Developments In Ecological Modeling Based On Cellular Automata

The models with focus on spatial clumping generally fail to consider the effects of local interactions and spatial contrasting. These factors are sometimes conclusive to the developments of ecosystems. Cellular Automata are individual potent systems in which many simple components act together locally to bring complex patterns, which may explain “self-organizing” behavior. Since cellular automaton has ability to consider local influences and spatial disparateness, it has been applied to various fields. This paper attempts to highlight important aspects of Cellular Automata and is centered on the development and application of the approach to ecological modeling. The results indicate that spatially distinct models such as cellular automata have a special capacity to connect the local operations and universal figures hence resulting in complex patterns. Keywords: Cellular automata, ecological modeling, spatially contrastin

Modeling the distribution of riverine vegetation in regulated rivers - from dynamic to static equilibrium

Doutoramento FLUVIO - River Restoration and Management / Instituto Superior de Agronomia / Faculdade de Arquitetura / Instituto Superior Técnico. Universidade de LisboaWhile methodological advances in ecosystem modeling reflect the growing recognition in the importance of accounting for dynamic change in river ecosystems, it is also recognized that various forms of regulation measures have completely disrupted its natural dynamics. In this context the underlying research question of this PhD is how river regulation affects the spatial distribution of riverine vegetation (aquatic and riparian) and whether rather simple static models that assume equilibrium between vegetation and environmental factors are adequate tools for its prediction. In a first step, we presented a systematic, quantitative literature review on models to predict the distribution of riverine vegetation on reach scale and identified research gaps to guide the further development of the thesis. Then, we developed and tested a habitat suitability model for aquatic vegetation based on hydrological variables. We concluded that during artificially stabilized (static) low flows the vegetation is in equilibrium with the physical instream condition and showed how the model can be used to define a flow threshold that reduces the risk of species invasion and proliferation. Further, we reconstructed the historic succession dynamics of a large river floodplain using a dynamic vegetation model and showed that typical regulation measures led to a steady progression of the vegetation communities toward mature phases without regression to younger stages. Finally, we applied different static and dynamic modeling approaches for the distribution of floodplain vegetation to the same study area and concluded from the comparison of their results that due to regulation measures the relevance of succession dynamics and disturbance stochasticity for the prediction of vegetation patterns is much reduced. Consequently, from a river manager ́s perspective, static models seem to be an adequate option for the modeling of the distribution of riverine vegetation in artificially stabilized environments since they show high accuracy, need relatively few resources (data, time, expert knowledge) when compared to dynamic models and are reproducibleN/

Exploring the key drivers of riparian woodland successional pathways across three European river reaches

"This is the peer reviewed version of the following article: Muñoz-Mas, R., V. Garófano-Gómez, I. Andrés-Doménech, D. Corenblit, G. Egger, F. Francés, M.T. Ferreira, et al. 2017. ¿Exploring the Key Drivers of Riparian Woodland Successional Pathways across Three European River Reaches.¿ Ecohydrology 10 (8). Wiley: e1888. doi:10.1002/eco.1888, which has been published in final form at https://doi.org/10.1002/eco.1888. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving."[EN] Climate change and river regulation are negatively impacting riparian vegetation. To evaluate these impacts, process-based models are preferred over data-driven approaches. However, they require extensive knowledge about ecohydrological processes. To facilitate the implementation of such process-based models, the key drivers of riparian woodland successional pathways across three river reaches, in Austria, Portugal, and Spain, were explored, employing two complementary approaches. The principal component analyses highlighted the importance of the physical gradients determining the placement of the succession phases within the riparian and floodplain zones. The generalized additive models revealed that the initial and pioneer succession phases, characteristic of the colonization stage, appeared in areas highly morphodynamic, close in height and distance to the water table, and with coarse substrate, whereas elder phases within the transitional and mature stages showed incremental differences, occupying less dynamic areas with finer substrate. The Austrian site fitted well the current successional theory (elder phases appearing sequentially further up and distant), but at the Portuguese site, the tolerance of the riparian species to drought and flash flood events governed their placement. Finally, at the Spanish site, the patchy distribution of the elder phases was the remnants of formative events that reshaped the river channel. These results highlight the complex relationships between flow regime, channel morphology, and riparian vegetation. The use of succession phases, which rely on the sequential evolution of riparian vegetation as a response to different drivers, may be potentially better reproducible, within numerical process-based models, and transferable to other geographical regions.This work was supported by the IWRM Era-NET Funding Initiative through the RIPFLOW project (references ERACCT-2005-026025, ERA-IWRM/0001/2008, CGL2008-03076-E/BTE), http://www.old.iwrm-net.eu/spip.php, by the Spanish Ministry of Economy and Competitiveness through the project SCARCE (Consolider¿Ingenio 2010 CSD2009-00065), and by the project ¿Natural and anthropogenic changes in Mediterranean river drainage basins: historical impacts on rivers morphology, sedimentary flows and vegetation¿ of the Spanish MINECO (CGL2013-44917-R). Virginia Garófano-Gómez received a postdoctoral grant from the Université Blaise Pascal (now: Université Clermont Auvergne). Rui Rivaes benefited from a PhD grant (SFRH/BD/52515/2014) sponsored by Fundação para a Ciência e Tecnologia (FCT) under the FCT PhD programme FLUVIO¿River Restoration and Management. Patricia María Rodríguez González was funded by FCT through an SFRH/BPD/47140/2008 postdoctoral fellowship and through an FCT Investigator Programme grant (IF/00059/2015). The authors also thank all the colleagues and master students who contributed enthusiastically to the field campaigns of this study.Muñoz Mas, R.; Garófano-Gómez, V.; Andrés Doménech, I.; Corenblit, D.; Egger, G.; Francés, F.; Ferreira, M.... (2017). Exploring the key drivers of riparian woodland successional pathways across three European river reaches. Ecohydrology. 10(8):1-19. https://doi.org/10.1002/eco.1888S11910

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

Trans-scale modelling of river morphodynamics

In a river, the local hydraulics, channel form and in-stream vegetation are interdependent. Although water, sediment and vegetation processes interact, they respond individually to flow characteristics at different spatial and temporal scales. This study employs a modelling approach that is based on the tendency of river systems to self-organise and produce emergence (emergent structures) in scale hierarchies. A hierarchical modelling strategy is proposed that arranges separate models describing vegetation and sediment dynamics at their appropriate scales, with their interaction described through feedback between the models. Prediction of the river state at time scales of decades, over a range of spatial scales, is required for ecological river management to be more effective. However, river systems are complex, with complexity rooted deep in the river processes of water, sediment and vegetation holding implications for their modelling. Dealing with complexity in river geomorphological modelling is vital for achieving reliable predictions over decades, especially when considering that small-scale processes must be described to achieve this. Description of small-scale river form is not only required for river habitat management, but also affects the rates at which river form at larger scales changes. Hierarchy and non-linear theory provide a way to deal with the complexity of rivers by separating the river system into parts, and enabling these parts to interact. Appropriate models and modelling methodologies were chosen or developed to represent the effect of interacting river processes of water, sediment and reeds at the progressively nested (largest) reach scale, the channel-type scale and (smallest) geomorphological-unit scale. Existing water flow models at the reach scale and the next largest channel-type scale are used. The reach scale water flow model solves one-dimensional (1-D) Saint-Venant equations whereas the channel-type scale water flow model is governed by twodimensional (2-D) Saint-Venant equations. The water flow model at the smallest organisational level chosen for modelling is the geomorphological-unit scale. Water flow at the geomorphological-unit scale is not based on the actual physics of water flow, but it does account for the smaller scale variability of the water distribution. ix The sediment model at the reach scale employs the Exner equation of sediment continuity in combination with gravel-bed-load transport equations to determine changes in bed elevation. At the channel-type scale, a Cellular Automaton (CA) model describes sediment transport through a river. The CA represents the river as a lattice of cells and predicts the volume of sediment stored in the cells. The sediment distribution obtained from the CA model describes the habitat for reeds. At the geomorphologicalunit scale, a combination of existing formulations is used to predict the dimensions and growth of bed-forms representing sediment dynamics. The vegetation models at the reach scale and the channel-type scale were developed specifically to describe dynamics of common reeds or Phragmites Australis. Reeds were chosen for modelling because of the large role they play as geomorphological modifiers. The reach scale model predicts the distribution of reed populations along the lateral river bank gradient whereas the channel-type scale reed model is a CA model that predicts the expansion of reed patches. The vegetation model at the geomorphological-unit scale is an existing model describing the growth of reeds by integrating finite differential equations of reed biomass growth. River process interactions affect river geomorphology across these organisational levels. The models are integrated to provide feedback within a hierarchical modelling structure. Process models simulating sediment, water and vegetation dynamics within a specific organisational level are coupled through sharing the same spatial scale. Models of the same process producing patterns at various organisational levels are linked to share model information across organisational levels. Trans-organisational modelling linkage allows models to share outputs which provide boundary conditions and values for model parameters at specific locations within the modelling domain. A hierarchical framework allows prediction of small-scale geomorphology and accounts for its variability at the large scale. The modelling strategy is demonstrated by simulations based on hypothetical scenarios of a gravel-bed river. The effect of sediment size and frequency of the flood event moving sediment, together with typical channel geometry, is shown for these. The modelling was computationally very intensive. x Results show that models focusing on only one organisational level can have very different outputs form those produced by trans-organisational modelling. the difference is due to emergence produced by dynamic small-scale processes that manifest at large scales.Emergence was found in changing flow resistance coefficients obtained from smaller scale modelling. The flow resistance affected the river bed elevation at the reach scale. Emergence was indicated by the channel aggrading more for modelling with the inclusion of the effect of smaller scale river process interactions than without it. Thes snall-scale process interactions include water flow affected by bed-forms and reeds. bed-forms and reed affected energy loss significantly and provided a strong coupling between the flow and the river bed elevation. Hierarchical modelling therefore allows for reliable river geomorphology modelling over a decadal time scale by describing river complexity more realisticall

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

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

Development and application of individual-based models for predicting upstream passage of European fish

Anthropogenic alteration of rivers is ubiquitous and leads to fragmented river systems that restrict the passage of aquatic fauna. There are considerable efforts to facilitate unhindered migration through the installation of fish passage facilities. However, recent assessments suggest upstream passage efficiencies of 42%, and suggest that only 3% of rivers in Great Britain are fully connected. Decoding the behaviours that govern up-migrating fish responses to flow fields has been dubbed a high research priority that would allow for computational metrics of fish passage and a reduction in invasive experiments. The aim of this project was to develop cellular automata (CA), individual-based models (IBM), and computational fluid dynamic (CFD) models to predict the trajectories of up-migrating fishes and subsequently provide a method to computationally assess passage facilities. Past work was critically assessed to determine: the appropriate CFD approach to quantify the flow through various domains, the hydrodynamic stimuli that influence fish responses, and the current state of fish path prediction models and their applications and limitations. Multiple 2D CA and IBMs were developed to predict the passage efficiency of various eel tile configurations for juvenile European eels (Anguilla anguilla) using CFD-derived flow fields. Predictions compared well to a published values (76% vs. 74%) and suggested passage efficiency was highest for shallow slopes and low discharges. Results were extended to define maximum pass lengths and incorporated into an easy-to-use graphic. A 3D IBM, fishPy, was developed to predict up-migration trajectories of brown trout (Salmo trutta) based fish responses to hydraulic stimuli. Artificial hydrodynamic domains were created using CFD and used to verify model function. A CFD model of a passage facility on the River Esk was created based on collected bathymetry data, and compared well to measured velocity data. The IBM was applied to the passage facility and compared against measured passage metrics and fish trajectories. Overall, 2D and 3D models of up-migrating fishes were successfully developed and compared well to measured data. Potential areas for further research and development of the models are highlighted, including development of additional species modules for the 3D IBM