My Spatial Problem

1. Research Question

Soil microbial communities are extremely complex, because in each gram of soil there are about 10⁹ microorganisms.  Due to this complexity, studying these communities at a species level and understanding any meaningful relationships is difficult.  Therefore, there is a lot of current research looking at how the composition of the community is dictated by environmental parameters in the soil and understanding how the community shifts as these parameters change.  However, before I can begin to examine these microbial communities, I need to explore the spatial distribution of these environmental factors.  If I do find a neat relationship between significant environmental parameters and microbial composition, I want to explore different methods of how to interpolate this sampled relationship over larger, unsampled areas.

2. The Dataset

The dataset is a set of soil parameters from samples throughout the state of Oregon. These parameters only include edaphic factors such as pH and texture metrics; however, I also hope to include climate factors such as mean annual temperature and precipitation when exploring this relationship between environmental factors and microbial community distribution.   Samples were collected across Oregon to try and encompass all the Common Resource Areas (CRA).  According to the NRCS (Natural Resource Conservation Service), a CRA is “a geographic area where resource concerns, problems, or treatment needs are similar.”  The CRA  geographic partitioning map has a scale of 1:250,000 and considers landscape factors, human use, climate and other natural resource information.

3. Hypothesis

I hypothesize that these environmental parameters are indeed influenced by spatial autocorrelation; however, due to the low sampling point density it will be difficult to confidently model the distribution of these soil parameters.  For this reason, it may be beneficial to see how conserved these environmental factors are within their respective CRA. If the values of a given environmental variable are similar within a CRA, the CRA polygon may be a more robust unit of analysis than individual sampling points.

4. Approaches

Firstly, I need to examine the spatial relationships across these environmental factors and see how strong the relationship are.  I also would like to examine how well these environmental factors are conserved within/between CRAs.

5. Outcome

I will produce a map of environmental factors interpolated across Oregon using either point data or relationships between CRAs and their respective points.

6. Significance

Soil microbes provide several different ecosystem services such as nutrient cycling; however, understanding the fundamental parameters dictating microbial community distribution through a landscape is not well understood.  Providing a map of the distribution of these microbial communities can help increase accuracy for regional nutrient cycling models and help quantify soil health.

7. Expertise

I have very little experience with GIS and Python; however, I have done a fair bit of work with R in my undergraduate degree and graduate work.  I hope to gain some proficiency in ArcGIS and learn how to incorporate R scripts into ArcGIS.  There are also several R packages built around spatial analysis in which I hope to become familiar with.