مدل سازی گستره پراکنش آرایه های خواهری دورگه زا در گونه های زردپره سرسرخ و زردپره سر سیاه از راسته گنجشک سانان

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه محیط زیست، دانشکده منابع طبیعی و علوم دریایی، دانشگاه تربیت مدرس، نور، ایران

2 کروه محیط زیست، دانشکده منابع طبیعی و علوم دریایی، دانشگاه تربیت مدرس، نور، ایران

3 بخش زیست شناسی، دانشکده علوم، دانشگاه شیراز، شیراز، ایران

چکیده

سابقه و هدف: جدایی گونه ها بر مبنای نتایج فیلوژنی می تواند با مدل سازی هایی که ورودی آنها داده های زیستگاهی هستند، پشتیبانی شود. در مطالعه حاضر دو آرایه خواهری که براساس مستندهای مولکولی جدا از هم هستند، از نظر عامل های تأثیرگذار زیستگاهی که احتمالا در این جدایی دخیل بوده اند و همچنین از نظر پراکنش در برهه تاریخی گذشته و آینده، مورد بررسی قرار گرفته اند. گونه ها ی مورد مطالعه شامل زردپره سرسرخ و زردپره سرسیاه از راسته گنجشک سانان هستند.
موا د و روش ها: در راستا ی مدل سازی توزیع گونه ها ، متغیرهای زیست اقلیمی از پایگاه داده CHELSA به همراه متغیرهای ارتفاع، شیب و سنجه پوشش گیاهی به عنوان داده های زیستگاهی برای ورود به مدل مورد استفاده قرار گرفتند. همچنین نقاط حضور گونه ها پس از جمع آوری در بازه تولیدمثلی غربالگری شد ه و به عنوا ن داده تعلیمی به مدل ها اضافه شد. در این مطالعه جهت مدل سا زی از پکیج sdm شامل 8 مدل ( GLM ، GAM ، BRT ، RF ، CART ، SVM ، MaxEnt و MARS ) در محیط نرم افزار R استفاده گردید. مدل سازی توزیع گونه ها در برهه زمانی آخرین دوره یخبندان، حال حاضر ( 1997 - 2013 ) و سال 2050 انجام شد.
نتایج و بحث: نتایج جدایی پردازه اکولوژیکی، گونه ها را تحت تأثیر متغیرهای محیطی نشان داد. مطابق نتایج ارزیابی صحت، معتبرین
مدل از نظر سنجه TSS و AUC ، مدل جنگل تصادفی برآورد شد. همچنین بنابر نتایج، در سال 2050 زیستگاه ها ی مطلوب برای گونه
زردپره سرسرخ محدو د به شمال شرق کشور و برای گونه زردپره سرسیاه مطلوبیت محدود به منطقه ها یی در جنوب رشته کوه البرز، شمال غرب و غرب ایران خواهد بود. مطابق با نتایج، وسعت زیستگاه های مطلوب برای گونه زردپره سرسیاه در غرب نسبت به امروز کمتر بوده است که بنابر مطالعات صورت گرفته ظاهرا عامل های درونی و اقلیمی هردو در تغییرات محدوده پراکنش دو گونه تأثیرگذار بوده اند. نتایج تحقیق گویای کاهش مطلوبیت زیستگاه برای گونه های مورد مطالعه در هر دو بازه زمانی (آخرین عصر یخبندان تا حال حاضر و حال حاضر تا سال 2050) می باشد.
نتیجه گیری: شناخت عامل های تأثیرگذار بر تعیین مطلوبیت زیستگاه های حیات وحش ضروری است. برخی تغییرات ناشی از دستکاری
اکوسیستم به شدت د ر محدوده پراکنش گونه ها اثر گذاشته است . پیش بینی کاهش مطلوبیت زیستگاه در آینده و ادامه روند از بین رفتن آن، پایش مستمر نواحی متمرکز پراکنش و اجرای تمهیدهای پیشگیری از تخریب این زیستگاه ها را می طلبد. همینطور منطقه های مستعد برای دورگه زایی گونه های خواهری که از استعداد ذاتی برای دورگه زایی برخوردارند، باید بیشتر مورد توجه و دقت قرار گیرند و تغییرات آنها تحت تأثیر شرایط اقلیمی آینده با حساسیت بیشتری مورد نظارت پیوسته قرار گیرد .

کلیدواژه‌ها


عنوان مقاله [English]

Distribution modeling of the hybrid sister taxa in red-headed bunting and black-headed bunting, Order Passeriformes

نویسندگان [English]

  • Shahrzad Rahmati 1
  • Mehdi Gholamalifard 2
  • Ali Gholamhosseini 3
  • Seyed Mahmoud Ghasempouri 1
1 Department of Environmental Science, Natural Resources and Marine Sciences Faculty, Tarbiat Modares University
2 Department of Environmental Science, Natural Resources and Marine Sciences Faculty, Tarbiat Modares University
3 Ornithology Research Lab, Department of Biology, School of Science, Shiraz University, Shiraz, Iran
چکیده [English]

Introduction: The concept of species distribution models is the relationship between known locations of a species and the environmental characteristics of these places to estimate the response performance and contribution of environmental variables and predict the potential geographical distribution of the species. Species separation based on phylogenetic results can be supported by modeling whose input is habitat data. In the present study, two sister taxa that have recently been separated based on molecular documentation have been examined in terms of habitat influencing factors that may have been involved in this separation, as well as in terms of past and future historical distribution.
Marterial and methods: In order to model the distribution of species, bio-climatic variables from CHESLA database with variables of DEM, slope, and vegetation index were examined as habitat data to input the model. Also, the presence points of the species were filtered after collection in the reproductive interval and added to the models as train data. In this study, sdm package including eight models (GLM, GAM, BRT, RF, CART, SVM, MaxEnt, and MARS) in the R environment was used for modeling. Modeling of species distribution was performed at the last glacial period, current, and 2050.
Results and discussion: The results showed the ecological niche separation of the species under the influence of environmental variables. According to the results of the accuracy assessment, the most reliable model in terms of AUC and TSS was the random forest model. Also, according to the results, in 2050, suitability habitats for Embriza bruniceps species will be limited to the northeast of the country, and for Embriza melanocephala species, suitability will be limited to areas in the south of Alborz Mountain range, northwest, and west of Iran. According to the results, it can be acknowledged that the area of suitable habitats for Embriza melanocephala species in the west was less than today, which according to studies, internal and climatic factors were effective in moving both species and hybridization area to the west. The results indicate decreasing habitat suitability for the studied species in both periods (the last ice age until now and now until 2050).
Conclusion: Understanding the factors influencing the suitability of wildlife habitats is essential. Some changes due to rapid ecosystem manipulation are seen in the new distribution of birds. In general, wildlife planning and conservation strategies should monitor the factors affecting habitats and maintain and manage these factors in order to prevent biodiversity

کلیدواژه‌ها [English]

  • sister taxa
  • species distribution models
  • habitat suitability
  • Embriza bruniceps
  • Embriza melanocephala
Abbasnia, M., Tavousi, T. and Khosravi, M., 2017. A comprehensive assessment of seasonal changes in future maximum temperature of Iran during the warm period based on GCM models. Geographical Planning of Space. 7(25). 121-134.
Ahmadi, K., Hosseini, S., Tabari, M. and Nouri, Z., 2019. Modeling the potential habitat of English yew (Taxus baccata L.) in the Hyrcanian forests of Iran. Journal of Forest Research and Development. 5(4), 513-525.
Allouche, O., Tsoar, A. and Kadmon, R., 2006. Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS). Journal of Applied Ecology. 43(6), 1223-1232.
Alström, P., Olsson, U., Lei, F., Wang, H. T., Gao, W. and Sundberg, P., 2008. Phylogeny and classification of the Old World Emberizini (Aves, Passeriformes). Molecular phylogenetics and evolution, 47(3), 960-973.
Barton, N.H. and Hewitt, G.M., 1985. Analysis of hybrid zones. Annual review of Ecology and Systematics. 16(1), 113-148.
Chala, D., Roos, C., Svenning, J.C. and Zinner, D., 2019. Species-specific effects of climate change on the distribution of suitable baboon habitats–Ecological niche modeling of current and Last Glacial Maximum conditions. Journal of Human Evolution. 132, 215-226.
De Marco, P. and Nóbrega, C.C., 2018. Evaluating collinearity effects on species distribution models: An approach based on virtual species simulation. PLoS One. 13(9), e0202403.
Eastman, J.R, 2012. IDRISI Help System. Accessed in IDRISI 17.00. Worcester, MA, Clark University, Massachusetts.
Fathinia, B., Rödder, D., Rastegar-Pouyani, N., Rastegar-Pouyani, E., Hosseinzadeh, M.S. and Kazemi, S.M., 2020. The past, current and future habitat range of the Spider-tailed Viper, Pseudocerastes urarachnoides (Serpentes: Viperidae) in western Iran and eastern Iraq as revealed by habitat modelling. Zoology in the Middle East. 66(3), 197-205.
Feilhauer, H., He, K.S. and Rocchini, D., 2012. Modeling species distribution using niche-based proxies derived from composite bioclimatic variables and MODIS NDVI. Remote Sensing. 4(7), 2057-2075.
Fourcade, Y., Engler, J.O., Rödder, D. and Secondi, J., 2014. Mapping species distributions with MAXENT using a geographically biased sample of presence data: a performance assessment of methods for correcting sampling bias. PLoS One. 9(5), e97122.
Gholamhosseini, A., Aliabadian, M., Darvish, J., Töpfer, T. and Sætre, G. P., 2017. An expanding hybrid zone between Black-headed and Red-headed Buntings in northern Iran. Ardea. 105(1), 27-37 .
Gholamhosseini, A., Aliabadian, M. and Darvish, J., 2015. Study of sexual dimorphism and morphological variations of Red-headed bunting (Emberiza bruniceps) within its hybrid zone with Black-headed bunting (Emberiza melanocephala) in the Iranian Plateau. Journal of Animal Research (Iranian Journal of Biology). 28(1), 72-84
Gholi pour, M. and Salman Mahini, A., 2012. Investigating the effects of climate change on biodiversity, ecosystems and impact mitigation strategies. In 2𝑡ℎ Conference on Environmental Planning and Management, 15𝑡ℎ 16th May, , University Tehran, Iran. p 9.
Girma, Z., Mamo, Y., Mengesha, G., Verma, A. and Asfaw, T., 2017. Seasonal abundance and habitat use of bird species in and around Wondo Genet Forest, south-central Ethiopia. Ecology and Evolution. 7(10), 3397–3405.
Guevara, L., Morrone, J. J. and León‐Paniagua, L., 2019. Spatial variability in species' potential distributions during the Last Glacial Maximum under different Global Circulation Models: Relevance in evolutionary biology. Journal of Zoological Systematics and Evolutionary Research. 57(1), 113-126.
Haffer, J., 1977. Secondary contact zones of birds in northern Iran. Bonner Zoologische Monographien 10, Bonn. Pp 64.
Haidarian Aghakhani, M., tamartash, R., Jafarian, Z., Tarkesh Esfahani, M. and Tatian, M., 2017. Predicting the impacts of climate change on Persian oak (Quercus brantii) using Species Distribution Modelling in Central Zagros for conservation planning. Journal of Environmental Studies. 43(3), 497-511.
Karger, D. N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R. W. and Kessler, M., 2017. Climatologies at high resolution for the earth’s land surface areas. Scientific Data. 4, 122-170.
Khaleghizadeh, A., Roselaar, K., Scott, D.A., Tohidifar, M., Mlíkovský, J., Blair, M. and Kvartalnov, P., 2017. Birds of Iran: Annotated Checklist of the Species and Subspecies. Iranian Research Institute of Plant Protection.
Karami, P. and Shayesteh, K., 2020. Habitat Suitability Modeling of Wild Sheep (Ovis orientalis) in Markazi Province by using Tree-Based Models. Experimental animal Biology. 8(4), 109-121.
Liu, C., White, M. and Newell, G., 2011. Measuring and comparing the accuracy of species distribution models with presence–absence data. Ecography. 34, 232-243.
Lobo, J. M., Jiménez‐Valverde, A. and Real, R., 2008. AUC: a misleading measure of the performance of predictive distribution models. Global ecology and Biogeography. 17(2), 145-151.
Madadi, M., Salman Mahini, A. and Varasteh Moradi, H., 2018. Habitat suitability modeling of wild goat (Capra aegagrus) using Ecological Niche Factor Analysis in Golestan National Park. Journal of Animal Environment. 10(2), 13-22.
Maviza, A. and Ahmed, F., 2020. Analysis of past and future multi-temporal land use and land cover changes in the semi-arid Upper-Mzingwane sub-catchment in the Matabeleland south province of Zimbabwe. International Journal of Remote Sensing. 41(14), 5206-5227.
Naghipour Borj, A., Haidarian Aghakhani, M. and Sangoony, H., 2019. Application of ensemble modelling method in predicting the effects of climate change on the distribution of Fritillaria imperialis L. Journal of Plant Research (Iranian Journal of Biology). 32(3), 609-621.
Naimi, B. and Araújo, M.B., 2016. sdm: a reproducible and extensible R platform for species distribution modelling. Ecography. 39(4), 368-375.
Nayeri, D. and Droudi, H., 2016. The Importance and Role of Mountain Habitats for the Conservation of the Birds. Biosphere. 11(3), 23-29.
Pearce‐Higgins, J.W., Eglington, S. M., Martay, B. and Chamberlain, D. E., 2015. Drivers of climate change impacts on bird communities. Journal of Animal Ecology. 84(4), 943-954.
Pontius Jr, R. G. and Schneider, L. C., 2001. Land-cover change model validation by an ROC method for the Ipswich watershed, Massachusetts, USA. Agriculture, Ecosystems and Environment. 85(1-3), 239-248.
Pyke, C. R., 2004. Habitat loss confounds climate change impacts. Frontiers in Ecology and the Environment. 2(4), 178-182.
Schwartz, M.W., Iverson, L.R., Prasad, A.M., Matthews, S.N. and O'Connor, R.J., 2006, Predicting extinction as a result of climate change. Ecology. 87, 1611-1615.
Shabani, F., Kumar, L. and Ahmadi, M., 2018. Assessing accuracy methods of species distribution models: AUC, Specificity, Sensitivity and the True Skill Statistic. GJHSS. 18(91), 6-18.
Somveille, M., Wikelski, M., Beyer, R.M., Rodrigues, A.S., Manica, A. and Jetz, W., 2020. Simulation-based reconstruction of global bird migration over the past 50,000 years. Nature Communications. 11(1), 1-9.
Taylor, S.A., White, T.A., Hochachka, W.M., Ferretti, V., Curry, R. L. and Lovette, I., 2014. Climate-mediated movement of an avian hybrid zone. Current Biology. 24(6), 671-676.
Usui, T., Butchart, S.H. and Phillimore, A.B., 2017. Temporal shifts and temperature sensitivity of avian spring migratory phenology: a phylogenetic meta‐analysis. Journal of Animal Ecology. 86(2), 250-261.
Yousefi, M., ALIZADEH, S.A. and Azarnivand, H., 2020. Modeling present and past habitat suitability of Western Rock Nuthatch (Sitta neumayer) in Iran. Journal of Natural Environment. 72(4), 543-554.
Yousefkhani, S.S.H., Aliabadian, M., Rastegar-Pouyani, E. and Darvish, J., 2017. Predicting the impact of climate change on the distribution pattern of Agamura persica (Dumeril, 1856) (Squamata: Gekkonidae) in Iran. Belgian Journal of Zoology. 147(2), 215-226.