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Effect of repeated fire on understory plant species diversity in Saravan forests, northern Iran

100%
Daryayi M. G., Adel M. N., Pashaki M. S., Kuhestani J. S.
Folia Forestalia Polonica. Series A . Forestry
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2013
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tom 55
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nr 3
Fire usually causes changes in the composition and diversity of herbaceous species. The present paper aimed to study the effect of repeated fire incidents on understory species diversity in the Saravan forests of Guilan Province located in the north of Iran. To do so, three 50-hectare areas with identical physiographical conditions and overstory (hand-planted softwood Pinus taeda) were selected. Seven fire incidences occurred for the 10-year period in one of the areas and the other area experienced three fire incidents within the same period. The area with no fire incidents was considered as the control area. All the fire incidents were surface ones. The systematic random method with a sample size 100 × 200 m was used for collecting data. Based on the above, 25 samples were determined in each area. The whole coverage of the understory was taken into consideration using Whittaker’s method and the Domain criterion so as to calculate species diversity indices. The results showed that Shannon-Wiener diversity and Menhinick’s richness in the regions which experienced 3 and 7 fire incidents were maximum and minimum, respectively, whereas no significant difference was seen between the regions with regard to Smith and Wilson’s evenness index.
2

Contribution to the knowledge Scarabaeoidea (Coleoptera) of Guilan province, Northern Iran

100%
Bunalski M., Ghahari H.
Wiadomości Entomologiczne
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2015
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tom 34
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nr 1
The paper deals with species diversity of Scarabaeoidea (Coleoptera) of Guilan Province, Northern Iran. In total 22 species of 17 genera (Adoretus LAPORTE, Aethiessa BURMEISTER, Anomala SAMOUELLE, Aphodius ILLIGER, Blitopertha REITTER, Cetonia FABRICIUS, Glaphyrus LATREILLE, Gymnopleurus ILLIGER, Onthophagus LATREILLE, Oryctes ILLIGER, Oxythyrea MULSANT, Paroniticellus BALTHASAR, Pentodon HOPE, Polyphylla HARRIS, Protaetia BURMEISTER, Scarabaeus LINNAEUS, Valgus SCRIBA) were collected and identified. Protaetia funesta (MEN.) has been recorded from Iran for the first time.
3

Seroepidemiology and associated risk factors of Toxoplasma gondii in hemodialysis patients

84%
Saadat F., Mahmoudi M. R., Rajabi E., Roshan Z. A., Shad B. M., Karanis P.
Acta Parasitologica
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2020
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tom 65
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nr 4
4
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Occurrence and distribution of nematodes in rice fields in Guilan province, Iran and the first record of Mylonchulus polonicus (Stefanski, 1915) Cobb, 1917 (Nematoda: Mononchina)

67%
Shahabi S., Kheiri A., Rakhshandehroo F., Jamali S.
Journal of Plant Protection Research
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2016
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tom 56
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nr 4
The distribution of nematodes was studied in rice fields in Guilan province, Iran, from 2014 to 2016. Nematode biodiversity of 250 soil and root samples was examined. Thirty nematode species were identified morphologically, including plant parasites, microbivores and mycetophagous and predator species. Molecular techniques were also used for further identification of three plant parasitic species. Indicators of population were also estimated. Spiral nematodes (Helicotylenchus crenacauda Sher, 1966 and H. digitiformis Ivanova, 1967) and stunt nematode (Tylenchorhynchus agri) were the predominant parasitic species identified. Among other species, three mononchid species were identified namely Mononchus aquaticus, Mylonchulus sigmaturus and M. polonicus. The species M. polonicus was found and reported in Iran for the first time. The two plant parasitic species T. agri and Xiphinema index were reported in association with rice in Iran for the first time. To evaluate the distribution and incidence of Aphelenchoides besseyi (rice white-tip nematode) in different regions of Guilan province, a total of 255 fresh seed samples were collected/inspected, of which, about 40% of them were infested with A. besseyi. Of the 16 studied counties, the highest percentage of infected seeds came from fields around the city of Astara (69.2%) and the second highest infection was observed near the city of Anzali (60%).
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Effect of weather factors on spore population dynamics of rice blast fungus in Guilan province

67%
Mousanejad S., Alizadeh A., Safaie N.
Journal of Plant Protection Research
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2009
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tom 49
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nr 3
319-329
Effect of weather factors on fluctuations of spore population of Pyricularia grisea and the occurrence of the disease was considered. During growing seasons of 2006-2007, paddy fields were chosen in distance of five kilometers from weather stations of Rasht, Lahijan and Anzali in Guilan province and spore population (Ps) were measured daily using sporetraps. Weather data including precipitation (P), daily maximum and minimum temperature (Tmax, Tmin), daily maximum and minimum relative humidity (RHmax, RHmin) and sunny hours (SH) were obtained from weather stations. The relationship between spore population fluctuations and weather data was analyzed and the most important weather factors affecting spore population and predicting blast were determined. Accordingly, weather factors such as P, Tmax, RHmin and SH are the most important factors predicting rice blast in Guilan and enough precipitation, increased daily RHmin, decreased daily Tmax and SH result in increased spore population and blast occurrence during next 7-10 days. To predict final leaf blast severity (Yflbs) and neck blast index (Ynbi), factors such as Tmax, Tmin, T, RHmax, RHmin, RH, P and SH and Ps were used for modeling. For leaf blast, these factors were considered for June and July and for neck blast, the same factors used for August. Step wise regression was applied for modeling. Statistics like r, R2, aR2, SE, F and Durbin-Watson were applied for evaluating the models. Finally, the two quantitative models: Yflbs = -2.41-2.80 Tmin+0.68RHmin-0.015Ps-0.014P+0.052SH (R2 = 96.73%) and Ynbi = -24.11+0.08Tmax+0.19 RHmax+0.034Ps-0.015P+0.016SH (R2 = 73.97%), were introduced for predicting final leaf blast severity and neck blast index, respectively. Related to effects of amount of applied N fertilizer (F) and date (D) and space (S) of transplanting, the results showed high correlation between F and Yflbs and Ynbi, but such high correlation was not observed for D and S. The best function for predicting Yflbs was Y = 4.46-4.12F+1.93F2 (R2 = 96.37). The best equation for predicting Ynbi acquired when F, D and S were applied in multiple regression, Y = 2.06+0.33F+0.10D-0.03S(R2 = 54.40).
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