Aquatic Ecology最新文献

Recent studies have documented rapid environmental changes impacting biological communities, such as shifts in phytoplankton composition and size distribution, with significant implications for the nutritional quality of the marine food web. Phytoplankton-derived macromolecules, including carbohydrates (CHO), proteins (PRT), and lipids (LIP), are crucial components of marine ecosystems; however, considerable knowledge gaps remain regarding their spatiotemporal variability and ecological consequences. This study investigates seasonal and regional variations in the macromolecular composition and calorie content of particulate organic matter (POM) across the Korean Peninsula's seas, aiming to identify primary environmental factors driving these variations. Our findings highlight significant variations in POM macromolecular compositions, with CHO and LIP generally dominating over PRT across most regions and seasons, influenced by environmental factors such as temperature, nutrient concentrations, and salinity. Food material (FM), defined as the total sum of CHO, PRT, and LIP, varied significantly among regions, with the Yellow Sea exhibiting notably higher FM, reflecting elevated nutrient concentrations and productivity compared to other regions. Despite broad ranges, both FM and calorie content were, on average, were approximately 40% lower compared to values reported in a previous study. Principal component analysis and multiple linear regression analysis identified similar environmental factors influencing both FM and calorie content, highlighting the importance of regional environmental conditions. This study enhances our understanding of phytoplankton biochemical dynamics in the Korean seas and emphasizes the need for future research on size-specific FM and calorie content to better predict ecosystem responses to ongoing environmental change.

Contamination by metals is among the most pervasive anthropogenic threats to the environment and the health of higher-trophic-level species. Metal concentrations in the tissues of Squalus megalops and Raja radula collected from Bizerte Bay and the Gulf of Gabes between November 2022 and November 2023, and their respective cestode parasites, Gilquinia robertsoni and Echinobothrium affine, were analyzed using an inductively coupled plasma optical emission spectrometer and a direct mercury analyzer. Cadmium (Cd) and lead (Pb) concentrations in the muscle tissue of both elasmobranchs exceeded legislated thresholds. Mercury (Hg) concentrations in S. megalops muscle surpassed the standard limits. Gilquinia robertsoni accumulated zinc (Zn) and manganese (Mn) 10 and 13 times higher than its host muscle, and Mn four times higher than its host’s intestine in Bizerte Bay. In the Gulf of Gabes, it accrued higher concentrations than in S. megalops muscle (six times for copper (Cu); seven times for Pb and Mn; and three times for Zn). Pb was about 56 times higher in the parasite than in the intestine of the fish. Echinobothrium affine accumulated Cu, Fe approximately four times higher, and Pb seven times higher than the muscle of R. radula in Bizerte Bay and stored Pb respectively 10 and 22 times higher than the host’s intestine and liver. In the Gulf of Gabes, higher concentrations of some metals were in E. affine than those in the host muscle (seven times Cu and Pb and five times Fe), host intestine (four times cadmium (Cd) and 12 times Pb), and host liver (six times Pb). In this regard, G. robertsoni and E. affine can be considered sensitive bioindicators of metal pollution in marine ecosystems.

Phytoplankton are the microorganisms that respond most rapidly to changing environmental factors in aquatic environments. Therefore, seasonal changes are effective in phytoplankton species composition and abundance. Seasonal sampling was conducted in the open waters of Gökova Bay to determine how seasonal changes will affect phytoplankton species composition and abundance. In this study, water samples were taken for physical, chemical and phytoplankton analyses between May 2022 and February 2023 from 6 stations vertically at 3 depths (0.5 m, 10 m and the deepest point of the photic zone) in Gökova Bay in order to understand the differences in the abundance, diversity, species richness and composition of phytoplankton among stations and seasons depending on environmental factors. A total of 112 taxa were identified in the phytoplankton, including 74 Dinoflagellata, 33 Heterokontophyta, 4 Haptophyta, and 1 Cyanobacteria taxa. There were significant differences between seasons among environmental parameters and phytoplankton communities. From spring to fall, dinoflagellates were dominant in phytoplankton concerning temperature, total nitrogen, pH, and salinity, while in winter, Heterokontophyta was dominant in relation to nitrite-nitrogen concentration. According to Redundancy Analysis (RDA), environmental parameters such as total nitrogen (TN), nitrite-nitrogen (NO₂-N), temperature (T), salinity (SAL), and pH significantly affected the distribution of Lingulodinium polyedra, Ceratium furca, Scrippsiella acuminata, Protodinium simplex, Oxytoxum semicollatum, Thalassionema frauenfeldii, Ulnaria ulna, Chaetoceras curvisetus, Chaetoceros affinis, Hemiaulus hauckii, and Bacteriastrum furcatum species. It was observed that phytoplankton species richness and diversity significantly increased in spring, while phytoplankton abundance slightly increase in the same period. As a result, while temporal (seasonal) changes were detected in phytoplankton species richness, diversity, composition and abundance depending on TN, NO2-N, T, SAL and pH, spatial (station-dependent) changes were not observed.

Larval mosquito control has increasingly relied on biologically derived larvicides, yet their impacts on non-target aquatic organisms remain insufficiently understood. Among these biopesticides, Bacillus thuringiensis israelensis (Bti)-based products are widely used due to their targeted action and direct application to aquatic environments. However, such application inevitably results in the exposure of non-target species, including fish. This study evaluated the behavioral effects of acute exposure to a Bti-based biopesticide (Bti-B²) in zebrafish (Danio rerio). Fish were exposed for 30 min to Bti-B² at concentrations of 1.5, 2.5, or 10 µg.L⁻¹, and assessed for exploratory activity using the novel tank test (NTT) and for social interaction via the social preference test (SPT). Exposure to Bti-B² elicited an anxiolytic-like response without affecting social behavior. These findings suggest that even biopesticides regarded as environmentally safe, such as Bti-B², can alter behavioral endpoints in aquatic vertebrates. This highlights the importance of including ecotoxicological evaluations in the risk assessment of biologically derived pest control agents.

For many years, excessive phytoplankton blooms have raised widespread public alarm. Based on monthly monitoring data from five fixed stations in Baihua Reservoir between January 2021 and December 2022, this study evaluated the seasonal dynamics of chlorophyll a (Chl.a) and its nonlinear responses to environmental drivers. We first applied Spearman rank correlation combined with variance-inflation-factor screening (VIF < 5) to remove highly collinear predictors, then used Random Forest analysis to rank the remaining variables, identifying water temperature (WT), pH and total phosphorus (TP) as the primary drivers of Chl.a. A Generalized Additive Model (GAM) explained 56% of the variance in Chl.a, showing that Chl.a increased monotonically with WT between 10 and 18 °C, rose almost linearly with pH from 7.8 to 8.4, and exhibited a threshold response as TP approached 0.04 mg L⁻¹. This study provides a fresh approach to assess the key factors influencing Chl.a and their interactions in Baihua Reservoir.

Understanding how spatial factors shape species distribution and geographic range remains a central question in community ecology, particularly for microorganisms with high dispersal capacities. Here, we applied variation partitioning to assess the impact of multiple spatial mechanisms on the β-diversity of a bacterioplankton metacommunity in 60 shallow lakes distributed across a broad landscape. Linear overland distances between sites provided the best explanation for bacterioplankton β-diversity, likely reflecting the dominance of ubiquitous, highly abundant bacteria. In contrast, rarer bacteria were associated with local neighborhoods, suggesting lower dispersal capacities. This pattern aligns with observations in other taxa and indicates a potential rescue effect. Moreover, regardless of abundance, most bacteria appear to occupy a geographic range of 600–700 km. Our results suggest that while deterministic factors play a critical role in shaping freshwater bacterial biodiversity, the spatial context also contributes to explaining bacterioplankton dissimilarity and community dynamics. Importantly, selecting the appropriate spatial metric—whether based on presence/absence or abundance data—is crucial for accurately capturing these patterns.

This study evaluated the effects of land-use, local environmental conditions, and the presence of non-native species on fish beta diversity in headwater streams of the Iguaçu, Piquiri, and Ivaí River basins, Brazil. A total of 25 streams were sampled over three annual campaigns. Data collection encompassed environmental variables and land-use characteristics within each stream’s drainage area. Fish were sampled using electrofishing, identified, and analyzed for species richness and abundance. For each stream, the local contribution to beta diversity was calculated and partitioned into species replacement and abundance differences. Species contribution to beta diversity were also assessed. Generalized linear models indicated that streams with greater forest cover had higher species richness in the Iguaçu and Ivaí River basins, whereas a negative relationship was observed in the Piquiri River basin, likely due to local environmental stressors. Beta diversity was driven by species replacement in preserved streams and by differential abundance in degraded streams. Non-native species made greater contributions in urbanized and agricultural areas. The research highlights the importance of conserving forested streams to sustain native fish diversity, while also recognizing that even degraded areas can contribute to variation in assemblage composition in the regional diversity. Ecological restoration of impacted streams is recommended as a conservation strategy to mitigate the effects of environmental degradation and preserve beta diversity in Neotropical stream ecosystems.

Over the past century, Lake Garda has been increasingly affected by the introduction of several non-indigenous species. In early 2022, the identification of Dreissena bugensis (quagga mussel) marked the first record of a naturalized population in lakes south of the Alps. To investigate the colonization patterns of this invader and its potential interaction with the established invader D. polymorpha (zebra mussel), a comprehensive field survey was conducted in 2022 across twelve stations, encompassing littoral, sublittoral, and profundal zones, during both spring and autumn. By spring 2022, quagga mussels had colonized the littoral and sublittoral zones of nearly all stations, with higher density in the northern part of the lake and a growth rate dependent on depth. Between spring and autumn, their population continued to grow, surpassing zebra mussels at all stations and expanding into the profundal zone as well. Analysis of population structure and veliger monitoring suggest that quagga mussels likely arrived in the lake in 2019. The evidence of D. bugensis already being firmly established in Lake Garda, as well as in nearby Lake Ledro, highlights the need for biosecurity protocols to prevent further invasions and the spread of established invaders to other Italian lakes.

Understanding biodiversity trends in highly disturbed urban landscapes is essential given that anthropogenic factors continue to drive global biodiversity loss. Within marine ecosystems, macrofaunal fouling communities, aggregations of epibenthic invertebrates that colonize human-made structures, represent an ecologically important subset of urban coastlines. Tampa Bay is a highly urbanized estuary in Florida, USA, and is home to the state’s largest port. Although many factors may contribute to the communities that form on urban structures, understanding the local drivers underpinning their assemblages is essential for management. We investigated relationships among spatial distribution, season, invasive species, and environmental factors and community richness to better understand macrofaunal fouling communities living on floating docks around Tampa Bay. We collected samples by scraping collections along transects below the water line of floating docks and then counting and identifying collected organisms to the lowest possible taxonomic unit. Our analyses show variation in taxonomic richness driven by changes in mean temperature. Although salinity and total dissolved solids varied significantly with location in the bay, we observed no significant correlation between these factors and taxonomic richness. Invasive striped barnacles occurred in high abundances throughout the bay; however, the historically dominant Asian green mussel appeared to be reduced in number. This study serves as a baseline to study nearshore fouling community structure and improve restoration and management of epibenthic macrofauna in this important urban estuary.

Cyanobacteria play a fundamental role in aquatic ecosystems, contributing to global biogeochemical cycles and serving as indicators of environmental change. Their classification is critical for monitoring water quality, detecting harmful algal blooms and understanding ecosystem dynamics. However, accurate identification remains a major challenge due to their vast taxonomic diversity and significant morphological similarities. Visual inspection alone is often insufficient, highlighting the need for computational approaches to enhance classification accuracy. In this study, we present a multimodal deep learning model that combines convolutional neural networks (CNNs) for image-based feature extraction with bidirectional transformers for text embedding. These complementary features are fused via concatenation to improve species-level classification. To our knowledge, this is the first application of a multimodal neural architecture integrating CNNs and bidirectional transformers for cyanobacteria classification. We evaluated five CNN backbones of varying depth, resulting in eight model configurations. Performance is benchmarked against unimodal CNN models that rely solely on image data. The model is trained and validated on a dataset of 1660 microscopic images and corresponding textual descriptions, covering nine cyanobacterial genera across three taxonomic orders. Results demonstrate the potential of multimodal deep learning to improve classification performance, supporting the development of scalable and accurate identification tools in microbiology and environmental monitoring.