کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6296592 1617434 2015 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Characteristics of the top-cited papers in species distribution predictive models
ترجمه فارسی عنوان
ویژگی های مقالات با ذکر در مدل های پیش بینی توزیع گونه
کلمات کلیدی
تجزیه و تحلیل استناد، مقالات بسیار ذکر شده، بهره وری علمی، مدل توزیع گونه،
موضوعات مرتبط
علوم زیستی و بیوفناوری علوم کشاورزی و بیولوژیک بوم شناسی، تکامل، رفتار و سامانه شناسی
چکیده انگلیسی
In this study, we analyzed the characteristics of the most cited papers regarding species distribution predictive models (SDPMs). We found 173 papers on SDPMs that received at least 100 citations until 2013, according to the Thomson Reuters Web of Science database. These papers were published between 1991 and 2012, with the majority published between 2002 and 2012, indicating the rapid development of this field of research. The papers were published mainly in journals listed in the ecology category on the Web of Science. Almost half of the top-cited papers were methodological, introducing novel modeling methods and software. Applied papers on species conservation and biodiversity management, climate change, phylogeography, and biosecurity also figured out among the top-cited papers. Researchers from 174 institutions in 27 countries, with 51% of the papers being internationally collaborative and 69% inter-institutionally collaborative, published the papers. Among all 173 papers, seven papers stood out as having a great impact on the field, receiving more than 1000 citations each. Finally, the results found by analyzing the top-cited SDPMs papers support the view of a growing interest and rapid development of this research field over the past two decades. The top-cited papers primarily focused on the development and evaluation of novel methods to improve the performance of the models, and thus, to better predict the environmental suitability for species in applied studies.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Ecological Modelling - Volume 313, 10 October 2015, Pages 77-83
نویسندگان
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