Effect of water motion and microhabitat preferences on spatio-temporal variation of epiphytic communities: a case study in an artificial rocky reef system, Laoshan Bay, China

Seasonal dynamics response mechanism of benthic microbial community to artificial reef habitats

Artificial reefs (ARs) have been globally deployed to enhance and restore coastal resource and ecosystems. Microorganisms play an essential role in marine ecosystems, while the knowledge regarding the impact of ARs on microecology is still limited, particularly data concerning the response of benthic microbial community to AR habitats. In this study, the seasonal dynamics of benthic microbial community in AR and adjacent non-artificial reef (NAR) areas surrounding Xiaoshi Island were investigated with high-throughput sequencing technology. The results revealed that the diversity and structure of microbial community between AR and NAR both displayed pronounced seasonal dynamics. There was a greater influence of season factors on microbial communities than that of habitat type. The microbial communities in AR and NAR habitats were characterized by a limited number of abundant taxa (ranging from 5 to 12 ASVs) with high relative abundance (8.35-25.53%) and numerous rare taxa (from 5994 to 12412 ASVs) with low relative abundance (11.91%-24.91%). Proteobacteria, Bacteroidota and Desulfobacterota were the common predominant phyla, with the relative abundances ranging from 50.94% to 76.76%. A total of 52 biomarkers were discovered, with 15, 4, 6, and 27 biomarkers identified in spring, summer, autumn and winter, respectively. Co-occurrence network analysis indicated that AR displayed a more complex interaction pattern and higher susceptibility to external disturbances. Furthermore, the neutral model and βNTI analyses revealed that the assembly of microbial communities in both AR and NAR is significantly influenced by stochastic processes. This study could provide valuable insights into the impact of ARs construction on the benthic ecosystems and would greatly facilitate the development and implementation of the future AR projects.

The effects of flow field on the succession of the microbial community on artificial reefs

The flow field is one of the most important external conditions affecting the development of biofouling community on artificial reefs (ARs), especially the microbial community. In this article, we investigated the temporal dynamics of microbial communities between the stoss side and the lee side of ARs. The results showed that the composition and structure of microbial and macrobenthic communities between the stoss side and the lee side both presented obvious temporal variations. Microbial diversity and richness were higher on the stoss side than that on the lee side. There was a greater impact on bacterial and archaeal communities on temporal scale compared to that on micro-spatial scale, which was not suitable for the fungal community. The organism biomass, abundance and coverage of macrobenthic community on the lee side were higher than those on the stoss side, and the microbial diversity on the stoss side increased significantly with the organism coverage.

Ensemble habitat suitability modeling for predicting optimal sites for eelgrass (Zostera marina) in the tidal lagoon ecosystem: Implications for restoration and conservation

Seagrass systems are in decline, mainly due to anthropogenic pressures and ongoing climate change. Implementing seagrass protection and restoration measures requires accurate assessment of suitable habitats. Commonly, such assessments have been performed using single-algorithm habitat suitability models, nearly always based on low environmental resolution information and short-term species data series. Here we address eelgrass (Zoostera marina) meadows' large-scale decline (>80%) in Shandong province (Yellow Sea, China) by developing an ensemble habitat model (EHM) to inform eelgrass conservation and restoration strategies in the Swan Lake (SL). For this, we applied a weighted EHM derived from ten single-algorithm models including profile, regression, classification, and machine learning methods to generate a high-resolution habitat suitability map. The EHM was constructed based on the predictive performances of each model, by combining a series of present-absent eelgrass datasets from recent years coupled with oceanographic and sediment data. The model was cross-validated with independent historical datasets, and a final habitat suitability map for conservation and restoration was generated. Our EHM scheme outperformed all single models in terms of habitat suitability, scoring ∼0.95 for both true statistic skill (TSS) and area under the curve (AUC) performance criteria. Machine learning methods outperformed profile, regression and classification methods. Regarding model explanatory variables, overall, topographic characteristics such as depth (DEP) and seafloor slope (SSL) are the most significant factors determining the distribution of eelgrass. The EHM predicted that the overlapping area was almost 90% of the current eelgrass habitat. Using results from our EHM, a LOESS regression model for the relationship of the habitat suitability to both the biomass and density of Z. marina outperformed better than the classic Ordinary Least Squares regression model. The EHM is a promising tool for supporting eelgrass protection and restoration areas in temperate lagoons as data availability improves.

Ecological and Industrial Implications of Dynamic Seaweed-Associated Microbiota Interactions

Seaweeds are broadly distributed and represent an important source of secondary metabolites (e.g., halogenated compounds, polyphenols) eliciting various pharmacological activities and playing a relevant ecological role in the anti-epibiosis. Importantly, host (as known as basibiont such as algae)–microbe (as known as epibiont such as bacteria) interaction (as known as halobiont) is a driving force for coevolution in the marine environment. Nevertheless, halobionts may be fundamental (harmless) or detrimental (harmful) to the functioning of the host. In addition to biotic factors, abiotic factors (e.g., pH, salinity, temperature, nutrients) regulate halobionts. Spatiotemporal and functional exploration of such dynamic interactions appear crucial. Indeed, environmental stress in a constantly changing ocean may disturb complex mutualistic relations, through mechanisms involving host chemical defense strategies (e.g., secretion of secondary metabolites and antifouling chemicals by quorum sensing). It is worth mentioning that many of bioactive compounds, such as terpenoids, previously attributed to macroalgae are in fact produced or metabolized by their associated microorganisms (e.g., bacteria, fungi, viruses, parasites). Eventually, recent metagenomics analyses suggest that microbes may have acquired seaweed associated genes because of increased seaweed in diets. This article retrospectively reviews pertinent studies on the spatiotemporal and functional seaweed-associated microbiota interactions which can lead to the production of bioactive compounds with high antifouling, theranostic, and biotechnological potential.

Freshwater diatom biomonitoring through benthic kick-net metabarcoding

Biomonitoring is an essential tool for assessing ecological conditions and informing management strategies. The application of DNA metabarcoding and high throughput sequencing has improved data quantity and resolution for biomonitoring of taxa such as macroinvertebrates, yet, there remains the need to optimise these methods for other taxonomic groups. Diatoms have a longstanding history in freshwater biomonitoring as bioindicators of water quality status. However, multi-substrate periphyton collection, a common diatom sampling practice, is time-consuming and thus costly in terms of labour. This study examined whether the benthic kick-net technique used for macroinvertebrate biomonitoring could be applied to bulk-sample diatoms for metabarcoding. To test this approach, we collected samples using both conventional multi-substrate microhabitat periphyton collections and bulk-tissue kick-net methodologies in parallel from replicated sites with different habitat status (good/fair). We found there was no significant difference in community assemblages between conventional periphyton collection and kick-net methodologies or site status, but there was significant difference between diatom communities depending on site (P = 0.042). These results show the diatom taxonomic coverage achieved through DNA metabarcoding of kick-net is suitable for ecological biomonitoring applications. The shift to a more robust sampling approach and capturing diatoms as well as macroinvertebrates in a single sampling event has the potential to significantly improve efficiency of biomonitoring programmes that currently only use the kick-net technique to sample macroinvertebrates.