Influence of sampling effort on ecological descriptors and indicatorsin perturbed and unperturbed conditions: A study case using benthicmacroinvertebrates in Mediterranean transitional waters

tThe effectiveness and accuracy of biomonitoring programs, based on benthic macroinvertebrates, isstrictly related to the sampling design and effort, whereas the feasibility depends on the economic sus-tainability of sample collection and processing methodologies. In the last decade, how to improve theRapid Bioassessment Protocols (RBPs) maintaining the accuracy of the results has been a topic recur-rently debated among researchers. It is well known that the sample unit size (i.e., surface of the sampledarea, SUS) and the sieve mesh size (SMS), selected to collect and to retain benthic macroinvertebratesfrom soft-bottom samples, may affect the evaluation of the aquatic ecosystem ecological status; however,studies analyzing the combined influence of SUS and SMS on assessment tools are lacking, in particu-lar for transitional water ecosystems. Even if the Water Framework Directive (WFD) suggests rapid andcost-effectiveness sampling effort and procedures, the identification of optimal SUS and SMS is a basicstep to improve the RBPs and to meet WFD suggestions. Therefore, this research analyses the effects offour soft-bottom sample unit sizes (0.0225 m2, 0.0450 m2, 0.0675 m2, 0.0900 m2), and three sieve meshsizes (4 mm2, 1 mm2, 0.25 mm2) on the selection of benthic macroinvertebrates and, thus, on assessmenttools, in a Mediterranean lagoon. A sampling survey was performed in September 2009 at a perturbedand an unperturbed study site in the Lesina lagoon (SE Italian coastline); three replicates were taken foreach SUS and SMS using an Ekman–Birge grab (15 cm × 15 cm). The samples were sieved on a column ofthree sieves, with decreasing mesh size. Benthic macroinvertebrates were sorted, identified, measured,weighted and included in twelve datasets (4 SUS × 3 SMS). Sampling effort (SE) was calculated for eachSUS and SMS combination as: SE = [SUS m2× (1/SMS mm2)] × 100. Four simple community descriptors(numerical density, taxonomic richness, biomass density, individual body-size) and four ecological indi-cators (AMBI, BENTIX, BITS, M-AMBI) were compared for each combination of SUS and SMS in both studysites. Simple community descriptors and ecological indicators varied significantly between perturbedand unperturbed study site. The results showed that SMS had significant effects on simple communitydescriptors and ecological indicators, except for BITS index. Conversely, no significant differences wereobserved for different SUS analyzing simple community descriptors and ecological indicators, exceptfor taxonomic richness and M-AMBI index. The response of the ecological indicators was only slightlyaffected by the SMS, whereas SUS choice did not influence the ecological status assessment. Anyway,using the larger SMS (4 mm2), all ecological indicators showed either the same ecological quality statusas the 1 mm2and 0.25 mm2SMS or, in some cases, one class higher, except for the AMBI index