Ecological Modelling

Aims & Scope

The journal is concerned with the use of mathematical models and systems analysis for the description of ecological processes and for the sustainable management of resources.

Human activity and well-being are dependent on and integrated with the functioning of ecosystems and the services they provide.

We aim to understand these basic ecosystem functions using mathematical and conceptual modelling, systems analysis, thermodynamics, computer simulations, and ecological theory.

This leads to a preference for process-based models embedded in theory with explicit causative agents as opposed to strictly statistical or correlative descriptions.

These modelling methods can be applied to a wide spectrum of issues ranging from basic ecology to human ecology to socio-ecological systems.

The journal welcomes research articles, short communications, review articles, letters to the editor, book reviews, and other communications.

The journal also supports the activities of the International Society of Ecological Modelling (ISEM).

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	3.2
2024	2.60

SJR (SCImago Journal Rank)

Year	Value
2024	0.896

Quartile

Year	Value
2024	Q1

h-index

Year	Value
2024	189

Journal Rank

Year	Value
2024	5728

Journal Citation Indicator

Year	Value
2024	2681

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Environmental Science, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Maximum entropy modeling of species geographic distributions

  Citation: 13535

  Authors: Steven J., Robert P., Robert E.

• Predictive habitat distribution models in ecology

  Citation: 4769

  Authors: Antoine, Niklaus E.

• The package “adehabitat” for the R software: A tool for the analysis of space and habitat use by animals

  Citation: 3368

  Authors: Clément

• A standard protocol for describing individual-based and agent-based models

  Citation: 2201

  Authors: Volker, Uta, Finn, Sigrunn, Vincent, Jarl, John, Tamara, Simone K., Geir, Andreas, Jane U., Christian, Wolf M., Birgit, Guy, Cyril, Steven F., Andrew M., Martha M., Eva, Nadja, Espen, Sami, Richard A., Rune, Ute, Donald L.

• Evaluating resource selection functions

  Citation: 1997

  Authors: Mark S, Pierre R, Scott E, Fiona K.A

• The ODD protocol: A review and first update

  Citation: 1916

  Authors: Volker, Uta, Donald L., J. Gary, Jarl, Steven F.

• Generalized linear and generalized additive models in studies of species distributions: setting the scene

  Citation: 1749

  Authors: Antoine, Thomas C, Trevor

• Spatial modelling: a comprehensive framework for principal coordinate analysis of neighbour matrices (PCNM)

  Citation: 1648

  Authors: Stéphane, Pierre, Pedro R.

• All-scale spatial analysis of ecological data by means of principal coordinates of neighbour matrices

  Citation: 1621

  Authors: Daniel, Pierre

• Evaluating the predictive performance of habitat models developed using logistic regression

  Citation: 1531

  Authors: Jennie, Simon

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