Cell size-dependent species sensitivity to nanoparticles underlies changes in phytoplankton diversity and productivity.

Nanoparticle pollution has been shown to affect various organisms. However, the effects of nanoparticles on species interactions, and the role of species traits, such as body size, in modulating these effects, are not well-understood. We addressed this issue using competing freshwater phytoplankton species exposed to copper oxide nanoparticles. Increasing nanoparticle concentration resulted in decreased phytoplankton species growth rates and community productivity (both abundance and biomass). Importantly, we consistently found that nanoparticles had greater negative effects on species with smaller cell sizes, such that nanoparticle pollution weakened the competitive dominance of smaller species and promoted species diversity. Moreover, nanoparticles reduced the growth rate differences and competitive ability differences of competing species, while having little effect on species niche differences. Consequently, nanoparticle pollution reduced the selection effect on phytoplankton community abundance, but increased the selection effect on community biomass. Our results suggest cell size as a key functional trait to consider when predicting phytoplankton community structure and ecosystem functioning in the face of increasing nanopollution.

Analysis of water quality indexes and their relationships with vegetation using self-organizing map and geographically and temporally weighted regression.

Natural vegetation has been proved to promote water purification in previous studies, while the relevant laws has not been excavated systematically. This research explored the relationships between vegetation cover and water quality indexes in Liaohe River Basin in China combined with self-organizing map (SOM) and geographically and temporally weighted regression (GTWR) innovatively and systematically based on the distributing heterogeneity of water quality conditions. Results showed that the central and northeast regions of the study area had serious organic and nutrient pollution, which needed targeted treatment. And SOM verified that high vegetation coverage with retention potential of organic and inorganic pollutants as well as nutrients improved water quality to some degree, while the excessive discharges of pollutants still had serious threats to nearby water environment despite the purification function of vegetation. GTWR indicated that the waterside vegetation was beneficial for dissolved oxygen increasing and contributed to the decreasing of organic pollutants and inorganic pollutants with reducibility. Natural vegetation also obsorbed nutrients like TN and TP to some degree. However, the retential potential of nitrogen and organic pollutants became not obvious when there were heavy pollution, which demonstrated that pollution sources should be controlled despite the purification function of vegetation. This study implied that natural vegetation purified water quality to some degree, while this function could not be revealed when there was too heavy pollution. These findings underscore that the pollutant discharge should be controlled though the natural vegetation in ecosystem promoted the purification of water bodies.

Abundance, spatial variation, and sources of rare earth elements in soils around ion-adsorbed rare earth mining areas.

Rare earth elements (REEs) concentrated in soils have attracted increasing attention about their impact on soil health as emerging contaminants. However, the sources of REEs enriched in soils are diverse and need to be further investigated. Here, surface soil samples were collected from southern Jiangxi Province, China. REEs contents and soil physicochemical properties were determined, and cerium (Ce) and europium (Eu) anomalies were calculated. Moreover, we established a model to further identify the main sources of REEs accumulation in the studied soils. Results show that the abundance of soil REEs reveals larger spatial variation, suggesting spatially heterogeneous distribution of REEs. The median content of light REEs in soils (154.5 mg kg-1) of the study area was higher than that of heavy REEs and yttrium (35.8 mg kg-1). In addition, most of the soil samples present negative Ce anomalies and all the soil samples present negative Eu anomalies implying the combined effect of weathering and potential exogenous inputs on soil REEs. Positive matrix factorization modeling reveals that soil REEs content is primarily influenced by soil parent materials. Potential anthropogenic sources include mining-related leachate, traffic exhaust, and industrial dust. These results demonstrate that the identification of sources of soil REEs is an important starting point for targeted REEs sources management and regulation of excessive and potentially harmful REEs levels in the soil.

Impacts of Land Use on Surface Water Quality Using Self-Organizing Map in Middle Region of the Yellow River Basin, China.

The Yellow River is one of the most important water sources in China, and its surrounding land use affected by human activities is an important factor in water quality pollution. To understand the impact of land use types on water quality in the Sanmenxia section of the Yellow River, the water quality index (WQI) was used to evaluate the water quality. A self-organizing map (SOM) was used for clustering analysis of water quality indicators, and the relationship between surface water quality and land use types was further analyzed by redundancy analysis (RDA). The results showed that WQI values ranged from 82.60 to 507.27, and the highest value was the sampling site S3, whose water quality grade was "Likely not suitable for drinking", mainly polluted by agricultural non-point sources ammonia nitrogen pollution. SOM clustered the sampling sites into 4 groups according to the water quality indicators, the main influencing factors for different groups were analyzed and explored in more depth in relation to land use types, suggesting that surface water quality was significantly connected with the proportion of land use types at the watershed scale in the interpretation of water quality change. The negative impact of cropland on surface water quality was greater than that of other land use types, and vegetation showed a greater positive impact on surface water quality than other land uses. The results provide evidence for water environment conservation based on land use in the watershed.

The effect of soil depth on temperature sensitivity of extracellular enzyme activity decreased with elevation: Evidence from mountain grassland belts.

Temperature sensitivity of soil extracellular enzyme activity (EEA), indicated by the temperature coefficient Q10, is used to predict the effect of temperature on soil carbon (C), nitrogen (N), and phosphorus (P) cycling. At present, we lack understanding of elevation and soil depth variations in Q10 of EEA. Here, we measured the Q10 of three enzymes participating in C- (ß-1,4-glucosidase, BG), N- (leucine aminopeptidase, LAP), and P- (acid phosphatase, AP) cycling along a vertical grassland belt of China. Soils from five depths (0-10, 10-20, 20-40, 40-60, and 60-100 cm) were sampled from three elevations (low, <1000 m; middle, 1000-2000 m; high, 2000-3000 m) and incubated at four temperatures (5, 15, 25, 35 °C). The average Q10 of soil EEA ranged from 0.97 to 1.11 and the Q10 of LAP was higher than that of BG and AP. Generally, the Q10 of BG and LAP both increased from low to middle elevation and then decreased, while the Q10 of AP was stable. Moreover, the effect of soil depth on Q10 of EEA was weakened from low elevation to high elevation, and the factors driving Q10 of soil EEA changed with elevation. This study improved the understanding of the vertical pattern of Q10 of soil EEA in water-limited ecosystems, and highlighted that elevation could regulate the effect of soil depth on Q10 of EEA.