B., & Almodóvar, A. (2006). Threatened fishes of the world: Chondrostoma arrigonis (Steindachner, 1866) (Cyprinidae). Environmental Biology of Fishes, 81(1), 27-28. doi:10.1007/s10641-006-9172-7Friedman, J. H. (2001). machine. The Annals of Statistics, 29(5), 1189-1232. doi:10.1214/aos/1013203451Fukuda, S., De Baets, B., Waegeman, W., Verwaeren, J., & Mouton, A. M. (2013). Habitat prediction and knowledge extraction for spawning European grayling (Thymallus thymallus L.) using a broad range of species distribution models. Environmental Modelling & Software, 47, 1-6. doi:10.1016/j.envsoft.2013.04.005Girard, V., Monti, D., Valade, P., Lamouroux, N., Mallet, J.-P., & Grondin, H. (2013). HYDRAULIC PREFERENCES OF SHRIMPS AND FISHES IN TROPICAL INSULAR RIVERS. River Research and Applications, 30(6), 766-779. doi:10.1002/rra.2675Gozlan, R. E., Britton, J. R., Cowx, I., & Copp, G. H. (2010). Current knowledge on non-native freshwater fish introductions. Journal of Fish Biology, 76(4), 751-786. doi:10.1111/j.1095-8649.2010.02566.xGuay, J. C., Boisclair, D., Rioux, D., Leclerc, M., Lapointe, M., & Legendre, P. (2000). Development and validation of numerical habitat models for juveniles of Atlantic salmon (Salmo salar). Canadian Journal of Fisheries and Aquatic Sciences, 57(10), 2065-2075. doi:10.1139/f00-162Guisan, A., Graham, C. H., Elith, J., & Huettmann, F. (2007). Sensitivity of predictive species distribution models to change in grain size. Diversity and Distributions, 13(3), 332-340. doi:10.1111/j.1472-4642.2007.00342.xHeggenes, J., Brabrand, Åg., & Saltveit, S. (1990). Comparison of Three Methods for Studies of Stream Habitat Use by Young Brown Trout and Atlantic Salmon. Transactions of the American Fisheries Society, 119(1), 101-111. doi:10.1577/1548-8659(1990)1192.3.co;2Jowett, I. G., & Davey, A. J. H. (2007). A Comparison of Composite Habitat Suitability Indices and Generalized Additive Models of Invertebrate Abundance and Fish Presence–Habitat Availability. Transactions of the American Fisheries Society, 136(2), 428-444. doi:10.1577/t06-104.1Jowett, I. G., & Duncan, M. J. (2012). Effectiveness of 1D and 2D hydraulic models for instream habitat analysis in a braided river. Ecological Engineering, 48, 92-100. doi:10.1016/j.ecoleng.2011.06.036Laurikkala, J. (2001). Improving Identification of Difficult Small Classes by Balancing Class Distribution. Lecture Notes in Computer Science, 63-66. doi:10.1007/3-540-48229-6_9Leunda, P. (2010). Impacts of non-native fishes on Iberian freshwater ichthyofauna: current knowledge and gaps. Aquatic Invasions, 5(3), 239-262. doi:10.3391/ai.2010.5.3.03Lin, X., & Zhang, D. (1999). Inference in generalized additive mixed modelsby using smoothing splines. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 61(2), 381-400. doi:10.1111/1467-9868.00183Liu, C., Berry, P. M., Dawson, T. P., & Pearson, R. G. (2005). Selecting thresholds of occurrence in the prediction of species distributions. Ecography, 28(3), 385-393. doi:10.1111/j.0906-7590.2005.03957.xMaceda-Veiga, A. (2012). Towards the conservation of freshwater fish: Iberian Rivers as an example of threats and management practices. Reviews in Fish Biology and Fisheries, 23(1), 1-22. doi:10.1007/s11160-012-9275-5Maggini, R., Lehmann, A., Zimmermann, N. E., & Guisan, A. (2006). Improving generalized regression analysis for the spatial prediction of forest communities. Journal of Biogeography, 33(10), 1729-1749. doi:10.1111/j.1365-2699.2006.01465.xMarr, S. M., Olden, J. D., Leprieur, F., Arismendi, I., Ćaleta, M., Morgan, D. L., … García-Berthou, E. (2013). A global assessment of freshwater fish introductions in mediterranean-climate regions. Hydrobiologia, 719(1), 317-329. doi:10.1007/s10750-013-1486-9MARTÍNEZ-CAPEL, F., GARCÍA DE JALÓN, D., WERENITZKY, D., BAEZA, D., & RODILLA-ALAMÁ, M. (2009). Microhabitat use by three endemic Iberian cyprinids in Mediterranean rivers (Tagus River Basin, Spain). Fisheries Management and Ecology, 16(1), 52-60. doi:10.1111/j.1365-2400.2008.00645.xMouton, A. 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). Ecological Engineering, 91, 365-377. doi:10.1016/j.ecoleng.2016.03.009Olaya-Marín, E. J., Martínez-Capel, F., Soares Costa, R. M., & Alcaraz-Hernández, J. D. (2012). Modelling native fish richness to evaluate the effects of hydromorphological changes and river restoration (Júcar River Basin, Spain). Science of The Total Environment, 440, 95-105. doi:10.1016/j.scitotenv.2012.07.093Paredes-Arquiola, J., Solera, A., Martinez-Capel, F., Momblanch, A., & Andreu, J. (2014). Integrating water management, habitat modelling and water quality at the basin scale and environmental flow assessment: case study of the Tormes River, Spain. Hydrological Sciences Journal, 59(3-4), 878-889. doi:10.1080/02626667.2013.821573Platts, P. J., McClean, C. J., Lovett, J. C., & Marchant, R. (2008). Predicting tree distributions in an East African biodiversity hotspot: model selection, data bias and envelope uncertainty. Ecological Modelling, 218(1-2), 121-134. doi:10.1016/j.ecolmodel.2008.06.028Reyjol, Y., Hugueny, B., Pont, D., Bianco, P. G., Beier, U., Caiola, N., … Virbickas, T. (2007). Patterns in species richness and endemism of European freshwater fish. Global Ecology and Biogeography, 16(1), 65-75. doi:10.1111/j.1466-8238.2006.00264.xRibeiro, F., Elvira, B., Collares-Pereira, M. J., & Moyle, P. B. (2007). Life-history traits of non-native fishes in Iberian watersheds across several invasion stages: a first approach. Biological Invasions, 10(1), 89-102. doi:10.1007/s10530-007-9112-2RIBEIRO, F., & LEUNDA, P. M. (2012). Non-native fish impacts on Mediterranean freshwater ecosystems: current knowledge and research needs. Fisheries Management and Ecology, 19(2), 142-156. doi:10.1111/j.1365-2400.2011.00842.xRincon, P. A., Correas, A. M., Morcillo, F., Risueno, P., & Lobon-Cervia, J. (2002). Interaction between the introduced eastern mosquitofish and two autochthonous Spanish toothcarps. Journal of Fish Biology, 61(6), 1560-1585. doi:10.1111/j.1095-8649.2002.tb02498.xRobalo, J. I., Almada, V. C., Levy, A., & Doadrio, I. (2007). Re-examination and phylogeny of the genus Chondrostoma based on mitochondrial and nuclear data and the definition of 5 new genera. Molecular Phylogenetics and Evolution, 42(2), 362-372. doi:10.1016/j.ympev.2006.07.003Romão, F., Quintella, B. R., Pereira, T. J., & Almeida, P. R. (2011). Swimming performance of two Iberian cyprinids: the Tagus nase Pseudochondrostoma polylepis (Steindachner, 1864) and the bordallo Squalius carolitertii (Doadrio, 1988). Journal of Applied Ichthyology, 28(1), 26-30. doi:10.1111/j.1439-0426.2011.01882.xShiroyama, R., & Yoshimura, C. (2016). Assessing bluegill (Lepomis macrochirus) habitat suitability using partial dependence function combined with classification approaches. Ecological Informatics, 35, 9-18. doi:10.1016/j.ecoinf.2016.06.005Thomas, J. A., & Bovee, K. D. (1993). Application and testing of a procedure to evaluate transferability of habitat suitability criteria. Regulated Rivers: Research & Management, 8(3), 285-294. doi:10.1002/rrr.3450080307Vezza, P., Muñoz-Mas, R., Martinez-Capel, F., & Mouton, A. (2015). Random forests to evaluate biotic interactions in fish distribution models. Environmental Modelling & Software, 67, 173-183. doi:10.1016/j.envsoft.2015.01.005Vilizzi, L., Copp, G. H., & Roussel, J.-M. (2004). Assessing variation in suitability curves and electivity profiles in temporal studies of fish habitat use. River Research and Applications, 20(5), 605-618. doi:10.1002/rra.767Wood, S. N. (2004). Stable and Efficient Multiple Smoothing Parameter Estimation for Generalized Additive Models. Journal of the American Statistical Association, 99(467), 673-686. doi:10.1198/016214504000000980Wood, S. N. (2006). Generalized Additive Models. doi:10.1201/9781420010404Zuur, A. F., Ieno, E. N., Walker, N., Saveliev, A. A., & Smith, G. M. (2009). Mixed effects models and extensions in ecology with R. Statistics for Biology and Health. doi:10.1007/978-0-387-87458-

Ecological models at fish community and species level to support effective river restoration

RESUMEN Los peces nativos son indicadores de la salud de los ecosistemas acuáticos, y se han convertido en un elemento de calidad clave para evaluar el estado ecológico de los ríos. La comprensión de los factores que afectan a las especies nativas de peces es importante para la gestión y conservación de los ecosistemas acuáticos. El objetivo general de esta tesis es analizar las relaciones entre variables biológicas y de hábitat (incluyendo la conectividad) a través de una variedad de escalas espaciales en los ríos Mediterráneos, con el desarrollo de herramientas de modelación para apoyar la toma de decisiones en la restauración de ríos. Esta tesis se compone de cuatro artículos. El primero tiene como objetivos modelar la relación entre un conjunto de variables ambientales y la riqueza de especies nativas (NFSR), y evaluar la eficacia de potenciales acciones de restauración para mejorar la NFSR en la cuenca del río Júcar. Para ello se aplicó un enfoque de modelación de red neuronal artificial (ANN), utilizando en la fase de entrenamiento el algoritmo Levenberg-Marquardt. Se aplicó el método de las derivadas parciales para determinar la importancia relativa de las variables ambientales. Según los resultados, el modelo de ANN combina variables que describen la calidad de ribera, la calidad del agua y el hábitat físico, y ayudó a identificar los principales factores que condicionan el patrón de distribución de la NFSR en los ríos Mediterráneos. En la segunda parte del estudio, el modelo fue utilizado para evaluar la eficacia de dos acciones de restauración en el río Júcar: la eliminación de dos azudes abandonados, con el consiguiente incremento de la proporción de corrientes. Estas simulaciones indican que la riqueza aumenta con el incremento de la longitud libre de barreras artificiales y la proporción del mesohabitat de corriente, y demostró la utilidad de las ANN como una poderosa herramienta para apoyar la toma de decisiones en el manejo y restauración ecológica de los ríos Mediterráneos. El segundo artículo tiene como objetivo determinar la importancia relativa de los dos principales factores que controlan la reducción de la riqueza de peces (NFSR), es decir, las interacciones entre las especies acuáticas, variables del hábitat (incluyendo la conectividad fluvial) y biológicas (incluidas las especies invasoras) en los ríos Júcar, Cabriel y Turia. Con este fin, tres modelos de ANN fueron analizados: el primero fue construido solamente con variables biológicas, el segundo se construyó únicamente con variables de hábitat y el tercero con la combinación de estos dos grupos de variables. Los resultados muestran que las variables de hábitat son los ¿drivers¿ más importantes para la distribución de NFSR, y demuestran la importancia ecológica de los modelos desarrollados. Los resultados de este estudio destacan la necesidad de proponer medidas de mitigación relacionadas con la mejora del hábitat (incluyendo la variabilidad de caudales en el río) como medida para conservar y restaurar los ríos Mediterráneos. El tercer artículo busca comparar la fiabilidad y relevancia ecológica de dos modelos predictivos de NFSR, basados en redes neuronales artificiales (ANN) y random forests (RF). La relevancia de las variables seleccionadas por cada modelo se evaluó a partir del conocimiento ecológico y apoyado por otras investigaciones. Los dos modelos fueron desarrollados utilizando validación cruzada k-fold y su desempeño fue evaluado a través de tres índices: el coeficiente de determinación (R2 ), el error cuadrático medio (MSE) y el coeficiente de determinación ajustado (R2 adj). Según los resultados, RF obtuvo el mejor desempeño en entrenamiento. Pero, el procedimiento de validación cruzada reveló que ambas técnicas generaron resultados similares (R2 = 68% para RF y R2 = 66% para ANN). La comparación de diferentes métodos de machine learning es muy útil para el análisis crítico de los resultados obtenidos a través de los modelos. El cuarto artículo tiene como objetivo evaluar la capacidad de las ANN para identificar los factores que afectan a la densidad y la presencia/ausencia de Luciobarbus guiraonis en la demarcación hidrográfica del Júcar. Se utilizó una red neuronal artificial multicapa de tipo feedforward (ANN) para representar relaciones no lineales entre descriptores de L. guiraonis con variables biológicas y de hábitat. El poder predictivo de los modelos se evaluó con base en el índice Kappa (k), la proporción de casos correctamente clasificados (CCI) y el área bajo la curva (AUC) característica operativa del receptor (ROC). La presencia/ausencia de L. guiraonis fue bien predicha por el modelo ANN (CCI = 87%, AUC = 0.85 y k = 0.66). La predicción de la densidad fue moderada (CCI = 62%, AUC = 0.71 y k = 0.43). Las variables más importantes que describen la presencia/ausencia fueron: radiación solar, área de drenaje y la proporción de especies exóticas de peces con un peso relativo del 27.8%, 24.53% y 13.60% respectivamente. En el modelo de densidad, las variables más importantes fueron el coeficiente de variación de los caudales medios anuales con una importancia relativa del 50.5% y la proporción de especies exóticas de peces con el 24.4%. Los modelos proporcionan información importante acerca de la relación de L. guiraonis con variables bióticas y de hábitat, este nuevo conocimiento podría utilizarse para apoyar futuros estudios y para contribuir en la toma de decisiones para la conservación y manejo de especies en los en los ríos Júcar, Cabriel y Turia.Olaya Marín, EJ. (2013). Ecological models at fish community and species level to support effective river restoration [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/28853TESI

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

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

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