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Re: [ai-geostats] Frightened of Spatial Autocorrelation

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  • Volker Bahn
    Hi Kevin, I work in the field of distribution modeling of birds and somewhat come from the other direction than most geostatistics people here on the list. In
    Message 1 of 10 , Sep 7, 2004
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      Hi Kevin,

      I work in the field of distribution modeling of birds and somewhat come from
      the other direction than most geostatistics people here on the list. In
      ecology, we first only predicted by local conditions and habitat, then were
      pointed to the problems of spatial autocorrelation in such an approach, then
      tried to compensate for autocorrelation problems in statistics and only
      lately recognized that autocorrelation is actually additional information
      that could improve prediction. Steve already posted the most current papers
      regarding this issue in Ecography, which helped me much
      (http://www.nceas.ucsb.edu/~liebhold/ecography/). I would add the following
      paper to the list:

      Lichstein J. W., T. R. Simons, S. A. Shriner, and K. E. Franzreb. 2002.
      Spatial autocorrelation and autoregressive models in ecology. Ecological
      Monographs 72(3):445-463.

      For birds it has been well documented that autocorrelation in distributions
      are caused by autocorrelation in underlying resources. Thus, in theory, if
      you cover ALL important predictors in your model (let's say a regular
      regression or any other "non-spatial" method), the spatial structure in the
      distribution is modeled implicitly by being contained in the predictors.
      However, if you miss a predictor (which in practice will always be the
      case), you will miss its spatial structure and the residuals of your
      analysis will reflect this structure rendering these approaches ineffective
      and statistically flawed. In addition, I'm trying to show in my research
      that dispersal of individuals (meaning leaving either the birthplace or the
      last breeding place permanently to breed elsewhere) also leads to
      autocorrelation in distributions. This could also be the case for
      archeological sites as there was undoubtedly some contact and exchange among
      neighbors and this contact would have been more intense with close neighbors
      as travel comes at a cost. Thus I would expect autocorrelation in the
      spatial distribution of archeological sites above and beyond the
      autocorrelation in the underlying conditions predicting archeological sites.
      I use conditional autoregressive regression models (CAR) in Splus to model
      bird distributions.

      I hope this helps

      Volker Bahn
      Dept. of Wildlife Ecology - Rm. 210
      University of Maine
      5755 Nutting Hall
      Orono, Maine
      04469-5755, USA
      Tel. (207) 581 2799
      Fax: (207) 581 2858

      ----- Original Message -----
      From: Kevin M. Curtin
      To: ai-geostats@...
      Sent: Thursday, September 02, 2004 15:43
      Subject: [ai-geostats] Frightened of Spatial Autocorrelation

      Hello All,
      I'm not sure if this is the correct forum for this.but a colleague has asked
      a question I'd like to address.

      This fellow wants to predict the location of archaeological sites based on
      factors such as soil type, proximity to a water source, slope, AND proximity
      to other archaeological sites.

      On proposing such a predictive model he has been challenged with, "How are
      you going to deal with Spatial Autocorrelation". We're not sure why SA
      should be a problem since we are suggesting that spatial proximity is a
      factor in settlement location.

      So, do we need to test for SA and why?

      Thanks in advance,

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