S. Lek

Publications
Influence

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

M. Gevrey, I. Dimopoulos, S. Lek
Mathematics
15 February 2003

Abstract Convinced by the predictive quality of artificial neural network (ANN) models in ecology, we have turned our interests to their explanatory capacities. Seven methods which can give the… Expand

Uncertainty in ensemble forecasting of species distribution

L. Buisson, W. Thuiller, Nicolas Casajus, S. Lek, G. Grenouillet
Environmental Science
1 April 2010

Species distribution modelling has been widely applied in order to assess the potential impacts of climate change on biodiversity. Many methodological decisions, taken during the modelling process… Expand

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

S. Lek, J. Guégan
Computer Science
17 August 1999

Abstract Artificial neural networks (ANNs) are non-linear mapping structures based on the function of the human brain. Expand

Application of neural networks to modelling nonlinear relationships in ecology

S. Lek, M. Delacoste, P. Baran, I. Dimopoulos, J. Lauga, S. Aulagnier
Mathematics
1 September 1996

Abstract Two predictive modelling principles are discussed: multiple regression (MR) and neural networks (NN). The MR principle of linear modelling often gives low performance when relationships… Expand

A comparison of self-organizing map algorithm and some conventional statistical methods for ecological community ordination

J. L. Giraudel, S. Lek
Computer Science
1 December 2001

In order to summarise the structure of ecological communities some ordination techniques are well known and widely-used, (e.g. Principal Component Analysis (PCA), Correspondence Analysis (CoA). Expand

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

Young-Seuk Park, R. Céréghino, A. Compin, S. Lek
Mathematics
15 February 2003

Abstract Two artificial neural networks (ANNs), unsupervised and supervised learning algorithms, were applied to suggest practical approaches for the analysis of ecological data. Four major aquatic… Expand

Applications of artificial neural networks predicting macroinvertebrates in freshwaters

P. Goethals, A. Dedecker, W. Gabriels, S. Lek, N. Pauw
Computer Science
Aquatic Ecology
9 May 2007

This paper focuses on the analysis of ANN development and application for predicting macroinvertebrate communities, a species group commonly used in freshwater assessment worldwide. Expand

Climate change hastens the turnover of stream fish assemblages

L. Buisson, W. Thuiller, S. Lek, P. Lim, G. Grenouillet
Biology
1 October 2008

Stream fish are expected to be significantly influenced by climate change, as they are ectothermic animals whose dispersal is limited within hydrographic networks. Nonetheless, they are also… Expand

The use of artificial neural networks to assess fish abundance and spatial occupancy in the littoral zone of a mesotrophic lake

S. Brosse, J. Guégan, J. Tourenq, S. Lek
Environmental Science
17 August 1999

The present work describes a comparison of the ability of multiple linear regression (MLR) and artificial neural networks (ANN) to predict fish spatial occupancy and abundance in a mesotrophic… Expand

Identifying rice fields at risk from damage by the greater flamingo

C. Tourenq, S. Aulagnier, +4 authors J. Martin
Biology
1 February 2001

Summary 1 Since the early 1980s, greater flamingos Phoenicopterus ruber roseus have been reported to cause damage to the rice fields of the Camargue, south-eastern France. 2 We tested… Expand

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