Habitat comparison: Realized niche breadth and overlap
The realized niche breadth obtained for scleractinians was considerably
greater than for octocoral recruits, in both, geographic (0.71 for
scleractinian recruits and 0.54 for octocoral recruits), and
environmental space (0.31 for scleractinians and 0.19 for octocorals).
Niche overlap measured with Schoener’s D and Warren’s Iwere 0.79 and 0.96 in geographic space, respectively, whereas in
environmental space were 0.39 and 0.63. Rho indicated both taxa
had similar positive responses to the environmental predictors, and asD and I, this metric was also higher in geographic space
compared to in environmental space (0.81 vs 0.46). The identity test
showed
both, Dand I were significantly lower than expected by chance in
geographic space, whereas only I was significant in environmental
space. Thus, we rejected the
hypotheses the taxa niches were identical in geographic space (usingD and I ) and in environmental space using I (Figure
5A; p ≤ 0.05). Similarly, the
background test was significant using both metrics of niche overlap in
geographic space, but not in environmental space. Finally,
habitats suitable for
scleractinian coral recruits were more abundant than for octocorals
(Figure 6), and the median suitability value for the scleractinians was
also higher than for octocoral recruits (W= 6.6159e+13, p <
0.01), indicating their relative abundances were independent of the
amount of suitable habitat available for each taxon.
DISCUSSION
Understanding recruitment niche
dynamics is crucial to improve our knowledge of processes assembling
communities and to detect sensitivity to environmental change and shifts
in community composition. In our study, we fitted and projected an SDM
on digital 3D reproductions of the reef. This new methodology allowed
us, for the first time to quantitatively characterize and map the
realized spatial niche for recruits of sessile taxa on a coral reef
ecosystem. Habitats suitable for octocoral and scleractinian recruits
were very similar but not identical, indicating that each taxon has
advantages in different subsets of the microhabitat space. The niches
overlapped due to the wider niche breadth of scleractinian recruits. The
result is consistent with the hypothesis that declining scleractinian
coral cover is providing habitat suitable for octocoral recruitment.
However, the amount of habitat available for recruits of each taxon did
not explain their relative abundances in the reef, which emphasizes
spatial niche dynamics solely are not responsible of these taxa recruit
dynamics.
In general, microhabitats suitable for both taxa were very similar, and
displayed high levels of overlap. Fine-scale (< 10 mm)
roughness was the most important predictor to characterize the
recruitment niche of both taxa, which is consistent with the numerous
studies reporting higher settlement and post-settlement survival on
settlement tiles with complex surfaces (Carleton & Sammarco 1987;
Lasker & Kim 1996; Raimondi & Morse 2000; Harrington et al.2004; Nozawa 2008; Edmunds et al. 2014; Whalan et al.2015; Gallagher & Doropoulos 2017; Zelli et al. 2020).
Microhabitats suitable for each taxon were not identical. Holes,
crevices, and grooves < 10 mm size, were more suitable for
octocorals whereas hummocks, ridges and bumps of similar dimensions were
better suited for scleractinians. At larger scales, microhabitats
suitable for octocorals were located on boulders, whereas, flat and
exposed areas of the reef were better suited for scleractinians.
Distribution patterns of octocoral recruits on reef surfaces have not
been previously studied, but our predictions for scleractinian corals
are consistent with the few observational studies reporting similar
associations between juvenile corals and exposed habitats of the reef
(Edmunds et al. 2004; Roth & Knowlton 2009; Trapon et al.2013).
The disparity between the distribution of scleractinian corals on
exposed natural substratum observed in our study and reports of higher
settlement and survival within refuges of settlement tiles (Whalanet al. 2015; Gallagher & Doropoulos 2017; Zelli et al.2020) can be attributed to settlement and post-settlement survival being
assessed on settlement tiles in the absence of competitors (Brandlet al. 2014). Including potential competitors in our study
revealed scleractinian recruits have a wider niche breadth compared to
octocorals, spatially overlapping with the latter taxon and potentially
competing for similar microhabitats on the reef. A wider niche breadth
indicates scleractinians can recruit to a broader range of microhabitats
compared to octocorals. We surveyed scleractinian recruits from the
genera Madracis , Siderastrea, Agaricia and Porites ,
which are stress-tolerant and “weedy” species (Aronson et al.2004; Green et al. 2008; Darling et al. 2012; Crameret al. 2021). Whether the realized niche breadth of competitive
and specialized scleractinians, such as Acropora spp. andOrbicella spp. is also broad needs to be quantified. In any case,
among co-existing species, those with the narrower niche, such as the
octocorals in this study, will be more likely to persist if they
outperform those with the wider niche in the locations where they
overlap (Adler et al. 2007). Low-profile and weedy scleractinian
species show low to medium interspecific aggression (Lang 1973; Crameret al. 2021), and some octocorals can use sweeper tentacles
against neighboring scleractinians, and even overgrow them (Sebens &
Miles 1988; Alino et al. 1992). Alternatively, distribution
patterns of octocoral recruits may reflect the outcome of non-transitive
competition against other common taxa within concealed microhabitats.
Macroalgae and fast-growing heterotrophic invertebrates are abundant in
cryptic microhabitats (Jackson 1977; Rützler et al. 2014). In the
Caribbean, low grazing pressure and high levels of eutrophication have
been correlated to an increase in their abundances (Edmunds & Carpenter
2001; Carpenter & Edmunds 2006; Mumby et al. 2006; Idjadiet al. 2010; Davies et al. 2013). We did not include
macroalgae in our analyses, but we found microhabitats in direct contact
with other benthic invertebrates, such as sponges, were less suitable
for scleractinian recruits than for octocorals. Caribbean octocorals can
be effective competitors against sponges (Slattery & Lesser 2021),
whereas sponges can interact with algae to negatively affect
scleractinian corals (González-Rivero et al. 2011). It has been
hypothesized the upright form in octocorallians could be allowing them
to “escape in height” within the microhabitats where heterotrophic
invertebrates are abundant (Meesters et al. 1996; Precodaet al. 2017). Although, intransitive or non-hierarchical
competition could allow species to coexist even without niche
differences (Laird & Schamp 2006). Mechanistic studies to test
non-hierarchical competition during the recruitment of historically
dominant taxa in the region are necessary to gain a better understanding
of its role in shaping reef’s benthic communities.
Importantly, we found microhabitats in direct contact with adult
scleractinians were unsuitable for octocoral recruits, and calcareous
rock was highly suitable. These results provide evidence of competitive
release, and that the decline of scleractinian coral cover is providing
suitable space for octocorals to recruit. Additionally, microhabitats in
direct contact with other invertebrates were suitable for octocoral
recruitment, which indicates this taxon is suited to deal with the high
abundances of macroalgae and heterotrophic invertebrates, characteristic
of contemporary coral reefs in the Caribbean. However, both, the amount
of suitable habitat available for recruits and the median suitability
scores were higher for scleractinians than for octocorals, suggesting
niche dynamics alone are not driving the higher recruit abundances of
octocorals on these reefs. Previous studies have found larval supply as
a major driver of octocoral recruit abundances (Martínez-Quintana &
Lasker 2021). Our results provide further evidence pre-settlement
processes might be driving the differences in the relative abundances
between recruits of these taxa, as well as the different trends the
populations are following on the Caribbean.
The physical 3-dimensional structure of habitats plays a critical role
on species distributions, and influences the function and resilience of
global ecosystems (Ishii et al. 2004; Taniguchi & Tokeshi 2004;
Ferrari et al. 2016). Developments in remote sensing such as, the
Global Ecosystem Dynamics Investigation (GEDI) Lidar (Coyle et
al. 2019), and next-generation optical sensing technologies capable of
imaging without distortion through ocean waves (NASA FluidCam, MiDAR and
NeMO-Net; Chirayath & Li 2019) are collecting geospatial information of
terrestrial and marine ecosystems in 3D at sub-cm resolution. These
data, in combination with methods such as the meshSDM we developed, have
the potential to transform landscape and seascape ecology, improving our
ability to analyze species-habitat relationships, infer ecological
processes and detect changes in habitat structure. On coral reefs,
living coral cover has declined globally by half since the 1950s (Eddyet al. 2021), and the decline has been even more precipitous in
the Caribbean (Gardner et al. 2003). While some studies projected
the collapse of reef ecosystems (Pandolfi et al. 2005), other
analyses hypothesize coral reefs will change rather than disappear
completely (Hughes et al. 2003; Pandolfi et al. 2011). In
this latter view, variability in physiological responses to temperature,
acidification, and nutrients; and rates to adaptation to rapid warming
will drive spatial heterogeneity on the degradation of coral reefs
(Pandolfi et al . 2011).
Populations maintenance requires
successful recruitment. Understanding recruitment niches of reef species
and the availability of suitable 3D microhabitats is equally important
to project coral reef futures. The meshSDM approach we have used is not
limited to recruitment studies alone. Ultimately, the method has
implications for the long-term conservation of structurally complex
ecosystems where species use 3D stratified habitats, such as forest
canopies, roots systems, caves, mesas and canyons.
ACKNOWLEDGEMENTS
We thank the staff of the University of the Virgin Islands, Virgin
Islands Environmental Resource Station, for their logistical support in
the field. Special thanks to Jacqueline Krawiecki, for providing help
and support during the field work and data collection. Thanks to Peter
J. Edmunds (California State University Northridge) for the logistics in
the field, and to Mary Alice Coffroth for providing insightful and
helpful comments throughout the project. In addition, special thanks to
Stuart A. Sandin, Clinton Edwards and Nicole Pedersen (Scripps
Institution of Oceanography) for teaching Ángela Martínez-Quintana
Structure from Motion photogrammetry during the earliest stages of the
project.
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FIGURE CAPTIONS
Figure 1: Digital reproduction of
a 0.25 m2 area at Grootpan Bay in the US Virgin
Islands comparing the profile of the reefscape generated with 3D data (A
and C) versus 2.5D (B and D). The two panels on the left (A and
B) the top view of the reef in 3D, and the digital elevation model (DEM)
of the same quadrat in 2.5D, respectively. Panels C and D represent
crossed sections of that area highlighted in white on A and B. The reef
profile on panel C is more complex than the one calculated with a DEM in
2.5D (panel D). Note that the vertical and overhanging areas in panel C
are detected in the 3D model (C) and are available to study the
distribution of species and microhabitats, while areas overlooked in the
2.5D representation and are not available (D)..
Figure 2: A) Map illustrating the location of the study sites. B) A
panoramic photograph of Grootpan Bay showing the benthic community of
shallow fringing reefs in the area. C) A 3D model of a small area of the
reef generated with SfM with stylized representations of where recruits
can be located. Pictures of recruits of different sizes and genera are
highlighted in brown for scleractinian corals and in blue for
octocorals.
Figure 3: Stacked histograms
showing the relative importance of the environmental predictors used to
characterize suitable habitat for recruits (A and C), and marginal
response curves (B and D) showing the predicted probability of suitable
habitat (logistic, blue line), as a function of each environmental
predictor, while all other variables are set to their mean. The
responses curves in panels B and D are ordered from the most important
predictor to the least. Panels A and B refer to octocoral recruits, and
panels C and D to scleractinians. Grey dashed lines show the
distribution of values of each environmental predictor on the reef
(background data) whereas orange dashed lines depict the distribution of
those variables within an area of 1 cm wide around the recruits
(presence data). Roughness and TEI are expressed in meters, whereas
Slope is expressed in degrees.
Figure 4: A and B) Images showing
top and front views, respectively, of a 50 x 50 cm area reconstructed
with SfM in Europa Bay and overlaid with natural color (RGB). From C to
F, top and front views of the SDM projected onto the polygonal mesh
derived from SfM. Colors represent the estimated probability of suitable
habitat for octocoral (C and D) and scleractinian recruits (E and F).
Suitability scores range from unsuitable (value = 0, in black) to highly
suitable (value = 1, in yellow).
Figure 5: Results of the identity
(A) and background tests (B) in geographic and environmental spaces.
Dashed lines indicate Schoener’s D , Warren’s I and
Spearman’s rank correlation values (rho) calculated from the
empirical models generated with the recruit data. The histograms
represent the distribution of D and I calculated from 100
null models. In geographic space, both metrics were significantly lower
than expected by chance. Whereas only Warren’s I and rhowere significant in environmental space. These results indicate
microhabitats suitable for each taxon were very similar, but not
identical (Figure 5A; p ≤ 0.05).
Figure 6: Violin plots showing the
distribution of suitability scores for scleractinian corals and
octocorals at our sites. The violin plots show the kernel density trace
of smoothed histograms to describe the distribution pattern of the data
and are overlaid with boxplots. Microhabitats suitable for scleractinian
recruits were more abundant and had higher suitability scores than those
calculated for octocorals (Mann-Whitney U test W= 6.6159e+13, p
< 0.01).
RICH MEDIA CAPTION
Video 1: Recording showing the rotation of the SDM projected onto the
polygonal mesh derived from a 50 x 50 cm area reconstructed with SfM in
Europa Bay (i.e., figure 4C and 4D). Colors represent the estimated
probability of suitable habitat for octocoral recruits. Suitability
scores range from unsuitable (value = 0, in black) to highly suitable
(value = 1, in yellow).