[R-sig-Geo] Modelling: opinion of new methods

Bede-Fazekas Ákos b|@|ev||@t @end|ng |rom gm@||@com
Fri Jun 7 16:03:11 CEST 2019


Dear Lara,

Several correlative species distribution models exist (and are used 
currently), including machine learning approaches as well, such as 
artificial neural network (ANN), boosted regression trees (RGB / GBM), 
genetic algorithm (GA), and random forests (RF).
You may find the papers comparing or grouping them interesting:
- Dormann CF, Elith J, Bacher S, Buchmann C, Carl G, Carré G, García 
Marquéz JR, Gruber B, Lafourcade B, Leitão PJ, Münkemüller T, McClean C, 
Osborne PE, Reineking B, Schröder B, Skidmore AK, Zurell D, Lautenbach S 
(2013): Collinearity: a review of methods to deal with it and a 
simulation study evaluating their performance. Ecography 36(1): 27–46.
- Elith J, Graham CH (2009)? Do they? How do they? Why do they differ? 
On finding reasons for differing performances of species distribution 
models. Ecography 32(1) 66–77.
- Heikkinen RK, Luoto M, Araújo MB, Virkkala R, Thuiller W, Sykes MT 
(2006): Methods and uncertainties in bioclimatic envelope modelling 
under climate change. Progress in Physical Geography 30(6): 751–777.
- Hernandez PA, Graham CH, Master LL, Albert DL (2006): The effect of 
sample size and species characteristics on performance of different 
species distribution modeling methods. Ecography 29(5): 773–785.
- Pearson RG, Thuiller W, Araújo MB, Martinez-Meyer E, Brotons L, 
McClean C, Miles L, Segurado P, Dawson TE, Lees DC (2006): Model-based 
uncertainty in species’ range prediction. Journal of Biogeography 
33(10): 1704–1711.
- Thuiller W (2004): Patterns and uncertainties of species’ range shifts 
under climate change. Global Change Biology 10(12): 2020–2027.

Also see package 'sdm' by Naimi and Araújo.
HTH,
Ákos Bede-Fazekas
Hungarian Academy of Sciences

2019.06.07. 15:45 keltezéssel, Lara Silva írta:
> Hello everyone!
>
> I am new in modelling species (plants). However, I used some approaches
> like ENFA (Biomapper), Maxent, generalized linear and additive models (in
> R) and Biomod2.
>
> I would like to improve my knowledge in this area.Currently, what methods
> have been used?
> Any suggestions?
>
> Regards,
>
> Lara
>
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