suggestion to jessica and others

[francis mwambo]

Dear Jessica,

Your research sounds very interesting. I happen to be also doing a modelling on human and cliamtic change impacts on Chimapnzees in Cameroon using Maxent. Your choice for variables sounds interesting. But my view is how would you input these variables for instance religion, politics, ban of of weapons in to maxent? I may suggest that if you wish to use religion as a variable you may better use culture beliefs as a variable instead. My opinion on this is that in some densely populated communities you may find muslims and christians mixed. Evident from may be the number of musks or churches one may find around especially in big cities. However, culture may be input as a categorical variable where the map of the country in question is subdivided into smaller regions based on the culture. This kind of subdivision may be similar to the kind one get from a landcover classification. In this case, the culture is input as a categorical variable with different ethic groupings.  I wish you the best in your research.


Francis Mwambo.

email:mwa...@gmail.com
ISEGI-UNL
Lisbon-Portugal

[jessica...@eva.mpg.de]

Dear Francis

Thank you for your email - it's great that we can exchange thoughts on
this, seeing that we work with the same species.

The religion map that I created is based on ethnicity, where each
country is subdivided into the different ethnic groups. However, as I
am trying to model potential ape distribution over a very large scale
(all ape range countries in West, Central and East Africa), I cannot
use the 300 plus ethnic groups as they are for the model, that's why I
assigned religion to each ethnic group, where I only included 3
categories: Islam, Christianity and Indigenous belief system.

I am not including socio-ecological factors or the weapon ban
directly, but I am including national boundaries instead. Imagine that
for example in Sierra Leone, chimpanzees occur in agricultural areas
with relatively high human densities, but in the DRC in a similar area
(i.e. a cell with the sililar properties - agricultural activity and
high human densities - as the one in Sierra Leone, no chimpanzees
occur - now both cells have different country values assigned to them,
so that the model predicts similar (agricultural) areas in Sierra
Leone as suitable, but not in the DRC. This is my line of thought, but
I'm not totally sure that this is right - perhaps someone can let me
know if I'm on the right track?

But now I still don't know whether Maxent looks at each variable in
isolation or whether it also incorporates interactions between the
variables (I mentioned the example of distance to rivers in the
previous email). Can someone help me with that???

Francis, which variables are you using? I would like to hear more
about your project - are you just going to model distribution, or are
you also going to do more analyses once you have built the model (you
can email me on my private email address if you like)?

Thank you!
Jessi

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