The Impact of Water Chemistry on Zooplankton Occurrence in Two Types (Field versus Forest) of Small Water Bodies

2010 ◽  
Vol 95 (2) ◽  
pp. 130-141 ◽  
Author(s):  
Natalia Kuczyńska-Kippen ◽  
Tomasz Joniak
Keyword(s):  
Water Chemistry ◽  
Water Bodies ◽  
Small Water ◽  
Field Versus ◽  
The Impact ◽  
Small Water Bodies

The impact of biometric parameters of a hydromacrophyte habitat on the structure of zooplankton communities in various types of small water bodies

2009 ◽  
Vol 38 (2) ◽  
Author(s):  
Natalia Kuczyńska-Kippen ◽  
Barbara Nagengast ◽  
Tomasz Joniak
Keyword(s):  
Water Bodies ◽  
Small Water ◽  
Biometric Parameters ◽  
Zooplankton Communities ◽  
The Impact ◽  
Small Water Bodies

The impact of biometric parameters of a hydromacrophyte habitat on the structure of zooplankton communities in various types of small water bodies

scholarly journals Influence of land development on the ecological status of small water bodies

2020 ◽  
Vol 49 (4) ◽  
pp. 345-353
Author(s):  
Anna Dudzińska ◽  
Barbara Szpakowska ◽  
Maria Pajchrowska
Keyword(s):  
Arable Land ◽  
Ecological Status ◽  
Land Development ◽  
Water Bodies ◽  
Urban Landscapes ◽  
Species Trees ◽  
Small Water ◽  
Q Index ◽  
The Impact ◽  
Small Water Bodies

AbstractSmall water bodies play a specific role in the landscape, as they increase the mosaic pattern of a given area, retain water and affect hydrological regime in adjacent soils. These water bodies are the most important in landscapes that have been largely transformed by man, such as agricultural and urban landscapes. The author of this study assessed the ecological status of small water bodies using the Q index and determined the impact of the development of adjacent areas on their ecological status. The analysis of the Q index referring to water bodies showed that its values changed considerably not only during the whole study period but also during one year (from 1.74 to 4.28). The land use analysis in the designated buffer zones stretching within 500 m and 1000 m from the water bodies showed that arable land occupied the largest area. This fact determines the ecological status of these water bodies. Ecotones that develop around ponds can function as biogeochemical barriers reducing pollution in the area. A total of 116 species of vascular plants were identified in the water bodies under study. Herbaceous plants constituted the largest group – 87 species. Trees and shrubs were represented by 16 species and macrophytes by 16 taxa.

Exploring the potential of small water bodies as an integrative management tool for fisheries production

2021 ◽  
Author(s):  
Christopher Mulanda Aura ◽  
Ruth Lewo Mwarabu ◽  
Chrisphine S. Nyamweya ◽  
Horace Owiti ◽  
Collins Onyango Ongore ◽  
...  
Keyword(s):  
Water Bodies ◽  
Management Tool ◽  
Small Water ◽  
Small Water Bodies ◽  
Integrative Management

scholarly journals Estimation of Chlorophyll-a Concentrations in Small Water Bodies: Comparison of Fused Gaofen-6 and Sentinel-2 Sensors

2022 ◽  
Vol 14 (1) ◽  
pp. 229
Author(s):  
Jiarui Shi ◽  
Qian Shen ◽  
Yue Yao ◽  
Junsheng Li ◽  
Fu Chen ◽  
...  
Keyword(s):  
Machine Learning ◽  
Chlorophyll A ◽  
Water Bodies ◽  
Gradient Boosting ◽  
Learning Models ◽  
Small Water ◽  
Extreme Gradient Boosting ◽  
Machine Learning Models ◽  
Sentinel 2 ◽  
Small Water Bodies

Chlorophyll-a concentrations in water bodies are one of the most important environmental evaluation indicators in monitoring the water environment. Small water bodies include headwater streams, springs, ditches, flushes, small lakes, and ponds, which represent important freshwater resources. However, the relatively narrow and fragmented nature of small water bodies makes it difficult to monitor chlorophyll-a via medium-resolution remote sensing. In the present study, we first fused Gaofen-6 (a new Chinese satellite) images to obtain 2 m resolution images with 8 bands, which was approved as a good data source for Chlorophyll-a monitoring in small water bodies as Sentinel-2. Further, we compared five semi-empirical and four machine learning models to estimate chlorophyll-a concentrations via simulated reflectance using fused Gaofen-6 and Sentinel-2 spectral response function. The results showed that the extreme gradient boosting tree model (one of the machine learning models) is the most accurate. The mean relative error (MRE) was 9.03%, and the root-mean-square error (RMSE) was 4.5 mg/m3 for the Sentinel-2 sensor, while for the fused Gaofen-6 image, MRE was 6.73%, and RMSE was 3.26 mg/m3. Thus, both fused Gaofen-6 and Sentinel-2 could estimate the chlorophyll-a concentrations in small water bodies. Since the fused Gaofen-6 exhibited a higher spatial resolution and Sentinel-2 exhibited a higher temporal resolution.

Suppression of Alga Blooming by Zooplankton Filter Feeders in Small Water Bodies

2018 ◽  
Vol 45 (2) ◽  
pp. 199-204 ◽  
Author(s):  
T. N. Gerasimova ◽  
P. I. Pogozhev ◽  
A. P. Sadchikov
Keyword(s):  
Water Bodies ◽  
Small Water ◽  
Filter Feeders ◽  
Small Water Bodies
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