Assessment of spatial and temporal variation of ecological environment quality in Ebinur Lake Wetland National Nature Reserve, Xinjiang, China

Jing, Yunqing; Fei, Zhang; He, Yufeng; Kung, Hsiang‐te; Johnson, Verner Carl; Arikena, Muhadaisi

doi:10.1016/j.ecolind.2019.105874

Cited by 150 publications

(80 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There were varieties of bacteria present in hypersaline environments from previous and current studies. These results were attributed to the selection of sampling locations of the lake or sea and the time of the month of sampling, each of which helps determine the microbial diversity that changes owing to continuous fluctuations in the physicochemical properties of the water and also possibly to the method used for analyses [32][33][34]. Since the bacterial composition was determined in samples collected only at specific sites, all studies have suggested that the results may not necessarily represent the entire lake but could serve as a baseline for future work owing to the fact that potential biases may be introduced.…”

Section: Bacterial Compositionmentioning

confidence: 99%

Functional profiling of bacterial communities in Lake Tuz using 16S rRNA gene sequences

Oyewusi

Wahab

Edbeib³

et al. 2020

Biotechnology & Biotechnological Equipment

View full text Add to dashboard Cite

The 16S rRNA amplicon sequencing technique is a key aspect of studies of microbial communities but does not provide direct evidence of a community's functional capabilities. This work aimed to assess the structure of the uncultured bacterial communities from two locations in Lake Tuz in Turkey to provide information on their roles in the lake ecosystem. The most abundant phyla in the lake water were Firmicutes (84%) for lake sample site 1 (TG1), 70% for lake sample site 2 (TG2), Fusobacteria (9% for TG1, 22% for TG2) and Proteobacteria (6% for TG1, 7% for TG2). The most abundant genera were Romboutsia (45% for TG1, 35% for TG2), Clostridium sensu stricto 1 (8% for TG1, 8% for TG2), Cetobacterium (9% for TG1, 22% for TG2) and Photobacterium (2% for TG1, 3% for TG2). PICRUSt constitutes a novel bioinformatics tool to establish profiles for bacterial protein functions based on metagenomic 16S rRNA data for a community of unculturable bacteria. PICRUSt also provides information on whole-community metabolic functions related to adaptation, bioremediation potential and the ability of various groups of microorganisms to survive in highly saline water. The overall results provide an effective strategy for assessing the metabolic capacities of microbes in situ in a high-salt aquatic environment such as Lake Tuz and the potential of these microbes to serve as bioremediation agents. This approach provides useful insights into predictive metagenomics of an unculturable microbial community for which only marker-gene surveys are currently available.

show abstract

Section: Bacterial Compositionmentioning

confidence: 99%

Functional profiling of bacterial communities in Lake Tuz using 16S rRNA gene sequences

Oyewusi

Wahab

Edbeib³

et al. 2020

Biotechnology & Biotechnological Equipment

View full text Add to dashboard Cite

show abstract

“…The reduction in bare land area and the increase in vegetation coverage have improved the quality of the ecological environment to a certain extent [76]. L-L was mainly distributed in the wasteland and bare land in the southwest in 2000 and 2018, where the vegetation coverage was low, and the ecological environment quality was poor [77]. To understand the spatial distribution characteristics of ecological environment quality, the local spatial correlation pattern of the ecological environment quality was analyzed using a LISA clustering map and a LISA significance level map (Figures 8 and 9).…”

Section: Spatial Clustering Of the Ecological Environment Of Hami Oasismentioning

confidence: 99%

“…The region with a significance level of 0.05 was mainly located in the periphery of the region where the significance level reached 0.01. The region of H-H mostly reached a significance level of 0.01 in 2000 and 2018 [78,79]. In future urban planning, proper consideration should be given to renovating or minimizing bare land.…”

Section: Spatial Clustering Of the Ecological Environment Of Hami Oasismentioning

confidence: 99%

Evaluation of the Temporal and Spatial Changes of Ecological Quality in the Hami Oasis Based on RSEI

et al. 2020

View full text Add to dashboard Cite

Given the restrictions on special geographic locations in development processes, the measurement and analysis of the ecological quality of the Hami Oasis are of great significance for the protection of this fragile oasis. In this study, the ecological quality of the Hami Oasis was monitored by constructing a remote sensing ecological index (RSEI) for arid areas. Using the standard deviation ellipse and moving window method, the ecological status and space–time changes were explored for both their external and internal factors in the Hami Oasis. Finally, a geo-detector was employed to determine the driving factors of the ecological quality of the Hami Oasis. The results revealed that: (1) In the remote sensing ecological index constructed in the Hami Oasis, the main influencing factors were dryness and wetness. The average value of the ecological quality of the oasis was less than 0.5, and the ecological quality level was relatively poor. Among the five grades of ecological quality in the Hami Oasis, the poor grade and the good grade showed the largest changes, decreasing by 200 and increasing by 300, respectively, which were mainly concentrated in the periphery of the oasis. (2) The improved ecological quality of the Hami Oasis was mainly manifested in the expansion of the artificial oasis, while the deteriorated area was manifested as an increase in the built-up area. Moreover, the ecological quality of the Hami Oasis presented a ringlike nesting distribution pattern from the internal built-up area to the artificial oasis periphery. (3) The external expansion direction of the ecological quality of the Hami Oasis featured southeast–northwest expansion, which was consistent with the direction of the rivers and traffic roads. The transformation between different ecological qualities in the oasis and the expansion of the built-up area were the reasons for the fragmentation of the Hami Oasis’ landscape. (4) Compared to a single factor, the dual-factor for the ecological quality of the Hami Oasis had stronger explanatory power. Moreover, changes in land use types caused changes in the ecological quality of the Hami Oasis. During the study period, we found that human activities had a more significant impact than natural factors on the development of the Hami Oasis. (5) The Moran’s I Index increased from 0.835268 in 2000 to 0.923976 in 2018, and the p values in the study area all reached a 0.05 significant level. At the same time, the areas with p values above the 0.01 and 0.001 significant levels have also increased significantly in the past 18 years.

show abstract

“…Reflecting land degradation synthesized by the index-based built-up index and the bare soil index [42][43][44] Food security Notes: ρ Blue , ρ Green , ρ Red , ρ NIR , ρ SWIR1 , and ρ SWIR2 respectively represent the reflectance of the blue, green, red, near-infrared (NIR), short wave infrared 1 (SWIR1), and short wave infrared 2 bands corresponding to the thematic mapper (TM) and the operational land unit (OLI) images; gain and skewness are the gain and offset values of TM6 band, or 0.056 and 1.238, respectively; K 1 and K 2 are scaling coefficients, obtained by image metadata, K 1 = 606.09 W/(m 2 × sr × µm), K 2 = 1282.71 K; center wavelength λ is 11.48 µm, α is 1.438 × 10 -2 mK; ε 6 is the surface specific emissivity based on TM6; while using the landsat OLI data, L 10 is the radiance value at the sensor, obtained by radiometric calibration; τ 10 is the transmittance of the atmosphere in the thermal infrared band; ε 10 is the surface specific emissivity; T s is the surface temperature; B 10 (T s ) is the same black body as T s radiation brightness; I 10 ↑ and I 10 ↓ are the radiance of the atmosphere up and down, respectively; the surface specific emissivity of the water bodies is 0.995; the surface specific emissivity ε 6 and ε 10 were obtained by Sobrino's NDVI threshold method; τ 10 , I 10 ↑, and I 10 ↓ parameters, with reference to the mid-latitude summer standard atmospheric profile, were obtained by interpolating the atmospheric profile according to the central latitude and longitude of the image and imaging time set; 1 RMB (yuan) ≈ 0.150 $.…”

Section: Remote Sensing Ecological Indexmentioning

confidence: 99%

Evaluation of Sustainable Regional Development Combining Remote Sensing Data and Ecological Constraints: A Case Study of Chaohu Basin, China

et al. 2020

View full text Add to dashboard Cite

The maintenance of sustainable development in light of climate change is presenting society with a serious challenge. This study analyzes the spatial environment and its coupled relationship with socio-economic and food security in the Chaohu Lake Basin in central Anhui Province, China. Previous studies have shown that this study area has good environmental conditions. However, the ecological security, economic development, and food security in the Chaohu Lake Basin was generally poor and poorly coordinated in 2018, especially in the center of local cities and surrounding areas. Nevertheless, many towns are in a well-organized state, meaning sustainable and coordinated regional development can be achieved through resource optimization. Generally, the economic conditions in the Chaohu Lake Basin should be improved in a way that ensures that the environment is not significantly degraded. The main functional zoning requirements of the counties’ land management planning designate most of the counties as parts of ecological conservation areas. The present study provides monitoring of important basin ecosystems and serves as a guide to future sustainable regional development by providing directions and paths to follow; it can also provide a reference for eco-functional zoning that is applicable to various natural basins worldwide.

show abstract

Assessment of spatial and temporal variation of ecological environment quality in Ebinur Lake Wetland National Nature Reserve, Xinjiang, China

Cited by 150 publications

References 24 publications

Functional profiling of bacterial communities in Lake Tuz using 16S rRNA gene sequences

Functional profiling of bacterial communities in Lake Tuz using 16S rRNA gene sequences

Evaluation of the Temporal and Spatial Changes of Ecological Quality in the Hami Oasis Based on RSEI

Evaluation of Sustainable Regional Development Combining Remote Sensing Data and Ecological Constraints: A Case Study of Chaohu Basin, China

Contact Info

Product

Resources

About