Evaluating the predictive performance of stacked species distribution models applied to plant species selection in ecological restoration

2013 ◽  
Vol 263 ◽  
pp. 103-108 ◽  
Author(s):  
Aitor Gastón ◽  
Juan I. García-Viñas
Keyword(s):  
Ecological Restoration ◽  
Plant Species ◽  
Species Distribution ◽  
Species Distribution Models ◽  
Predictive Performance ◽  
Species Selection ◽  
Distribution Models

Species distribution models applied to plant species selection in forest restoration: are model predictions comparable to expert opinion?

New Forests ◽  
2014 ◽  
Vol 45 (5) ◽  
pp. 641-653 ◽  
Author(s):  
Aitor Gastón ◽  
Juan I. García-Viñas ◽  
Alfredo J. Bravo-Fernández ◽  
César López-Leiva ◽  
Juan A. Oliet ◽  
...  
Keyword(s):  
Plant Species ◽  
Expert Opinion ◽  
Species Distribution ◽  
Forest Restoration ◽  
Species Distribution Models ◽  
Species Selection ◽  
Distribution Models ◽  
Model Predictions

scholarly journals Correction: Oleas, N.H., et al. Muddy Boots Beget Wisdom: Implications for Rare or Endangered Plant Species Distribution Models. Diversity, 2019, 11, 10

Diversity ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 401
Author(s):  
Nora H. Oleas ◽  
Kenneth J. Feeley ◽  
Javier Fajardo ◽  
Alan W. Meerow ◽  
Jennifer Gebelein ◽  
...  
Keyword(s):  
Plant Species ◽  
Species Distribution ◽  
Species Distribution Models ◽  
Endangered Plant ◽  
Distribution Models ◽  
Endangered Plant Species

An error on our paper [...]

scholarly journals blockCV: an R package for generating spatially or environmentally separated folds for k-fold cross-validation of species distribution models

2018 ◽  
Author(s):  
Roozbeh Valavi ◽  
Jane Elith ◽  
José J. Lahoz-Monfort ◽  
Gurutzeta Guillera-Arroita
Keyword(s):  
Species Distribution ◽  
Cross Validation ◽  
Species Distribution Models ◽  
Predictive Performance ◽  
R Package ◽  
Species Distribution Modelling ◽  
List Type ◽  
Distribution Models ◽  
Distribution Modelling ◽  
Evaluation Approaches

SummaryWhen applied to structured data, conventional random cross-validation techniques can lead to underestimation of prediction error, and may result in inappropriate model selection.We present the R package blockCV, a new toolbox for cross-validation of species distribution modelling.The package can generate spatially or environmentally separated folds. It includes tools to measure spatial autocorrelation ranges in candidate covariates, providing the user with insights into the spatial structure in these data. It also offers interactive graphical capabilities for creating spatial blocks and exploring data folds.Package blockCV enables modellers to more easily implement a range of evaluation approaches. It will help the modelling community learn more about the impacts of evaluation approaches on our understanding of predictive performance of species distribution models.

scholarly journals Testing whether ensemble modelling is advantageous for maximising predictive performance of species distribution models

Ecography ◽  
2020 ◽  
Vol 43 (4) ◽  
pp. 549-558 ◽  
Author(s):  
Tianxiao Hao ◽  
Jane Elith ◽  
José J. Lahoz‐Monfort ◽  
Gurutzeta Guillera‐Arroita
Keyword(s):  
Species Distribution ◽  
Species Distribution Models ◽  
Predictive Performance ◽  
Distribution Models ◽  
Ensemble Modelling

scholarly journals Application of consensus theory to formalize expert evaluations of plant species distribution models

2013 ◽  
Vol 17 (3) ◽  
pp. 528-542 ◽  
Author(s):  
Maarten van Zonneveld ◽  
Nora Castañeda ◽  
Xavier Scheldeman ◽  
Jacob van Etten ◽  
Patrick Van Damme
Keyword(s):  
Plant Species ◽  
Species Distribution ◽  
Species Distribution Models ◽  
Distribution Models ◽  
Consensus Theory
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