بررسي برخي ويژگي‌هاي بوم شناختي گياه دارويي (Artemisia sieberi Besser.) و تخمين تراكم آن به روش شبكه‌هاي عصبي در بخش روداب سبزوار

Investigation of Some Ecological Characteristics of Artemisia sieberi Besser. and Estimation of its Density by Neural Networks in Roodab Section of Sabzevar

درمنه دشتي (Artemisia sieberi Besser) از تيره Asteraceae گونه­اي دارويي در فلور ايران بوده كه اسانس آن در درمان بيماري­هاي انگلي و عفوني كاربرد دارد. طي ساليان اخير، بخش­هايي از رويشگاه­هاي درمنه، توسط عوامل انساني تخريب شده است. اين تحقيق با هدف بررسي نيازهاي آت اكولوژي و برآورد تراكم درمنه در سال 1396 در منطقه روداب سبزوار انجام گرفت. ابتدا محدوده درمنه­زار بر روي عكس­هاي ماهواره­اي، تعيين و اطلاعات بوم شناختي آن، شامل (توپوگرافي، اقليم، خاك، زمين­شناسي و فنولوژي) جمع­آوري گرديد. در مرحله­ي بعد، تراكم درمنه در مراتع تخريب­ شده با استفاده از مدل شبكه عصبي مورد آزمون قرار گرفت. بدين منظور 70 نمونه تصادفي خاك متشكل از متغيرهاي مستقل (بافت، EC،SAR ، pH،N ،P ،K ، كاتيون­ها، ماده آلي و درصد آهك) و نيز تراكم درمنه (متغير وابسته) براي ساخت مدل­ استفاده گرديد. نتايج نشان دادند كه درمنه دشتي، ارتفاعات 1400 تا 1800 متر، شيب­هاي صفر تا 12%، بارندگي 160 تا 200 ميلي‌متر و خاك­هاي لومي تا لومي­ماسه­اي آهك­دار با شوري كم را ترجيح ميدهد. فعّاليت رويشي درمنه از اواخر اسفند شروع شده و تا اوايل آذر بذرها مي­رسند. همچنين نتايج پيش­بيني مدل نشان داد، كمترين تراكم درمنه با 11/0 در مترمربع مربوط به اراضي مي­باشد كه 40 سال تحت تنش شخم قرار داشته­اند و بيشترين تراكم درمنه با 4/0 در مترمربع مربوط به اراضي است كه دو سال از تخريب آنها مي­گذرد.مدل رگرسيون (R2) نشان داد كه متغيرهاي مستقل، 95% در تعيين تراكم درمنه نفش دارند.

Artemisia sieberi Besser. (Asteraceae) is a medicinal plant belongs to flora of Iran , which is used in treatment of parasitic and infectious diseases. In recent years, many habitats parts of this plant have been destroyed by human activities. The purpose of this study was to evaluate the autecological characteristics and estimation of Artemisia density in Roodab region of Sabzevar in 2017. At first the A.sieberi habitats was determined on satellite images, then ecological information including topography, climate, soil, geology and phenology was collected. In the next step, Artemisia densities in degraded rangelands were investigated by using neural network model. For this purpose, 70 random soil samples consisting of independent variables (texture, EC, SAR, pH, N, P, K, cations, organic matter and lime percentage) as well as dependent variable (plant density) were used to construct the model. The results were showed that A.sieberi prefers altitudes of of 1400 to 1800 m, 0% to 12% slope, 160 to 200 mm rainfall, and loamy to calcareous loam soils with low salinity. plant vegetative activity begins in late March and seed ripening occurs early in December. The results of model prediction indicated that the lowest plant density with 0.11 / m2 was related to the plots that were 40 years under plowing stress and the highest density with 0.4 /m2 was related to the plots after two years of degradation. The regression model (R2) showed that 95% of independent variables were involved in determining plant density. Model prediction also indicated that the lowest density by 0.11 and 0.4 plant per m2 belonged to rangelands have been plowed more than 40 years and which lasted two years from their destruction, respectively. Regression model (R2) also showed that independent variables have a 95% effect on the determination of A.sieberi density.