Data Preparation
Data were combined into Midwestern (Table S1) and Oklahoma (Table S2)
datasets. Each dataset was formatted and analyzed using tools in thespatstat (Baddeley et al. 2015) package in R (R Core Team
2021). For each sample plot, the coordinates and measurable attributes
(deemed marks ) of each point were converted into marked
multivariate point-pattern data (ppp objects). The pppobjects were combined into a two multivariate hyperframes(the Midwestern and Oklahoma, respectively), wherein each row
corresponds with one sample site. Working in a hyperframe allowed
analytical operations to be performed on an entire dataset at a time.
Prior to analyses, the unmarked point-pattern data associated with each
site were checked for homogeneity. The Midwestern and Oklahoma
hyperframes were subset into groups based on the area of the sampling
window of each plot (see Table S1 and Table S2). A quadrat-count test
was conducted to establish whether a given point-pattern had a
homogeneous distribution of points. In the Midwestern dataset, certain
plots were inhomogeneous, and thus, subsequent analyses conducted on
those plots accounted for that characteristic. All 13 point-patterns in
the Oklahoma dataset were homogeneous.