2.1 | Plant species and deer browse
The four species included in this study were the indigenous treeNyssa sylvatica Marshall, the indigenous shrub Lindera
benzoin L. Blume, the nonindigenous, invasive shrub Euonymus
alatus (Thunb.) Siebold, and the nonindigenous, invasive semi-woody
shrub Rosa multiflora Thunb. We selected them based on four
criteria. First, they were sufficiently abundant in the understory to
provide a sample of individuals in both fenced and unfenced plots.
Second, they included a mix of indigenous and nonindigenous, invasive
species, since both types are common in suburban forests and comparisons
of their ecologies is relevant to a broader understanding of plant
invasions. Both invasive species are of conservation concern . Third,
they include both a tree species and shrubs. The ecological success of
both groups is essential for maintaining the physical layers of forest
structure and food sources that support a diversity of other forest
species . Fourth, the four species were all vulnerable to deer browse,
but at somewhat different rates.
Deer browse rates for each species were measured on unfenced and fenced
plants in the summer of 2018, the season when we sampled the leaves for
metabolomic analysis, and over multiple seasons from 2012-2019,
including one fall, two winters, and seven summers. The rates
were calculated in each plot by inspecting all individuals of the
species in an L-shaped, 0.5 x 7.5 m belt transect that followed two
edges of the plot, and recording the presence or absence of the
distinctive, tell-tale signs of deer browse: bitten, shredded twig tips
. Any browse signs inside the fences should be considered as the error
rate of falsely assigning a damaged twig tip to deer browse when it was
due to some other cause. For the browse rates presented for the species
in this study, the fenced rate on the species was subtracted from its
unfenced rate. The browse rates were compared among species for the
summer 2018 rates and the rates pooled across years, using G-tests for
overall heterogeneity among the species along with pairwise tests with a
Bonferroni correction for multiple tests on the same data set. G-tests
were done in R v 4.1.2 , with the G.test function in the RVAideMemoire
package.