Aquatic Ecology最新文献

The primary objective of this study was to develop a scientific framework for analyzing catch patterns and determining the most suitable fishing quotas for tuna and tuna-like species in southern Iranian waters. Given the ecological and economic importance of these species, an effective assessment approach is essential for sustainable fisheries management. A 26-year dataset (1997–2022) on tuna and tuna-like catches from the Persian Gulf and the Sea of Oman was analyzed using the Transparent Analytical Framework (TAF) within the R programming environment. Time series forecasting models—specifically, ARIMA and Extreme Learning Machine (ELM) neural networks—were applied to predict future catch trends. Model performance was evaluated using statistical metrics including Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). The results revealed a statistically significant increasing trend in total catch over the study period (significance level 0.9, P < 0.05). Among the species assessed, Yellowfin Tuna (YFT) and Longtail Tuna (LOT) were identified as overexploited and full exploited with high and medium depletion rates (“red” and “yellow” status), while Skipjack Tuna (SKJ), Kawakawa (KAW), Frigate Tuna (FRI), Narrow-barred Spanish Mackerel (COM), and Indo-Pacific Spanish Mackerel (GUT) showed low depletion rates and were categorized as underutilized (“green” status). The ARIMA (0,1,0) model outperformed the ELM model (MAE = 1.6 vs. 22; RMSE = 1.7 vs. 23), indicating its superior predictive accuracy. Current exploitation levels for YFT and LOT exceed sustainable thresholds, necessitating urgent reductions in fishing effort. In contrast, other species remain underexploited, offering potential for increased but controlled harvesting. The application of time-series modeling, particularly ARIMA, provides a robust tool for forecasting stock dynamics and supporting data-driven fisheries management in the region. These findings contribute to improved conservation strategies and policy-making for sustainable utilization of marine resources in the Persian Gulf and the Sea of Oman.

Understanding how phytoplankton diversity changes over time and the driving mechanisms behind these changes is crucial for the development of freshwater ecosystem conservation policies. However, few studies have simultaneously explored the temporal patterns of lake phytoplankton diversity in three dimensions: taxonomy, function, and phylogeny. Using 20 years (January 1997–December 2016) of plankton monitoring data from Lake Kasumigaura, a temperate lake in Japan, we explored the correlations and ecological drivers between multidimensional temporal beta diversity of lake phytoplankton and their components (i.e., turnover and nestedness). Different dimensions of temporal beta diversity and their components were weakly correlated, suggesting that they provide complementary ecological information. Although temporal beta diversity was found to be primarily driven by stochastic processes, it is worth noting that biotic interactions play a more important role in deterministic processes compared to local environmental and climatic factors. Temporal functional and phylogenetic beta diversity showed a stronger response to deterministic processes compared to temporal taxonomic beta diversity. Our study emphasizes the need for integrated multidimensional biodiversity studies and calls for the incorporation of biological factors in studies of biodiversity drivers.

The Pearl River Delta (PRD) has experienced substantial environmental changes due to anthropogenic activities, with biological invasion emerging as a major consequence. However, our understanding of nonnative fish species and their adaptability to the estuarine environment remains limited. To address this gap, we focused on salinity as a key factor, conducting a literature survey to identify nonnative fish species and assess their salinity tolerance. We then analyzed spatial variations in alpha diversity and trophic levels across sampling sites. Additionally, we simulated salinity distributions during saltwater intrusion to evaluate potential adaptive areas for nonnative fish in the PRD. Our findings identified 25 nonnative fish species, phylogenetically belonging to nine orders, with three being translocated species within China and the remaining 22 being exotic introductions. Although most of the nonnative fish are freshwater species and exhibit species-specific differences in salinity tolerance, they generally can adapt to brackish water, with an average salinity tolerance of 23.7 ppt. The proportion of nonnative fish species richness decreased as distance from the head of the PRD to the estuary mouth declined (p = 0.02). Spatial analysis unveiled pronounced heterogeneity in salinity distribution, particularly in the east PRE of the LingDing Bay. Notably, under salinity intrusion circumstances, a gap region between salinity levels of 5.0 ppt and 15.0 ppt, spanning 3111.2 km², emerged as a potential adaptation zone for nonnative fish. By emphasizing salinity as a key factor, our study may contribute to elucidating invasion mechanisms and enhancing the assessment of invasion risks in estuarine environments.

Offshore and onshore activities introduce significant amounts of organic carbon into coastal waters, elevating CO₂ levels through microbial decomposition and contributing to ocean acidification. This process reduces the availability of dissolved silica, a key nutrient essential for diatom growth. As primary producers, diatoms link carbon and silica cycles and serve as sensitive bioindicators of aquatic health. A preliminary assessment of the coastal zones of the Cambay Basin identified two distinct areas: a highly economically active zone (Alang and Ghogha) with elevated chemical oxygen demand (COD) and variable Silicon (Si) levels, and another zone where COD remains within permissible limits with low Silicon (Khambhat). The influence of these differing environmental conditions on the structure of diatom assemblages was examined. Results revealed a shift towards opportunistic and pollution-tolerant diatom taxa, alongside a decline in more sensitive species, indicating ecological disturbance. Sentinel species like Entomoneis alata, Halamphora coffeaeformis, Chaetoceros gracilis, Iconella sp., and Surirella librile thrived under high COD, suggesting their potential as indicators of organic pollution. These findings underscore the value of diatom assemblages in monitoring the ecological impact of industrial and shipping activities and support the development of diatom-based indices for assessing coastal water quality.

The distribution of the species is influenced by many factors, like biogeographic patterns, riverscape, and local features. Despite being well studied since the publication of the River Continuum Concept, different local characteristics are important in determining fish distribution along the longitudinal gradient in the Neotropical region. Here, we tested how local characteristics can affect fishes in the Upper Paraná River basin. To perform such analyses, we measured metrics related to canopy, hydraulic, fish shelter, and others, using adapted EPA protocol in 40 streams located in Upper Paraná basin. After using an exclusion metric method (e.g., collinearity, low variance, and high proportion of zeros), we used GLM (quasi-Poisson; link Log) to identify the best metrics to respond to fish richness and abundance. We recorded 44 fish species, including 3 non-native species, with the first record of Gymnotus cf. pantanal for the Rio Grande. Our results indicate that fish richness increases in streams with high proportion of roots and decreases in streams with a high proportion of Leaf banks and Riparian mid-layer cover. Shannon index decreases in streams with high proportion of mid-layer vegetation cover and abundance decreases in stream with high proportion of riparian canopy cover and high proportion of sand. Pielou index decreases in streams with a high proportion of fine substrate and wetted width.

The river-reservoir continuum is a key area for important water sources and receiving water bodies. Dissolved organic matter (DOM) is an important factor affecting the water quality and aquatic ecological health in the continuum. However, there is currently a lack of research and quantification of the contributions of abiotic and biotic factors to DOM in the continuum during algal proliferation. In this study, single-turnover active chlorophyll fluorescence (LabSTAF) was used to obtain the photosynthetic characteristics of algae. At the same time, the sources of DOM were analyzed by combining three-dimensional fluorescence spectra with parallel factor analysis, and various statistical methods were used to deeply explore the impact mechanisms of abiotic and biotic factors on DOM. The results show that water temperature (WT), pH, and DO drive algal growth in the inflow river. The algal density in the estuary area did not increase significantly, but it has a high production potential; algae proliferated significantly in the backwater area, but their photosynthetic activity was inhibited by WT. Algal proliferation increased the DOC concentration in the inflow river. The river is dominated by humic-like components (C1+C2), followed by protein-like components (C3+C4); the fluorescence concentration of DOM shows a decreasing trend from the estuary to the backwater area. Algal proliferation significantly changed the sources of DOM in the river, with strong endogenous characteristics in the later stage of proliferation. The results of mixed-effect models and partial least squares structural equation modeling show that biotic and environmental factors together explain 73%, 76%, 49%, and 41% of the variations in C1, C2, C3, and C4, respectively. In addition, the photochemical flux per unit volume (JV_PII) is a key factor for algae to indirectly drive DOM changes through photosynthetic activity. This study is of great significance for a deeper understanding of the biogeochemical cycling of DOM in the river-reservoir area.

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.