Hi first time posting here, I'm currently doing my PhD modelling the distributions of Australian parrots in response to climate change. I have two climate scenarios (present and future), and have used Maximum Entropy modelling to generate maps of future distributions. These distribution maps are binary maps consisting only of 'presence pixels' or 'absence pixels'.
I am wanting to use three different dispersal scenarios in the future projections to limit how far each parrot species can disperse; for example 'no dispersal' and 'unlimited dispersal'. The third scenario is what I am needing help with: contiguous dispersal. I want to create a raster layer that limits the future distribution of a species only to pixels that directly or indirectly touch presence pixels from the current distribution, i.e. limiting the distribution to presence pixels (under the future scenario) that are indirectly contiguous with presence pixels of the current climate scenario.
For example I've included a diagram of one of the species. I have a species that has a relatively small distribution under current conditions (purple pixels), and a much larger projected range under future conditions (yellow pixels), the area of presence overlap between the two scenarios is shown by brown pixel, areas of absence in both scenarios are grey. I want to create a presence-absence raster layer that excludes all yellow pixels that do not form a contiguous surface with a brown or purple pixel - i.e. exclude yellow pixels that are separated from purple/brown pixels (and the yellow pixels that are contiguous with them) by areas of absence.
I'm hoping there is a tool that will allow me to exclude these 'discontinuous' yellow pixels so that the extent of the presence pixels in the presence-absence raster layer is restricted. I'd be super grateful for any help, thanks!
You can do what you describe in your posted question. It will be a little convoluted, but isn't all that different from transportation models that are pretty common (i.e. if a major highway is cutting across a city, people can't easily move across it other than at interchanges. The scale of your figure isn't given, but most parrots can fly. Thus, I would think that they can cross some distance to get to some isolated new habitat.
That said, what your proposed model is neglecting is that state of habitat during the time between your two end members. Those birds are going to be needing to move through areas of changing habitat. The model you propose above, if I am understanding you correctly, neglects this. The evolution of the habitat may create pathways that don't appear in comparing the two end members as you propose. Conversely, the evolution of the habitat may preclude pathways that seem to exist in the process you propose. What you propose is a interesting first step, but I think you really need to look at intermediate time steps too.
You didn't mention the time frames for your two end members.
Don't lose sight of the error bars on the rate and magnitude of climate change. These are only models we are dealing with. Giving the impression of exactness for these predictions has already given the "truth" of climate change a few black eyes because actual observations don't precisely match predictions. To a scientist this isn't surprising, but the way some scientists, and most politicians, have presented the predictions to the public has unnecessarily undermined their credibility as time passes.
I definitely second Kenneth Towe's suggestion that you see how your methodology does at matching what has happened over the past 100 to 200 years. There has been entirely too little effort been put into using the historic, prehistoric, and geologic record to guide and improve our understanding of how changes in the atmosphere, land-use, water-use, and species assemblages (natural and man caused) will induce changes in climate etc. The Earth has a very extensive and long record of climate change that can help us better predict the implications of current alterations to these many parameters.
Here's a solution in R:
http://r-sig-geo.2731867.n2.nabble.com/groupping-contiguous-identical-raster-cells-td7413376.html
Joseph - thanks for your quick response, will give it a try today and see if it all goes well.
Kenneth - my 'current' scenario is based upon data from the WorldClim data set, averaging the period of 1960-1990 ('present' probably isn't the best descriptor, more just a convenience thing). I haven't considered comparing to earlier time periods for the present exercise but looking at the responses of parrots (particularly those that have become extinct) to both climate change and human interactions since European colonisation of Australia is definitely something I'd like to look into for one of my PhD chapters.
You can do what you describe in your posted question. It will be a little convoluted, but isn't all that different from transportation models that are pretty common (i.e. if a major highway is cutting across a city, people can't easily move across it other than at interchanges. The scale of your figure isn't given, but most parrots can fly. Thus, I would think that they can cross some distance to get to some isolated new habitat.
That said, what your proposed model is neglecting is that state of habitat during the time between your two end members. Those birds are going to be needing to move through areas of changing habitat. The model you propose above, if I am understanding you correctly, neglects this. The evolution of the habitat may create pathways that don't appear in comparing the two end members as you propose. Conversely, the evolution of the habitat may preclude pathways that seem to exist in the process you propose. What you propose is a interesting first step, but I think you really need to look at intermediate time steps too.
You didn't mention the time frames for your two end members.
Don't lose sight of the error bars on the rate and magnitude of climate change. These are only models we are dealing with. Giving the impression of exactness for these predictions has already given the "truth" of climate change a few black eyes because actual observations don't precisely match predictions. To a scientist this isn't surprising, but the way some scientists, and most politicians, have presented the predictions to the public has unnecessarily undermined their credibility as time passes.
I definitely second Kenneth Towe's suggestion that you see how your methodology does at matching what has happened over the past 100 to 200 years. There has been entirely too little effort been put into using the historic, prehistoric, and geologic record to guide and improve our understanding of how changes in the atmosphere, land-use, water-use, and species assemblages (natural and man caused) will induce changes in climate etc. The Earth has a very extensive and long record of climate change that can help us better predict the implications of current alterations to these many parameters.
Just happened across a somewhat related publication:
http://bit.ly/PNAS-climate-connect
It may be helpful both directly and through its references.
http://bit.ly/PNAS-climate-connect
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