Results
Lineage genetic diversity
We found significant genetic divergence between the populations ofT. hemprichii in the Western Tropical Indo-Pacific and Central
Tropical Indo-Pacific regions. Although we found some minor
discrepancies (see Data availability) between the two datasets after
carefully inspecting the calibrated fragment lengths of the
microsatellites (Hernawan et al. 2017; Jahnke et al.2019a), even after deleting a few microsatellites (e.g., Thh41, TH07 and
TH37), two genetic lineages in T. hemprichii remained
significantly diverged (i.e., CTIP and WTIP) across the Tropical
Indo-Pacific (Fig. 1b, 1c). Genetic variation among lineages accounted
for 43.42% of the total genetic variation (Ф CT =
0.43, P < 0.0001; Supporting Information Table S1).
Very limited genetic admixture was observed between the CTIP and WTIP
lineages. The CTIP lineage harbored strikingly rich genetic diversity,
with three times more alleles and allelic richness, and eight times
fewer private alleles than the WTIP lineage (Supporting Information
Table S2).
Niche differentiation between
hypervolumes
The size of the realized niche of the CTIP lineage was one order of
magnitude greater than that of the WTIP lineage (CTIP lineage: 17295.6;
WTIP lineage: 2273.2) (Fig. 2). Niche differentiation between the two
hypervolumes (0.97) was mainly due to variation in niche size (0.79),
whereas niche shift contributed only marginally (0.18). Difference in
realized niches was easily distinguished via water depth and distance to
land, with the WTIP lineage selecting a narrow range of water depth and
distance to land (Fig. 2). The two lineages also exhibited niche
differentiation with respect to annual mean sea surface salinity. In
addition, the CTIP lineage niche was broader with respect to annual mean
SST and annual range SST, whereas that of the WTIP lineage was broader
for annual mean current velocity, minimum current velocity, and annual
range of sea surface salinity (Fig. 2).
Niche differentiation between the
two hypervolumes was also high (0.86) when we considered only marine
environmental predictors (i.e., excluding water depth and distance to
land) (Supporting Information Fig. S2).
Model performance
The tuning parameter settings with optimal complexity for the
species-level and lineage-level models ranged from relatively simple to
complex. The optimal species-level model was the most complex (hinge
features and 0.5 RM), while those for the lineage-level models were
simpler (CTIP: linear/quadratic/hinge features and 2.5 RM; WTIP:
linear/quadratic features and 0.5 RM) (Table 1). The average 10%
omission rate was considerably lower for the WTIP lineage-level model
(3.57%) than for the other models (CTIP: 26.69%; species: 17.93%;
Table 1) — as this was lower than the expection of average 10%
omission for the metric, it indicates that the optimal settings results
in models that may over-predict to some extent for WTIP. Although
omission rate was used primarily for model selection, the average
validation AUC scores used to break ties were very high for all optimal
models (Table 1); we think this is due to the fact that a majority of
presence data are in near-shore waters (Fig. 1a), which likely inflated
the model’s ability to discriminate between these presences and
background records in deeper water. In addition, all three optimal
models had relatively high continuous Boyce index scores (over 0.90;
Table 1), indicating that final model predictions matched the presence
data well. The eight predictors had different levels of importance in
the three models, but water depth and distance to land consistently
played important roles (Table 2). In particular, these two predictors
accounted for more than 95% of permutation importance in the WTIP model
(Table 2). For the CTIP and species models, annual mean SST also had a
high permutation importance (~29% and
~24%, respectively) (Table 2). Response curves for
water depth and distance to land suggest that shallow coastal waters are
more suitable for T. hemprichii (Supporting Information Fig. S3).
Present-day habitat suitability
projections
Under present-day conditions, species and lineage models projected
similar but not identical habitat suitability patterns, with a large
part of the East African coast and the Pacific region as suitable
habitat for this species (Fig. 3). Compared with the species model, the
CTIP model predicted more southern distribution in Australia (Fig. 3c,
3d). In particular, the CTIP model predicted suitable conditions in the
Spencer Gulf, Southern Australia, where the species does not naturally
occur (Fig. 3a, 3c). The species model did not capture this pattern
(Fig. 3b, 3d). Moreover, the WTIP model identified more suitable habitat
in the Red Sea than the species-level model (Fig. 3c, 3d). Overall,
species- and lineage-level models predicted comparable suitable areas
for T. hemprichii in the WTIP region (species model: 302,800
square km; WTIP model: 315,000 square km), while the species model
predicted broader suitable area for the CTIP region (species model:
1,873,800 square km; CTIP model: 1,757,900 square km).
Climate change impacts on habitat
suitability
Species- and lineage-level models resulted in different future habitat
suitability projections in the CTIP region, with the lineage-level model
resulting in predictions of more loss of suitable areas (Table 3; Fig.
4). Both species- and lineage-level models predict considerable future
loss of suitable area in the CTIP region, especially on the Sunda Shelf
(i.e., Indonesia and Malaysia) (Table 3; Fig. 4). Compared with the
species model, the CTIP model projected more extensive range loss under
all climatic scenarios (Table 3). Interestingly, both models predicted
that the species will shift slightly southwards in Australia.
Species-level and lineage-level models predicted different impacts of
climate change on habitat suitability for T. hemprichii in the
WTIP region (Table 3). The WTIP model predicted range expansion (except
under the RCP 2.6 scenario for the 2050s), whereas the species model
consistently indicated range contraction (Table 3). Overall, both
species- and lineage-level models predicted that future climate change
marginally affects habitat suitability in the WTIP region and that
changes in range size were mostly < 15%, with the exception
of a higher value (~24%) for the species model in the
2100s for the RCP 8.5 scenario (Table 3). The WTIP model predicted that
habitat suitability of T. hemprichii in the WTIP region will
remain stable in the future, while the species model predicted range
contraction in the Red Sea and expansion in southern Madagascar and
South Africa (Fig. 4).
Both species and CTIP models consistently showed that MESS values in the
Sunda Shelf were slightly negative, which demonstrates small differences
in climatic conditions between the present-day and future scenarios for
this region (Supporting Information Fig. S4). For the WTIP region, the
lineage and species model showed high environmental similarity except
slight environmental dissimilarity in the Red Sea between present-day
and future scenarios (Supporting Information Fig. S4). These results
indicate a low degree of extrapolation in our model predictions.