Spatial distribution and temporal variation ofMicrocystis species composition and microcystin concentration in Lake Biwa

2005 ◽  
Vol 20 (3) ◽  
pp. 270-276 ◽  
Author(s):  
Kazuhiko Ozawa ◽  
Hiroki Fujioka ◽  
Minoru Muranaka ◽  
Atsushi Yokoyama ◽  
Yukimi Katagami ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Species Composition ◽  
Temporal Variation ◽  
Lake Biwa ◽  
Microcystin Concentration

scholarly journals Species composition and spatial distribution of sediment propagule bank in Lake Biwa

2012 ◽  
Vol 38 (1) ◽  
pp. 85-90
Author(s):  
Ayumi IMANISHI ◽  
Kimisato ODA ◽  
Junichi IMANISHI ◽  
Yosihiro NATUHARA ◽  
Yukihiro MORIMOTO
Keyword(s):  
Spatial Distribution ◽  
Species Composition ◽  
Lake Biwa ◽  
Propagule Bank

Species composition and spatio-temporal variation of bycatch from mid-water trawlers operating in the Arabian Sea along north-west coast of India

2021 ◽  
Vol 43 ◽  
pp. 101692
Author(s):  
P. Abdul Azeez ◽  
Prathibha Rohit ◽  
Latha Shenoy ◽  
Ashok Kumar Jaiswar ◽  
Mini Raman ◽  
...  
Keyword(s):  
Species Composition ◽  
Temporal Variation ◽  
West Coast ◽  
Arabian Sea ◽  
North West ◽  
West Coast Of India ◽  
Spatio Temporal

scholarly journals Spatial distribution and temporal variation of microcrustaceans assembly (Cladocera and Copepoda) in different compartments of a reservoir in the brazilian semiarid region

2018 ◽  
Vol 30 (0) ◽  
Author(s):  
Josiane Souza Santos ◽  
Nadson Ressyé Simões ◽  
Sérgio Luiz Sonoda
Keyword(s):  
Spatial Distribution ◽  
Spatial Variation ◽  
Temporal Variation ◽  
Aquatic Macrophytes ◽  
Temporal Dynamics ◽  
Lateral Compartment ◽  
Spatial And Temporal Variation ◽  
Semiarid Region ◽  
Brazilian Semiarid ◽  
Significant Spatial Variation

Abstract Aim: The objective of this study was to investigate the spatial and temporal variation of microcrustacean assemblages of a reservoir in the Brazilian semiarid region. Methods Physical and chemical water variables and samples of microcrustaceans were collected at eight sites of the reservoir between July 2013 and November 2014, in a total of seven campaigns. For this study, the reservoir was categorized in two compartments: lateral and central. Results Limnological variables showed significant temporal variation (PERMANOVA, Pseudo-F = 19.51, p = 0.001). Higher turbidity values and suspended solids were observed in the rainiest months, while during the dry months, we measured higher values of transparency, dissolved oxygen, and chlorophyll-a. It was not found significant spatial variation of limnological variables (PERMANOVA, Pseudo-F = 0.96; p = 0.394). During the study period, ten species were recorded: four Cladocera (Ceriodaphnia cornuta, Daphnia gessneri, Diaphanosoma birgei and Diaphanosoma spinulosum ) three Copepoda Calanoida (Argyrodiaptomus azevedoi, Notodiaptomus cearensis and Notodiaptomus iheringi) and three Copepoda Cyclopoida (Macrocyclops albidus, Thermocyclops minutus and Thermocyclops decipiens). The microcrustacean assemblages showed significant temporal variation (PERMANOVA, Pseudo-F = 4.34; p = 0.001) as well as significant spatial variation (PERMANOVA, Pseudo-F = 9.46; p = 0.001). The highest values of abundance and richness were observed in the lateral compartment, this result is mainly related to the presence of aquatic macrophytes in this region, because the analysis of partial RDA indicated that limnological variables explained only 11% of this variation (Pseudo-F = 2.08, p = 0.001). Conclusions The results suggest that the seasonality of the semiarid is an important factor in the temporal dynamics of the limnological variables, while the aquatic macrophytes play an important role in the spatial distribution of the microcrustacean assembly.

scholarly journals Temporal-spatial Distribution Characteristics of Air Pollutants in Chengdu Economic Region, China

2019 ◽  
Vol 118 ◽  
pp. 04027
Author(s):  
Hongjin Tong ◽  
Sha Liu ◽  
Ruixue Liao ◽  
Xiaomei Wei ◽  
Kangli Che ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Temporal Variation ◽  
Air Pollutants ◽  
Interpolation Method ◽  
Central Area ◽  
Average Concentration ◽  
Distribution Characteristics ◽  
Economic Region ◽  
Spatial Distribution Characteristics ◽  
Variation Characteristics

The previous characteristics researches of air pollution were almost based on data from national environmental monitoring stations in 2015. The temporal variation curves of air pollutants and the ArcGIS grid interpolation method were used to analyze the spatial-temporal variation of air pollutants in five cities of Chengdu economic region. In 2015, the monthly change trends of PM2.5, PM10, CO, NO2 and NO of air pollutants in Chengdu economic region were basically the same. The maximum monthly average concentration was in January or December, and the minimum was in May to September. The temporal variation of SO2 was characterized by little fluctuation of monthly concentration. The temporal variation characteristics of O3 were opposite to other pollutants. The spatial distribution of PM10 and PM2.5 was characterized by the largest concentration in Chengdu and the southwest of Meishan, in which they were mainly concentrated in the central area of Chengdu in winter. The average concentration of CO in Chengdu was the largest, followed by Deyang and Mianyang, and Meishan and Ziyang was the smallest. The concentrations of NO2 and NO in Chengdu were the largest, while those in Ziyang were the smallest. The spatial distribution characteristics of O3 were different from other pollutants. The areas with the largest concentration of O3 were Ziyang and a small part of west in Chengdu. The spatial distribution of SO2 was characterized by the largest concentration of SO2 in Ziyang, the lowest concentration in Mianyang and Deyang.

Spatial distribution and temporal variation of reference evapotranspiration in arid and semi-arid regions of Iran

2011 ◽  
Vol 26 (4) ◽  
pp. 500-512 ◽  
Author(s):  
Hossein Tabari ◽  
Ali Aeini ◽  
P. Hosseinzadeh Talaee ◽  
B. Shifteh Some'e
Keyword(s):  
Spatial Distribution ◽  
Temporal Variation ◽  
Arid Regions ◽  
Reference Evapotranspiration ◽  
Semi Arid

A measurement based analysis of the spatial distribution, temporal variation and chemical composition of particulate matter in Munich and Augsburg

2011 ◽  
Vol 20 (1) ◽  
pp. 47-57 ◽  
Author(s):  
Klaus Schäfer ◽  
Stefan Emeis ◽  
Stefanie Schrader ◽  
Szabina Török ◽  
Balint Alföldy ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Particulate Matter ◽  
Chemical Composition ◽  
Temporal Variation

scholarly journals Spatial distribution and species composition of small pelagic fishes in the Gulf of California

2006 ◽  
Author(s):  
Edgar Lanz ◽  
Manuel O. Nevárez Martínez ◽  
Juana López Martínez ◽  
Juan A. Dworak
Keyword(s):  
Spatial Distribution ◽  
Species Composition ◽  
Gulf Of California ◽  
Pelagic Fishes
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