ORIGINAL_ARTICLE
The effect of higher fuel price on pollutants emission in Iran
A key aspect of sustainable development in a country is how energy, environment and economic sectors interact. Greenhouse gas emissions and their impacts are among important environmental issues that have been in focus. The increase in the concentration of these gases in atmosphere to levels above the natural level results in global warming, depletion of the Earth’s protective layer against harmful solar radiation, and threatening whole natural life. The present study aimed at examining the factors affecting CO2 emission in Iran in 1981-2015. The studied variables included per capita CO2 emission, fuel price, per capita production, and per capita energy consumption. The relationship was examined by auto-regressive distributed lag (ARDL) model. It was found that CO2 emission is related to actual price of fuel indirectly and to per capita production and per capita energy consumption directly. According to the findings, 1% higher price of fuel would decrease CO2 emission by 0.14%, while 1% higher per capita production would increase it by 0.59%. Given the effectiveness of subsidy reform policy and the increased price of fuel on the alleviation of greenhouse gas emissions by road transport sector, it is advisable to gradually increase fuel price until it reaches FOB price in the Persian Gulf.
https://cjes.guilan.ac.ir/article_2777_fae5d0312396ad039afbae653b114bce.pdf
2018-03-01
1
10
10.22124/cjes.2018.2777
CO2 Emission
Environment
Fuel
Kuznets Curve
ARDL
S.N
Mousavi
1
Islamic Azad University of Marvdasht
AUTHOR
Z
Mozaffari
2
University of Tabriz
AUTHOR
M.K
Motamed
3
University of Guilan
AUTHOR
Abbaspour, M 2007, Energy, environment, and sustainable development. (S Khadivari, Ed.) Tehran, Iran: Sharif University Press, Elmi Publishing Institute (In Persian).
1
Amadeh, H, Ghafari, A & Farajzadeh, Z 2015, Analysis of environmental and welfare effects of energy subsidy reform (application of computable general equilibrium model). Journal of Iranian Energy Economics, 4: 33-62 (In Persian).
2
Andrews, J, Jelley, N & Jelley, NA 2013, Energy science: principles, technologies, and impacts. Oxford University Press.
3
Barghi Osgooyi, M 2008, The impact of trade liberalization on the greenhouse gases (CO2) emissions in EKC. Journal of Economic Research (Tahghighat-e-Eghtesadi), 43: 1-22 (In Persian).
4
Bastola, U & Sapkota, P 2015, Relationships among energy consumption, pollution emission, and economic growth in Nepal. Energy, 80: 254-262.
5
Beckerman, W 1992, Economic growth and the envrionment: Whose growth? Whose environment? World Development, 20: 481-496.
6
Behbudi, D, Fallahi, F & Barghi, E 2010, The economical and social factors affecting CO2 emission in Iran. Journal of Economic Research (Tahghighat-e-Eghtesadi), 45: 1-17 (In Persian).
7
Bonney, M & Jaber, MY 2011, Environmentally responsible inventory models: Non-classical models for a non-classical era. International Journal of Production Economics, 133: 43-53.
8
Delangizan, S, Khanzadi, A & Heidarian, M 2015, Studying the effects of fuel price changes on greenhouse gas emissions in the road transportation sector of Iran: Approach of robust least squares. Quarterly Journal of Quantitative Economics, 11: 47-77 (In Persian).
9
Fukui, H & Miyoshi, C 2017, The impact of aviation fuel tax on fuel consumption and carbon emissions: The case of the US airline industry. Transportation Research Part D: Transport and Environment, 50: 234-253.
10
Grossman, GM & Krueger, AB 1991, Environmental impacts of a North American free trade agreement (No. w3914). National Bureau of Economic Research.
11
Gurtu, A, Jaber, M & Searcy, C 2015, Impact of fuel price and emissions on inventory policies. Applied Mathematical Modelling, 39: 1202-1216.
12
Hatzigeorgiou, E, Polatidis, H & Haralambopoulos, D 2011, CO2 emissions, GDP and energy intensity: A multivariate cointegration and causality analysis for Greece, 1977-2007. Applied Energy, 88: 1377-1385.
13
Kaika, D & Zervas, E 2013, The environmental Kuznets curve (EKC) theory - Part A: Concept, causes and the CO2 emissions case. Energy Policy, 62: 1392-1402.
14
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15
Lotfalipour, M & Ashena, M 2010, A study on factors affecting the variations of CO2 emission in Iran's economics. Quarterly Energy Economics Review, 7: 121-145 (In Persian).
16
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17
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18
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19
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20
Roca, J, Padilla, E, Farré, M & Galletto, V 2001, Economic growth and atmospheric pollution in Spain: discussing the environmental Kuznets curve hypothesis. Ecological Economics, 39: 85-99.
21
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Shahbaz, M, Solarin, SA, Mahmood, H & Arouri, M 2013, Does financial development reduce CO2 emissions in Malaysian economy? A time series analysis. Economic Modelling, 35, 145-152.
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Tashkini, A 2005, Practical econometrics by Microfit package. Tehran, Iran: Dibagaran Institute (In Persian).
24
Varian, H 1992, Microeconomic analysis. (R Hosseini, Trans.) Tehran, Iran: Nashreney.
25
Vaseghi, E & Esmaeili, A 2010, Investigation of the determinant of CO2 emission in Iran (Using environmental Kuznets curve). Journal of Environmental Studies, 35: 99-110 (In Persian).
26
Virley, S 1993, The effect of fuel price increases on road transport CO2 emissions. Transport Policy, 1: 43-48.
27
ORIGINAL_ARTICLE
Models for length back-calculation in Caspian Kutum, Rutilus kutum (Pisces: Cyprinidae) from the Caspian Sea
The Caspian Kutum, Rutilus Kutum (Kamensky 1901) specimens were sampled by purse seine in the northern Iranian coast of the Caspian Sea at four locations: Feridoonkenar Shahed, Mahmoudabad Khoram, Lariim Azadi fishing coop, and the Shiroud River in Ramsar city. “Back-calculation” is a retrospective method of estimating the characteristics of growth of fish in terms of length and rate of growth in the years preceding capture. Back-calculation of fish lengths at previous ages from scales or otoliths is a widely used approach to estimate both individual and population growth history. The back-calculated lengths of the Caspian kutum,Rutilus kutum (Kamensky 1901) were obtained using six different models, namely scale proportional hypothesis, body proportional hypothesis, Fraser Lee, nonlinear scale proportional hypothesis, nonlinear body proportional hypothesis, and the newest method, Morita Matsuishi model. The results showed that the preferred back-calculation models is Fraser Lee model for both males and females, while the nonlinear body proportional hypothesis is only for the females.
https://cjes.guilan.ac.ir/article_2778_e21a186c4bd51f7eb83fff8684029c24.pdf
2018-03-01
11
21
10.22124/cjes.2018.2778
Northern Iran, Back-calculation
Rutilus kutum
s
eskandari
s.kohestan@sanru.ac.ir
1
Department of Fisheries, Faculty of Animal Science and Fisheries, Sari Agricultural Sciences and Natural Resources University, Sari, Iran
AUTHOR
M.K
Khalesi
2
Department of Fisheries, Faculty of Animal Science and Fisheries, Sari Agricultural Sciences and Natural Resources University, Sari, Iran
AUTHOR
M
Khoramgah
3
Department of Fisheries, Faculty of Animal Science and Fisheries, Sari Agricultural Sciences and Natural Resources University, Sari, Iran
AUTHOR
S
Asgari
4
Department of Fisheries, Faculty of Animal Science and Fisheries, Sari Agricultural Sciences and Natural Resources University, Sari, Iran
AUTHOR
N
Mirzakhani
5
Department of Fisheries, Faculty of Animal Science and Fisheries, Sari Agricultural Sciences and Natural Resources University, Sari, Iran
AUTHOR
Bagenal, TB & Tesch, FW 1978, Age and growth. In Methods for Assessment of Fish
1
Production in Fresh Waters (Bagenal, TB & Tesch, FW.), Oxford, Blackwell Scientific Publications. pp. 101–136.
2
Borkholder, BD & Edwards, BD 2001, Comparing the use of dorsal fin spines with scales to back-calculate length at age estimates in Walleyes. North American Journal of Fisheries Management, 21: 935-942.
3
Escot, C & Lorencio, G 1999, Comparison of four methods of back-calculating growth using otoliths of a European barbel, Barbus sclateri (Gunther) (Pisces: Cyprinidae). Marine and Freshwater Research, 50: 83–88.
4
Francis, RICC 1990, Back-calculation of fish length: a critical review. Journal of Fish Biology, 36: 883–902.
5
Fraser, C 1916, The growth of the spring salmon. Transactions of the Pacific Fisheries Society, 29–39.
6
Fukuwaka, MA & Kaeriyama, M 1997, Scale analyses to estimate somatic growth in sockeye salmon .Canadian Journal of Fisheries and Aquatic Sciences, 54: 631-636.
7
Heidarsson, T, Antonsson, T & Snorrason, SS 2006, The relationship between body and scale growth proportions and validation of two back-calculation methods using individually tagged and recaptured wild Atlantic salmon. Transactions of the American Fisheries Society, 135: 1156-1164.
8
Horppila, J & Nyberg, K 1999, The validity of different methods in the back-calculation of the lengths of roach-a comparison between scales and cleithra. Journal of Fish Biology, 54: 489–498.
9
Johal, MS, Esmaeili, H & Tandon, K 2001, A comparison of back-calculation length of silver carp derived from bony structures. Journal of Fish Biology, 59: 1483-1493.
10
Klumb, RA, Bozek, MA & Frie, RV 1999, Proportionality of body to scale growth: validation of two back-calculation models with individually tagged and recaptured smallmouth bass and walleyes. Transactions of the American Fisheries Society, 128: 815-831.
11
Klumb, RA, Bozek, MA & Frie, RV 2001, Validation of three back-calculation models by using multiple oxytetracycline marks formed in the otoliths and scales of bluegill × green sunfish hybrids. Canadian Journal of Fisheries and Aquatic Sciences, 58: 352-364.
12
Lee, RM 1920, A review of the methods of age and growth determination in fishes by means of scales. Board of Agriculture and Fisheries. Fishery Investigations, Series, 2, 4: 32p.
13
Li, H et al. 2010, Comparison of four methods using scales and lapilli for back-calculation of roach Rutilus rutilus (Linnaeus, 1758) in Ulungur Lake, Xinjiang Uigur Autonomous region, China. Acta Hydrobiologica Sinica, 34: 286-292
14
Lowerrebarbieri, SK, Chittenden, ME & Jones, CM 1994, A Comparison of a validated otolith method to age Weakfish, Cynoscion regalis, with the traditional scale method. Fishery Bulletin, 92: 555-568.
15
Martinson, CE, Masuda, MM & Helle, JH 2000, Back-calculated fish lengths, percentages of scale growth, and scale measurements for two scale measurement methods used in studies of salmon growth. Auke Bay Laboratory. Alaska Fisheries Science Center. 11305 Glacier Highway, Juneau, AK 99801-8626 USA.
16
Milicich, MJ & Choat, JH 1992, Do otoliths record changes in somatic growth-rate conflicting evidence from a laboratory and field study of a temperate reef fish, Parika scaber. Australian Journal of Marine and Freshwater Research, 43: 1203-1214.
17
Morita, K & Matsuishi, T 2001, A new model of growth back-calculation incorporation age effect based on otoliths. Canadian Journal of Fisheries and Aquatic Sciences, 58: 1805-1811.
18
Morita, K 2001, Back-calculation of fork length 282 of white-spotted charr from scales: a comparison between major and minor axes measurements. Journal of Fish Biology, 59: 1104–1107.
19
Mugiya, Y 1990, Long-term effects of hypophysectomy on the growth and calcification of otoliths and scales in the gold fish, Carassius auratus. Zoology Science, 7: 273–279.
20
Razavi, B 1989, The biology of the Caspian Kutum, Rutiluskutum. Master’s thesis. The University of Tehran. Iran.
21
Reznick, D, Lindbeck, E & Bryga, H 1989. Slower growth results in larger otoliths: an experimental test with guppies (Poecilia reticulata). Canadian Journal Fisheries and Aquatic Sciences, 46: 108–112.
22
Roemer, ME & Oliveira, K 2007, Validation of back-calculation equations for juvenile bluefish (Pomatomus saltatrix) with the use of tetracycline-marked otoliths. Fishery Bulletin, 105: 305–309.
23
Secor, DH & Dean, JM 1992, Comparison of otolith-based back-calculation methods to determine individual growth histories of larval striped bass, Morone saxatilis. Canadian Journal of Fisheries and Aquatic Sciences, 49: 1439–1454.
24
Smale, MA & Taylor, WW 1987, Sources of back-calculation 301 error in estimating growth of Lake Whitefish. In Age and Growth of Fish (Summerfelt, RC & Hall, GE, eds.), Ames, IA: Iowa State University Press, pp. 189–202.
25
Smedstad, OM & Holm, JC 1996, Validation of back-calculation formulae for cod otoliths. Journal of Fish Biology, 49: 973–985.
26
Whitney, RR & Carlander, KD 1956, Interpretation of body-scale regression for computing body length of fish. Journal of Wildlife Management, 20: 21–27.
27
ORIGINAL_ARTICLE
Evaluation of antimicrobial activities of microalgae Scenedesmus dimorphus extracts against bacterial strains
The study was conducted to analyze the existence of bioactive phytochemicals extracts in green alga Scenedesmus dimorphus and their antimicrobial role. Various solvents such as methanol, ethanol, N-hegzane and diethylether were used for extraction. The extracts of of Scenedesmus dimorphus were tested against two Gram - positive bacteria (Bacillus subtilis and Micrococcus luteus), a Gram - negative bacterium (A. hydrophila) and Escherichia coli by the agar well diffusion method. Four different methanolic, ethanolic, hexane and diethylether extracts showed effective inhibition against different bacterial pathogens. Diethylether extract was very effective against bacterial strains compared to other extracts. Methanolic extract effectively inhibited A. hydrophila in comparison with other extracts, while ethanolic extract did not have any inhibitory effect on the bacterium. Methanolic, ethanolic, hexane and diethylether extracts were analyzed by GC mass. The most abundant compounds in methanolic extract of S. dimorphus included esters, plasticizer compound and terpens, while in the ethanolic, N-hexane and diethylether extracts, the most abundant compounds were found to be plasticizers, hydrocarbon and esters. These results indicate the presence of promising antimicrobial compounds in the examined algal species. Further phytochemical studies are required to elucidate the structutre and detailed activities of these compounds. So, we achieved antimicrobial activity in the methanolic, ethanolic, hexane and ether extracts of green microalgae against some pathogenic bacteria as well as employing GC mass autogram for S. dimorphus extracts for preliminary detection of active constituents.
https://cjes.guilan.ac.ir/article_2779_385908e7e0a7b579468004b454405371.pdf
2018-03-01
23
34
10.22124/cjes.2018.2779
Scenedesmus dimorphus
Antibacterial
Antimicrobial
Aeromonas hydrophila
Bacillus subtilis
Z
Habibi
1
University of Guilan
AUTHOR
J
Imanpour Namin
2
University of Guilan
AUTHOR
Z
Ramezanpour
3
International Research Institute of Sturgeons of Rasht
AUTHOR
Alghazeer, R, Whida, F, Abduelrhman, E, Gammoudi, F, Naili, M 2013, In vitro antibacterial activity of alkaloid extracts from green, red and brown macroalgae from western coast of Lybia. African Journal of Biotechnology, 12: 7086-7091.
1
Al-Salif, SSA, Abdel-Raouf, N, El-Wazanani, HA, Aref, IA 2014, Antibacterial substances from marine algae isolated from Jeddah coast of Red Sea, Saudi Arabia. Saudi Journal of Biological Sciences, 21: 57–64.
2
Amaro, HM, Guedes, AC, Malcata, FX 2011, Science against microbial pathogens: communicating current research and technological advances A. Mendez-Vilas (Ed.), Antimicrobial activities of microalgae: an invited review, pp. 1272–1280.
3
Bhagavathy S, Sumathi, P & Bell, J, Sh 2011, Green algae Chlorococcum humicola- a new source of bioactive compounds with antimicrobial activity, Asian Pacific Journal of Tropical Biomedicine, S1-S7
4
Beena, B, Nair & Krishnika, A 2011, Antibacterial activity of freshwater microalga (Scenedesmus sp.) against three bacterial strains. Journal of Bio-Science Research, 2: 160-165.
5
Borowitzka, MA 1988, Algal growth media and sources of algal cultures. In: Borowitzka, M. A., & Borowitzka L J (eds.) Micro-algal Biotechnology. Cambridge University Press, Cambridge, pp. 456-465.
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Borowitzka, MA & Borowitzka LJ 1992, In: Microalgal Biotechnology, Cambridge University Press, Great Britain, pp. 179.
7
Cowan, MM 1999, Plant products as antimicrobial agents. Clinical Microbiological Reviews, 12: 564-582.
8
Desbois, AP, Lebl, T, Yan, L & Smith, VJ 2008, Isolation and structural characterization of two antibacterial free fatty acids from the marine diatom, Phaeodactylum tricornutum. Applied Microbiology and Biotechnology, 81: 755-764.
9
Dussault, D, Khanh, Dang, VuA, Vansach, Horgen, B & Lacroix, M 2016, Antimicrobial effects of marine algal extracts and cyanobacterial pure compounds against five foodborne pathogens. Food Chemistry, 199: 114–118
10
Ely, R, Supriya, T & Naik, CG 2004, Antimicrobial activity of marine organisms collected off the coast of South East India. Journal of Experimental Marine Biology and Ecology, 309: 121-127.
11
Febles, CI, Arias, A, Gil-Rodriguez, MC et al. 1995, In vitro study of antimicrobial activity in algae (Chlorophyta, Phaeophyta and Rhodophyta) collected from the coast of Tenerife. Anuario Del Estudios Canarios, 34: 181-192 (In Spanish).
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Ghasemi, Y, Tabatabaei Yazdi, M, Shafiee, A, Amini, M, Shokravi, S & Zarrini Parsiguine G 2004, A novel antimicrobial substance from Fischerella ambigua. Pharmacutical Bioloogy, 42: 318-322.
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Kotai, J 1972, Instructions for preparation of modified nutrient solution Z8 for algae. Norwegian Institute for Water Research, Oslo, 11(69): 5.
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Kulik MM 1995, The potential for using cyanobacteria (bluegreen algae) and algae in the biological control of plant pathogenic bacteria and fungi. European Journal of Plant Pathology, 101: 585-599.
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Lima-Filho, JVM, Carvalho, AFFU, Freitas, SM et al. 2002, Antibacterial activity of extracts of six macroalgae from the Northeastern Brazilian Coast. Brazilian Journal of Microbiology, 33: 311-313.
21
Maftuch, I, Adam, A, Zamzami, I 2016, Antibacterial effect of Gracilaria verrucosa bioactive on fish pathogenic bacteria. Egyptian Journal of Aquatic Research, 42: 405–410
22
Ming, L, Yixiang, MJ, Cao, L, Guang-Ming, Q, Chen, L, Sun, H & Chen, H 2017, Antibacterial activity and mechanisms of depolymerized fucoidans isolated from Laminaria japonica, Carbohydrate Polymers, 172: 294–305
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Moreau, J, Pesando, D, Bernad P et al. 1988, Seasonal variations in the production of antifungal substances by some Dictyotales (brown algae) from French Mediterranean coast. Hydrobiology, 162: 157- 162.
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Patra, JK, Patra, AP, Mahapatra, NK, Thatoi, N, Das, S, Sahu, RK & Swain, GC 2009, Antimicrobial activity of organic solvent extracts of three marine macroalgae from Chilika Lake, Orissa, India. Malaysian Journal of Microbiology, 5: 128-131.
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Pina-Perez1, MC, Rivas, A, Martinez, A & Rodrigo, D 2017, Antimicrobial potential of macro and microalgae against pathogenic and spoilage microorganisms in food. Food Chemistry, http://dx.doi.org/ 10.1016/j.foodchem,2017.05.033
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Prakash, JW, Johnson, M & Solomon, J 2011, Antimicrobial activity of certain fresh water microalgae from Thamirabarani. Asian Pacific Journal of Tropical Biomedicine, 1: 170-173.
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Rabia, A, Fauzi, W, Entesar, A, Fatiem, G & Mahboba, N 2013, In vitro antibacterial activity of alkaloid extracts from green, red and brown macroalgae from western coast of Libya. African Journal of Biotechnology, 12: 7086-7091.
34
Radhika, D, Veerabahu, C & Priya, R 2012, Antibacterial activity of some selected seaweeds from the Gulf of Mannar Coast, South India. Asian Journal of Pharmaceutical and Clinical Research, 5: 89-90.
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Reverter, M, Bontemps, N, Lecchini, D, Banaigs, B & Sasal, P 2014, Use of plant extracts in fish aquaculture as an alternative to chemotherapy: Current status and future perspectives, Aquaculture, doi: 10.1016/j. aquaculture .2014.05.048
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Rizk, MA 2006, Growth activities of the sugarbeet pathogens Sclerotium rolfsii Sacc. Rhizoctonia solani Kühn. and Fusarium verticillioides Sacc. under cyanobacterial filtrates stress. Plant Pathology Journal, 5: 212-215.
37
Rosell, KG & Srivastava, LM 1987, Fatty acids as antimicrobial substances in brown algae. Hydrobiologia 151/152: 471-475.
38
Sastry, VMVS & Rao, GRK 1994, Antibacterial substances from marine algae: successive extraction using benzene, chloroform and methanol. Botanica Marina, 37: 357-360.
39
Senthilkumar, P & Sudha, S 2012, Antioxidant and Antibacterial Properties of Methanolic Extract of Green Seaweed Chaetomorpha linum From Gulf of Mannar: Southeast Coast of India. Jundishapur Journal of Microbiology, 5: 411–415
40
Sieradzki, K, Robert, RB, Haber, SW & Tomasz, A 1999, The development of vanomycin resistance in patient with methicillin resistant S. aureus. The New England Journal of Medicine, 340: 517-523.
41
Skulberg, OM 2006, Bioactive chemicals in microalgae. In: Richmond, A. (ed) Handbook of microalgal culture, biotechnology and applied phycology. Blackwell, Oxford, pp. 485 512.
42
Soltani, N, Khavari-Nejad, RA, Tabatabaei Yazdi, M, Shokravi, S & Fernandez-Valiente E 2005, Screening of soil cyanobacteria for antifungal and antibacterial activity. Pharmaceutical Biology, 43: 455 459.
43
Tuney, I, Cadirci, BH, Unal, D & Sukatar A 2006, Antimicrobial activities of the extracts of marine algae from the coast of Urla (Izmir, Turkey). Turkish Journal of Biology, 30: 171-175.
44
Zheng H, Yin, J, Gao Z, Huang, HJiX & Dou, C 2011, Disruption of Chlorella vulgaris Cells for the Release of Biodiesel Producing Lipids: A Comparison of grinding, ultrasonication, bead milling, enzymatic lysis, and microwaves. Applied Biochemistry and Biotechnology, 164: 1215- 1224.
45
ORIGINAL_ARTICLE
Bacterial responses to environmental herbicide pollutants (glyphosate and paraquat)
The toxic effect of herbicides on non- target microorganisms may influence degradation of organic matter resulting in changes to nutrient cycling. In the present study, different strains of bacteria incubated in media containing different concentrations of glyphosate and paraquat were assessed over a period of two incubation terms. The deleterious impact of the herbicide was observed as glyphosate and paraquate treatments led to a reduction in the bacterial population. Analysis of the colony- forming unit (CFUs) showed a declining in microbial growth from 0 to 24 hours of incubation in all concentrations of glyphosate followed by a steady declining rate of the bacterial population after 48 h. The greatest bacterial population developed in media containing concentrations of glyphosate and paraquat was observed with strains S13.3, while strains S55 and S35 showed the lowest biomass production in response to all concentrations of glyphosate and paraquat. Based on the results obtained, strain S13.3 was determined to be resistant to the herbicides examined and may be useful for bioremediation of these compounds in soil.
https://cjes.guilan.ac.ir/article_2780_30afd3cf19d9809d932ed8a31dd2273b.pdf
2018-03-01
35
43
10.22124/cjes.2018.2780
Herbicides
Microbial populations
Microbial biomass
Glyphosate
Paraquat
M
Mazhari
1
Islamic Azad University of Karaj
AUTHOR
J
Ferguson
2
University of Minnesota
AUTHOR
Adomako, MO & Akyeampong, S 2016, Effect of some commonly used herbicides on soil microbial population. Journal of Environment and Earth Science, 6: 30-38.
1
Baboo, M, Pasayat, M, Samal, A, Kujur Maharana, JK & Patel, AK 2013, Effect of four herbicides on soil Organic carbon, microbial biomass, enzyme activity and microbial populations in agricultural soil. International Journal of Research in Environmental Science and Technology, 3: 100 - 112.
2
Benslama, O & Boulahrouf, A 2013, Isolation and characterization of glyphosate- degrading bacteria from different soils of Algeria. African Journal of Microbiology Research, 7: 5587- 5595.
3
Busse, MD, Ratcliff, AW, Shestak, CJ& Powers, RF 2001, Glyphosate toxicity and the effects of long-term vegetation control on soil microbial communities. Soil Biology and Biochemistry, 33:1777-2789.
4
Carp, RJ, Bilton, RF & Atkinson, T 1985, Mechanism of biodegradation of paraquat by Lipomyces starkeyi. Applied and Environment Microbiology, 49: 1290- 1294.
5
Chapalamadugu, S & Chaudhry, GR 1992, Microbial and biotechnological aspects of metabolism of carbamates and organo -phosphates. Critical Reviews in Biotech -nology, 12: 357-389.
6
De Lorenzo, ME, Scott, GI & Ross, PE 2001, Toxicity of pesticides to aquatic microorganisms: A review. Environmental Toxicology and Chemistry, 20: 84-98.
7
Furukawa, K 2003, Super bugs for bioremediation. Trends in Biotechnology, 21: 187- 190.
8
Haney, RL, Senseman, SA, Hons, FM & Zuberer, DA 2000, Effect of glyphosate on microbial activity and biomass. Weed Science, 48: 89- 93.
9
Kolawole, OA & Akinsoji, AO 2011, Biodegradation of glyphosate pesticide by bacteria isolated from agricultural soil. Report and Opinion, 3: 124- 128.
10
Latha, PC & Gopal, H 2010, Effect of herbicides on soil microorganisms. Indian Journal of Weed Science, 42: 217-222.
11
Margino, S, Martani, E & Sunarminto, BH 2000, Paraquat in Peat Land: I. Its Effect on the Dynamics of microbial population. Journal of PerlindunganTanaman Indonesia, 6: 91- 100.
12
Matsumara, F & Boush, GM 1971, Metabolism of insecticides by microorganisms. In: Soil biochemistry, McLaren, AD, Skujins J (eds.), Marcel Dekker, Inc., New York, USA, pp. 320 - 336.
13
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14
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15
pp. 169-216.
16
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17
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18
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19
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20
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21
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22
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24
ORIGINAL_ARTICLE
Heavy metals in coastal sediments of South Caspian Sea: natural or anthropogenic source?
This paper focuses on heavy metal distribution patterns in sediments of central Guilan (CG) and east Mazandaran (EM) in the south Caspian Sea coasts, north of Iran. Sediment sub-samples were retrieved from core and surficial samples in different environments of marine and coastal lagoons as well as coastal outcrops. Inductively Coupled Plasma Mass Spectrometry and Atomic Emission Spectrometry (ICP-MS and ICP-AES) analysis were used to determine the metal chemistry. Concentration of the selected heavy metals exhibited variations through sediment samples which are partially related to grain size and organic matter content. Geoaccumulation index and statistical procedures have been implemented for analyzing the absolute metal values. Result of the geoaccumulation index demonstrated that the metal distribution reflects the influence of geological background of the watershed area. Some elements including Pb, Ni, Cu, Sr and Ba showed elevated concentration in the CG that could be attributed to development of industrial activities. A comparison of the metal concentration in the marine sediments and the Late Holocene outcrops revealed that the level of the metals concentration at the sea generally corresponds to natural background. The northern part of Iranian multi-lithological catchments basin is the main source for the sediments that drained by the rivers to the South Caspian Sea basin
https://cjes.guilan.ac.ir/article_2781_2f60b4cfb45ba88cbbfaf155a182f686.pdf
2018-03-01
45
61
10.22124/cjes.2018.2781
Caspian Sea
Geoaccumulation Index
Heavy metals
Principal component analysis
Sediment
H
Alizadeh Ketek Lahijani
1
Iranian National Institute for Oceanography and Atmospheric Science of Tehran
AUTHOR
A
Naderi Beni
2
Iranian National Institute for Oceanography and Atmospheric Science of Tehran
AUTHOR
V
Tavakoli
3
University of Tehran
AUTHOR
Adams, WJ, Kimerle, RA & Barnett Jr, JW 1992, Sediment quality and aquatic life assessment. Environmental Science & Technology, 26: 1864-1875.
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63
ORIGINAL_ARTICLE
Estimating the carrying capacity of tourism and the necessity of forest stands management (Case study: Darkeshforest, North Khorasan, Iran)
This study focuses on the carrying capacity estimation for Darkesh forest in Northeast Iran. Four factors were used for estimating the carrying capacity including tourist flows, size of the area, optimum space available for each tourist, and visiting time. Results showed that the physical carrying capacity was 2727 ha or 165 visitors/day, while the real carrying capacity was 2719 ha or 132 visitors/day. An average of 200 tourists per day visited the park during 2015, which was much higher than the estimated carrying capacity. Development of recreational uses in the study area would also affect the forest production and other benefits in long term. This study suggested that to prevent intense use of the forest area, a plan must be developed. On the other hand, the number of visitors has to be precisely calculated in order to maintain healthy forest stands and to secure the ecological benefits for future generations.
https://cjes.guilan.ac.ir/article_2782_7447e96d7c5608c473d615ada7ca2fb7.pdf
2018-03-01
63
69
10.22124/cjes.2018.2782
Estimation
Carrying capacity
Management
Darkesh forest
Iran
A
Mashayekhan
1
University of Sari
AUTHOR
M.R
Pourmajidian
2
University of Sari
AUTHOR
H
Jalilvand
3
University of Sari
AUTHOR
M.R
Gholami
4
Shirvan Higher Education Complex
AUTHOR
Canestrelli, Elio & Costa, Paolo 1991, Tourist carrying capacity: A fussy approach, Annals of Tourism Research, Vol.18, pp.295-311.
1
Cifuentes, MA 1992, Determinación de capacidad de cargaturísticaenáreasprotegidas .Costa Rica: Biblioteca Orton IICA/CATIE. (in France).
2
Eker, O 2008, Recreational Carrying Capacity of Belgrad Forest. KSU Journal of Science and Engineering, 11(2): 77-80.
3
Getz, D 1982, A rational and methodology for assessing capacity to absorb tourism, Ontario Geographic, 19: 92-102.
4
Harshaw, HW& Meitner, MJ 2006, Chapter 8: Recreation Management. In S Watts (Ed.), Forestry Handbook for British Columbia (5th ed.), Vancouver, 293p.
5
Hendee, JC 1990, Principles of wilderness management. In J CHendee, G HStankey & R C Lucas (Eds.), Wilderness Management (2th ed., pp. 181-193). Golden, CO: North American Press.
6
Lee, wk, Son, MH, & Kwak, DA 2005, Development of a Carrying Capacity Assessment System for the Chi-Ri National Park. 5 pp.
7
Manning, R, Lime, D & Hof, M 1996a, Social Carrying Capacity of natural Areas: Theory and Application in the US National Parks. Natural Areas Journal, 16(2): 118-127.
8
Mexa, A & Coccossis, H 2004, Tourism carrying capacity: a theoretical overview. In HCoccossis & AMexa (Eds.), The challenge of tourism carrying capacity assessment: Theory and practice. England: Ashgate.
9
Mitchell, J.G, 1995, Our National Parks. National Geographic, 186: 1-55.
10
Munar, FXR 2002, Análisis de capacidad de cargaen los espacioslitorales, calas e playas, situadosenáreasnaturales de especial interés de la Isla de Menorca. Spain: Universidad de Almería. 11 pp (in France).
11
Nash, R 2001, Wilderness and the American Mind (4thed.). New Haven CT: YaleUniversity Press. pp. 433-446.
12
Stankey, GH, Cole, DN, Lucas, RC, Peterson, ME, Frissell, SS & Washburne, RF 1985, The limits of acceptable change (LAC) system for wilderness planning. USDAForest Service General Technical Report INT-176. 43 pp.
13
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14
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15
Zacarias, DA, Williams, AT& Newton, A 2011, Recreation carrying capacity estimations to support beach management at Praia de Faro, Portugal. Applied Geography, 31: 1075-1081.
16
ORIGINAL_ARTICLE
Assessment of geostatistical and interpolation methods for mapping forest dieback intensity in Zagros forests
During recent years, oak decline has been widely spread across Brant’s oak (Quercus Brantii Lindl.) stands in the Zagros Mountains, Western Iran, which caused large-area forest dieback in several sites. Mapping the intensity and spatial distribution of forest dieback is essential for developing management and control strategies. This study evaluated a range of geostatistical and interpolation methods to explore the spatial structure and provide area-based maps of the intensity of forest dieback across a representative test site - Ilam Province - that was severely affected by Oak decline. The geostatistical analysis provided in-depth measures of the spatial structure amongst the selective sampling units (120 quadratic sample plots of 1200 m2), which eventually resulted in an area-based maps of dieback intensity. The accuracy of the applied methods was assessed by mean error percentage (%ME), root mean squared error percentage (%RMSE) and coefficient of determination (R2). Results showed moderate spatial structure within the sampling units. Moreover, cokriging (associated with soil humidity and aspect as independent variables) approach resulted in the highest accuracy, followed by two other methods of kriging and Radial Basis Function. Results suggested that cokriging can accurately estimate the intensity of dieback and its spatial distribution in the study area. According to this, an average dieback intensity of 18.12 % was estimated within the study area.
https://cjes.guilan.ac.ir/article_2783_f4f36e7ab7c90d170657c55df22c0383.pdf
2018-03-01
71
84
10.22124/cjes.2018.2783
Oak decline
Spatial structure
Interpolation
Geostatistics
Zagros
O
Karami
1
Sari University
AUTHOR
A
Fallah
2
Sari University
AUTHOR
S.H
Shataei
3
Gorgan University
AUTHOR
H
Latifi
taxus22@gmail.com
4
University of Wuerzburg
AUTHOR
Akhavan, R & Kleinn, C 2009, On the potential of kriging for estimation and mapping of forest plantation stock (Case study: Beneshki plantation). Iranian Journal of Forest and Poplar Research, 17: 303-318.
1
Akhavan, R, Zahedi Amiri, Gh & Zobeiri, M 2010, Spatial variability of forest growing stock using geostatistics in the Caspian region of Iran. Caspian Journal of Environment Sciences, 8: 43-53.
2
Akima, H 1970, A new method of interpolation and smooth curve fitting based on local procedures. Journal of Association for Computing Machinery, 17: 589–602.
3
Anonymous, 2012, Instructions of forest sustainable management in Zagros forest ecosystems for prevention and control of oak dieback. Organization of Forests, Rangelands and Watershed Management, Tehran, Iran, 61 p.
4
Baguskas, SA, Peterson, SH, Bookhagen, B & Still, CJ 2014, Evaluating spatial patterns of drought - induced tree mortality in a coastal California pine forest. Forest Ecology and Management, 315: 43–53.
5
Borrough, PA 2001, GIS and geostatistics: Essential partners for spatial analysis, Environmental and Ecological Statistics, 8: 361 –377.
6
Cambardella, CA & Karlen, DK 1999, Spatial analysis of soil fertility parameters. Precision Agriculture, 1: 5–14.
7
Cocco, A, Cossu, AQ, Erre, P, Nieddu, G & Luciano, P 2012, Spatial analysis of gypsy moth populations in Sardinia using geostatistical and climate models. Agricultural and Forest Entomology, 12: 417–426.
8
Duffera, M, Jeffrey, GW & Weisz, R 2007, Spatial variability of Southeastern U.S. Coastal Plain soil physical properties: Implications for site - specific manag -ement. Geoderma, 137: 327–339.
9
Erre, P, Chessa, I, Nieddu, G & Jones, PG 2009, Diversity and spatial distribution of Opuntia spp. in the Mediterranean Basin. Journal of Arid Environments, 73: 1058–1066.
10
Fan, Z, Fan, X, Spetich, MA, Shifley, SR, Moser, WK, Jensen, RG & Kabrick, JM 2011, Developing a stand hazard index for oak decline in upland oak forests of the Ozark Highlands, Missouri. Northern Journal of Applied Forestry, 28: 19-26.
11
Foster, JR, Townsend, PA & Mladenoff, DJ 2013, Spatial dynamics of a gypsy moth defoliation outbreak and dependence on habitat characteristics. Landscape Ecology, 28: 1307-1320.
12
Gunnarsson, F, Holm, S, Holmgren, P & Thuresson, T 1998, On the potential of kriging for forest management planning. Scandinavian Journal of Forest Research, 13: 237- 245.
13
Habashi, H, Hosseini, SM, Mohammadi, J & Rahmani, R 2007, Application of geostatistics techniques in the study of soils in forest areas. Iranian Journal of Agricultural Sciences and Natural Resources, 14: 18-27 (In Persian).
14
Hassani-Pak, A 2006, Geostatistics. Tehran University Press, Tehran, Iran, 2th edition, 314 p.
15
Heidari, R 2006, Investigation of different methods of distance inventory in Zagros forests. PhD Dissertation, Department of Natural Resources, Tehran University, 116 p.
16
Hlásny, T, Vizi, L, Turčáni, M, Koreň, M, Kulla, L & Sitková, Z 2009, Geostatistical simulation of bark beetle infestation for forest protection purposes. Journal of Forest Science, 55: 518–525.
17
Hohn, ME, Liebhold, AM & Gribko, LS 1993, A geostatistical model for forecasting the spatial dynamics of defoliation caused by the gypsy moth, Lymantria dispar (Lepidoptera: Lymantriidae). Environme -ntal Entomology, 22: 1066–1077.
18
Holdenrieder, O, Pautasso, M, Weisberg, P & Lonsdale, D 2004, Tree diseases and landscape processes: The challenge of landscape pathology. Trends in Ecology and Evolution, 19: 446− 452.
19
Hosseini, A, Hosseini, SM, Rahmani, A & Azadfar, D 2014, Comparison between two oak stands (healthy and affected by oak decline) in respect to characteristics of competitive environments at Ilam province. Iranian Journal of Forest and Poplar Research, 21: 565-577 (In Persian).
20
Hosseini, V, Akhavan, R & Tahmasebi, M 2012, Effect of Pistachio (Pistacia atlantica) canopy on the spatial distribution of soil chemical characteristics (Case study: Sarvabad, Kurdistan Province, Iran). Iranian Journal of Forest, 4: 13-24 (In Persian).
21
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ORIGINAL_ARTICLE
Serum profiles of calcium, phosphorus, magnesium, vitamin D and parathyroid hormone in Caspian horses during different seasons
Minerals play an essential role in the normal vital process.Calcium, phosphorus and magnesium are the most abundant minerals. Vitamin D and parathyroid hormone play a key role in regulation of their homeostasis as well. The aim of this study was to evaluate calcium, phosphorus, magnesium, vitamin D and parathyroid hormone on 30 Caspian horses of Guilan Province (south of the Caspian Sea) in two different seasons. So that, 15 stallions and 15 mares were sampled at the age groups ≤ 3 years and > 3 years, respectively. Fasting blood samples were collected twice, in August and January 2015 from jugular vein of horses. Serum calcium, phosphorus and magnesium were measured by colorimetric methods, while 25(OH)D3 and parathyroid hormone were measured by ELISA. The calcium (11.50 vs. 14.25 mg dL-1), magnesium (2.13 vs. 3.72 mg dL-1) and vitamin D (1.66 vs. 2.48 ng mL-1) levels were lower in winter than in summer (P < 0.05). The Caspian horses had higher phosphorus (4.52 vs. 3.26 mg dL-1) in winter than in summer (P < 0.05). Effect of sex on the measured parameters was not significant. Effects of age on the calcium, magnesium, vitamin D and parathyroid hormone levels were not significant, but ≤ 3 year - old horses had higher phosphorus (4.63 vs. 3.15 mg dL-1) than > 3 year - old ones (P < 0.05). The vitamin D level of mares was higher (3.10 vs. 1.43 ng mL-1) in summer than in winter (P < 0.05). Effects of sex, season, age and their interactions on parathyroid hormone were not significant. In conclusion, calcium, phosphorus, magnesium and parathyroid hormone levels in Caspian horses were within their physiological range, but vitamin D was low without any signs of deficiency. The Caspian horses had lower calcium, magnesium and vitamin D levels in winter than in summer.
https://cjes.guilan.ac.ir/article_2784_007cdacb0d5bfcc150f659d72923f520.pdf
2018-03-01
85
92
10.22124/cjes.2018.2784
Caspian horse
Calcium
Phosphorous
Vitamin D
Parathyroid hormone
N
Effati
1
University of Guilan
AUTHOR
M
Mohammadi
2
University of Guilan
AUTHOR
S
Nazifi
3
Shiraz University
AUTHOR
E
Rahimabadi
4
Agricultural and Natural Resources Research Center of Guilan
AUTHOR
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