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

Muñoz‐Mas, Rafael; Papadaki, Christina; Martínez‐Capel, Francisco; Zogaris, Stamatis; Ntoanidis, Lazaros; Dimitriou, Elias

doi:10.1016/j.ecoleng.2016.03.009

Cited by 37 publications

(44 citation statements)

References 67 publications

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“…Similar results have been reported for small and medium trout in literature (Ayllon et al, 2009;Bovee, 1978). Decrease in adult fish finding probability by increase in substrate index is in contrast with previous studies on trout species (Ayllon et al, 2009;Bovee, 1978;Munoz-Mas et al, 2016).…”

Section: Turkish Journal Of Fisheries and Aquatic Sciencescontrasting

confidence: 54%

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Rezaei¹,

Şengül²

2019

Turk. J. Fish. Aquat. Sci.

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Generalized Additive Models (GAMs) are widely used statistical models for species distribution in habitat and environmental management modeling as they enable incorporation of non-linearity. The objective of this study is to develop relationships between habitat variables, fish absence/presence (logistic GAM) and abundance (Poisson GAM) for the S. rizeensis using onsite observations in Solaklı River. Logistic GAMs correctly predicted absence/presence of adult and juvenile S. rizeensis at 79.3% and 74% of sampling areas respectively. Response curves of logistic GAMs results show differences in probability of finding the adult and juvenile fish. Adult S. rizeensis were mostly found in higher velocities (0.5-0.8 m/s) than in juvenile fish (≈ 0 m/s). Also, the highest number of adult fish were recorded in deeper habitats (≈ 0.4 m) rather than in juvenile fish (≈ 0 m). Curves show adult fish are more independent to the presence of cover compared to juvenile fish. Velocity shelter and bedrock formation were the most common cover types. Chi-square test results of predicted values showed that developed Poisson GAMs of adult and juvenile S. rizeensis could not accurately represent fish abundance. The results show that while logistic GAM is applicable, Poisson GAM model is not applicable for the area.

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Section: Turkish Journal Of Fisheries and Aquatic Sciencescontrasting

confidence: 54%

“…Munoz-Mas et al (2016) study results on Salmo farioides showed that the large fish prefer low velocity and deep parts. The pool sections of the river are where the large fish could be found.…”

Section: Discussionmentioning

confidence: 99%

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Rezaei¹,

Şengül²

2019

Turk. J. Fish. Aquat. Sci.

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“…In the past two decades, advancements in statistical methods have promoted the development of SDMs, and numerous statistical methods and software programs have been developed to describe the niche characteristics of species and predict species distribution patterns. The popular algorithms are as follows: surface range envelope (SRE, i.e., BIOCLIM) (Booth, Nix, Busby, & Hutchinson, 2014), flexible discriminant analysis (FDA) (Basile et al, 2016), generalized linear model (GLM) (Lopatin, Dolos, Hernández, Galleguillos, & Fassnacht, 2016), generalized additive model (GAM) (Muñoz-Mas, Papadaki, Martinez-Capel, Zogaris, & Ntoanidis, 2016), multiple adaptive regression splines (MARS) (Friedman, 1991), generalized boosting model (GBM) (Moisen et al, 2006), classification tree analysis (CTA) (Thuiller & Lavorel, 2010), artificial neural network (ANN) (Segurado & Araujo, 2004), random forest (RF) (Mi, Huettmann, Guo, Han, & Wen, 2017), and maximum entropy (MaxEnt) (Phillips, Anderson, & Schapire, 2006). However, differential niche requirements of species shape the geographic distribution of species within an environment.…”

Section: Introductionmentioning

confidence: 99%

Potential distribution of Notopterygium incisum Ting ex H. T. Chang and its predicted responses to climate change based on a comprehensive habitat suitability model

Zhao

Guo

Wei

et al. 2020

Ecology and Evolution

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Notopterygium incisum Ting ex H. T. Chang is a rare and endangered traditional Chinese medicinal plant. In this research, we built a comprehensive habitat suitability (CHS) model to analyze the potential suitable habitat distribution of this species in the present and future in China. First, using nine different algorithms, we built an ensemble model to explore the possible impacts of climate change on the habitat distribution of this species. Then, based on this model, we built a CHS model to further identify the distribution characteristics of N. incisum‐suitable habitats in three time periods (current, 2050s, and 2070s) while considering the effects of soil and vegetation conditions. The results indicated that the current suitable habitat for N. incisum covers approximately 83.76 × 103 km2, and these locations were concentrated in the Tibet Autonomous Region, Gansu Province, Qinghai Province, and Sichuan Province. In the future, the areas of suitable habitat for N. incisum would significantly decrease and would be 69.53 × 103 km2 and 60.21 × 103 km2 in the 2050s and 2070s, respectively. However, the area of marginally suitable habitat would remain relatively stable. This study provides a more reliable and comprehensive method for modelling the current and future distributions of N. incisum, and it provides valuable insights for highlighting priority areas for medicinal plant conservation and resource utilization.

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“…Artificial networks have been analogously used to infer the most relevant variables to discriminate riparian from terrestrial forest (Blackard & Dean, 1999), whereas generalized linear models (Nelder & Wedderburn, 1972) have been used to infer the general topographic patterns that determine riparian forest distribution (Shoutis, Patten, & McGlynn, 2010). Finally, fuzzy-logic-based methods (Zadeh, 1965) have been profusely applied due to their capability to consider expert knowledge (Muñoz-Mas, Papadaki, et al, 2016). Consequently, fuzzy logic has been used to mathematize the stress tolerance of several lowland riparian woody species across Europe, demonstrating their disparate ecological requirements (Glenz et al, 2008).…”

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

et al. 2017

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International audienceClimate 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

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

Cited by 37 publications

References 67 publications

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Untitled

Potential distribution of Notopterygium incisum Ting ex H. T. Chang and its predicted responses to climate change based on a comprehensive habitat suitability model

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

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