The use of zooplankton distribution maps for assessment of ecological status of the Shardara reservoir (Southern Kazakhstan)

Krupa, Elena; Barınova, Sophia; Isbekov, Kuanysh Baibulatovich; Asylbekova, Saule Zhangirovna

doi:10.1016/j.ecohyd.2017.10.001

Cited by 10 publications

(10 citation statements)

References 24 publications

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“…Statistical maps were used in earlier environmental studies Krupa, Barinova, Amirgaliyev, et al, 2017b;Krupa, Barinova, Assylbekova, et al, 2018c;Krupa, Barinova, Isbekov, et al, 2018a;Krupa, Barinova, Ponamareva, et al, 2018b;Krupa, Barinova, Tsoy, et al, 2017a). Within the framework of the present study, however, overlaying of statistical maps on the contours of waterbodies for the first time made data visualization easier for analysis purposes, compared to previous methods.…”

Section: Discussionmentioning

confidence: 99%

“…Accordingly, an informative method of presenting spatial data is development of statistical maps, which can be used for any data, including physical (Firoz, Laxmi, & Abdul, ), hydrochemical, toxicological (Krupa, Barinova, Tsoy, Lopareva, & Sadyrbaeva, ), biological (Barinova, Krupa, & Kadyrova, ; Bresciani et al, ), evaluative and integrative (Barinova, Bilous, & Ivanova, ; Bilous, Barinova, Ivanova, & Huliaieva, ). Previous research has highlighted the effectiveness of this method for solving theoretical and applied ecology issues (Barinova & Krupa, ; Barinova et al, ; Krupa & Barinova, ; Krupa, Barinova, Amirgaliyev, Issenova, & Kozhabayeva, ; Krupa, Barinova, Assylbekova, & Isbekov, ; Krupa, Barinova, Isbekov, & Assylbekova, ; Krupa, Barinova, Ponamareva, & Tsoy, ; Krupa, Barinova, Tsoy, et al, ). The present study demonstrates further possibilities of utilizing cartographic methods in the ecological study of aquatic ecosystems.…”

Section: Introductionmentioning

confidence: 99%

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Tracking pollution and its sources in the catchment‐lake system of major waterbodies in Kazakhstan

Krupa¹,

Barınova

Aubakirova

2020

Lakes & Reservoirs

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The objective of the present study was to identify the sources and routes of entry of heavy metals and nutrients into several large waterbodies in the arid zone of Kazakhstan, namely Lake Balkhash and Samarkan and Shardara reservoirs. A data visualization method was used for this purpose. Statistical mapping, based on referencing coordinates of the material selection points, was performed with the Statistics 12.0 program. Matching statistical maps with the waterbody contours was performed in Adobe Photoshop. Maps of the spatial distribution of heavy metals (cadmium, nickel, cobalt, lead, zinc and copper) and nutrients were constructed for all three study waterbodies. Data visualization clearly illustrated the relationship between the distribution of pollutants in the study waterbodies, as well as the sources of anthropogenic pollution. Based on the mapping exercise, it was established that Cu and Zn entered the waterbodies mainly in agricultural waste waters, while Cd, Ni, Co, Pb and partly Zn entered the waterbodies mainly in industrial and surface run‐off. Nutrients enter the waterbodies mainly in river and municipal waters. The constructed maps demonstrate the role of the constant flow in the distribution of pollutants in the waters of Lake Balkhash. The results also indicate that statistical mapping is an effective tool for identifying the sources and routes of pollutant entry into waterbodies. The imposition of statistical maps on the contours of waterbodies of concern provides a mapping method allowing for more visually compelling data and information for a wide circle of users and managers.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Tracking pollution and its sources in the catchment‐lake system of major waterbodies in Kazakhstan

Krupa¹,

Barınova

Aubakirova

2020

Lakes & Reservoirs

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“…Statistical data mapping is a useful tool for solving this application problem [28,29]. The effectiveness of this method in monitoring studies of water bodies in Kazakhstan has been shown previously [30][31][32]. During occasional hydrochemical and hydrobiological studies of Borovoe Lake, a comprehensive assessment of its ecological status has not been performed yet.…”

Section: Introductionmentioning

confidence: 99%

Zooplankton as Indicator of the Ecological State of Protected Aquatic Ecosystems (Lake Borovoe, Burabay National Nature Park, Northern Kazakhstan)

Krupa

Romanova

Berkinbaev

et al. 2020

Water

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The enrichment of the protected Borovoe Lake with nutrients has taken place within the last 100 years, from the moment the first resort was formed on its shores. The purpose of this study was to assess the current ecological state of Borovoe based on the structure of zooplankton. According to the chemical data, in the summer of 2019, the content of nutrients in the water was, relatively, not high; the content of heavy metals was very low. Twenty-seven species were found in zooplankton. The average abundance of zooplankton was 988.8 thousand ind./m3 with a biomass of 1.52 g/m3. Rotifera dominated. Cladocera sub-dominated. The Shannon index values were 2.31 bit/ind. and 2.57 bit/mg; the values of Clarke’s W-statistics and Δ-Shannon were negative. The abundance of zooplankton increased more than nine times, but the average individual mass of an organism decreased from 0.0112 to 0.0016 mg over the past decade. Despite the relatively low content of nutrients, the structure of zooplankton demonstrated that the nutritional load on Lake Borovoe is currently close to critical. Statistical mapping of the data and redundancy analysis (RDA) showed that the primary source of lake pollution is the village of Borovoe and sanatoriums located on the southeast and northwest coasts.

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“…Marine zooplankton, which has scientific and economic value in marine ecosystem, is both good indicators of the ecological status of the water body and the food source of some fish fry [1,2]. At present, species identification and quantitative statistics of marine zooplankton mainly rely on manual operation, which cannot meet the development of marine zooplankton science.…”

Section: Introductionmentioning

confidence: 99%

Study on Holographic Image Recognition Technology of Zooplankton

Shi¹,

Wang²,

Cao³

et al. 2019

dtcse

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Marine zooplankton has important ecological and economic value. The observation and automatic image recognition technology of marine zooplankton is an important mean to acquire data such as species, quantity, spatial distribution and behavioral postures of zooplankton, and is an important support for marine scientific research. Digital holography has an innate advantage of refocusing and reconstruction, which is suitable for deep learning and living zooplankton recognition. In this study, a large number of holographic images was trained by using the improved YOLOv2 model, and after test, the study achieved satisfactory results: the models trained by the images with sharpness assessment score of 0.6 or higher, have precision rate above 94% and a recall rate above 88%. This study mainly discusses: (1) the detection method of moving targets to acquire the images of moving zooplankton; (2) the two factors that affect the holographic images recognition results, mean (pixel mean of images) subtraction operation and image sharpness, and the no-reference sharpness assessment based on structural similarity for holographic images; (3) the relationship between sharpness assessment index or mean subtraction and the recognition results.

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The use of zooplankton distribution maps for assessment of ecological status of the Shardara reservoir (Southern Kazakhstan)

Cited by 10 publications

References 24 publications

Tracking pollution and its sources in the catchment‐lake system of major waterbodies in Kazakhstan

Tracking pollution and its sources in the catchment‐lake system of major waterbodies in Kazakhstan

Zooplankton as Indicator of the Ecological State of Protected Aquatic Ecosystems (Lake Borovoe, Burabay National Nature Park, Northern Kazakhstan)

Study on Holographic Image Recognition Technology of Zooplankton

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