Towards a unified ontology for monitoring ecosystem services

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Authors

Flavio Affinito , Jennifer M Holzer, Marie-Josee Fortin, Andrew Gonzalez

Abstract

The concept of ecosystem services (ES) has greatly evolved since it was first proposed and, as it gained popularity, has been used in diverse applications. Today, ES are an important part of global and national environmental policies. In this context, there is a call for the monitoring of ES to support their management. The proliferation of terms used with the concept of ES may be a barrier to systematic monitoring. Monitoring ES requires knowing exactly what variables to measure and how they relate to change in the states of ES. It further requires interoperability between methodologies used by the information systems used to operationalise data flows. As such, there is a need to systematise the language used to define ES and the terminology used in their monitoring in a way that is unambiguous and both human and computer readable. Building on advances in other biological fields, we develop an ontology for monitoring ES. Ontologies are tools that operationalise concepts and the relationships among terms used to define them. An ontology further allows people and machines to use the terms consistently. The ES monitoring ontology aligns the language of ES with other ontologies in the biological sciences. We test the ES monitoring ontology with data from three ES in British Columbia, Canada, to highlight how it can enable information sharing and monitoring. We invite members of the ES community to join the effort of developing this ontology for ES so that can it contribute to the challenge of systematically monitoring change in social-ecological systems.

DOI

https://doi.org/10.32942/X21W5S

Subjects

Life Sciences

Keywords

Ecosystem services monitoring, interoperability, ontology

Dates

Published: 2024-11-16 07:35

Last Updated: 2024-11-16 12:35

Older Versions
License

CC BY Attribution 4.0 International

Additional Metadata

Language:
English

Conflict of interest statement:
None

Data and Code Availability Statement:
All data used in this article are available from (Schwantes et al., 2024) and code is available at: https://github.com/FlavAff/ESMOntology