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The roots of a plant can be viewed as a graph, with vertices representing points in Euclidean space and edges representing the connective material. Such graphs will ideally be designed in order to optimize one or more relevant objectives. Two objectives that are particularly important for biological reasons include minimizing the total length of the edges in the graph (wiring cost), and minimizing the total lengths of the shortest paths from each point to the root of the graph (conduction delay). These two objectives compete with each other, as optimizing for one objective generally results in poorer performance of the other. Additionally, sensitivity to gravitational forces constrains the curvature of edges in the graph, and by extension how well these objectives can be optimized. In this paper we show how ideas from economics can be used to resolve the tradeoff between competing objectives, and we define a concrete optimization problem that accounts for the role of gravity in constraining the solution space. We then show two techniques for solving this seemingly impossible optimization problem, both of which will be accessible to undergraduate math students.