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کاربرد مدل جمعی تعمیم یافته و درخت طبقهبندی و رگرسیون در برآورد پراکنش رویشگاه بالقوه گونههای مرتعی (مطالعه موردی: مراتع خضری دشت بیاض، خراسان جنوبی) | ||
| تحقیقات مرتع و بیابان ایران | ||
| مقاله 13، دوره 27، شماره 3 - شماره پیاپی 80، مهر 1399، صفحه 561-576 اصل مقاله (1.3 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/ijrdr.2020.342106.1947 | ||
| نویسندگان | ||
| ملیحه کیقبادی1؛ حسین پیری صحراگرد* 2؛ محمدرضا پهلوان راد3؛ پیمان کرمی4؛ رضا یاری5 | ||
| 1دانشآموخته کارشناسی ارشد مرتعداری، دانشگاه زابل، ایران | ||
| 2استادیار، گروه مرتع و آبخیزداری، دانشکده آب و خاک، دانشگاه زابل، ایران | ||
| 3استادیار، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی گلستان، سازمان تحقیقات، آموزش و ترویج کشاورزی، گرگان، ایران | ||
| 4دانشجوی دکتری، گروه علوم محیطی، دانشکده منابع طبیعی و علوم محیطی، دانشگاه ملایر، ایران | ||
| 5استادیار، دانشگاه علوم کشاورزی و منابع طبیعی گرگان، ایران | ||
| چکیده | ||
| مدلهای پراکنش گونهها با کمیکردن ارتباط بین پراکنش گونهها و متغیرهای محیطی تأثیرگذار، اساس تصمیمات آگاهانه در مدیریت پوشش گیاهی هستند. هدف این پژوهش ارزیابی کارایی روشهای جمعی تعمیم یافته (GAM) و درخت طبقهبندی و رگرسیون (CART) در برآورد پراکنش رویشگاه بالقوه و شناخت نیازهای بومشناختی گونههای گیاهی در مراتع خضری دشت بیاض خراسان جنوبی بود. با توجه به شرایط منطقه و بازدید میدانی، نمونهبرداری از پوشش گیاهی بهروش تصادفی- سیستماتیک در سطحی حدود 14500 هکتار انجام شد. 18 متغیر محیطی شامل خصوصیات زمین، شاخص تراکم پوشش گیاهی (NDVI) و شاخص شوری بهعنوان تخمینگر برای تهیه نقشههای متغیرهای پیشگو مورد استفاده قرار گرفت. پس از انجام مدلسازی پیشبینی پراکنش رویشگاه با استفاده از روش CART و GAM در نرمافزار R 3.5.2، ارزیابی دقّت مدلها نیز با استفاده از آماره سطح زیرمنحنی (AUC) انجام شد. بعد از تعیین حد آستانه به روش TSS، نقشه پیوسته مطلوبیت به نقشه حضور/عدم حضور تبدیل و میزان تطابق نقشهها با شاخص کاپا محاسبه شد. بر اساس نتایج حاصل از مدلهای مورد استفاده، متغیرهای سطح پایه شبکه کانالها، فاصله عمودی به شبکه کانال، عمق دره، شاخص خیسی و موقعیت نسبی شیب در مطلوبیت رویشگاه برای استقرار گونهها تأثیرگذار هستند. در مجموع، روش GAM در برآورد دامنه پراکنش رویشگاه همه گونههای مورد بررسی از دقّت بالاتری برخوردار است ( ). بر اساس نقشههای حاصل از مدل GAM، بیشترین و کمترین وسعت رویشگاه بالقوه به گونههای S. rigida و T. serotina اختصاص دارد. بنابراین روشGAM میتواند در شناخت دقیق از نیازهای بومشناختی گونههای گیاهی و در نتیجه حدود پراکنش آنها در مقیاس محلی مفید باشد. در نتیجه پیشنهاد میشود این روش بهعنوان بخشی از یک سیستم پشتیبان مدیریتی در حفاظت و احیای پوشش گیاهی در مراتع خضری دشت بیاض مورد استفاده قرار گیرد. | ||
| کلیدواژهها | ||
| مرتع؛ رویشگاه بالقوه؛ GAM؛ CART؛ مراتع خضری | ||
| عنوان مقاله [English] | ||
| Application of Generalized Additive Model and Classification and Regression Tree to Estimate Potential Habitat Distribution of Range plant species (Case Study: Khazri Rangelands of Beyaz Plain, Southern Khorasan) | ||
| نویسندگان [English] | ||
| Maliheh Keyghobadi1؛ Hossein Piri Sahragard2؛ Mohammad Reza Pahlavan Rad3؛ Peyman Karami4؛ reza yari5 | ||
| 1Former M.Sc. Student in Range Management, Zabol University, Iran | ||
| 2Assistant Professor, Department of Rangeland and Watershed Management, Zabol University, Iran | ||
| 3Assistant professor, Soil and Water Research Department, Golestan Agricultural and Natural Resources Research and Education Center, AREEO, Gorgan, Iran | ||
| 4PhD student, Department of Environmental Sciences, Faculty of Natural Resources and the Environment Sciences, Malayer University, Malayer, Iran | ||
| 5Assistant Professor, rangeland science, Gorgan University of Agricultural Sciences and Natural Resources, Iran | ||
| چکیده [English] | ||
| Species distribution models (SDMs) are the basis of informed decisions in vegetation management by quantifying the relationship between species distribution and influential environmental variables. The present study aimed to evaluate the GAM and CART models' performance in estimating the potential habitat distribution as well as recognizing the ecological needs of plant species in the Khezri rangelands of Bayaz plain of southern Khorasan. According to the regional condition and field observation, in an area of about 14500 hectares, vegetation sampling was done using the randomized-systematic method. Eighteen environmental variables including land characteristics, Normalized Difference Vegetation Index (NDVI), and salinity index were used as an estimator to generate maps of predictor variables. After modeling the habitat distribution prediction using CART and GAM methods in R 3.5.2 software, the accuracy of the models was assessed using the subsurface area (AUC) statistics. After determining the threshold by the TSS method, the continuous utility map was converted to the presence/absence map and the degree of conformity of the maps with the kappa index was calculated. Based on the results of the used models, the variables of the base level of the channels network, the vertical distance to the channels network, the depth of the valley, the wetness index, and the relative position of the slope are effective in habitat suitability for species establishment. In general, the GAM method has high accuracy in estimating the habitat distribution range of all species studied (Kappa≥ 0.9). According to the maps obtained from the GAM model, the highest and lowest potential habitats belong to S. rigida and T. serotina species. Therefore, the GAM method can be useful in accurately identifying the ecological needs of plant species and therefore their distribution useful at the local scale. As a result, it is suggested that this method be used as part of a management support system in the protection and restoration of vegetation in the rangelands of the Bayaz plain. | ||
| کلیدواژهها [English] | ||
| Rangeland, Potential habitat, Machine learning models, Khezri rangelands | ||
| مراجع | ||
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