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biomonitoR: an R package for managing ecological data and calculating biomonitoring indices
Laini, A.; Guareschi, S.; Bolpagni, R.; Burgazzi, G.; Bruno, D.; Gutiérrez-Cánovas, C.; Miranda, R.; Mondy, C.; Várbíró, G.; Cancellario, T. (2022). biomonitoR: an R package for managing ecological data and calculating biomonitoring indices. PeerJ 10: e14183. https://dx.doi.org/10.7717/peerj.14183
In: PeerJ. PeerJ: Corte Madera & London. ISSN 2167-8359; e-ISSN 2167-8359
|   |
| Auteurs | | Top |
- Laini, A.
- Guareschi, S.
- Bolpagni, R.
- Burgazzi, G.
|
- Bruno, D.
- Gutiérrez-Cánovas, C.
- Miranda, R.
|
- Mondy, C.
- Várbíró, G.
- Cancellario, T.
|
| Abstract |
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 stressor-specific 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. |
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