biomonitoR: an R package for managing ecological data and calculating biomonitoring indices

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The monitoring of biological indicators is required to assess the impacts of environmental policies, compare ecosystems and guide management and conservation actions. However, the growing availability of ecological data has not been accompanied by concomitant processing tools able to facilitate data handling and analysis. Multiple common challenges limit the usefulness of biomonitoring information across ecosystems and biological groups. Biomonitoring data analysis is currently constrained by time-consuming steps for data preparation and a data processing environment with limited integration in terms of software, biological groups, and protocols. We introduce biomonitoR, a package for the R programming language that addresses technical challenges for the management of ecological data and metrics calculation. biomonitoR implements most of the biological indices currently used or proposed in different fields of ecology and water resource management. Its combination of customizable functions aims to support a transferable and comprehensive biomonitoring workflow in a user-friendly environment. biomonitoR represents a versatile toolbox with five main assets: (i) it checks taxonomic information against reference datasets allowing for customization of trait and sensitivity scores; (ii) it supports heterogeneous taxonomic resolution allowing computations at multiple taxonomic levels; (iii) it calculates multiple biological indices, including metrics for both broad and stressorspecific ecological assessments; (iv) it enables user-friendly data visualization, helping both decision-making processes and data interpretation; and (v) it allows working with an interactive web application straight from R. Overall, biomonitoR can benefit the wide biomonitoring community, including environmental private consultants, ecologists and natural resource managers.

Alex Laini was supported by COST (European Cooperation in Science and Technology) within the Action CA15113 (Science and Management of Intermittent Rivers and Ephemeral Streams) and by the project PRIN-NOACQUA (Community responses and ecosystem processes in intermittent streams, Prot. 201572HW8F). Daniel Bruno was funded by CSIC Interdisciplinary Thematic Platform (PTI) Síntesis de Datos de Ecosistemas y Biodiversidad (PTI-ECOBIODIV). Cayetano Gutiérrez Cánovas was supported by a “Juan de la Cierva—Incorporación” contract (MINECO, IJC2018-036642-I). Simone Guareschi was supported by a Royal Society-Newton International Fellowship at Loughborough University (NIF R1 180346) and by European Regional Development Fund (SUMHAL, LIFEWATCH-2019-09-CSIC-13, POPE 2014–2020) at Doñana Biological Station (2021–2022). Gábor Várbíró was supported by the National Research, Development and Innovation Office—NKFIH FK 135 136 grant. There was no additional external funding received for this study.

Peer reviewed