Figure Captions
Figure
1 The global distribution map of
Tridacna maxima (A) and the study area map (B). The red dots represent
existing occurrence records of the T. maxima worldwide, while the yellow
and blue dots represent occurrence records of the East Indian
Ocean-South China Sea population (EIOS) and the West Pacific-Indonesian
population (WPI), respectively.
Figure 2 Results of collinearity analysis of nine predictors.
Scatter collinearity analysis (A), Pearson’s correlation analysis (B),
and variance inflation factor analysis (C) results for nine predictor
variables. Depth - ocean depth; LandD - land distance; Cv - current
velocity; Do - dissolved oxygen; Sal - salinity; Tmean – temperature
mean; Trange – temperature mean; Lb - Light at bottom; Pp -
Phytoplankton.
Figure
3Ecological
niche differentiation. (A) Percentage of explained variance of each
principal component of principal component analysis for the nine
selected predictors. (B) The niches of the two populations ofTridacna maxima quantified via four-dimensional hypervolumes. To
visualize the shape and boundary of the hypervolumes in two dimensions,
a random selection of 20,000 stochastic points for each hypervolume was
used. The large blue and orange points indicate the mean niche position
(niche centroid) of EIOS and WPI, respectively. (C) Contribution of
environmental predictors to each principal component (PC). The number in
the bar indicates the contribution rate (%) of each predictor to PC
axes, and only values>15% are shown. Depth - ocean depth;
LandD - land distance; Cv - current velocity; Do - dissolved oxygen; Sal
- salinity; Tmean – temperature mean; Trange – temperature mean; Lb -
Light at bottom; Pp - Phytoplankton.
Figure
4Model
evaluation and importance of environmental factors. Predictive abilities
of the ten modeling algorithms in projecting the distribution ofTridacna maxima at the population and species levels. (A) the
True Skill Statistics (TSS) value; (B) the Area Under the receiver
operating characteristic Curve (AUC) value. The black horizontal lines
indicate the cutoff values of the AUC (0.8) and TSS (0.7) of the single
model used to build the ensemble model. (C) Relative importance of the
nine predictor variables in the three ensemble models built at
population and species levels. Data are expressed as mean ± standard
error. Depth - ocean depth; LandD -
land distance; Cv - current velocity; Do - dissolved oxygen; Sal -
salinity; Tmean – temperature mean; Trange – temperature mean; Lb -
Light at bottom; Pp - Phytoplankton.
Figure
5The
response curves of Tridacna maxima occurrence probability against
the two most important driving factors based on the population-level
(A1, A2) and species-level model
(including the Eastern Indian Ocean – South Sea population (B1, B2) and
the Western Pacific – Indonesia population (C1, C2)). LandD - land
distance; Tmean – temperature mean; Lb - Light at bottom.
Figure 6Habitat
suitability maps of Tridacna maxima predicted by species and
population level integrated models under current climate scenarios.
Panels (A1, A2) show the corresponding continuous and binary maps for
the species; panels (B1, B2) show the corresponding maps for EIOS;
panels (C1, C2) show the corresponding maps for WPI.
Figure7Future predictions and changes.
Habitat suitability maps ofTridacna maxima predicted by
an integrated model established at both species and population levels
under future climate scenarios. Panels (A1, B1, C1) are binary maps for
each species, and panels (A2, B2, C2) show the predicted changes in
suitable habitats for the 2100s under RCP 8.5 (0085). The category
“loss” represents areas projected to be suitable under current
climatic conditions but unsuitable under future climatic conditions;
“stable” represents areas projected to be suitable under both current
and future climatic conditions;
“gain” represents areas projected
to be unsuitable under current climatic conditions but suitable under
future climatic conditions; and “unsuitable” represents areas
projected to be unsuitable under current and future climatic conditions.
Figure
8 Analysis of Marine Protected Area (MPA) Gaps. (A) Analysis of
suitable habitats for Tridacna maxima in the current climate
scenario and existing MPA gaps. (B) Analysis of suitable habitats forTridacna maxima in the 2100s under the RCP 8.5 climate scenario
and existing MPA gaps.
Table 1The nine environmental variables
selected for this study