Performance of the STAR Icmi Macroinvertebrate Index and Implications for Classification and Biomonitoring of Rivers

Performance of the STAR Icmi Macroinvertebrate Index and Implications for Classification and Biomonitoring of Rivers

Knowl. Manag. Aquat. Ecosyst. 2017, 418, 20 Knowledge & © D. Spitale, Published by EDP Sciences 2017 Management of Aquatic DOI: 10.1051/kmae/2017012 Ecosystems www.kmae-journal.org Journal fully supported by Onema RESEARCH PAPER Performance of the STAR_ICMi macroinvertebrate index and implications for classification and biomonitoring of rivers Daniel Spitale1,2,* 1 BioMonitoring Team, Via Stenico 2, 38095 Tre Ville, Italy 2 Museo delle Scienze À MUSE, Limnology and Phycology Section, Corso del Lavoro e della Scienza 3, 38123 Trento, Italy Abstract – Although biomonitoring is the core approach adopted by the European Union’s Water Framework Directive (WFD), many biotic indices still lack a thorough analysis of their performance and uncertainty. The multihabitat sampling and the application of STAR_ICMi index on macroinvertebrates are the standard methods to assess the ecological status of rivers in Italy. Ever since the Italians’ implementation, dates back to 2010, few studies have tested the index performance with different sampling efforts, and even rarer are those assessing index uncertainty. However, these are worthwhile topics to investigate because all the Environmental Agencies are applying this index with both ecological and economic consequences. Aims of this study were (i) to assess the effect of subsampling on the STAR_ICMi index, (ii) to propose a standard method to calculate the index precision, and (iii) to test several less time- consuming alternatives to census all the individuals in the sample. I showed that the index is strongly affected by subsampling, and unbiased comparisons of ecological status can only be done at the same sampling effort. The index precision, calculated by bootstrapping the observed abundance of taxa, was so low in some circumstances, to increase the risk of misclassification. Finally, I showed that to avoid counting all the individuals in a sample, it is possible to estimate the most abundant taxa using a rank-abundance model. With this less time-consuming method, the STAR_ICMi index is predicted with sufficient precision. Keywords: sampling effort / rarefaction / index uncertainty / sampling variation / Italy Résumé – Performance de l’indice macroinvertébrés STAR_ICMi et implications pour la classification et la biosurveillance des cours d’eau. Bien que le biomonitoring soit l’approche de base adoptée par la directive-cadre sur l’eau de l’Union européenne, de nombreux indices biotiques manquent encore d’une analyse approfondie de leur performance et de leur incertitude. L’échantillonnage multihabitat et l’application de l’indice STAR_ICMi sur les macroinvertebrés sont les méthodes standard pour évaluer l’état écologique des rivières en Italie. Depuis leur mise en œuvre qui remonte à 2010, peu d’études ont testé la performance de l’indice avec différents efforts d’échantillonnage, et encore plus rares sont ceux qui évaluent l’incertitude de l’indice. Cependant, ce sont des sujets intéressants à étudier parce que toutes les agences environnementales appliquent cet indice avec des conséquences écologiques et économiques. Les objectifs de cette étude étaient les suivants : (i) évaluer l’effet du sous-échantillonnage sur l’indice STAR_ICMi, (ii) proposer une méthode standard pour calculer la précision de l’indice et (iii) tester plusieurs alternatives moins coûteuses au recensement de tous les individus dans l’échantillon. L’indice est fortement influencé par le sous-échantillonnage et des comparaisons impartiales de l’état écologique ne peuvent être faites qu’au même effort d’échantillonnage. La précision de l’indice, calculée par la méthode de bootsrapping sur l’abondance observée de taxons, était très faible dans certaines circonstances, augmentant le risque de classification erronée. Finalement, pour éviter de compter tous les individus d’un échantillon, il est possible d’estimer les taxons les plus abondants en utilisant un modèle de rang-abondance. Avec cette méthode moins longue, l’indice STAR_ICMi est estimé avec une précision suffisante. Mots clés : effort d’échantillonnage / raréfaction / incertitude d’indice / variation d’échantillonnage / Italie * Corresponding author: [email protected] This is an Open Access article distributed under the terms of the Creative Commons Attribution License CC-BY-ND (http://creativecommons.org/licenses/by-nd/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. If you remix, transform, or build upon the material, you may not distribute the modified material. D. Spitale: Knowl. Manag. Aquat. Ecosyst. 2017, 418, 20 1 Introduction consequences in terms of expensive remedial measures but also as missed economic benefits. Biological monitoring, or biomonitoring, is the use of biota In Italy, like in many MS of EU, macroinvertebrate indices to track changes in the environment (Friberg et al., 2011). In are calculated examining a variable number of individuals freshwater habitats, biomonitoring is a key tool used by (Bennett et al.,2011). However, the use of unfixed abundance managers and environmental agencies to support their hinders the correct comparison of samples because of the decisions. In European Union, the Water Framework Directive inconsistentsampling effort.Weurgently need additionalstudies (WFD 2000/60/EC) is the main normative in the field of water addressing the effect of this unfixed abundance on bioassess- monitoring and conservation. The WFD introduced profound ment. The ecological status of many rivers could be wrongly innovations, changing the perspective of monitoring from a assigned only as a result of this source of error. Moreover, the mere detection of pollution to a determination of the ecological lack of a measure of uncertainty in the STAR_ICMi index is a status comparing the observed status against the reference serious drawback, which should be overcome (Friberg, 2014). condition. Even though this approach is ecologically sound, as An estimate of uncertainty can help the Environmental Agencies any measurement of the ecological status, it is associated with in interpreting situations in which the ecological status of rivers an unknown source of uncertainty that would hamper a correct falls near boundary classes. If on one hand a careful attention to decision-making process by water managers (Friberg, 2014). these topics seems desirable, it should be admitted that the The benthic macroinvertebrates are indicators used application of the STAR_ICMi index is more demanding in throughout the world for evaluating the river quality for their terms of time, in respect to early indices like the IBE (the Italian capacity to assess multiple anthropogenic pressures. Member version of the Extended Biotic Index, Ghetti, 1997). Therefore, it States of EU employ different sampling methods to collect seems useful to devise alternative methods ensuring rigorous macroinvertebrates in rivers (e.g. fixed time kick sampling, assessments in shorter time. Surber sampler on fixed or not area), and they record Aim of the study was threefold. (1) To test if and to what abundance either using real estimates or classes (Bennett et al., extent subsampling has an effect on the STAR_ICMi index and 2011). Although assessed in the early stages of the classification of the water bodies; (2) to suggest a method able intercalibration process among Member States, the use of to provide a measure of index precision, even on a single fixed number of individuals to calculate macroinvertebrate sample basis; and (3) to assess the effects of less time- index was not widely adopted (Clarke et al., 2006a). However, consuming alternatives to the complete census of individuals the effect of using different sampling efforts (=different in the samples. number of individuals) has long been recognised as a serious pitfall in comparing samples (Gotelli and Colwell, 2001). 2 Methods In Italy, the ecological status of rivers is assessed using diatoms, macrophytes, fish and macroinvertebrates, each one 2.1 The multihabitat approach with specific methods and procedures (ISPRA, 2014). Concerning macroinvertebrates, the sampling method relies The multihabitat approach has been devised to provide a on the multihabitat approach (Hering et al., 2003), and the standardised assessment of the macroinvertebrates community ecological status is calculated with the STAR_ICMi index as in a water body. The method requires two steps: (1) visual fi ratio with the reference condition (Buffagni et al., 2006; quanti cation of the different abiotic substrates within a Bennett et al., 2011). The STAR_ICMi (for an historical representative river reach, and (2) proportional assignments of account of the index see Bo et al., 2016) is a multimetric index samples according to the area occupied by substrates. For composed of 6 metrics thought to represent different aspects of example, if in a reach the relative abundance of substrates is 80% > – the macroinvertebrate community. Even though the perfor- megalithal (stones 40 cm) and 20% mesolithal (20 40 cm), mance of this index has been extensively tested across Europe the multihabitat sampling requires to collect 8 subsamples on megalithal and 2 on mesolithal. Subsamples are taken disturbing especially for harmonisation purpose (e.g. Bennett et al., 2 2011), a wide knowledge gap still exists concerning the an area of 0.1 m and collecting macroinvertebrates with an hand accuracy of the metrics (but see Clarke et al., 2006b; Clarke, net (mesh size 500 micron). In standard biomonitoring 2013;

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