Ecological Informatics

by

Friedrich Recknagel

• LAST REVIEWED: 26 July 2022
• LAST MODIFIED: 26 July 2022
• DOI: 10.1093/obo/9780199830060-0174

Introduction

The emerging discipline of ecological informatics takes into account the data-intensive nature of ecology, the precious information content of ecological data, and the growing capacity of computational technology to leverage complex data as well as the critical need for informing sustainable management of complex ecosystems. It comprehends novel concepts and techniques for image- and genome-based monitoring, data management, data analysis, synthesis, and forecasting.

General Overviews

Ecological informatics introduced in Recknagel 2003 and Recknagel 2008 emphasize primarily leveraging complex ecological data by machine learning. Jones, et al. 2006 and Michener and Jones 2012 suggest archiving, sharing, and integrating ecological data as the key focus of ecological informatics. Brewer, et al. 2012 demonstrates that ecological informatics largely benefits from the inclusion of paleoecology, while Farina, et al. 2011 and Matzner, et al. 2015 establish acoustic and thermal imaging as strong components of ecological informatics. Recknagel and Michener 2018 focuses the scope of ecological informatics on acquisition, archival, analysis, synthesis, and forecasting of ecological data by novel computational techniques.

• Brewer, S., S. T. Jackson, and J. W. Williams. 2012. Paleoecoinformatics: Applying geohistorical data to ecological questions. Trends in Ecology and Evolution 27.2: 104–112.

  DOI: 10.1016/j.tree.2011.09.009

  Extends the scope of ecological informatics by integrating information-rich paleoecological data.

• Farina, A., N. Pieretti, and L. Piccioli. 2011. The soundscape methodology for long-term bird monitoring: A Mediterranean Europe case-study. Ecological Informatics 6.6 (November): 354–363.

  DOI: 10.1016/j.ecoinf.2011.07.004

  Ecoacoustic techniques allow continent-wide long-term monitoring of birds.

• Jones, M. B., M. P. Schildhauer, O. J. Reichman, and S. Bowers. 2006. The new bioinformatics: Integrating ecological data from the gene to the biosphere. Annual Review of Ecology, Evolution and Systematics 37:519–544.

  DOI: 10.1146/annurev.ecolsys.37.091305.110031

  Describes ecoinformatics as informatics frameworks for ecology, from subject-specific data warehouses to generic data collections that use detailed metadata descriptions and formal ontologies to catalogue and cross-reference information.

• Matzner, S., V. I. Cullinan, and C. A. Duberstein. 2015. Two-dimensional thermal video analysis of offshore bird and bat flight. Ecological Informatics 30:20–28.

  DOI: 10.1016/j.ecoinf.2015.09.001

  Applies thermal imaging for determining flight behavior of birds and bats.

• Michener, W. K., and M. Jones. 2012. Ecoinformatics: Supporting ecology as data-intensive science. Trends in Ecology and Evolution 27.2: 85–93.

  DOI: 10.1016/j.tree.2011.11.016

  States that integrative informatics platforms, adoption of standard informatics protocols, and good data stewardship as well as sociocultural changes such as promoting informatics literacy, data sharing, and scientific transparency are central to understanding the nature and pace of ecological and environmental change.

• Recknagel, F. 2003. Ecological informatics: Understanding ecology by biologically-inspired computation. New York: Springer-Verlag.

  DOI: 10.1007/978-3-662-05150-4

  Ecological informatics focuses on archival, retrieval, and visualization as well as analysis, synthesis, and forecasting of ecological data by novel computation techniques.

• Recknagel, F. 2008. Ecological informatics: Overview. In D–F. Vol. 2 of Encyclopedia of ecology. Edited by S. E. Jørgensen, 1041–1058. Amsterdam: Elsevier B. V.

  Ecological informatics defined as a multidisciplinary framework that takes into account the data-intensive nature of ecology, the precious information content of ecological data, and the growing capacity of computational technology to leverage complex data as well as the critical need for informing sustainable management of complex ecosystems.

• Recknagel, F., and W. K. Michener. 2018. Ecological informatics: Data management and knowledge discovery. 3d ed. Cham, Switzerland: Springer Nature.

  DOI: 10.1007/978-3-319-59928-1

  Comprehensive guidebook into ecological informatics and data science that consists of four parts, addressing “Managing Ecological Data”; Analysis, Synthesis and Forecasting of Ecological Data”; Communication and Informing Decision”; and “Case Studies.”