Late gestational exposure to fenvalerate impacts ovarian reserve in neonatal mice via YTHDF2-mediated P-body assembly.

Fenvalerate (FEN), a type II pyrethroid pesticide, finds extensive application in agriculture, graziery and public spaces for pest control, resulting in severe environmental pollution. As an environmental endocrine disruptor with estrogen-like activity, exposure to FEN exhibited adverse effects on ovarian functions. Additionally, the presence of the metabolite of FEN in women's urine shows a positive association with the risk of primary ovarian insufficiency (POI). In mammals, the primordial follicle pool established during the early life serves as a reservoir for storing all available oocytes throughout the female reproductive life. The initial size of the primordial follicle pool and the rate of its depletion affect the occurrence of POI. Nevertheless, there is very limited research about the impact of FEN exposure on primordial folliculogenesis. In this study, pregnant mice were orally administrated with 0.2, 2.0 and 20.0 mg/kg FEN from 16.5 to 18.5 days post-coitus (dpc). Ovaries exposed to FEN exhibited the presence of large germ-cell cysts that persist on 1 days post-parturition (1 dpp), followed by a significant reduction in the total number of oocytes in pups on 5 dpp. Moreover, the levels of m6A-RNA and its associated proteins METTL3 and YTHDF2 were significantly increased in the ovaries exposed to FEN. The increased YTHDF2 promoted the assembly of the cytoplasmic processing bodies (P-body) in the oocytes, accompanied with altered expression of transcripts. Additionally, when YTHDF2 was knocked-down in fetal ovary cultures, the primordial folliculogenesis disrupted by FEN exposure was effectively restored. Further, the female offspring exposed to FEN displayed ovarian dysfunctions reminiscent of POI in early adulthood, characterized by decreases in ovarian coefficient and female hormone levels. Therefore, the present study revealed that exposure to FEN during late pregnancy disrupted primordial folliculogenesis by YTHDF2-mediated P-body assembly, causing enduring adverse effects on female fertility.

Analysis of spatial variation of street landscape greening and influencing factors: an example from Fuzhou city, China.

Urban street greening is an important part of urban green infrastructure, and Green View Index (GVI) is widely used to assess urban street quality and ecosystem service value as an important indicator to quantify the perception of green street landscape from a pedestrian perspective. However, the distribution of street greenery is imbalanced. Therefore, to explore the differences in street greening levels within urban cities, we crawled streetscape data using the Internet to assess the spatial distribution patterns of urban street GVI using deep learning and spatial autocorrelation, and combined 11 surrounding environmental features with multi-source geographic data to further analyze the key factors influencing the spatial variation of block GVI using ordinary least squares, geographically weighted regression (GWR) models, and multi-scale geographically weighted regression (MGWR) models. The results show that the mean value of GVI in Fuzhou city is low (23.08%), with large differences among neighborhoods and a significant spatial autocorrelation. Among the regression models, MGWR has the best fit with an R2 of 0.702, where the variables of NDVI, house price, accessibility of water bodies and parks, and the proportion of built-up land have a greater impact on GVI, and the factors do not have the same spatial effect size. The results can provide a scientific basis for promoting green visual equity in different blocks.

[Spatiotemporal Variations in Nutrient Loads in River-lake System of Changdang Lake Catchment in 2016-2017].

Eutrophication of shallow lakes in the middle and lower reaches of the Yangtze River has become an increasingly serious problem. In this study, we investigated the temporal and spatial variations in nutrient loads (nitrogen, N and phosphorus, P) in the Changdang Lake Catchment located to the northwest of Lake Taihu through field sampling and laboratory analysis in 2016-2017. The results show the severity of the N and P pollution in the Changdang Lake catchment. The mean river water concentrations of TN, NO3--N, NH4+-N, TP, Chla, and permanganate index are (3.70±0.76) mg ·L-1, (1.81±0.42) mg ·L-1, (1.03±0.61) mg ·L-1, (0.38±0.31) mg ·L-1, (25.74±37.00) µg ·L-1, and (6.35±0.81) mg ·L-1, respectively. N pollution in the river is more severe in winter and spring than in summer and autumn whereas P pollution in the river is worse in autumn and winter than in spring and summer. Spatially, the magnitude of river N and P pollution follows the order of northern > northwestern > southern > eastern part of the study area. The rivers are in a state of moderate to severe eutrophication. The mean lake water concentrations of TN, NO3--N, NH4+-N, TP, Chla, and permanganate index are (2.25±0.94) mg ·L-1, (0.98±0.47) mg ·L-1, (0.19±0.14) mg ·L-1, (0.11±0.03) mg ·L-1, (18.71±8.76) µg ·L-1, and (4.59±1.09) mg ·L-1, respectively. The water quality in Changdang Lake is categorized as worse than class Ⅲ for TN and TP concentrations, which show decreasing trends from the west to the east to the south of the lake. The lake is in a status of slight to moderate eutrophication. The lake water quality is affected by the combination of sewage discharge and non-point source pollutant losses. The inflow rivers including the Danjinlicao River, Tongji River, and Xuebu River are the dominant pollution sources for Changdang Lake. The Danjinlicao River transports 10-12 times the total N and P loads transported by Tongji and Xuebu rivers. Changes in land use and atmospheric deposition are the driving factors of the deterioration of water quality and eutrophication in the catchment.

Modeling phosphorus sources and transport in a headwater catchment with rapid agricultural expansion.

Increasing riverine phosphorus (P) levels in headwaters due to expanded and intensified human activities are worldwide concerns, because P is a well-known limiting nutrient for freshwater eutrophication. Here we adopt the conceptual framework of the SPAtially Referenced Regressions On Watershed attributes (SPARROW) model to describe total phosphorus (TP) sources and transport in a headwater watershed undergoing rapid agricultural expansion in the upper Taihu Lake Basin, China. Our models, which include variables for land cover, river length, runoff depth, and pond density, explain 94% of the spatio-temporal variability in TP loads. Agricultural lands contribute the largest percentage (61%) of the TP loads delivered downstream, followed by forestland (21%) and urban land (18%). Future agricultural expansion to 15% of the total basin area is possible, which could lead to a 50% increase in TP loads. According to our analysis, an average of 24% of the total P export from the watershed landscape was intercepted in ponds. The exported amount was subsequently retained by tributaries and along the mainstem river, accounting for 14% and 43% of their inflowing loads, respectively. The remaining ∼6 tons yr-1 of TP was eventually transported into Tianmu Lake, in Southeastern China. The model identified several sub-catchments as hotspots of TP loss and thus logical sites for targeted management. Our study underscores the significance of agricultural expansion as a factor that can exacerbate headwater TP pollution, highlighting the importance of landscapes to buffer TP losses from sensitive hilly catchments. This also points to a need for an integrated management strategy that considers the spatial-varying P sources and associated transport of TP in precious headwater resources.

Carbon dynamics and environmental controls of a hilly tea plantation in Southeast China.

Tea plantations are widely distributed and continuously expanding across subtropical China in recent years. However, carbon flux exchanges from tea plantation ecosystems are poorly understood at the ecosystem level. In this study, we use the eddy covariance technique to quantify the magnitude and temporal variations of the net ecosystem exchange (NEE) in tea plantation in Southeast China over four years (2014-2017). The result showed that the tea plantation was a net carbon sink, with an annual NEE that ranged from -182.40 to -301.51 g C/m2, which was a much lower carbon sequestration potential than other ecosystems in subtropical China. Photosynthetic photon flux density (PPFD) explained the highest proportion of the variation in NEE and gross primary productivity (GPP) (for NEE: F = 389.89, p < .01; for GPP: F = 1,018.04, p < .01), and air temperature (Ta) explained the highest proportion of the variation in ecosystem respiration (RE) (F = 13,141.81, p < .01). The strong pruning activity in April not only reduced the carbon absorption capacity but also provided many plant residues for respiration, which switched the tea plantation to a carbon source from April to June. Suppression of NEE at higher air temperatures was due to the decrease in GPP more than the decrease in RE, which indicated that future global warming may transform this subtropical tea plantation from a carbon sink to carbon source.

Nitrogen transport and retention in a headwater catchment with dense distributions of lowland ponds.

The existence of lowland ponds alter watershed nitrogen (N) cycles via combined changes in runoff and N processing potential, which can significantly buffer watershed N transport. Here, we adopt the conceptual framework of the SPAtially Referenced Regressions On Watershed attributes (SPARROW) model to describe N transport and explore the buffering roles of lowland ponds in a small headwater watershed of Taihu Lake Basin, China. Our model, which included variables for nutrient sources, riverine length, precipitation and pond density, explained 95% of the spatio-temporal variability in total N loads. Results indicated that the northern parts of this watershed were hotspot regions, which contributed relatively large N yields. While their contributions have high temporal variations, they depend upon local precipitation rates. The model results also revealed important processes of landscape N retention. On average, approximately 87% of terrestrial N inputs were removed via denitrification, plant uptake, and other processes or retained in the subsurface during land-to-water delivery. This amount can be further differentiated into 12% retained by lowland ponds and the remaining 75% associated with other landscapes including nutrient storage in soils and groundwater, as a legacy of historical inputs. By contrast, in-stream retention processes only removed 3% of the total terrestrial N inputs. In the future, riverine N pollution will likely be exacerbated by releases from legacy storage and intensified human activities, especially as climate change is expected to enhance extreme rainfall conditions. An integrated N management strategy that appropriately considers the buffering roles of lowland ponds and other landscapes, is required to optimize N fertilizer inputs and protect precious headwater resources.