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

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

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

Spatially explicit migration models of pike to support river management

De status van verschillende vissoorten in ons land, waaronder ook snoek (Esox lucius) voldoet niet aan de gestelde Europese vereisten. Behalve door een matige chemische waterkwaliteit komt dit voornamelijk door een ondermaatse habitatkwaliteit door habitatdegradatie, fragmentatie en obstructie. Rivierbeheerders plannen daarom maatregelen om het habitat te beschermen, te verbeteren of opnieuw toegankelijk te maken voor migrerende vissen. Habitatgeschiktheid- en soortverspreidingsmodellen kunnen helpen om het effect van deze maatregelen te voorspellen. Deze modellen zijn vaak niet in staat rekening te houden met factoren die gerelateerd zijn aan migratie en toegankelijkheid omdat ze niet ruimtelijk expliciet en dynamisch tegelijk zijn. In dit doctoraatsonderzoek evalueerden we de toepasbaarheid voor het simuleren van snoekmigratie van twee modelleertechnieken die wel geschikt lijken: Individueel Gebaseerde Modellen (IBMs) en Cellulaire Automaten (CAs). Daarnaast onderzochten we de migratiedynamiek, het habitatgebruik en de habitatpreferentie van volwassen snoeken ter ondersteuning van het rivierbeheer. Hiervoor werden veldgegevens verzameld van snoeken in de Ijzer (West-Vlaanderen) m.b.v. radiotelemetrie. De resultaten van dit onderzoek wijzen op een goede toepasbaarheid van IBMs en moeilijkheden bij het toepassen van de CAs voor de simulatie van snoekmigratie. De analyses van de veldgegevens tonen grote individuele verschillen in gedrag en onderlijnen het belang van habitatheterogeniteit en het toegankelijk maken van bestaande geschikte habitats voor volwassen snoeken. Dit onderzoek geeft meer inzicht in het ruimtelijk expliciet simuleren van snoekmigratie en levert kennis over de ecologie van snoek met directe suggesties voor rivierbeheerders

Epidemiology and control strategies applied to ash dieback and chestnut ink disease

Main goal of forest diseases’ management is to reduce economic, biological and aesthetic damages and biodiversity loss caused by plant parasites. The many strategies used can be grouped under two main actions, prevention (prophylaxis in some early writings) and therapy (treatment or cure). Prevention is limited primarily by the lack of knowledge of the organisms involved, including host plants. Mathematical models have been used to extend the understanding of plant disease epidemiology on a number of fronts, providing an opportunity for a more rational use of resources on expensive field trials and representing a step towards more sustainable control measures. From a curative point of view, current efforts by scientists have focused on developing diseases management (Pest Management = PM) concepts in order to balance the benefits of pesticides with the ecological concerns of their residues contaminating the environment. In this thesis, the two PM principles were applied from an innovative point of view on two case studies: ash dieback caused by Hymenoscyphus fraxineus, which can be considered the most serious disease for Fraxinus genus in Europe, and chestnut ink disease, caused by Phytophthora cambivora and P. cinnamomi. In the first part of the thesis, the two diseases are introduced, in order to permit the evaluation of similarities and differences (chapter I). Subsequently, from chapter II to chapter V, the experimental trials performed are described. In particular, in chapter II a study of the ecological niche of H. fraxineus, with the characterization of the environmental variables associated with naturally infected zones, is reported. This procedure was realized with Species Distribution Models (SDM), widely utilized in the ecological field and only recently applied to plant pathology. The presence of the pathogen was highly correlated to three summer predictors: abundant precipitation, high soil moisture and low air temperature, in comparison with the averages of the study area. The ensemble forecasting technique was then applied to obtain a prediction of the potential distribution of the pathogen at European scale, considering the distribution maps of Fraxinus excelsior and Fraxinus angustifolia, susceptible to the parasite. At last, an innovative method of network analysis permitted to identify the suitable areas that are not reachable by the pathogen with a natural spread. Chapter III reports a study conducted to evaluate six fungicides for their potential to control ash dieback. Initially, in vitro tests of the active ingredients against five different strains of the pathogen indicated thiabendazole, propiconazole and allicin as the most effective fungicides, with lower median lethal doses than procloraz. In contrast, copper sulphate and potassium phosphite were totally ineffective. Subsequently, the antifungal activities of the best three compounds were investigated in planta against H. fraxineus by trunk injection on European ashes inoculated with an indigenous strain. The test was preceded by preliminary trials to maximize the efficacy of injections; in the experimental conditions highest speed was reached with the addition of 1.2 % acetic acid to the aqueous solution and making treatments in early morning or late afternoon. Considering the results of in planta trial, thiabendazole and allicin significantly slowed down the growth of the necroses in the growing season, in contrast propiconazole injections were impracticable. The studies in chapters IV and V recall the methodologies applied to ash dieback, with application to chestnut ink disease complex. In particular, in chapter IV fuzzy logic theory was applied considering the environmental variables, such as minimum winter temperature, summer drought, slope's aspect, streams' distance and soil's permeability, that mainly can influence the development of the disease. The model was validated with a broad field survey conducted in a chestnut area in Treviso province. Moreover, uncertainty maps (regarding model structure, inputs and parameters) were produced for the correct interpretation of the prediction. Great part of the chestnut area in the study zone resulted as suitable for the development of ink disease, whereas only the 18.8 %, corresponding to higher elevation zones, presented inferior risks. In a second study (chapter V), a comparative efficacy trial on four potassium phosphite formulations by means of endotherapy against chestnut ink disease is performed. P. cinnamomi was isolated with baiting technique from symptomatic chestnuts and was inoculated on 50 asymptomatic trees. As a result of endotherapic treatments, the unique solution that significantly slowed down necroses' growth was potassium phosphite (35 %) with an addition of 0.1 % micronutrient solution. An additional endotherapic trial was conducted in a preliminary way in the chestnut where P. cinnamomi was isolated, with the main aim to evaluate growth stimulation of active growing callus next to the shape flame necroses by the injected solution of potassium phosphite 70 %. In this case, results did not highlight a significant difference between treated trees and water control ones, probably for the need of longer times for older trees. On the base of the achieved results, epidemiological modelling and endotherapic treatments, applied both to ash dieback and chestnut ink disease, can represent fundamental tools in the management of these important diseases and should be applied in an Integrated Pest Management (IPM) approach, together with appropriate cultural techniques to maximize benefits