Interdisciplinarity was the nature of my work this summer,
looking to see if there was a correlation between social distance and
geographic distance within the farmer social network. The farmer social network
is a visual diagram that was created by the sociologists from last year’s LAKES
team that shows which farmers talk to each other about farming practices within
the Red Cedar watershed. Small dots called nodes represent people, while lines
connecting them called edges represent their connection.
Surveys that were sent to farmers create the
social network. These surveys ask about best management practices (BMP), as
well as interest in learning about conservation agriculture, and who the farmers
talks to about their land use practices.
Why does this information matter?
By seeing the lines of communication between farmers, we can see who would be
open to learning about BMPs for their farms, and how to effectively disseminate
information about conservation agriculture.
While the sociologists were able to create a fantastic
social network, they did not look at it in terms of geography. That is, seeing
if there is a correlation between social distance and geographic distance. I
started my work by getting familiar with the survey that created the farmer
social network, as well as prepping the current data for statistical analysis
in a geographic information system (GIS) software called ArcMap. I also
recreated the farmer social network in terms of geography.
In AcrMap, I looked to see if there
was a spatial autocorrelation between any of the questions in the survey.
Spatial autocorrelation measures the clustering of values within a map.
As for the new social network, I
made the sub-watersheds within the Red Cedar into nodes from which to anchor the
social network. Edges were made, connecting to the farmers within their
boundaries. By viewing the social network as such, I could see if there was any
clustering of social connection based on sub-watershed.
From my analysis of the farmer social network, I found that
there is a contrasting relationship between two sub-watersheds within the Red
Cedar.
On one hand, the Lower Pine Creek-Red Cedar
shows a high clustering of farmers who would be interested in learning about
conservation agriculture, soil health, and economic projections for their
farms, while at the same time, having a high clustering of BMP usage.
Where do we go from here? My findings open the door for many
different avenues of research. From what I’ve found, we can start asking: what
are the differences between these two sub-watersheds in terms of geography, and
society? What is working for one, and why is it not working for the other?
With this
information, we can better learn the factors that affect the farmer social
network in the Red Cedar, and how to better disseminate information about
conservation agriculture.
