ALBERT

Description: The ecological approach to comparative cognition emphasizes that the ecological and social environment are important predictors of cognitive performance. We used this approach to test whether differences in habitat use and social behavior in the facultative Caribbean cleaning goby Elacatinus prochilos predict differences in learning performance in two discriminatory two-choice tasks. This species has two behavioral ecotypes: one that frequently engages in cleaning interactions and inhabits corals in male–female pairs (cleaning gobies) and another that rarely engages in cleaning interactions and inhabits barrel sponges in large groups (sponge-dwellers). We predicted that cleaning gobies would outperform sponge-dwellers in a pattern-cued task, which consisted of identifying the pattern on a plate that consistently provided food, while sponge-dwellers would outperform cleaning gobies in a spatial task, which consisted of identifying the location of the plate. Contrary to our predictions, there was no difference in performance between the two ecotypes. Most of the gobies performed poorly in the pattern-cued task and well in the spatial task. A possible explanation for these results is that the association of a pattern with positive and negative reinforcement may not be a pre-requisite for engaging in cleaning interactions, while spatial skills might be equally required in both ecotypes. Alternatively, the two ecotypes can flexibly adjust to new feeding conditions, which would explain their similar performance in the spatial task. Further research should investigate which aspects of E. prochilos’ social and ecological environment might impose challenges that require spatial cognition and whether individuals can flexibly adjust to new habitats and feeding conditions.

Description: Marine community diversity surveys require a reliable assessment to estimate ecosystem functions and their dynamics. For these, non-invasive environmental DNA (eDNA) metabarcoding is increasingly applied in zoological studies to complement or even replace traditional morphological identification methods. However, uncertainties remain about the accuracy of the diversity detected with eDNA to capture the actual diversity in the field. Here, we validate the reliability of eDNA metabarcoding in identifying metazoan biodiversity in highly dynamic marine waters of the North Sea. We analyzed biodiversity from water (eDNA) and zooplankton samples with cytochrome c oxidase subunit 1 (COI) and 18S rRNA (18S) metabarcoding at Helgoland Roads and validated the optimal molecular resolution by morphological and molecular zooplankton identification (metabarcoding) with the result of merely a few false-negative detections. eDNA and zooplankton metabarcoding resolved 354 species from all major and in total 16 metazoan phyla. This molecular genetic species inventory overlapped by 95.9% (COI) and 81.9% (18S) with published inventories of local, morphologically identified species, among them neozoa and rediscovered species. Even though half of all species were detected by both eDNA and zooplankton metabarcoding, the methods differed significantly in their detected diversity. eDNA metabarcoding performed very well in cnidarians and annelids, whereas zooplankton metabarcoding identified higher numbers of fish and malacostraca. Species assemblages significantly differed between the individual sampling events and the cumulative number of identified species increased steadily over the sampling period and did not reach saturation. About a third of the species were detected only once while a core community of 22 species was identified continuously. Our study confirms eDNA metabarcoding to be a powerful tool to identify and analyze North Sea fauna in highly dynamic waters and we recommend investing in high sampling efforts by repetitive sampling and replication using at least 0.45 μm filters to increase filtration volume.