I see, thanks for the explanation and the reference Clément. I'll read it!
Consuelo
-------------
Consuelo Hermosilla
PhD student
Departamento de Ecología y Biología Animal
Departamento de Bioquímica, Genética e Inmunología, Área de Genética
Facultad de Ciencias del Mar
Campus de As Lagoas-Marcosende
Universidad de Vigo
36310 Vigo
SPAIN
Mobile: +34 692 633 298
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Stop Gaza Massacre
2010/5/4 Clément Calenge <clement.cale...@gmail.com>
> Hello Consuelo,
>
> Have a look at:
>
> Calenge, C., Darmon, G., Basille, M., Loison, A. and Jullien J.M.
> (2008) The factorial decomposition of the Mahalanobis distances in
> habitat selection studies. _Ecology_, *89*, 555-566.
>
> See especially the section "The MADIFA and the ecological-niche factor
> analysis" (p. 559), which explains the reasons for this message. Basically:
> the ENFA distinguishes two very different parameters: the marginality (the
> vector connecting the mean of available points to the mean of used points)
> and the specialization (ratio of the available variance/used variance). From
> this paper:
>
> "On the other hand, as the marginality axis does not have the same
> mathematical status as the specialization axes of the ENFA (the marginality
> axis is orthogonal to the specialization axes, but the specialization axes
> are not orthogonal among each other; Hirzel et al. 2002), it is often
> difficult to combine all these axes into one single index of environmental
> suitability. So far, existing methods trying to combine the marginality and
> specialization axes use ad hoc algorithms (Hirzel et al. 2002, Hirzel and
> Arlettaz 2003). Although these ENFA-based methods have proven to return
> biologically consistent
> environmental suitability maps (ESMs; e.g., Bryan and Metaxas 2007), the
> MADIFA is probably a better way to build environmental suitability maps: it
> returns axes, all with the same mathematical status, which can be combined
> into ESMs in a consistent manner."
>
> The function predict.enfa uses the Mahalanobis distances (Clark et al.
> 1993) calculated on the marginality and specialization axes to calculate
> these suitability maps. But, as for other methods (such as those implemented
> in Biomapper), the "habitat suitability modelling" is a second step of the
> analysis; the ENFA itself is not optimal for such mapping. On the other
> hand, the ENFA can be very useful for the exploration of the niche (see the
> help page of the function enfa, and references therein). A deeper
> description of these aspects can be found in the paper cited above.
> HTH,
>
>
> Clément Calenge
>
>
>
> On 05/04/2010 01:41 PM, Consuelo Hermosilla wrote:
>
> Hello guys,
>
> I have a couple of questions regarding enfa (adehabitat package).
>
> The first is related to this message: "In predict.enfa(enfa1,
> octopus.hab$index, octopus.hab$attr) :
> the enfa *is not mathematically optimal for prediction*:
> please consider the madifa instead".
> I was wondering why that message and if it does appear every time you make
> your analysis or it means you have a problem with your data/grids. Do I
> explain myself? I mean, is this the default message? does it always appear?
> And if it so, why madifa is better?
> I'm curious since this code should do the same as Biomapper does, right?
> Then, is biomapper not mathematically optimal for prediction too? Maybe I'm
> misunderstanding something...
>
> Another thing, what would you suggest to compare maxent and enfa outputs?
>
> One last thing is regarding plotting the result. If I use image(), then, how
> do I plot the legend? I tried plot() with the prediction, and it does plot
> the legend, but I don't understand the values it has. Shouldn't it range
> from 1 to 100, like in other prediction models? Again, I'm sorry if I'm
> making wrong assumptions...
>
> I hope this is helpful to someone else too!
>
> Thank you very much!
>
> Consuelo
>
> PS. You know Mathieu, another big advantage of the enfa implementation in R
> is that you don't have to convert all your grids to Idrisi format... it can
> be really a pain... I love that!
>
> -------------
> Consuelo Hermosilla
> PhD student
> Departamento de Ecología y Biología Animal
> Departamento de Bioquímica, Genética e Inmunología, Área de Genética
> Facultad de Ciencias del Mar
> Campus de As Lagoas-Marcosende
> Universidad de Vigo
> 36310 Vigo
> SPAIN
> Mobile: +34 692 633 298
>
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> ( ) Oooo
> ( ( )
> _) ) /
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>
> Stop Gaza Massacre
>
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