کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6297166 | 1617483 | 2013 | 6 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Evaluating the predictive performance of stacked species distribution models applied to plant species selection in ecological restoration
ترجمه فارسی عنوان
ارزیابی عملکرد پیش بینی مدل های توزیع گونه ای دسته بندی شده برای انتخاب گونه های گیاهی در بازسازی اکولوژیک
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کلمات کلیدی
مدل های محل سکونت، اعتبار مدل، پرورش ماهی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علوم کشاورزی و بیولوژیک
بوم شناسی، تکامل، رفتار و سامانه شناسی
چکیده انگلیسی
We propose an evaluation approach to validate stacked species distribution models applied to plant species selection in ecological restoration. The evaluation method does not assess the accuracy of individual species models, but focuses on the ability of the stacked models to discriminate between present and absent species in a vegetation relevé. We measured the discriminative ability using the area under the ROC curve (AUC) to avoid the drawbacks of converting occurrence probabilities into binary predictions. Using the proposed method, we compared competing sets of predictors and validated stacked species distribution models for plant species selection in ecological restoration projects in Spain. 120,938 vegetation relevés included in the Forest Map of Spain were used to train models for 188 species and an independent set of 100 vegetation relevés was used for validation. The best performing set of predictors included climate and soil related predictors derived from coarse resolution datasets. The model performance was acceptable on average (mean AUC: 0.88, sd: 0.07) and high (AUCÂ >Â 0.9) in 42% of the relevés evaluated. We recommend the proposed evaluation approach to validate stacked species distribution models used to support species selection in ecological restoration projects.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Ecological Modelling - Volume 263, 10 August 2013, Pages 103-108
Journal: Ecological Modelling - Volume 263, 10 August 2013, Pages 103-108
نویسندگان
Aitor Gastón, Juan I. GarcÃa-Viñas,