Contents lists available atScienceDirect
Ecological Informatics
journal homepage:www.elsevier.com/locate/ecolinf
PhytoNumb3rs: An easy-to-use computer toolkit for counting microalgae by
the Utermöhl method
Maria Rosaria Vadrucci
⁎, Leonilde Roselli, Daniela Castelluccia, Tiziana Di Festa,
Daniela Donadei, Marisa Florio, Emanuela Longo, Stefania D'Arpa, Flavia Maci, Sergio Ranieri,
Mariangela Spinelli, Annamaria Pastorelli, Nicola Ungaro
Regional Agency for the Environmental Prevention and Protection (ARPA Puglia), Corso Trieste 27, Bari, Italy
A R T I C L E I N F O
Keywords:
Phytoplankton uncertainty Quantitative detection limit Counting strategy Toolkit for counting
A B S T R A C T
Phytoplankton is recognised as a biological quality element and a biological descriptor in European Directives (WFD, MSFD) and several national laws. To determine the biodiversity and abundance of phytoplankton as-semblages, the Utermöhl method, using an inverted light microscope, is the most widely used. Nevertheless, the Utermöhl method, standardised as UNI EN 15204 (2006), is time-consuming and labour intensive. We developed and tested PhytoNumb3rs, a tool for supporting microscope-based analysis of phytoplankton. PhytoNumb3rs is designed to make cell density calculation easier and to take account of qualitative and quantitative aspects regarding data precision, bias and method sensitivity. Specifically, it makes it possible to assess the performance characteristics of single analyses. PhytoNumb3rs is a user-friendly computing system based on a combination of Excel® spreadsheets. It allows the user to count phytoplankton cells, at various magnifications using various counting strategies, and to obtain the relative cell density, uncertainty and detection limit for each taxon. PhytoNumb3rs enables analysts to adopt a suitable counting strategy, run the analyses and easily perform all the steps associated with conventional microscope-based phytoplankton procedures (counting, data entry, compu-tation, and data storage in a structured database). It allows the user to calculate the performance characteristics associated with the analytical results in accordance with UNI EN 15204 (2006) quality control procedures. Finally, it represents a useful tool for data harmonisation and data standardisation which in turn, are needed in order to increase the quality, comparability and accessibility of intra- and inter-laboratory data over time.
1. Introduction
In the context of conservation, protection and management of aquatic resources, assessment of phytoplankton community structure helps to understand aquatic ecosystem functioning. Phytoplankton constitute a biological quality element that can be used to assess the ecological health status of water bodies as well as changes occurring under a range of environmental conditions including anthropogenic pressures. Demographic traits such as presence/absence, abundance and biomass have traditionally been included in directives and mon-itoring programs as descriptors of the ecological status of aquatic eco-systems (Water Framework Directive (EU/2000/60), Marine Strategy Directive (EU/2008/56), Copeland, 2016). The implementation of European Union Directives, particularly in Member States, has led to the development of monitoring plans for collecting metadata and in-formation on phytoplankton. Indeed, EU policies call for the scientific community to resolve large-scale questions facing aquatic science, such
as global warming, the spread of invasive species and resource deple-tion. All of these issues require the development of monitoring pro-grams for collecting data and the improvement of large-scale data sharing and data integration for meta-analysis. The heterogeneity of data sources creates a barrier in terms of making connections within and among multiple domains of information (Bonacin et al., 2016). Data are collected by organisations and institutions using a variety of different standards, technologies and conventions, making it difficult to combine information from different surveys or different databases.
Even though the Utermöhl method (Lund et al., 1958; Utermöhl, 1958) is the most widely adopted method to determine the abundance of phytoplankton assemblages, the procedures used for phytoplankton analysis vary widely between research and monitoring groups, despite the numerous efforts to standardise phytoplankton data. Such data may need to be used several decades after they were first gathered, by users that did not participate in their production, and a fundamental effort is thus required in order to ensure the harmonisation and consistency of
https://doi.org/10.1016/j.ecoinf.2018.06.007
Received 19 March 2018; Received in revised form 8 June 2018; Accepted 26 June 2018
⁎Corresponding author.
E-mail address:m.vadrucci@arpa.puglia.it(M.R. Vadrucci).
Ecological Informatics 46 (2018) 147–155
Available online 27 June 2018
1574-9541/ © 2018 Elsevier B.V. All rights reserved.
