Ecological Interchangeability
We evaluated a proxy for ecological interchangeability by measuring the
overlap between ENMs for the sister lineages being compared (generally
following the approach of Stockman and Bond 2007) as well as taking into
account previous morphological and behavioral criteria for
distinguishing A. microunicolor (Hendrixson & Bond, 2005a).
Current climate data from 1970-2000 for 19 bioclimatic variables at 30
arc-second resolution were downloaded for tiles 12 and 13 from WorldClim
v.2 (http://worldclim.org/version2; Fick and Hijmans 2017).
Climate data from the tiles were then merged into layers, cropped to the
area of interest, and converted to a raster stack using the packages
‘raster’ (Hijmans, 2015) and ‘rgdal’ (Bivand et al., 2019) in R. The
software ENMTools v1.4.4 (Warren et al., 2010) was used to estimate the
amount of correlation between the 19 bioclimatic variables, with
significant correlation defined as r > .90 following
(Jezkova et al., 2011). Six variables were removed and the 13 retained
variables (BIO 2-9,12,13,15,16,18) were used for generating ENMs. Maxent
v.3.4.1 (Phillips et al., 2006) was used to estimate ENMs with default
settings for the lineages. The receiver-operating characteristic (ROC)
plot’s area under the curve (AUC) was used as a measure of model
prediction accuracy, with values > 0.9 indicating optimal
model performance as opposed to values < 0.7 indicating poor
model performance (Swets, 1988). Occurrence records were based on
specimens collected for this study and specimens from prior publications
(Hendrixson & Bond, 2005a, 2005b) also included in this study.
To statistically compare the ENMs of each lineage, we conducted analyses
of niche overlap, niche identity, and niche similarity (i.e. background)
tests in ENMTools (Warren et al., 2008, 2010). Niche overlap for each
sister lineage comparison was quantified using Schoener’s D(Schoener, 1968), which ranges from 0 (no overlap between ENMs) to 1
(complete overlap of ENMs). To assess the significance of D , we
employed both niche identity and niche similarity tests. For the niche
identity test, 100 pseudoreplicates were used to construct a null
distribution of niche overlap compared to the observed overlap value
using a one-tailed test (Supplemental Figure S3). Warren, Glor, and
Turelli (2008) highlighted that the niche identity test may be too
strict and results in the null hypothesis often being rejected, so the
more conservative niche similarity test was also conducted. The
background regions for each lineage were generated based on minimum area
polygons from occurrence points in ArcMap v10.7 (ESRI), and occurrence
points of one lineage were tested against random points from the
background region of the other lineage and vice versa. A hundred
pseudoreplicates were used to construct a null distribution of niche
similarity compared to the observed overlap value using a two-tailed
test (Supplemental Figures S4-7). In order to reject ecological
interchangeability with the niche similarity test, both of the
background tests for a pair of lineages should have a D value
that is more different (niche divergence) than expected by chance. Since
some of our comparisons involved parapatric/sympatric lineages which
results could potentially be affected by the defined background region,
we conducted sensitivity tests by defining alternative background
regions based on buffer polygons from occurrence points of differing
distances (25 km, 50 km, 75 km, and 100 km) in ArcMap v10.7.