Blockquote Can my process/decision for interpolation be adequately justified for a paper, or should I be doing something else?
Well, +1 for this one.
Bear with me, I am not a (geo-)statistician at all, but I am always a bit stumped when I see people trying to interpolate datasets that simply aren't suitable for interpolation, even in the face of exploratory spatial data analysis results clearly showing they shouldn't be interpolating the data.
It is probably true that nowadays there are better interpolation tools and methods than maybe 20 years ago when I studied, that can also better deal with more "erratic" data, but people often seem almost blindly to assume that interpolation is the only way to deal with any dispersed "point" datasets, and that if they can derive a surface, it is "the truth".
Even worse, people often fail to see the great opportunities their datasets may offer for "normal" (non-spatial and geostatistical) statistical analysis. They may have measured a plethora of factors possibly influencing their depended variable, but proceed to just interpolating their main variable of interest.
Having studied biology too, I know from experience vegetation data varies very non-continuous. That type of data generally is not very suitable for any kind of geostatistical interpolation, contrary to stuff like groundwater levels that tend to vary much more smoothly and continuous.
I would really start out by comparing your data with other environmental or geographic data and abiotic factors, like information about soil types, groundwater types and levels, sun and climatic exposure, incline etc. that may be real factors in determining biomass. Input those into a statistical package, and see if you can determine any statistical correlations with the biomass. If these statistical results aren't "enough" by themselves, you might possibly use those to classify maps of the existing abiotic factors / data to show areas that are likely to have low or high biomass potential. This wouldn't require an interpolation, your statistical analysis would be your guide.