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Ecological Informatics - Elsevier | 2024 Impact Factor:7.3 | Cite Score:11.4 | Q1

Ecological Informatics Journal

Impact Factor and Journal Rank of Ecological Informatics

  • About: Ecological Informatics is dedicated to publishing high-quality, peer-reviewed articles covering all aspects of computational ecology, data science, and biogeography. The journal recognizes the data-intensive nature of ecology and the increasing capability of information technology to access, harness, and utilize complex data. It serves as a leading publication for researchers and practitioners seeking to advance understanding and application of ecological data science in the context of global environmental and climate challenges.
  • Objective: The primary objective of Ecological Informatics is to foster interdisciplinary research and innovation in computational ecology and biogeography. The journal aims to publish groundbreaking research that integrates ecological principles with advanced data analytics and modeling techniques. By showcasing high-quality articles, the journal promotes collaboration and knowledge exchange among researchers, facilitating advancements in ecological informatics.
  • Interdisciplinary Focus: Ecological Informatics adopts an interdisciplinary approach, inviting contributions from ecology, environmental science, data science, biogeography, and related fields. It encourages research that applies computational methods to ecological data to address pressing environmental issues such as biodiversity conservation, ecosystem management, and climate change impacts. The journal supports studies that leverage big data analytics, machine learning, spatial analysis, and modeling to enhance ecological understanding and inform sustainable management practices.
  • Global Reach and Impact: With a global readership and authorship, Ecological Informatics significantly influences research and development in computational ecology worldwide. Its publications contribute to advancing methodologies, technologies, and theoretical frameworks in ecological informatics. The journal impact extends to various applications, including environmental policy-making, conservation planning, ecological forecasting, and adaptive management.
  • High Standards and Rigorous Review: Maintaining high academic standards, Ecological Informatics employs a rigorous peer-review process. Each submitted manuscript undergoes comprehensive evaluation by experts in the field to ensure scientific rigor, methodological robustness, and originality of research contributions. This stringent review process upholds the integrity and credibility of the journal, ensuring that only impactful and authoritative studies are published.
  • Significance: Ecological Informatics plays a pivotal role in advancing research and innovation at the intersection of ecology and data science. By providing a platform for cutting-edge research findings and technological advancements, the journal supports the development of informed strategies for addressing complex ecological challenges. It serves as an essential resource for researchers, practitioners, and policymakers committed to leveraging data-driven approaches to achieve sustainable environmental management and conservation goals.

  • Editor-in-Chief:  George Arhonditsis

  • Scope: Ecological Informatics is a peer-reviewed journal dedicated to publishing high-quality research articles covering computational ecology, data science, and biogeography. The journal focuses on the intersection of ecology and information technology, addressing the data-intensive nature of ecological research and its implications for sustainable environmental management in the context of global environmental and climate change. Here is an overview of its key focus areas and scope:
  • 1. Computational Ecology:
    Advancements in computational methods and models for ecological research.
    Research on ecological data analysis, simulation modeling, predictive modeling, and ecological informatics.
  • 2. Data Science in Ecology:
    Innovations in data acquisition, management, integration, and analysis in ecological studies.
    Research on big data approaches, machine learning techniques, data mining, and data-driven discovery in ecology.
  • 3. Biogeography:
    Studies on the spatial distribution of biodiversity and its environmental correlates.
    Research on species distribution modeling, habitat suitability modeling, biogeographic patterns, and landscape ecology.
  • 4. Information Technology in Ecology:
    Integration of information technology tools and platforms for ecological research.
    Research on remote sensing, GIS (Geographic Information Systems), sensor networks, and data visualization in ecology.
  • 5. Sustainable Environmental Management:
    Applications of ecological informatics to support sustainable environmental practices.
    Research on ecosystem services, conservation biology, biodiversity conservation, and environmental decision support systems.
  • 6. Global Environmental and Climate Change:
    Impact of global environmental change and climate change on ecosystems and biodiversity.
    Research on ecological responses to climate change, adaptation strategies, and mitigation measures.
  • 7. Interdisciplinary Research:
    Collaborative research integrating ecology with computer science, statistics, mathematics, and other disciplines.
    Studies that bridge ecological theory with technological innovations to address complex environmental challenges.
  • 8. Policy and Management Implications:
    Research that informs policy-making and environmental management practices.
    Studies on environmental policy analysis, ecosystem management strategies, and the socio-economic dimensions of ecological informatics.
  • Latest Research Topics for PhD in Computer Science
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  • Print ISSN:  15749541

    Electronic ISSN:  

  • Abstracting and Indexing:  Scopus, Science Citation Index Expanded

  • Imapct Factor 2024:  7.3

  • Subject Area and Category:   Agricultural and Biological Sciences , Ecology, Evolution, Behavior and Systematics , Computer Science , Computational Theory and Mathematics , Computer Science Applications , Environmental Science , Ecological Modeling , Ecology , Mathematics , Applied Mathematics , Modeling and Simulation

  • Publication Frequency:  

  • H Index:  88

  • Best Quartile:

    Q1:  Applied Mathematics

    Q2:  

    Q3:  

    Q4:  

  • Cite Score:  11.4

  • SNIP:  1.795

  • Journal Rank(SJR):  1.491