Effects of environmental factors on benthic species in a coastal wetland by redundancy analysis

Chen, Ho Wen; Lin, Han; Chuang, Yen Hsun; Sun, Chu Ting; Chen, Wei Yea; Kao, Chang Yi

doi:10.1016/j.ocecoaman.2018.12.003

Cited by 19 publications

(9 citation statements)

References 48 publications

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“…The ecosystem of the short-term reed restoration has a relatively simple structure, and the soil fauna living environment fluctuates greatly (Abdallah et al 2018). Reproduction of soil fauna may be restricted at this site by the low quality and quantity of vegetation litter, and the periodic flooding (Ho et al 2019). These conditions may also affect the amount and distribution of soil fauna, leading to low density and biological diversity of soil fauna (Fitoussi, Pen-Mouratov, and Steinberger 2016).…”

Section: Discussionmentioning

confidence: 99%

Soil fauna diversity at different stages of reed restoration in a lakeshore wetland at Lake Taihu, China

Wei

Dou

Zhao

et al. 2020

Ecosyst Health Sustain

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Introduction: Wetland soil fauna support material cycling and restoration processes in wetland ecosystems. In our study, we observed variations in wetland soil fauna on the shores of Lake Taihu, China. We examined the relationships between fauna and major environmental factors, and looked at the short-and long-term changes in reed wetlands under restoration and in the natural reed lakeshore. Outcomes: We identified 93 groups of soil fauna in different wetlands and found significant differences in the lakeshore wetlands' soil fauna assemblages, depending on the length of the restoration period. By analyzing the soil fauna community evenness, dominance, number of taxa, and diversity, we found minimal seasonal variation in the soil fauna community diversity and abundance. The abundance of soil fauna in the sites under restoration decreased with depth below the soil surface. The reed restoration was obvious in the succession of the soil fauna groups in the long-term site. Although the restoration had an overall positive long-term effect on the soil fauna communities, there were no obvious short-term changes in the number of individuals. Conclusion: The study explored various potential measures to restore soil fauna in the Lake Taihu wetland and developed a theoretical basis for restoring the lakeshore wetland ecosystem.

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Section: Discussionmentioning

confidence: 99%

Soil fauna diversity at different stages of reed restoration in a lakeshore wetland at Lake Taihu, China

Wei

Dou

Zhao

et al. 2020

Ecosyst Health Sustain

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“…As the main contamination index in aquatic environment, the concentration of ammonium should be paid attention closely. The composition of different water samples was demonstrated by the distance between the dots, and the correlations between water samples and the environmental factors were demonstrated by the projections onto the lines of environmental variables by the sample symbols (Chen et al, 2019a). The composition of river water samples (RV) was mainly influenced by the concentration of ammonium and nitrate, and the composition of coastal water was influenced by ammonium, nitrate and salinity.…”

Section: Correlations Between Args Inti1 and Environmental Factorsmentioning

confidence: 99%

Occurrence and spatial distribution of antibiotic resistance genes in the Bohai Sea and Yellow Sea areas, China

Lü

Zhang

et al. 2019

Environmental Pollution

102

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a b s t r a c tRapid development of Bohai and Yellow Sea Economic Rim has led to the concern of emerging contamination of marine environments. This study investigated the spatial distribution of antibiotic resistance genes (ARGs) in Bohai and Yellow Sea areas. A large scale sampling from Bohai Sea, Yellow Sea and the major cities along the coastline from the mouth of Yalu River to the Yangtze River was performed. The spatial distribution of target ARGs based on the absolute abundances was in the trend of river water z coastal water > the Bohai Sea > the Yellow Sea, inshore > offshore and inner bay > bay mouth. The total absolute abundances of selected ARGs in the coastal waters (1.23 Â 10 4 e3.94 Â 10 5 copies/mL) were about 1e4 orders of magnitude higher than those in the sea (21.1e8.00 Â 10 3 copies/ mL). The abundances of ARGs fluctuated greatly in the Yellow Sea and the coastal areas. Sulfonamide resistance genes hold the highest abundances in the Bohai and Yellow Sea (up to 2.13 Â 10 3 copies/mL of sul1 and 6.23 Â 10 3 copies/mL of sul2), followed by tetracycline and quinolone resistance genes, while qnrA hold the highest abundances in coastal areas (up to 3.66 Â 10 5 copies/mL). The distribution coefficients of target genes between sediments and corresponding water samples were more than 1.0 in the majority of different aquatic systems. According to the principle component analysis and redundancy analysis, water samples collected from the sea clustered together while those from the coastal zone and rivers were separated. Ammonium and nitrate played important roles in the distribution and variation of ARGs. Co-occurrence network analysis revealed that the potential multi-antibiotics resistant bacteria were detected with higher abundances in the Yellow Sea than in the Bohai Sea. These observations provided a comprehensive new insight into the pollution status of ARGs in the Bohai and Yellow Sea areas.

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“…RDA can quantitatively analyze the influence degree of different types of factors, which can make up for the previous studies that only analyzed the influence of various factors on NDVI [ 19 , 53 ]. In this paper, the R vegan package [ 54 ] was used to analyze the correlation and multiple linear regression between NDVI and environmental factors.…”

Section: Methodsmentioning

confidence: 99%

Comprehensive Insights into Spatial-Temporal Evolution Patterns, Dominant Factors of NDVI from Pixel Scale, as a Case of Shaanxi Province, China

Chen

2021

IJERPH

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Based on long term NDVI (1982–2015), climate, topographic factors, and land use type data information in Shaanxi Province, multiple methods (linear regression, partial and multiple correlation analysis, redundancy analysis and boosted regression trees method) were conducted to evaluate the spatial-temporal change footprints and driving mechanisms in the pixel scale. The results demonstrated that (1) the overall annual average and seasonal NDVI in this region showed a fluctuating upward trend, especially in spring. The difference between the end of season (eos) and start of season (sos) gradually increased, indicating the occurrence of temporal “greening” across most Shaanxi Province. (2) The overall spatial distribution of annual mean NDVI in Shaanxi Province was prominent in the south and low in the north, and 98.83% of the areas had a stable and increasing trend. Pixel scale analysis reflected the spatial continuity and heterogeneity of NDVI evolution. (3) Trend and breakpoint evaluation results showed that evolutionary trends were not homogeneous. There were obvious breakpoints in the latitude direction of NDVI evolution in Shaanxi Province, especially between 32–33°N and in the north of 37° N. (4) Compared with precipitation, the annual average temperature was significantly correlated with the vegetation indices (annual NDVI, max NDVI, time integrated NDVI) and phenology metrics (sos, eos). (5) Considering the interaction between environmental variables, the NDVI evolution was dominated by the combined influence of climate and geographic location factors in most areas.

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Effects of environmental factors on benthic species in a coastal wetland by redundancy analysis

Cited by 19 publications

References 48 publications

Soil fauna diversity at different stages of reed restoration in a lakeshore wetland at Lake Taihu, China

Soil fauna diversity at different stages of reed restoration in a lakeshore wetland at Lake Taihu, China

Occurrence and spatial distribution of antibiotic resistance genes in the Bohai Sea and Yellow Sea areas, China

Comprehensive Insights into Spatial-Temporal Evolution Patterns, Dominant Factors of NDVI from Pixel Scale, as a Case of Shaanxi Province, China

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