DNA metabarcoding and morphological analysis - Assessment of zooplankton biodiversity in transitional waters
Introduction
Transitional waters (estuaries, deltas, lagoons) belong to the most productive ecosystems and provide important habitats for a plethora of species, particularly during their juvenile and reproductive life stages (Milardi et al., 2018). Such waters also act as important nursery areas for many (commercially) important fish species (Tournois et al., 2017), to which zooplankton is a very important food source. These distinct coastal ecosystems are characterised by composite gradients (Tagliapietra et al., 2009) that have a prominent role in the organization of biological communities (Reizopoulou et al., 2014), as they directly influence productivity, colonization and dispersal processes (Ghezzo et al., 2015). In addition, they are strongly characterized by temporal variability of hydrodynamic (fresh water inputs, meteo-marine conditions) and thermo-haline factors that lead to a high natural instability, consequently resulting in wide seasonal variations of pelagic species diversity (Reizopoulou et al., 2014). Zooplankton in transitional environments occupies a variety of niches and significantly contributes to key ecosystem functions due to its high functional diversity (Morabito et al., 2018), not only as prey for juvenile fish species, but also as consumers of primary production. In general, in transitional environments the species are adapted to high environmental variability and show a decrease in species richness, an increase in abundance and a greater importance of small taxa along a confinement gradient (Belmonte et al., 2013; Riccardi, 2010). Due to its pronounced degree of unpredictability, however, the impact of local and large-scale environmental changes on planktonic population dynamics is hard to evaluate (Morabito et al., 2018).
In this framework, high taxonomic resolution assessments of zooplankton biodiversity accompanied with species richness estimations are essential. As accurate morphological assessments are labour-intensive, the characterization of the spatio-temporal variability of zooplankton assemblages is scarcely investigated despite their ecological importance (Djurhuus et al., 2018). Moreover, the complexity of zooplankton assemblages, including cryptic and sibling species, and the lack of diagnostic characters for immature (larval) stages are key impediments to understand patterns of biodiversity with classical taxonomic identification methods (Bucklin et al., 2016). Regardless of the rising necessity for taxonomic information across trophic levels to support ecological research and ecosystem-based management, morphological taxonomic expertise is in decline and its importance often underestimated (Hopkins and Freckleton, 2002; Kim and Byrne, 2006). Additionally, in transitional waters, monitoring requires high sampling effort in order to take into account the above-mentioned spatial and temporal variability, even more so regarding zooplankton, which is especially sensitive to altering environmental conditions (Hays et al., 2005; Richardson, 2008).
The estimation of biodiversity with DNA metabarcoding (Taberlet et al., 2012) using high-throughputsequencing (HTS) is becoming an important tool for surveying biodiversity thanks to the broad taxonomic coverage and the possibility of increased sample processing speed allowing to increase the sampling effort (frequency and spatial coverage) with sustainable costs (Brannock et al., 2014; Coissac et al., 2012). An additional significant advantage is the prospective to detect the ‘hidden diversity’ of zooplankton assemblages, including holo-, mero- and ichthyoplankton (Lindeque et al., 2013). As most marine species are planktonic at some point in their life cycle, this will give us new insights into the overall marine biodiversity (Bucklin et al., 2016). Several studies have shown that DNA metabarcoding can be used as an efficient tool for zooplankton biodiversity assessments in various marine environments (e.g. Bucklin et al., 2019; Deagle et al., 2018; Harvey et al., 2017; Stefanni et al., 2018). With constant progress in this technology, metabarcoding will be extremely helpful in the study of community changes e.g. driven by climate change or other habitat alterations and studies of the ecology of cryptic taxa within zooplankton assemblages (Sommer et al., 2017).
The present study aims at evaluating the suitability of DNA metabarcoding for assessments of zooplankton diversity patterns in transitional waters using a fragment (313 bp) of the cytochrome c oxidase subunit 1 (COI) corresponding to the second half of the universal animal DNA barcode (Leray et al., 2013), a DNA metabarcoding marker for which several studies have demonstrated its high value when studying marine metazoans (Carroll et al., 2019; Clarke et al., 2017; Stefanni et al., 2018; Zhang et al., 2018). Two important Mediterranean heterogeneous ecosystems were chosen as study area: the Gulf of Venice and the Venice Lagoon, located in the north-western Adriatic Sea, both of which are subject of investigation within the Long Term Ecological Research (LTER) network (LTER_EU_IT_016 and LTER_EU_IT_057, respectively), the Biodiversity and Ecosystem Research LifeWatch-ERIC, and the European WFD and MSFD directives. In this context, there is a need to increase the knowledge on the zooplankton biodiversity and non-indigenous species (NIS), in order to support the definition of Good Environmental Status (GES) and the identification of management strategies.
This study compares the molecular and morphological approach along environmental gradients and over the year, evaluating it as a tool for zooplankton biodiversity investigations in ecosystems with high spatial and temporal variability and where high frequency monitoring is preferable.
Section snippets
Study area
The Venice Lagoon is located in the Northern Adriatic Sea, a shallow coastal area (mean depth of 35 m) strongly influenced by the inputs of large rivers bringing water from the Alps and characterized by meso-eutrophic conditions and by a remarkable spatial and temporal variability of trophic and physico-chemical gradients (Bernardi Aubry et al., 2006) (Fig. 1). The Gulf of Venice in the Northern Adriatic is a highly productive ecosystem and important nursery area, especially for fish species.
Taxonomical composition and richness of molecular and morphological data
The raw sequencing data produced more than 4 × 106 raw sequences in the 24 samples analysed. After quality check and chimera removal, the 1.97 × 106 left sequences had a mean length of 311.9 bp and a median length of 313 bp (Fig. 2A).
At the similarity threshold of 97% mostly Arthropoda, followed by Cnidaria, Chordata and Echinodermata were identified, while the alignment at 94% similarity threshold resulted mostly in Sagittidae (Chaetognatha), Branchostomatidae, Percomorphaceae (Chordata) and
Discussion
This study demonstrates that COI metabarcoding can be successfully applied to follow zooplankton biodiversity in such complex and seasonally changing environments as transitional waters. In this study, the effectiveness of DNA metabarcoding was confirmed on three levels. First, this approach revealed a substantial level of often overlooked diversity of zooplankton, mostly due its ability in detecting the diversity of mero- and ichthyoplankton. Second, the ecological analysis revealed that DNA
Conclusion
Safeguarding the biodiversity of coastal and transitional waters is an environmental priority and a main objective of European legislation frameworks (Water Framework Directive, WFD, 2000/60/EC; Marine Strategy Framework Directive, MSFD, 2008/56/EC). Metabarcoding became a promising tool for biodiversity assessment, but protocol biases and issues regarding the reference database reduce its reliability. In this study, an innovative bioinformatic pipeline has been applied. In addition to the
CRediT authorship contribution statement
Anna Schroeder: Data curation, Visualization, Investigation, Formal analysis, Writing - original draft. David Stanković: Formal analysis, Data curation, Methodology, Writing - review & editing. Alberto Pallavicini: Conceptualization, Supervision, Data curation, Funding acquisition, Writing - review & editing. Fabrizia Gionechetti: Formal analysis. Marco Pansera: Data curation, Formal analysis, Investigation. Elisa Camatti: Conceptualization, Data curation, Funding acquisition, Supervision,
Declaration of competing interest
None.
Acknowledgments
This study is based on a monitoring program within LTER-ITALY (Italian Long-Term Ecological Research Network) that we wish to acknowledge. A.S. was supported by the joint PhD Program “Environmental Life Sciences” of the University of Trieste and the University of Udine co-financed by the National Research Council, Institute of Marine Sciences (CNR ISMAR). D.S. was financially supported by Slovenian Ministry of Education, Science and Sport and the European Regional Development Fund (Operational
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