Relationship of physicochemical factors with fish biomass and production in Shadegan Wetland, Iran

Hashemi S, Ghorbani R, Kymaram F, Hossini SA, Eskandari G, Hedayati A. 2016. Relationship of physicochemical factors with fish biomass and production in Shadegan Wetland, Iran. Biodiversitas 17: 515-522. The biomass of fishes was estimate in the Shadegan Wetland with Leslie model. Also the relations...

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Autores principales: SEYEDAHMADREZA HASHEMI, RASOUL GHORBANI, FARHAD KYMARAM, SEYED ABASS HOSSINI, GHOLAMREZA ESKANDARI, ALIAKBAR HEDAYATI
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Publicado: MBI & UNS Solo 2016
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spelling oai:doaj.org-article:599f1e0044b146a3b829dbb0a96992ab2021-11-14T02:27:09ZRelationship of physicochemical factors with fish biomass and production in Shadegan Wetland, Iran1412-033X2085-472210.13057/biodiv/d170221https://doaj.org/article/599f1e0044b146a3b829dbb0a96992ab2016-06-01T00:00:00Zhttps://smujo.id/biodiv/article/view/325https://doaj.org/toc/1412-033Xhttps://doaj.org/toc/2085-4722Hashemi S, Ghorbani R, Kymaram F, Hossini SA, Eskandari G, Hedayati A. 2016. Relationship of physicochemical factors with fish biomass and production in Shadegan Wetland, Iran. Biodiversitas 17: 515-522. The biomass of fishes was estimate in the Shadegan Wetland with Leslie model. Also the relationships between fish biomass and physic-chemical parameters of were studies. Sampling was carried out seasonally at five stations; include Atish, Khorosy, Mahshar, Rogbe, and Salmane from April 2013 to March 2014. During this study, 2795 specimens were measured and weighed. The highest fish biomass and lowest fish biomass were in spring and winter seasons and Khorosy and Rogbe stations have highest and lowest fish biomass. The mean biomass of fish in four seasons Shadegan, 243±35 (kg/ha) and the amount of biomass in different seasons were not significantly different (P>0.05). Average values of water physicochemical parameters in different seasons were no significant (P>0.05), however average values of salinity stations were significant differences (P<0.05). Fish biomass regressions was estimated as Fish Biomass = 0.41 (temperature) 2.56. CCA ordination explained temperature, salinity, PH and DO, as the most important variables influencing the variation of fish composition in the Shadegan Wetland. Multi-layer artificial neural network showed four parameters (temperature, salinity, depth and DO) have the greatest impact on fish biomass.SEYEDAHMADREZA HASHEMIRASOUL GHORBANIFARHAD KYMARAMSEYED ABASS HOSSINIGHOLAMREZA ESKANDARIALIAKBAR HEDAYATIMBI & UNS Soloarticleartificial neural network, fish biomass, water physic-chemical parametersBiology (General)QH301-705.5ENBiodiversitas, Vol 17, Iss 2 (2016)
institution DOAJ
collection DOAJ
language EN
topic artificial neural network, fish biomass, water physic-chemical parameters
Biology (General)
QH301-705.5
spellingShingle artificial neural network, fish biomass, water physic-chemical parameters
Biology (General)
QH301-705.5
SEYEDAHMADREZA HASHEMI
RASOUL GHORBANI
FARHAD KYMARAM
SEYED ABASS HOSSINI
GHOLAMREZA ESKANDARI
ALIAKBAR HEDAYATI
Relationship of physicochemical factors with fish biomass and production in Shadegan Wetland, Iran
description Hashemi S, Ghorbani R, Kymaram F, Hossini SA, Eskandari G, Hedayati A. 2016. Relationship of physicochemical factors with fish biomass and production in Shadegan Wetland, Iran. Biodiversitas 17: 515-522. The biomass of fishes was estimate in the Shadegan Wetland with Leslie model. Also the relationships between fish biomass and physic-chemical parameters of were studies. Sampling was carried out seasonally at five stations; include Atish, Khorosy, Mahshar, Rogbe, and Salmane from April 2013 to March 2014. During this study, 2795 specimens were measured and weighed. The highest fish biomass and lowest fish biomass were in spring and winter seasons and Khorosy and Rogbe stations have highest and lowest fish biomass. The mean biomass of fish in four seasons Shadegan, 243±35 (kg/ha) and the amount of biomass in different seasons were not significantly different (P>0.05). Average values of water physicochemical parameters in different seasons were no significant (P>0.05), however average values of salinity stations were significant differences (P<0.05). Fish biomass regressions was estimated as Fish Biomass = 0.41 (temperature) 2.56. CCA ordination explained temperature, salinity, PH and DO, as the most important variables influencing the variation of fish composition in the Shadegan Wetland. Multi-layer artificial neural network showed four parameters (temperature, salinity, depth and DO) have the greatest impact on fish biomass.
format article
author SEYEDAHMADREZA HASHEMI
RASOUL GHORBANI
FARHAD KYMARAM
SEYED ABASS HOSSINI
GHOLAMREZA ESKANDARI
ALIAKBAR HEDAYATI
author_facet SEYEDAHMADREZA HASHEMI
RASOUL GHORBANI
FARHAD KYMARAM
SEYED ABASS HOSSINI
GHOLAMREZA ESKANDARI
ALIAKBAR HEDAYATI
author_sort SEYEDAHMADREZA HASHEMI
title Relationship of physicochemical factors with fish biomass and production in Shadegan Wetland, Iran
title_short Relationship of physicochemical factors with fish biomass and production in Shadegan Wetland, Iran
title_full Relationship of physicochemical factors with fish biomass and production in Shadegan Wetland, Iran
title_fullStr Relationship of physicochemical factors with fish biomass and production in Shadegan Wetland, Iran
title_full_unstemmed Relationship of physicochemical factors with fish biomass and production in Shadegan Wetland, Iran
title_sort relationship of physicochemical factors with fish biomass and production in shadegan wetland, iran
publisher MBI & UNS Solo
publishDate 2016
url https://doaj.org/article/599f1e0044b146a3b829dbb0a96992ab
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AT rasoulghorbani relationshipofphysicochemicalfactorswithfishbiomassandproductioninshadeganwetlandiran
AT farhadkymaram relationshipofphysicochemicalfactorswithfishbiomassandproductioninshadeganwetlandiran
AT seyedabasshossini relationshipofphysicochemicalfactorswithfishbiomassandproductioninshadeganwetlandiran
AT gholamrezaeskandari relationshipofphysicochemicalfactorswithfishbiomassandproductioninshadeganwetlandiran
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