D-Index & Metrics Best Publications
Ecology and Evolution
France
2023

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Ecology and Evolution D-index 62 Citations 14,522 239 World Ranking 1231 National Ranking 47

Research.com Recognitions

Awards & Achievements

2023 - Research.com Ecology and Evolution in France Leader Award

Overview

What is he best known for?

The fields of study he is best known for:

  • Ecology
  • Statistics
  • IUCN Red List

His main research concerns Ecology, Artificial neural network, Species richness, Backpropagation and Self-organizing map. His Ecology study incorporates themes from Sampling and Biological dispersal. The study incorporates disciplines such as Statistics, Linear regression and Black box in addition to Artificial neural network.

His Species richness study integrates concerns from other disciplines, such as Habitat fragmentation, Barbus barbus, Climate change, STREAMS and Leuciscus. His Backpropagation study combines topics in areas such as River ecosystem, Operations research, Soil science and Multilayer perceptron. His biological study spans a wide range of topics, including Principal component analysis, Unsupervised learning, Data mining and Community structure.

His most cited work include:

  • Review and comparison of methods to study the contribution of variables in artificial neural network models (751 citations)
  • Artificial neural networks as a tool in ecological modelling, an introduction (636 citations)
  • Application of neural networks to modelling nonlinear relationships in ecology (548 citations)

What are the main themes of his work throughout his whole career to date?

The scientist’s investigation covers issues in Ecology, Species richness, Abundance, Fishery and Artificial neural network. His study in Habitat, Species diversity, Benthic zone, Littoral zone and Ecosystem falls within the category of Ecology. The concepts of his Ecosystem study are interwoven with issues in Trophic level and Aquatic ecosystem.

His research in Species richness intersects with topics in Climate change, Biodiversity, Indicator species and Community structure. His research brings together the fields of Hydrology and Abundance. His Artificial neural network research incorporates themes from Statistics and Linear regression.

He most often published in these fields:

  • Ecology (66.41%)
  • Species richness (16.02%)
  • Abundance (15.23%)

What were the highlights of his more recent work (between 2015-2021)?

  • Ecology (66.41%)
  • Fishery (16.80%)
  • Habitat (13.28%)

In recent papers he was focusing on the following fields of study:

His scientific interests lie mostly in Ecology, Fishery, Habitat, Abundance and Fishing. His Ecology research includes elements of Freshwater fish and Rhinogobius giurinus. He has included themes like Biomass, Fish migration and Hydropower in his Fishery study.

His research integrates issues of Climate change, Competition and Overfishing in his study of Habitat. His research on Abundance also deals with topics like

  • Floodplain which connect with Flood myth,
  • Oreochromis most often made with reference to Water level. His work carried out in the field of Species richness brings together such families of science as Cross-validation, Indicator species, Cohen's kappa, Species diversity and Community structure.

Between 2015 and 2021, his most popular works were:

  • Evidence of Water Quality Degradation in Lower Mekong Basin Revealed by Self-Organizing Map (50 citations)
  • Flow alterations by dams shaped fish assemblage dynamics in the complex Mekong-3S river system (40 citations)
  • Evidence of indiscriminate fishing effects in one of the world's largest inland fisheries. (36 citations)

In his most recent research, the most cited papers focused on:

  • Ecology
  • Statistics
  • IUCN Red List

Sovan Lek spends much of his time researching Ecology, Species richness, Ecosystem, Water quality and Beta diversity. His studies deal with areas such as Freshwater fish and Fishery as well as Ecology. His work deals with themes such as Biodiversity, Indicator species, Statistics, Receiver operating characteristic and Random forest, which intersect with Species richness.

He combines subjects such as Trophic level, Intraspecific competition and Ecological niche with his study of Ecosystem. His Water quality study combines topics from a wide range of disciplines, such as Current, Aquatic ecosystem, Nutrient and Water resource management. He has researched Beta diversity in several fields, including Abundance and Invertebrate.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Review and comparison of methods to study the contribution of variables in artificial neural network models

.
Ecological Modelling (2003)

1211 Citations

Review and comparison of methods to study the contribution of variables in artificial neural network models

.
Ecological Modelling (2003)

1211 Citations

Artificial neural networks as a tool in ecological modelling, an introduction

.
Ecological Modelling (1999)

1006 Citations

Artificial neural networks as a tool in ecological modelling, an introduction

.
Ecological Modelling (1999)

1006 Citations

Application of neural networks to modelling nonlinear relationships in ecology

.
Ecological Modelling (1996)

833 Citations

Application of neural networks to modelling nonlinear relationships in ecology

.
Ecological Modelling (1996)

833 Citations

Uncertainty in ensemble forecasting of species distribution

.
Global Change Biology (2010)

582 Citations

Uncertainty in ensemble forecasting of species distribution

.
Global Change Biology (2010)

582 Citations

Applications of artificial neural networks for patterning and predicting aquatic insect species richness in running waters

.
Ecological Modelling (2003)

438 Citations

Applications of artificial neural networks for patterning and predicting aquatic insect species richness in running waters

.
Ecological Modelling (2003)

438 Citations

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