Trends in Abundance and Phenology: Because list length analysis is a metric of relative abundance, average
trends in abundance are expected to be centered around 0 across species;
this expectation held (mean = 0.003 , sd = 0.045, greatest decline =
-0.137 (Nymphalis vaualbum Compton tortoiseshell; Fig 1a),
greatest increase = 0.190 (Poanes zabulon Zabulon skipper; Fig
1b)). Trends estimated from count models were also broadly centered
around 0 (mean = 0.012, sd = 0.057, greatest decline = -0.159
(Nymphalis vaualbum Compton tortoiseshell), greatest increase =
0.213 (Poanes zabulon Zabulon skipper)). Trends estimated from
list length were strongly congruent with trends estimated from counts
(Pearson’s r = 0.89, P < 0.001). Therefore, we focus the rest
of our analyses on trends estimated from list length analyses (see Appendix S2 ).
Across 26 years of continuous observation, species were, on average,
advancing their onset of flight approximately 0.20 days per year (sd =
0.42, range = (advancing) -1.75 days per year for Battus philenor (Pipevine swallowtail; Fig 1c), to (delaying) +1.22 days per year for Vanessa cardui (Painted lady; Fig 1d)) with an estimated 75% of
species advancing their 0.1 quantile observations. Species were, on
average, delaying their 0.9 quantile day of year observation
approximately 0.04 days per year (sd = 0.50, range = -1.76 days per year
(Nymphalis vaualbum Compton Tortoiseshell), +1.29 days per year
(Erynnis horatius Horace Duskywing)). Approximately 58% of
species delayed their 0.9 quantile observations. Species were, on
average, increasing their flight period (measured as the difference
between the 0.9 quantile trend and 0.1 quantile trend) by 0.16 days per
year (sd = 0.55 days per year, range = -1.96 days per year for Nymphalis vaualbum (Compton tortoiseshell), +2.05 days per year Battus philenor (Pipevine swallowtail). Approximately an
estimated 63% of species increasing their observed flight period.
Trends in the onset of flight activity (0.1 quantile) were negatively
correlated with changes in relative abundance, i.e., advancing the start
of the flight period was associated with increasing abundance (r =
-0.27, t = -2.7 , df = 87, p = 0.009, 98.03% of bootstrapped
correlations < 0; Fig 2a). Trends in the end of flight
activity (0.9 quantile) were positively correlated with changes in
relative abundance, i.e., species that were extending their activity
later into the year also tended to be increasing in abundance (r = 0.36,
t = 3.59, df = 87, p < 0.001; 99.07% of bootstrapped
correlations > 0; Fig 2b). The strongest association in our
data was a positive correlation between the annual change in the flight
period and the annual change in the relative abundance (r = 0.54, t =
5.9, df = 87, p < 0.001; 99.88% of bootstrapped correlations
> 0; Fig 2c) such that species elongating their total
flight time were increasing in relative abundance.
Mean flight dates were significantly changing in univoltine species
(slope of mean day of year observation vs time ± SE: -0.27 ± 0.16) but
not for multivoltine species (slope of mean day of year observation vs.
time ± SE: -0.03 ± 0.26. Overall, there was no significant association
between trend in mean date and trend in abundance for all species
combined (r = 0.061, t = 0.574, df = 87, p = 0.568; 93.5% of
bootstrapped correlations > 0). Grouping by voltinism and
using abundance trends estimated using counts for direct comparison with
MacGregor et al. (2019), mean day of year trends were not significantly
associated with abundance trends for multivoltine species (r = -0.06, t
= -0.43, df = 50, p = 0.672; 74.18% of bootstrapped correlations
< 0 ), but were marginally significantly associated with
abundance trends for univoltine species (r = 0.32, t = 2.00, df = 35, p
= 0.053; 88.75% of bootstrapped correlations > 0).
Structural equation models: Our a priori structural equation model (Fig. 3)
showed significant direct effects of flight period trends (scaled
regression coefficient ± SE, β = 0.472 ± 0.087) and species’ range type
(β = 0.308 ± 0.101) on trends in abundance, which presumably reflects
other traits associated with northern vs. southern species. The effect
of flight period trends on abundance trends was larger than the direct
effects of range type. Differences in flight period were significantly
associated with differences in voltinism (β = 0.430 ± 096). Compared to
univoltine species, multivoltine species more often increased their
flight period (days/year ± SE: -0.13 ± 0.09 and 0.35 ± 0.0 for
univoltine and multivoltine, respectively) and increased in relative
abundance (trend ± SE: -0.01 ± 0.01 and 0.02 ± 0.01 for univoltine and
multivoltine, respectively). Differences in voltinism were weaker but
significantly associated with range type (proportion multivoltine ± SE:
0.69 ± 0.06 and 0.32 ± .10 for southern and northern species,
respectively). This a priori model demonstrated adequate, but not
exceptional fit (χ2 = 3.076, df = 2, p = 0.215;
recalling that, in SEMs p < 0.05 represents significant
inconsistency with data).
Post hoc inspection of modification indices revealed one
additional factor that was not present in our a priori model.
This missing factor was a relationship between range type and flight
period trends; species with southerly ranges were increasing flight
periods more than species with northerly ranges (days/year ± SE: 0.35 ±
0.07 and -0.13 ± 0.09, for southern and northern species, respectively),
regardless of voltinism. Including this relationship improved model fit
(χ2 = 0.614, df = 1, p = 0.433), and slightly
decreased the strength of the association between voltinism and flight
period (updated β = 0.381 ± 0.099).