Spotting intruders: Species distribution models for managing invasive intertidal macroalgae

Valorisation of the Invasive Macroalgae Undaria pinnatifida (Harvey) Suringar for the Green Synthesis of Gold and Silver Nanoparticles with Antimicrobial and Antioxidant Potential

Bacterial and fungal infections are a challenging global problem due to the reported increasing resistance of pathogenic microorganisms to conventional antimicrobials. Nanomaterials are a promising strategy to fight infections caused by multidrug-resistant microbes. In this work, gold (Au@UP) and silver (Ag@UP) nanoparticles were produced for the first time by green synthesis using an aqueous extract of the invasive macroalgae Undaria pinnatifida (UP). The nanoparticles were characterized by a wide range of physicochemical techniques. Au@UP and Ag@UP demonstrated to be spherical and crystalline with an average size of 6.8 ± 1.0 nm and 14.1 ± 2.8 nm, respectively. Carbohydrates and proteins of the UP extract may participate in the synthesis and capping of the nanoparticles. The UP extract, Ag@UP, and Au@UP were assessed for their antimicrobial activity against Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa, Candida albicans, and Candida auris. Ag@UP showed the highest antimicrobial activity with very low MIC and MBC values for all the tested bacteria, and Au@UP demonstrated to be very effective against biofilm-producing bacteria. The antifungal properties of both Ag@UP and Au@UP were remarkable, inhibiting hyphae formation. This study points towards a very promising biomedical exploitation of this invasive brown algae.

The effects of intraspecific variation on forecasts of species range shifts under climate change

As global climate change is altering the distribution range of macroalgae across the globe, it is critical to assess its impact on species range shifts to inform the biodiversity conservation of macroalgae. Latitude/environmental gradients could cause intraspecific variability, which may result in distinct responses to climate change. It remains unclear whether geographical variation occurs in the response of species' populations to climate change. We tested this assumption using the brown alga Sargassum thunbergii, a habitat-forming macroalgae encompassing multiple divergent lineages along the Northwest Pacific. Previous studies revealed a distinct lineage of S. thunbergii in rear-edge populations. Given the phylogeographic structure and temperature gradients, we divided these populations into the southern and northern groups. We assessed the physiological responses of the two groups to temperature changes and estimated their niche differences using n-dimensional hypervolumes. A higher photosynthetic rate and antioxidative abilities were detected in the southern group of S. thunbergii than in the northern group. In addition, significant niche differentiation was detected between the two groups, suggesting the possibility for local adaptation. Given these results, we inferred that the southern group (rear-edge populations) may be more resilient to climate change. To examine climate-driven range shifts of S. thunbergii, we constructed species- and lineage-level species distribution models (SDMs). Predictions of both levels showed considerable distribution contracts along the Chinese coasts in the future. For the southern group, the lineage-level model predicted less habitat loss than the species-level model. Our results highlight the importance of considering intraspecific variation in climate change vulnerability assessments for coastal species.

Brown Macroalgae Sargassum cristaefolium Extract Inhibits Melanin Production and Cellular Oxygen Stress in B16F10 Melanoma Cells

The brown macroalgae Sargassum has been reported for its anti-UV and photoprotective potential for industrial applications. This study evaluated the melanin inhibition activity of Sargassum cristaefolium (SCE) ethanol extract. Melanogenesis inhibition by SCE was assessed in vitro with B16-F10 melanoma cell models and in silico against melanin regulatory proteins Tyrosinase (TYR) and Melanocortin 1 Receptor (MC1R). The regulatory properties evaluated were the melanin content, intracellular tyrosinase activity and cellular antioxidant activities. In addition, the bioactive compounds detected in SCE were subjected to molecular docking against TYR and MC1R. Based on the results, 150 µg/mL SCE effectively inhibited the production of melanin content and intracellular tyrosinase activity. Cellular tyrosinase activity was reduced by SCE-treated cells in a concentration-dependent manner. The results were comparable to the standard tyrosinase inhibitor kojic acid. In addition, SCE effectively decreased the intracellular reactive oxygen species (ROS) levels in B16-F10 cells. The antioxidant properties may also contribute to the inhibition of melanogenesis. In addition, LCMS UHPLC-HR-ESI-MS profiling detected 33 major compounds. The results based on in silico study revealed that the bioactive compound putative kaurenoic acid showed a strong binding affinity against TYR (-6.5 kcal/mol) and MC1R (-8.6 kcal/mol). However, further molecular analyses are needed to confirm the mechanism of SCE on melanin inhibition. Nevertheless, SCE is proposed as an anti-melanogenic and antioxidant agent, which could be further developed into cosmetic skin care products.

The Effects of Secondary Growth of Spartina alterniflora after Treatment on Sediment Microorganisms in the Yellow River Delta

As a typical invasive species, Spartina alterniflora is widely recognized as one of the primary threats to biodiversity in various habitats, including wetlands. Although the invasion by S. alterniflora has been managed in multiple ways, it may reappear after treatment. How S. alterniflora affects the soil microbial community in coastal wetlands during its regeneration process has not yet been clarified. Here, rhizosphere soil samples (RSPs) and bulk soil samples (SSPs) were collected in the S. alterniflora community and a high-throughput sequencing method was conducted to analyze the composition and diversity of soil microorganisms. Meanwhile, we also obtain the soil physicochemical properties. In the present study, there was no significant difference in the alpha diversity of both bacterial and fungal communities in the SSP and RSP groups. The PCoA (principal coordinate analysis) also showed that the microbial community structure did not differ significantly between the SSP and RSP groups. The results showed that except for pH, the total sulfur (TS) content, total nitrogen (TN) content, and electrical conductivity (EC) did not differ significantly (p > 0.05) between the SSP and RSP groups. The composition of the bacterial and fungal community in the rhizosphere of S. alterniflora was similar to that found in the surrounding soils. The top two dominant bacterial phyla were Proteobacteria and Desulfobacterota in the present study. Venn diagram results also support this view; most OTUs belong to the common OTUs of the two groups, and the proportion of unique OTUs is relatively small. The LEfSe (LDA effect size) analysis showed that Campylobacterota (at the phylum level) and Sulfurimonas (at the genus level) significantly increased in the RSP group, implying that the increased Sulfurimonas might play an essential role in the invasion by S. alterniflora during the under-water period. Overall, these results suggest that the bacterial and fungal communities were not significantly affected by the S. alterniflora invasion due to the short invasion time.

A multifaceted ecological assessment reveals the invasion of the freshwater red macroalga Montagnia macrospora (Batrachospermales, Rhodophyta) in Taiwan

Invasive freshwater macroalgae are rarely described. Montagnia macrospora is a freshwater red alga introduced from South America to East Asia via the global aquarium trade. The earliest occurrence record of this alga in Taiwan is dated 2005. To determine whether M. macrospora has become invasive in Taiwan and to understand the traits that facilitated its invasion, we took a multifaceted approach that combines examination of ecological background and population genetic analysis. Our island-wide survey showed that M. macrospora is widespread in the field across Taiwan, where the climate greatly differs from that of South America, and can self-sustain for nearly a decade. Our population genetic analysis revealed a lack of genetic diversity of M. macrospora in Taiwan, consistent with the hypothesis that the alga expanded through asexual reproduction. Moreover, during our long-term ecological assessments and field surveys, we observed that M. macrospora is an ecological generalist that can survive in a wide range of temperature, pH, illumination, and nutrient enrichment. Taken together, our data suggest that M. macrospora has successfully invaded the freshwater ecosystems of Taiwan, likely due to its ability to disperse asexually and to grow under broad environmental conditions. We hope that our study brings attention to invasive freshwater algae, which have been overlooked in conservation planning and management.

Selection of predictor variables for species distribution models: a case study with an invasive marine bryozoan

Species distribution models (SDMs) are important tools for predicting the occurrence and abundance of organisms in space and time, with numerous applications in ecology. However, the accuracy and utility of SDMs can be compromised when predictor variables are selected without careful consideration of their ecophysiological relevance to the focal organism. We conducted an in-depth examination of the variable selection process by evaluating predictors to be used in SDMs for Membranipora membranacea, an ecologically significant marine invasive species with a complex lifecycle, as a case study. Using an information-theoretic and multi-model inference approach based on generalized linear mixed models, we assessed multiple environmental variables (depth, kelp density, kelp substrate, temperature, and wave exposure) as predictors of the abundance of multiple life stages of M. membranacea, investigating species-environment relationships and relative and absolute variable importance. We found that the relative importance of a predictor, the metric calculated to represent a predictor, and whether a predictor was proximal or distal were important considerations in the variable selection process. Data constraints (e.g. sample size, characteristics of available predictor data) may inhibit accurate assessment of predictor variables during variable selection. Importantly, our results suggest that species-environment relationships derived from small-scale studies can inform variable selection for SDMs at larger spatiotemporal scales. We developed a conceptual framework for variable selection for SDMs which can be applied to most contexts of species distribution modelling, but particularly those with several candidate predictors and a large dataset.