There are four sampling sites on a hillslope (top, upper, lower, bottom), each site has three replications. We have studied soil nutrients and plant biomass in these four treatments, a reviewer suggested that a proper statictical analysis (autocorrelation between topographic positions) was needed.
My question is that how can I do the analysis for autocorrelation for my study? I am familiar with SPSS. Thank you very much.
Probably the below reference may help you.
Multi-scale linkages between topographic attributes and vegetation indices in a mountainous landscape, Deng et al (2007), Remote Sensing of Environment, 111(1), 122-134.
https://doi.org/10.1016/j.rse.2007.03.016
Autocorrelation (AC) is a characteristic of data in which the correlation between the values of the same variables is based on related objects. AC violates the assumption of independence, which underlies most conventional statistical models. AC generally exists in those types of data-sets in which the data, instead of being randomly selected, is from the same source.
So you don't want autocorrelation in your study! But certainly check that it's not present.
A better approach would be to use GLM and post-hoc tests to determine significant differences between the sites. Your factor would be 'site' (within hill-slope) and variables will be soil nutrient and biomass. However, your study is pseudo-replicated because your 'replicates' are on only one hill-slope (but you can still obtain valid results about that one hill slope area). It's always best to have at least 3 widely spaced areas to study – these areas would then be the true replicates.
You could also consider using canonical ordination.
I hope this helps :)
Here is a short, relevant, easily understood editorial article which explains pseudo-replication from a journal editor's point-of-view:
Binkley, D. (2008). Three key points in the design of forest experiments. Forest Ecology and Management 255.
https://www.elsevier.com/__data/promis_misc/keypointsindesign.pdf
Use the article to understand how to draw appropriate conclusions from your present and future studies.
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