Understanding the seasonal variation characteristics and trends in water quality is one of the most important aspects for protecting and conserving lakes. Lake Yangzong water quality parameters and nutrients, including water temperature, dissolved oxygen (DO), pH, conductivity, Chlorophyll-a, phycocyanin, total nitrogen (TN) and total phosphorus (TP), were monitored in different seasons from 2015 to 2021. Based on the monitoring data, the temporal and spatial variations of various parameters were analyzed. The results showed that Lake Yangzong is a warm monomictic lake. The Pearson correlation coefficient and correlation analysis showed water quality parameters were significantly correlated and probably affected by temperature. Cyanobacteria were at risk of blooming in spring and autumn. The contents of TN and TP in winter were significantly higher than in summer, especially TN, with both reaching a peak at the epilimnion and hypolimnion in December 2020 (TN = 1.3 mg/L, TP = 0.06 mg/L). We also observed a dual risk of endogenous release and exogenous input. Therefore, strengthening the supervision for controlling eutrophication caused by human activities and endogenous release is urgently needed.

Understanding the spatiotemporal distributions and variation characteristics of water quality parameters is crucial for ecosystem restoration and management of lakes, in particular, Lake Qilu (QL), a typical plateau shallow lake on the Yunnan-Guizhou Plateau, southwestern China. To identify the main causes of harmful algal blooming and continuous water quality decline, the total phosphorus (TP), total nitrogen (TN), water temperature (WT), dissolved oxygen (DO), chlorophyll-a (Chl-a), pH, and turbidity in hypereutrophic Lake Qilu from January 2017 to December 2021 were analyzed. The results showed a complex pattern in spatiotemporal distribution and variation. WT showed no significant change in the vertical profile. DO and pH value variations were caused by both physical and biochemical processes, especially at the bottom of Lake QL with an anaerobic environment. The Trophic State Index (TSI) assessment results showed that Lake QL is a eutrophic (70.14% of all samples, 50 < TSI < 70) to a hypereutrophic lake (29.86%, 70 < TSI) with poor water quality (WQI < 25). TP and WT were the main factors controlling harmful algal blooms (HABs) based on the statistical analysis of Principal Component Analysis (PCA), Random Forest Model (RFM), and Correlation Analysis (CA). In lake QL, TP loading reduction and water level increase might be the key strategies for treating HABs in the future. Based on our results, reducing TP loading may be more effective than reducing TN to prevent HABs in the highly eutrophicated Lake Qilu.

Eutrophication remediation is an ongoing priority for protecting aquatic ecosystems, especially in plateau lakes with fragile ecologies and special tectonic environments. However, current strategies to control the phosphorus (P) and nitrogen (N) levels in eutrophication sites have been mainly guided by laboratory experiments or literature reviews without in-field analyses of the geochemical processes associated with the hydrological and eutrophic characteristics of lakes. This study analyzed the water quality parameters of 50 sites at Lake Jian in May 2019, a moderate eutrophication shallow plateau lake, based on dissolved/sedimentary nitrogen, phosphorous and organic matter, grain size, C/N ratios and stable isotope ratios of δ¹³C or δ¹⁵N in sediments. The results showed that the average total nitrogen (TN) and total phosphorus (TP) concentrations in the lake water were 0.57 mg/L and 0.071 mg/L, respectively. The TN and TP contents of surface sediment ranged from 2.15 to 9.55 g/kg and 0.76 to 1.74 g/kg, respectively. Stable isotope and grain source analysis indicated that N in sediments mainly existed in organic matter form and P mainly occurred as inorganic mineral adsorption. Endogenous pollution contributed to >20% of TN. Furthermore, our findings showed that phosphorus was the nutrient that limited eutrophication at Lake Jian, unlike other eutrophic shallow lakes. In contrast, the nutrient levels in the sediment and input streams belonged entirely to the N-limitation state. The distinctness in release intensity of N and P could modify the N/P limitation in the lake, which affects algae growth and nutrient control. These results demonstrated that reducing exogenous nutrients might not effectively mitigate lake eutrophication due to their endogenous recycling; thus, detailed nutrient monitoring is needed to preserve aquatic ecosystems.

Microplastics (MPs) in freshwater environments, such as lakes, have become a significant issue in recent years. However, studies on the lakes of the Yunnan Plateau have been limited. To understand the pollution status and sources of MPs in Lake Chenghai (LCH), 36 sampling sites were selected for the surface water and sediment samples. Morphological identification, compositional analysis, abundance measurement, and spatial distribution mapping of the MPs were carried out. We also performed correlation analyses with hydrological parameters and physicochemical indexes of water and sediments. We aimed to uncover the spatial distribution patterns of the MPs in LCH, along with potential sources. Our findings revealed that all samples contained MPs and all of them were fibers. The abundance of MPs ranged from 90 to 770 n/m³ (329.44 rms) in the water and from 10 to 115 n/kg (43.19 rms) in the sediments, with particle sizes of 1-3 mm and less than 1 mm, respectively. Transparent MPs were prevalent, comprising 68% of the MPs found in the water and 63% in the sediments. The primary components of the MPs were polypropylene (PP), polyethylene terephthalate (PET), and man-made fibers (rayon). The spatial distribution showed an increasing concentration of MPs from south to north in the surface water, whereas the opposite trend was found in the sediments. Human activities, prevailing winds, and the river flowing into the lake influenced the spatial distribution pattern of the MPs. The abundance and assemblage characteristics of the MPs were directly correlated with the factors of nitrogen, phosphorus, and particle size in the water and sediments, but the correlation was not significant. The main source of MPs was the production and livelihoods of the neighboring residents, especially the use of fishing gears and nets. Since LCH shows significant pollution from MPs, there is an urgent need to control and manage the watershed in order to reduce the input of MPs in the future.

Fish population fluctuations have been widely documented and are often attributed to climate variability, but little is known about their relationship. This is a barrier that restricts our capacity to understand climate effects on fish fluctuations. Here, we collected published data to conduct a comparative analysis of time series in terms of both scale deposition rate (SDR) and catch to indicate the abundance of anchovy and explored its relationships with climatic and environmental parameters. We first conducted a Spearman correlation analysis to identify the differences in the SDR between sites. Then, we used Generalized Additive Models to evaluate the effects of external forcing at multiple spatial scales (i.e., local and global scales) on the anchovy catches recorded at the California Current Ecosystem (CCE), Humboldt Current Ecosystem (HCE), and Kuroshio Current Ecosystem (KCE). We found that the SDRs at different sites in the same Current Systems are generally consistent, while there are more differences between different systems. We also found that the Pacific Decadal Oscillation index (PDOI), North Pacific index (NPI), North Pacific Gyre Oscillation index (NPGOI), Sea Surface Temperature anomaly (SSTA), and Air Temperature anomaly (ATA) were the most influential factors explaining the variability in anchovy catch for CCE, whereas the NPGOI was the most influential factor for HCE. The PDOI was the best at explaining the variability in anchovy catch for KCE. Our results suggest that anchovy fluctuations in the Pan-Pacific occurred synchronously. These seemingly unrelated events, which occurred thousands of kilometers apart, were actually not isolated. Therefore, we suggest that large-scale climate forcing may activate synchronous fluctuations for anchovy populations at the basin scale, whereas local-scale environmental forces are also responsible for anchovy fluctuations in the “micro-environment”.

Algal blooms caused by eutrophication are a major global problem, and the monitoring and prediction of algal densities in lakes are important indicators of eutrophication management. However, the reliability of the commonly used chlorophyll-a (Chl-a) to characterize phytoplankton density in lake environments needs to be further investigated. In this paper, we sampled and analyzed 365 samples from nine plateau lakes in Yunnan Province during the dry and rainy seasons. The Chl-a data measured by the laboratory spectrophotometric method and the portable YSI multi-parameter water quality meter (YSI) directly used in the field were compared, and regression analysis and correlation analysis with phytoplankton density were performed. Most of the Chl-a values measured by the laboratory instrument were greater than those measured by the YSI, and the correlation between the two methods was weak (0.492, p < 0.001). The correlation between Chl-a and phytoplankton density measured by the YSI reached 0.67 (p < 0.001) in the dry season, while the laboratory methods used to measure Chl-a to characterize phytoplankton density may have led to an overestimation of phytoplankton density due to nonspecific sources of Chl-a. However, both methods are relatively inaccurate for characterizing phytoplankton density. For different trophic states of lakes, nutrient concentration changes affect the Chl-a concentration of phytoplankton. During different seasons, changes in the fluorescence intensity of phytoplankton in response to environmental conditions prevent the YSI results from reflecting the authentic phytoplankton density. Furthermore, high species diversity can lead to inconsistent changes in Chl-a and phytoplankton because the content of Chl-a in individual cells of different phytoplankton is different. The relationship between Chl-a and phytoplankton density was species specific. Therefore, when applying Chl-a to characterize phytoplankton density in lakes, it is necessary to consider environmental conditions, phytoplankton community structure and other practical conditions. In addition, laboratory analytical methods and instrumental techniques and instruments need to be improved.