مدلسازی اجماعی هجوم بالقوه کهور پاکستانی (Prosopis juliflora (SW.) DC) در منطقه مکران

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه مرتع و آبخیزداری، دانشکده منابع طبیعی، دانشگاه صنعتی اصفهان، اصفهان، ایران گروه علوم کشاورزی، دانشگاه فنی و حرفه ای، تهران، ایرا ن

2 گروه محیط زیست، دانشکده منابع طبیعی، دانشگاه صنعتی اصفهان، اصفهان، ایران

3 گروه مرتع و آبخیزداری، دانشکده منابع طبیعی، دانشگاه صنعتی اصفهان، اصفهان، ایران

4 گروه جنگلداری، دانشکده منابع طبیعی، دانشگاه علوم کشاورزی و منابع طبیعی ساری، ساری، ایران

چکیده

سابقه و هدف: گیاهان مهاجم، در حال حاضر مورد توجه اکولوژیست­ ها، حافظان محیط زیست و مدیران منابع طبیعی هستند و به دلیل گسترش سریع تنوع زیستی را کاهش می ­دهند. این گونه ­ها تغییراتی را در فرآیندهای بوم ­شناختی، ساختار و کارکرد جامعه در اکوسیستم ­های طبیعی ایجاد می ­کنند. بارزترین تغییر در مناطق مورد هجوم، کاهش تنوع زیستی و ایجاد اجتماع خالصی از گیاهان مهاجم می­ باشد. یکی از گونه­ های مهاجم در کشور کهور پاکستانی (Prosopis juliflora) می­ باشد که به دلیل مقاومت به شرایط نامساعد محیطی، در حوزه بیابان ­زدایی، کنترل بیولوژیک و تثبیت تپه­ های ماسه ­ای روان در مناطق جنوبی کشور حائز اهمیت است.
مواد و روش ­ها: در مطالعه حاضر، کارایی پنج مدل متمایز کننده گروهی (GLM، GBM، ANN، SRE، RF) و یک مدل پروفیل (MAXENT) و اجماع آن­ها با رویکرد میانگین وزنی در مدل­سازی پراکنش مکانی این گونه در منطقه مکران و تعیین مهم ­ترین عوامل محیطی مؤثر بر پراکنش هجوم مورد بررسی قرار گرفت. با ثبت 63 نقطه رخداد و 100 نقطه غیاب طی برداشت میدانی، استفاده از متغیرهای اقلیمی، فیزیوگرافی و انسانی به عنوان متغیرهای محیطی، و ارزیابی کارایی مدل ­ها با معیارهای سطح زیر منحنی، TSS، شاخص­ های حساسیت و ویژه ­انگاری پتانسیل هجوم گونه مشخص گردید.
نتایج و بحث: از میان الگوریتم­ های مجزا، با توجه به معیارهای ارزیابی مستقل از آستانه و وابسته به آستانه، دو تکنیک مبتنی بر یادگیری ماشینی شامل RF و GBM گستره مورد هجوم این گونه را با صحت و توانایی تشخیص بالاتری پیش ­بینی کردند. همچنین معیارهای صحت­ سنجی در پیش­ بینی اجماعی نسبت به تمام الگوریتم ­های مجزای مدل­ سازی میانگین بیشتری را به خود اختصاص دادند. طبق مدل اجماعی، گستره هجوم کهور پاکستانی تقریباً 15 درصد از کل منطقه مورد مطالعه را به خود اختصاص داده است. پس از تعمیم مدل­ ها به فضای جغرافیایی مشخص شد که مناطق مورد هجوم گونه به صورت نواری یکدست در سواحل دریای عمان و خلیج فارس گسترش یافته­اند. ارزیابی اهمیت متغیرها حاکی از این بود که متغیر ارتفاع از سطح دریا با توجیه نمودن تقریباً نیمی از تغییرات در مدل اجماعی به­ عنوان مهمترین متغیر مستقل، بیشترین تأثیر را در پراکنش گونه دارد. متغیر فاصله از جاده در درجه بعدی اهمیت قرار دارد، اما جهت شیب کم اهمیت ­ترین متغیر محیطی مؤثر بر پراکنش هجوم عنوان شد. بر اساس منحنی ­های عکس­ العمل گونه، اوج احتمال حضور گونه در ارتفاع 50 متری از سطح دریا و فاصله کمتر از 50 متری جاده مشاهده می­شود. همچنین در صورتیکه درجه حرارت در گرم­ترین ماه و سردترین فصل سال به ترتیب بیش از 34 و 14 درجه سانتیگراد، و ضریب تغییرات بارندگی نیز بین 150-100 باشد، گونه حداکثر احتمال حضور را دارد.
نتیجه­ گیری: مشخص شد که الگوریتم­ های تلفیق شده در چارچوب مدل ­سازی اجماعی، صحت بالاتری را نشان دادند و نقشه ­های حاصل از پراکنش بالقوه هجوم گونه این امکان را فراهم می­ آورند تا با ارائه راهکارهای مدیریتی و طرح­ ریزی­ های حفاظتی در جهت حفاظت از گونه­ های بومی، گستره پراکنش گونه­ های مهاجم را محدود و مدیریت کرد. در واقع، از نتایج این مطالعه می ­توان به عنوان مبنایی برای پایش ­های بعدی جهت ممانعت از گسترش بیشتر گونه ­های مهاجم و ایجاد تعادلی بین برنامه ­های حفاظت از پوشش گیاهی بومی منطقه و اقدامات مدیریتی بیابان­ زدایی استفاده نمود.

کلیدواژه‌ها

عنوان مقاله [English]

Ensemble modelling of the potential invasion of Prosopis juliflora (SW.) DC in Makuran region

نویسندگان [English]

  • Mohadeseh Amiri 1
  • Mohammad Shafiezadeh 2
  • Mostafa Tarkesh 3
  • Seyyed Mostafa Moslemi 4
1 Department of Range and Watershed Management, Faculty of Natural Resources, Isfahan University of Technology, Isfahan, Iran
2 Department of Environmental Science, Faculty of Natural Resources, Isfahan University of Technology, Isfahan, Iran
3 Department of Range & Watershead Management, Faculty of Natural Resources, Isfahan University of Technology
4 Department of Forest Management, Faculty of Natural Resources, Sari Agricultural and Natural Resources University, Sari, Iran
چکیده [English]

Introduction: Invasive species are currently the concern of ecologists, conservationists and natural resource managers, and they may decrease biodiversity due to their rapid spread. These species cause changes in ecological processes, function and structure of communities in natural ecosystems. The most obvious change in the invaded areas is the reduction of biodiversity and the creation of a pure community of invasive plants. One of the invasive species in our country is Prosopis juliflora, which is important in the field of combat desertification, biological control and stabilization of quicksand dunes in the southern regions of Iran due to its resistance to adverse environmental conditions.
Material and methods: In the present study, the efficiency of five discrimination group models (GLM, GBM, ANN, SRE, RF) and a profile model (MAXENT) and their ensemble with the weighted average approach in the spatial distribution of this species in Makuran region and determining the most important environmental factors affecting the invasion distribution were investigated. By recording 63 occurrence points and 100 absence points, using climatic, physiographic and human variables as environmental variables, and evaluating the performance of models by Area under Curve (AUC), True Skill Statistics (TSS), Sensitivity and Specificity, the species invasion potential was determined.
Results and discussion: Among the single algorithms, according to the threshold-independent and threshold-dependent evaluation criteria, two machine learning techniques, i.e. RF and GBM, predicted the climatic habitat of this invasive species with higher accuracy. Also, the evaluation criteria in the ensemble prediction were higher than the average of all single modeling algorithms. According to the ensemble model, P. juliflora habitats occupy about 15% of the total study area. After generalization of the models to the geographical space, it was found that the invaded areas have spread in a uniform strip on the shores of the Oman Sea and the Persian Gulf. Evaluation of variable importance indicated that altitude was the most important independent variable justifying about half of the changes in the ensemble model and has the greatest effect on species distribution. The variable of distance from the road was the next important variable. However, the aspect was mentioned as the least important environmental variable affecting the scattering of the invasion. Based on response curves, the maximum probability of the species' presence was observed at the altitude of 50 m above sea level and a distance less than 50 m from the road. Also, the species is most likely to be present, if the temperature in the warmest month and the coldest season of the year is more than 34 and 14 °C, respectively, and the precipitation seasonality is 100-150. 
Conclusion: It was found that the integrated algorithms in the framework of ensemble modeling showed higher accuracy and the maps derived from the potential distribution of species invasion make it possible to restrict and manage the distribution range of invasive species by providing management solutions and conserving plans to protect native species. In fact, the results of this study can be used as a basis for subsequent monitoring to prevent further spread of invasive species and to create a balance between the native vegetation protection programs of the region and desertification management measures.

کلیدواژه‌ها [English]

  • Ensemble approach
  • Biological invasion
  • Environmental variables

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فصلنامه علوم محیطی
دوره 21، شماره 1
1402
صفحه 205-224

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