ارزیابی پتانسیل مراتع برای توسعه استفاده چندمنظوره و استفاده صحیح از توانمندی‌های این منابع یک چالش جدی برای مدیریت مراتع است. در این راستا این پژوهش با هدف ارزیابی شایستگی مراتع به‌منظور توسعه کاربری زنبورداری با استفاده از روش منطق فازی در محیط نرم افزار Arc GIS در مراتع تمین در شمال تفتان انجام شد. بدین‌منظور نمونه‌برداری از پوشش گیاهی در تیپ‌های گیاهی منطقه به روش تصادفی-سیستماتیک با استقرار 3 ترانسکت 300 متری انجام شد. پس از تعیین اولویت معیارهای مؤثر در شایستگی زنبورداری با استفاده از روش پیشنهادی فائو، معیارهای مؤثر از طریق پرسشنامه توسط کارشناسان و متخصصین، اولویت‌بندی و وزن‌دهی شد. در مرحله بعد روش منطق فازی بر روی معیارها اعمال شد. در نهایت نقشه نهایی شایستگی منطقه جهت کاربری زنبورداری تهیه شد. نتایج نشان داد که بر اساس روش منطق فازی از مجموع 5572 هکتار اراضی مرتعی منطقه مورد مطالعه، 4/1387 هکتار (9/24 درصد) در طبقه شایستگی S1 (بدون محدودیت)، 3/1571 هکتار (2/28 درصد) در طبقه شایستگی S2 (با محدودیت اندک)، 2/2262هکتار (6/40 درصد) در طبقه شایستگی S3 (با محدودیت زیاد) و 351 هکتار (3/6درصد) در طبقه شایستگی N (غیرشایسته) برای استفاده زنبورداری است. علاوه بر این، ارزش شاخص پوشش گیاهی (84/0) بیشتر از دسترسی به منابع آب(81/0) و عوامل محیطی (37/0) است. با توجه به نتایج حاصل، مناطق شرقی مراتع تمین از شایستگی بالاتری جهت کاربری زنبورداری برخوردار بوده و این موضوع می‌بایستی در توسعه کاربری زنبورداری و مدیریت پوشش گیاهی مراتع تمین مورد توجه قرار گیرد. تفاصيل المقالة

This study aimed to identify the most important physical variables affecting the distribution of four range plants species (Tamarix aphylla, Calligonum comosum, Prosopis spicigera and Salsola rigida) habitats and to prepare potential habitat map of the species using Maximum Entropy (MaxEnt) method in rangelands of Jiroft city, Kerman province, located in SE Iran. To this end, sampling of vegetation including species type and percent cover was conducted with randomized-systematic method in 2015. Sample size was determined as 60 plots with a quadrat size of 25-100 m2. For soil sampling, eight profiles were dug in each habitat and samples were taken at two depths, i.e., 0–30 and 30–60 cm. Results indicated that the classification accuracy of the model was acceptable and soil variables including EC, percentage of lime, organic matter, moisture content and texture had the greatest effect on the distribution of the studied plant species habitats. Correlations between the actual and predicted maps for Tamarix aphylla and Calligonum comosum habitats were at a very good level, Kappa = 0.81 and 0.79, respectively, for Prosopis spicigera habitat was at a good level, Kappa = 0.75, and finally for Salsola rigida was at a moderate level, Kappa = 0.53. These results indicate that the MaxEnt method can provide valuable information about the physical conditions of plant habitats in arid rangeland. Knowledge on physical characteristics of plant habitats can be useful in determination of potential habitats and rangeland improvement projects. تفاصيل المقالة

The object of this study was to compare predictive accuracy of some individual modeling methods versus ensemble modeling approach in estimating the spatial potential distribution and identifying ecological requirements of Artemisia sieberi in desert rangelands of Yazd province, Central Iran. For this purpose, the species presence data were collected using the random systematic sampling method in 2019. Individual modeling of the species distribution was performed using Random Forest, Classification and Regression Tree and Generalized Additive Model after preparing environmental variable maps using GIS and geostatistics. Predictive performance of individual models was evaluated using Area Under Curve and Root Mean Square Error statistics. Furthermore, the Ensemble model was used based on the weighted average AUC. The appropriate threshold limit value was calculated based on True Skill Statistic for conversion of continuous maps to binary ones of habitat suitability. Comparison of the performance of individual models showed that the RF model had a more accurate prediction compared to the other models (AUC= 0.971 and RMSE= 0.256). Evaluation of the models implemented using threshold-dependent metrics such as Sensitivity, Specificity, and Kappa index also confirmed this finding. The overall comparison of the results from the three models versus the Ensemble model also indicates the high performance of this model compared to the individual models. Based on Ensemble model results, 45.38% of the study area had a high suitability for the establishment of A. sieberi. Based on the analysis of the importance of variables in the RF model, elevation (42%), Clay (40.02%) and pH (38.97%) in 0-30 cm soil depth had the highest effect on the presence of species. In general, Ensemble modeling can reduce the uncertainty and provide more reliable results by combining the results of the different algorithms of individual modeling. تفاصيل المقالة