Variability in Symbiont Chlorophyll of Hawaiian Corals from Field and Airborne Spectroscopy

: Corals are habitat-forming organisms on tropical and sub-tropical reefs, often displaying diverse phenotypic behaviors that challenge field-based monitoring and assessment efforts. Symbiont chlorophyll (Chl) is a long-recognized indicator of intra-and inter-specific variation in coral’s response to environmental variability and stress, but the quantitative Chl assessment of corals at the reef scale continues to prove challenging. We integrated field, airborne, and laboratory techniques to test and apply the use of reflectance spectroscopy for in situ and reef-scale estimation of Chl a and Chl c2 concentrations in a shallow reef environment of K¯ane‘ohe Bay, O‘ahu. High-fidelity spectral signatures (420–660 nm) derived from field and airborne spectroscopy quantified Chl a and Chl c2 concentrations with demonstrable precision and accuracy. Airborne imaging spectroscopy revealed a 10-fold range of Chl concentrations across the reef ecosystem. We discovered a differential pattern of Chl a and Chl c2 use in symbiont algae in coexisting corals indicative of a physiological response to decreasing light levels with increasing water depth. The depth-dependent ratio of Chl c2:a indicated the presence of two distinct light-driven habitats spanning just 5 m of water depth range. Our findings provide a pathway for further study of coral pigment responses to environmental conditions using field and high-resolution airborne imaging spectroscopy.


Introduction
Corals are foundational reef-building organisms that are in decline globally due to climate change, pollution, and overfishing [1,2].These declines have spurred an explosive growth of effort to monitor coral change over time [3].Spatial extent and bleaching are two commonly reported metrics of coral condition [4,5], but local variability between coral colonies renders field-based methods prone to enormous spatial uncertainties [6], making estimates of coral change difficult to report at the reef level.Beyond spatial extent, a lack of colony-level monitoring over broad areas limits our ability to quantify the range of coral phenotypic responses to external stress [7].This subsequently impedes our understanding of the coral genotypic diversity needed to predict reef-level changes in coral communities, our ability to strategize for the selection of climate-tolerant corals for propagation and restoration, and our efforts to pursue new conservation approaches based on environmentally relevant traits [8][9][10].
Whether in situ on reefs or ex situ in laboratory experiments, coral response to stress is readily observed as change in the algal symbiont community, which fixes carbon for coral growth [11,12].Because the symbionts house the light-capturing apparatus that includes chlorophyll (Chl), changes in coral color are a well-known visual expression of the dynamic, convolved effect of changing symbiont density and their in vivo pigment concentrations.Field-based monitoring of coral color is usually relegated to qualitative approaches such Remote Sens. 2024, 16, 732 2 of 14 as diver-based color cards [13,14].This works well for determining major changes in symbiont presence, such as during coral bleaching surveys [15].However, despite efforts to standardize such visual colorimetric methods, there remains a need for increasingly quantitative, physiologically based approaches to support reef research and conservation applications [16].This is particularly pressing at the ecosystem level, where the full range of coral responses to external stresses occur but are rarely quantified [17].
Remote sensing of coral symbiont pigments has been demonstrated in several study systems [18][19][20].From a field-based perspective, spectral measurements of individual coral colonies have yielded demonstrably accurate estimates of Chl concentration [Chl], often in areal units of µg cm −2 as employed in this paper.In situ spectral measurements utilize handheld spectrometers in underwater housings, illuminating corals with either ambient or artificial light, to collect reflectance data in the 400-680 nm wavelength range [21].These data are then used with a subset of harvested corals to calibrate and validate relationships with [Chl], and other pigment concentrations, determined via lab-based wet chemical assays [22,23].
Despite the known accuracy of in situ colony-scale [Chl] estimates using spectrometers, the use of spectral reflectance is more uncertain at the ecosystem level, which requires airborne or satellite-based imaging spectrometers [24].Moreover, while the determination of live coral and macroalgal cover in shallow reefs has become operational using airborne imaging spectrometers [25][26][27], the same level of capability has not been achieved in quantifying coral symbiont [Chl].This is, in part, due to spatial resolution (2 to 60 m) limitations of airborne and space-based sensors.However, it is also due to a limited availability of quantitative research determining relationships between in situ field spectroscopic studies and imaging spectroscopy from aircraft or satellite sensors.
We investigated the relationships linking field-based and airborne spectroscopy to laboratory-derived assays of coral symbiont [Chl], for two common coral genera found in shallow Pacific reefs: Montipora and Porites.Using Kāne'ohe Bay, O'ahu, as a model ecosystem, we quantified [Chl] in and among phenotypically diverse coral colonies of 0.5-2 m in diameter [7,8].This approach provided an opportunity to establish a quantitative relationship between coral symbiont [Chl] and spectral measurements at two scales of measurement: 10 cm in the field and 40 cm from airborne imaging spectroscopy.Findings from this effort build upon previous field-based spectral studies and expand the approach to airborne observational scales as a precursor to further work on more complex reefs in the Pacific region.

Field Sites
The study was conducted in the field and from the air at Kāne'ohe Bay on the island of O'ahu in the State of Hawai'i (Figure 1a).Corals of Kāne'ohe Bay exist on a constellation of very shallow patch reefs situated at depths of <1 to 7 m.The two dominant coral species throughout the bay are Montipora capitata and Porites compressa, comprising more than 90% of the areal extent in the patch reef locations containing live coral cover [7].Each patch reef is also covered by areas of bare sand and macroalgae.
Across seven patch reefs spanning the environmental gradient of Kāne'ohe Bay [28], a total of 147 coral colonies were selected and tagged in the field (Figure 1a), including 48 colonies of Montipora and 99 colonies of Porites.For each tagged coral colony, we collected in situ spectral measurements, tissue samples for laboratory-based [Chl] assays, and airborne spectroscopic measurements (Figure 1b,c).

Field Measurements
For each tagged coral colony, in situ spectral measurements were collected using an underwater spectrometer (Analytical Spectral Devices HH2-Pro, Boulder CO USA) with an underwater halogen light calibrated to the solar spectrum (Keldan Inc., Brugg, Switzerland) operated by two divers.The spectrometer collects spectral radiance measurements in the 400-700 nm range at 1.3 nm full-width at half maximum sampling.We collected three replicate spectra from each coral with the spectrometer fiber cable mounted to the light and placed at a constant distance of 10 cm from the coral colony surface.Immediately prior to each spectral measurement, a reference panel (Spectralon; Labsphere Inc., North Sutton, NH, USA) was used to calibrate each measurement to surface

Field Measurements
For each tagged coral colony, in situ spectral measurements were collected using an underwater spectrometer (Analytical Spectral Devices HH2-Pro, Boulder, CO, USA) with an underwater halogen light calibrated to the solar spectrum (Keldan Inc., Brugg, Switzerland) operated by two divers.The spectrometer collects spectral radiance measurements in the 400-700 nm range at 1.3 nm full-width at half maximum sampling.We collected three replicate spectra from each coral with the spectrometer fiber cable mounted to the light and placed at a constant distance of 10 cm from the coral colony surface.Immediately prior to each spectral measurement, a reference panel (Spectralon; Labsphere Inc., North Sutton, NH, USA) was used to calibrate each measurement to surface reflectance.The reference panel was placed within 5 cm of each coral colony in order to control for water depth, water composition, and variable ambient lighting conditions.Reflectance was calculated as the ratio of the measured spectral radiance from the coral colony and the measured spectral radiance from the calibration panel.The derived reflectance spectra were subsequently resampled to 5 nm resolution to match the airborne imaging spectrometer data.

Laboratory Assays
For each coral colony, we harvested replicate coral branches for subsequent surface area-corrected [Chl] using an acetone extraction from homogenized slurries.Coral branches collected during field surveys were airbrushed using 0.2 µm filtered seawater, and slurry was collected and homogenized for 30 s (Scilogex D-160 Homogenizer, Scilogex Inc., Rocky Hill, CT, USA).A 1 mL aliquot was extracted with acetone following [29], and Chl a and Chl c2 were quantified on a plate reader (SpectraMax M2, Molecular Devices, Sunnyvale, CA, USA) with absorbance read at 650, 663, and 750 nm.Chl a is the main pigment in the photosynthetic apparatus of the zooxanthellae, absorbing solar radiation most efficiently in the blue and red parts of the electromagnetic spectrum [30,31].Chl c2 is an accessory pigment to Chl a, increasing light absorption at a wider range of wavelengths.Concentrations were calculated using the equations of [32]  where A is absorbance and PL = path length in cm.To standardize to surface area, skeletons were dried for 48 h at 60 • C and weighed.Dried skeletons were dipped for 1 s into paraffin wax at 65 • C, allowed to dry, and re-dipped for 1 s [33].Surface area standards (1-20 cm 2 ) were used to derive a standard assay curve (R2 = 0.99) to calculate the surface area of each fragment [7].

Airborne Remote Sensing
We collected airborne high-fidelity visible-to-shortwave imaging spectrometer (VSWIR) data with the Global Airborne Observatory (GAO) [34].The GAO integrates the VSWIR spectrometer with a LiDAR and a 3-channel visible-wavelength 60-megapixel digital camera.During data collection, the aircraft speed was maintained at approximately 105 kts and within 20 m of the nominal planned elevation of 400 m above sea level, yielding a per-pixel resolution of 40 cm.The VSWIR data were collected in 427 wavelength channels between 350 and 2485 nm at 5 nm increments (full-width at half maximum).The highresolution camera data were collected at 4 cm spatial resolution, boresight-aligned with the VSWIR spectrometer [34].This facilitated the visual confirmation of each of the tagged coral colonies in the VSWIR data as selected for the study (Figure 1b,c).
Benthic reflectance and water depth retrieval was accomplished using a modified version of the atmospheric removal method [35,36] applied to the GAO VSWIR data [25].This method uses Bayesian estimation to simultaneously estimate a combination of water properties, water depth, and bottom reflectance.Using the water-leaving reflectance, the benthic reflectance from 400-700 nm and depth were retrieved for each VSWIR pixel.Prior to the application of the derived airborne Partial Least Squares Regression (PLSR) chemometric equations (see Section 2.5) to the GAO imagery, the VSWIR data were preprocessed to classify pixels as live coral, macroalgal, and sand cover fractions using [26,27].Only pixels classified as live coral cover were subsequently analyzed for Chl a and Chl c2 concentration in units of µg cm −2 .

Chemometric Analyses
We used PLSR analysis [37] to develop quantitative chemometric models relating the brightness normalized field and airborne reflectance data to lab-assayed surface areacorrected Chl a and Chl c2 concentrations from coral branches.PLSR is particularly suited for chemometric analyses where the number of input variables is large relative to the number of observations and collinearity among spectral wavelengths is present [38].In addition, it is important to utilize the full suite (shape) of spectral data to quantify the convolved signal derived from the chemical constituents, rather than a band-by-band analysis.For the purpose of PLSR model development and testing, data for lab-assayed Chl a and Chl c2 concentrations with their respective spectra, either field or airborne, were randomly split 70:30 percent for ten replicate models.Each model utilizing 70% of the data (n = 94-111) was constructed using leave-one-out cross-validation.To avoid overfitting, the number of factors used in the PLSR model was determined by minimizing the Prediction Residual Error Sum of Squares (PRESS) statistic [39].The precision and accuracy of each of the ten model replicates and their test results (n = 36-53) were assessed based on the coefficient of determination (R2) and root mean square error (RMSE), respectively, using standard least squares linear regression between the remotely sensed Chl (field or airborne modeled) and lab-assayed Chl values.Final models for Chl a and Chl c2 were generated using all the available data (n = 147).

Field and Airborne Spectroscopy
Field spectroscopic measurements revealed a nearly 15-fold range of reflectance values among coral colonies (Figure 2a).Montipora colonies had up to 40% lower mean spectral reflectance values (depending upon wavelength) relative to Porites colonies.Following brightness normalization to minimize ambient lighting effects [37], the intra-specific spectral variability of the two coral species was greatly reduced but remained distinct from one another (Figure 2b).On average, Porites had higher brightness-normalized reflectance in the 420-570 nm range and lower values in the 570-670 nm range compared to Montipora.
corrected Chl a and Chl c2 concentrations from coral branches.PLSR is particularly suited for chemometric analyses where the number of input variables is large relative to the number of observations and collinearity among spectral wavelengths is present [38].In addition, it is important to utilize the full suite (shape) of spectral data to quantify the convolved signal derived from the chemical constituents, rather than a band-by-band analysis.For the purpose of PLSR model development and testing, data for lab-assayed Chl a and Chl c2 concentrations with their respective spectra, either field or airborne, were randomly split 70:30 percent for ten replicate models.Each model utilizing 70% of the data (n = 94-111) was constructed using leave-one-out cross-validation.To avoid overfitting, the number of factors used in the PLSR model was determined by minimizing the Prediction Residual Error Sum of Squares (PRESS) statistic [39].The precision and accuracy of each of the ten model replicates and their test results (n = 36-53) were assessed based on the coefficient of determination (R2) and root mean square error (RMSE), respectively, using standard least squares linear regression between the remotely sensed Chl (field or airborne modeled) and lab-assayed Chl values.Final models for Chl a and Chl c2 were generated using all the available data (n = 147).

Field and Airborne Spectroscopy
Field spectroscopic measurements revealed a nearly 15-fold range of reflectance values among coral colonies (Figure 2a).Montipora colonies had up to 40% lower mean spectral reflectance values (depending upon wavelength) relative to Porites colonies.Following brightness normalization to minimize ambient lighting effects [37], the intra-specific spectral variability of the two coral species was greatly reduced but remained distinct from one another (Figure 2b).On average, Porites had higher brightness-normalized reflectance in the 420-570 nm range and lower values in the 570-670 nm range compared to Montipora.A very similar set of patterns was found for the airborne spectroscopic measurements of the colocated coral colonies.We found greater variability and higher reflectance among Montipora colonies as compared to Porites colonies (Figure 2c).Following brightness A very similar set of patterns was found for the airborne spectroscopic measurements of the colocated coral colonies.We found greater variability and higher reflectance among Montipora colonies as compared to Porites colonies (Figure 2c).Following brightness normalization, we also found a reduction in intra-specific variability and the same differences in mean reflectance as found with the field-based spectral measurements (Figure 2d).

Chlorophyll Chemistry
Laboratory-based assays of the coral symbiont [Chl] revealed an extremely wide distribution of Chl a (0.47-13.68 µg cm −2 ), and Chl c2 (0.29-4.43 µg cm −2 ), partially resulting from overall lower concentrations in Montipora compared to Porites (Figure 3).Overlap of Chl a and Chl c2 among the two coral genera occurred in less than 5% and 10% of field samples, respectively.These chemical differences broadly tracked the observed spectral separability of these coral genera (Figure 2a,c).
normalization, we also found a reduction in intra-specific variability and the same differences in mean reflectance as found with the field-based spectral measurements (Figure 2d).

Chlorophyll Chemistry
Laboratory-based assays of the coral symbiont [Chl] revealed an extremely wide distribution of Chl a (0.47-13.68 µg cm −2 ), and Chl c2 (0.29-4.43 µg cm −2 ), partially resulting from overall lower concentrations in Montipora compared to Porites (Figure 3).Overlap of Chl a and Chl c2 among the two coral genera occurred in less than 5% and 10% of field samples, respectively.These chemical differences broadly tracked the observed spectral separability of these coral genera (Figure 2a,c).

Spectroscopic Estimation of Chlorophyll in Corals
Field spectroscopy yielded estimates of Chl a and Chl c2 with demonstrably high precision (R2) and accuracy (RMSE) (Figure 4a,b, Table 1).The pronounced separation in these spectrally derived concentration estimates between Montipora and Porites paralleled that of the spectral reflectance (Figure 2) and chemical concentration values (Figure 3).Standardized spectral weightings, derived from the PLSR approach, indicated that the continuous spectrum between 420 nm and 670 nm was required to make the chemical determinations (Figure S1).Whereas some local spectral features emerged with greater importance at around 610 nm, for example, no single reflectance feature proved dominant in the retrieval of Chl a or Chl c2 from the field spectroscopic measurements.
Table 1.Partial least squares regression model results (R2; RMSE; mean standardized % RMSE) for Chl a and Chl c2 derived using field or airborne imaging spectroscopy data.Statistics were generated using ten iterations of randomly selected chlorophyll values from 70% of the data for training (n = 94-111) and 30% for validation (n = 36-53).The resulting number of latent vectors varied between 5 and 15 for models using field spectra and between 8 and 15 for models using airborne spectra.The final model was generated using all the available data (n = 147).

Spectroscopic Estimation of Chlorophyll in Corals
Field spectroscopy yielded estimates of Chl a and Chl c2 with demonstrably high precision (R2) and accuracy (RMSE) (Figure 4a,b, Table 1).The pronounced separation in these spectrally derived concentration estimates between Montipora and Porites paralleled that of the spectral reflectance (Figure 2) and chemical concentration values (Figure 3).Standardized spectral weightings, derived from the PLSR approach, indicated that the continuous spectrum between 420 nm and 670 nm was required to make the chemical determinations (Figure S1).Whereas some local spectral features emerged with greater importance at around 610 nm, for example, no single reflectance feature proved dominant in the retrieval of Chl a or Chl c2 from the field spectroscopic measurements.for Chl a and Chl c2 derived using field or airborne imaging spectroscopy data.Statistics were generated using ten iterations of randomly selected chlorophyll values from 70% of the data for training (n = 94-111) and 30% for validation (n = 36-53).The resulting number of latent vectors varied between 5 and 15 for models using field spectra and between 8 and 15 for models using airborne spectra.The final model was generated using all the available data (n = 147).

R2 RMSE %RMSE
Chl a (µg cm  A similar set of results was derived from the colocated airborne spectroscopic observations (Figure 4c,d).The precision and accuracy of [Chl] estimates rivaled those derived from in situ field spectroscopic estimates (Table 1), and similar to the field-based results, the two coral genera had relatively distinct Chl a and Chl c2 concentrations, with less than 10% overlap in values (Figure 4c,d).

Application to Airborne Imaging Spectroscopy
To visualize and assess spatial patterns of Chl a and Chl c2, we applied the PLSR chemometric calibration equations (from Figures 2d, 3 and S1) to the airborne brightnessnormalized bottom reflectance data over the seven patch reefs (Figure 5).Areas of bare sand and macroalgal cover were masked out prior to quantifying coral symbiont Chl concentrations ([Chl], see Section 2).Spatial [Chl] patterns were highly variable by patch reef, with reefs 1, 4, and 5 harboring narrow bands of coral [Chl] that were visually uniform in A similar set of results was derived from the colocated airborne spectroscopic observations (Figure 4c,d).The precision and accuracy of [Chl] estimates rivaled those derived from in situ field spectroscopic estimates (Table 1), and similar to the field-based results, the two coral genera had relatively distinct Chl a and Chl c2 concentrations, with less than 10% overlap in values (Figure 4c,d).

Application to Airborne Imaging Spectroscopy
To visualize and assess spatial patterns of Chl a and Chl c2, we applied the PLSR chemometric calibration equations (from Figures 2d, 3 and S1) to the airborne brightnessnormalized bottom reflectance data over the seven patch reefs (Figure 5).Areas of bare sand and macroalgal cover were masked out prior to quantifying coral symbiont Chl concentrations ([Chl], see Section 2).Spatial [Chl] patterns were highly variable by patch reef, with reefs 1, 4, and 5 harboring narrow bands of coral [Chl] that were visually uniform in value (Figure 5a-f  Distributions of Chl a and Chl c2 derived from all live coral pixels on each reef fur emphasized the pronounced ecological variability of symbiont pigment concentrat (Figure 6).Chl a concentrations averaged 9 µg cm −2 , with a slightly skewed distributio higher values (Figure 6).Chl c2 averaged 2.3 µg cm −2 with a slightly negative skew (Fig 6 ).Distributions of Chl a and Chl c2 derived from all live coral pixels on each reef further emphasized the pronounced ecological variability of symbiont pigment concentrations (Figure 6).Chl a concentrations averaged 9 µg cm −2 , with a slightly skewed distribution to higher values (Figure 6).Chl c2 averaged 2.3 µg cm −2 with a slightly negative skew (Figure 6).
We quantified Chl a and Chl c2 relative to water depth (Figure 7).Chl a distributions underwent a distinct shift from near normal distribution, with a median value of 8.06 µg cm −2 in the 0-1 m depth range, to a highly skewed median of 9.14 µg cm −2 at depths greater than 5 m (Figure 7a, Table 2).In contrast, we found no pattern of Chl a variation based on patch reef location (Figure S2, Table 2).
We found a similar overall pattern of increasing Chl c2 with increasing water depth, but the relative change was even greater for Chl c2 (49% increase) compared to Chl a (13% increase) (Figure 7b, Table 2).These differential rates of increasing pigment concentration with water depth generated a 44% increase in the Chl c2:a ratio with depth increases from <1 m to >5 m (Figure 7c, Table 2).Finally, on a reef by reef basis, we found no pattern of variation in the distribution of Chl c2 or ratios of Chl c2:a (Figure S2, Table 2).We quantified Chl a and Chl c2 relative to water depth (Figure 7).Chl a distributions underwent a distinct shift from near normal distribution, with a median value of 8.06 µg cm −2 in the 0-1 m depth range, to a highly skewed median of 9.14 µg cm −2 at depths greater than 5 m (Figure 7a, Table 2).In contrast, we found no pattern of Chl a variation based on patch reef location (Figure S2, Table 2).We found a similar overall pattern of increasing Chl c2 with increasing water depth, but the relative change was even greater for Chl c2 (49% increase) compared to Chl a (13% increase) (Figure 7b, Table 2).These differential rates of increasing pigment concentration with water depth generated a 44% increase in the Chl c2:a ratio with depth increases from <1 m to >5 m (Figure 7c, Table 2).Finally, on a reef by reef basis, we found no pattern of variation in the distribution of Chl c2 or ratios of Chl c2:a (Figure S2, Table 2).We quantified Chl a and Chl c2 relative to water depth (Figure 7).Chl a distrib underwent a distinct shift from near normal distribution, with a median value of 8 cm −2 in the 0-1 m depth range, to a highly skewed median of 9.14 µg cm −2 at depths g than 5 m (Figure 7a, Table 2).In contrast, we found no pattern of Chl a variation bas patch reef location (Figure S2, Table 2).We found a similar overall pattern of increasing Chl c2 with increasing water d but the relative change was even greater for Chl c2 (49% increase) compared to Chl a increase) (Figure 7b, Table 2).These differential rates of increasing pigment concent with water depth generated a 44% increase in the Chl c2:a ratio with depth increase <1 m to >5 m (Figure 7c, Table 2).Finally, on a reef by reef basis, we found no patt variation in the distribution of Chl c2 or ratios of Chl c2:a (Figure S2, Table 2).

Discussion
We integrated field, airborne, and laboratory techniques to test and apply the use of reflectance spectroscopy for in situ and airborne estimations of coral Chl a and Chl c2 concentrations in Hawai'i.The results presented here serve as a step to further operationalize the combined use of field and airborne spectroscopy to map and monitor coral chlorophyll concentration variability in space and time at sub-colony (field) to inter-colony (airborne) resolutions.The applications driving our work range from coral health monitoring, including coral phenotypic bleaching response to environmental stress, to coral restoration planning and outplant performance monitoring.Our findings also build upon and agree with previous work presented at the sub-colony scale [18,19,21,40], which we extend to high-resolution airborne imaging spectroscopy.
Our initial findings indicated that both field and airborne spectroscopy can quantify coral [Chl] in a shallow reef environment, such as Kāne'ohe Bay, with demonstrable precision and accuracy.Often, remote sensing achieves good precision by resolving relative differences in a parameter of interest, but rarely is high accuracy also achieved [24,41,42].Calibrated bottom reflectance, combined with full-spectrum chemometric techniques, was key to obtaining scale-independent retrievals of [Chl] at the 10 cm field and 40 cm airborne resolutions (Figure 4).
We note that the continuous reflectance spectrum from 420 to 660 nm was critically important to achieving high precision and accuracy results at the field and airborne levels (Figure S1).No one spectral absorption or scattering feature proved more or less important in the spectral analyses, rather the continuum spectral signature carried the signal of differential coral symbiont chlorophyll concentration [22].This finding is also highly synonymous with similar work on terrestrial plants, suggesting that spectrometers and spectro-chemometric methods, combined with appropriate observational controls, are required [43].On land, observational controls often include masking out structural gaps in vegetation as well as controlling sun-sensor geometry prior to the chemometric analysis of plant canopies [44].On reefs, observational controls must focus on the masking of benthic areas without live coral, such as sand and macroalgal patches [45].Without such controls, the spectral reflectance signature of the benthos is convolved with many features, rendering the retrieval of coral-specific symbiont chemistry an underdetermined spectroscopy problem.For this reason, we masked out sand and macroalgal areas on each patch reef using the method previously presented by Asner et al. [26].
Following the benthic masking process, we used airborne imaging spectroscopy to assess [Chl] variability at the ecosystem scale while maintaining a spatial resolution commensurate with the size of coral colonies found throughout the reef system under study.Doing so revealed new patterns in both Chl a and Chl c2 concentrations at intra-and inter-reef levels (Figure 5).We found a 10-fold range of [Chl] within each patch reef across the bay (Figure S2), suggestive of diverse biotic controls, such as intra-and inter-specific genotypic effects, environmental controls such as light attenuation driven by water depth, and the convolved effects of both types of controls [7].
Despite strong intra-reef variability, the extremely large number of samples derived from airborne spectroscopy revealed systematic increases in Chl a and Chl c2 concentrations with increasing water depth (Figure 7, Table 2).Both occurred over a relatively narrow depth range of 1 to 5 m, with a pronounced step up in concentration at about 3 m depth.However, we also discovered a differential rate and pattern of Chl a and Chl c2 adjustment with depth.The Chl c2:a ratio increased markedly with increasing depth, particularly at 3 m and deeper.Chl a is the primary light harvesting pigment in the zooxanthaelle; Chl c2 is an accessory pigment generated by the symbiont to increase solar energy absorption in lower light environments [31,46,47].Increasing ratios of Chl c2:a are thus indicative of decreasing solar irradiance along a gradient of increasing water depth and the physiological response to this limiting resource.We postulate that the 3 m step increase in Chl c2:a reveals a transition between two distinct physiological regimes in response to light-dependent habitat conditions (sensu [48]).This effect may be due in part to functional diversification of algal symbionts in Montipora capitata, which harbors both Cladocopium and Durusdinium spp. in Kāne'ohe Bay [49].Durusdinium, a highlight specialist symbiont found in shallower depths, strongly influences the metabolic and pigment dynamics in this species [50] and is associated with performance during thermal stress events [51].
Finally, we observed that Chl c2 variability greatly increased, while Chl a variability decreased, with increasing water depth (Figure 7).Decreasing Chl a variability is indicative of the physiological limit to adding more Chl a as solar irradiance decreases with depth.Spectrally, Chl a displays maximum absorption at 440 nm and secondarily at 675 nm [48], and both wavelengths of light are found in abundance in the 0-1 m depth range.At these shallow depths, we observed wide-ranging variability in Chl a concentration across all reefs (Figure 7a).Because 675 nm light is strongly attenuated at depths greater than 3 m [52], the distribution of Chl a values narrowed with increases in depth, becoming largely dependent on the already highly absorptive 440 nm light that penetrates the water column [23].This led to a peak investment of about 12 µg cm −2 beyond the 4 m depth (Figure 7a).In contrast, Chl c2 displays peak absorption at 460 nm, but its absorption efficiency is about 50% lower than the 440 nm light absorption in Chl a [23].Nonetheless, light at 460 nm penetrates the water column similarly to 440 nm light [52].Whereas the investment in Chl c2 is relatively fixed around 2.3 µg cm −2 in the shallowest portion of the reef system, it shifts upward in concentration at depths beyond 3 m (Figure 7b).While we did not attempt to determine the causal mechanisms behind these observed shifts in Chl a and c2, an enhanced view of chlorophyll variability among corals on reefs provides an avenue to factor physiological patterns into research applications ranging from biogeochemistry to genetics.
A limitation of the current study involves our use of very high spatial resolution (40 cm) airborne imaging spectroscopy, which is not available from satellite sensors.While we did not test the retrievability of coral symbiont chlorophyll concentrations at coarser spatial resolutions, we believe that controlling for inter-colony variability in sand and macroalgal cover does provide some leverage to focus spectroscopy on portions of the reef that are dominated by living corals.This may be translatable to satellite-based observations at coarser resolutions, such as 10-30 m, if similar methods that account for scale-dependent filtering can be applied, such as has been achieved by Zeng et al. [53].Future research will test this possibility.Additional opportunities may continue to develop for high spatial resolution imaging spectroscopy of reefs, such as with the advent of drone-based imaging spectrometers [54].

Supplementary Materials:
The following supporting information can be downloaded at https: //www.mdpi.com/article/10.3390/rs16050732/s1, Figure S1: Mean and standard deviation of standardized spectral weighting vectors for Partial Least Squares Regression analyses; Figure S2: Distributions of Chl a, Chl c2, and the ratio of Chl c2:a by patch reef.; Table S1: In situ chlorophyll concentrations, including mean, standard deviation, and in parentheses, minimum and maximum values for all samples combined as well as by species or each patch.

Figure 1 .
Figure 1.(a) Location and sample distribution of 147 coral colonies throughout Kāne'ohe Bay, Oʻahu, included in the field and airborne spectroscopic study of coral symbiont Chl a and Chl c2 concentration.(b) Example zoom image and digital tagging of coral colonies selected for field, airborne and laboratory analyses using the Global Airborne Observatory.(c) Underwater photo of the same colonies shown in panel (b).

Figure 1 .
Figure 1.(a) Location and sample distribution of 147 coral colonies throughout Kāne'ohe Bay, O'ahu, included in the field and airborne spectroscopic study of coral symbiont Chl a and Chl c2 concentration.(b) Example zoom image and digital tagging of coral colonies selected for field, airborne and laboratory analyses using the Global Airborne Observatory.(c) Underwater photo of the same colonies shown in panel (b).

Figure 2 .
Figure 2. (a) Spectral reflectance and (b) brightness-normalized reflectance of coral colonies collected in situ with an underwater spectrometer.(c) Spectral reflectance and (d) brightness-normalized reflectance of the same coral colonies measured using the Global Airborne Observatory Visible to Shortwave Infrared Imaging Spectrometer (VSWIR).Mean spectra for species shown by thick lines in blue for Montipora capitata, red for Porites compress, and black for all spectra combined.

Figure 2 .
Figure 2. (a) Spectral reflectance and (b) brightness-normalized reflectance of coral colonies collected in situ with an underwater spectrometer.(c) Spectral reflectance and (d) brightness-normalized reflectance of the same coral colonies measured using the Global Airborne Observatory Visible to Shortwave Infrared Imaging Spectrometer (VSWIR).Mean spectra for species shown by thick lines in blue for Montipora capitata, red for Porites compress, and black for all spectra combined.

Figure 3 .
Figure 3. Distribution of (a) Chl a and (b) Chl c2 concentrations derived from laboratory assays of Porites compressa (red dots, n = 99) and Montipora capitata (blue dots, n = 48).Box plots indicate means and one standard deviation, and whiskers indicate range.

Figure 3 .
Figure 3. Distribution of (a) Chl a and (b) Chl c2 concentrations derived from laboratory assays of Porites compressa (red dots, n = 99) and Montipora capitata (blue dots, n = 48).Box plots indicate means and one standard deviation, and whiskers indicate range.

Figure 4 .
Figure 4. Linear regression between field spectroscopy-based estimates and laboratory-based assays of (a) Chl a and (b) Chl c2 concentrations.Panels (c,d) are the same but derived from airborne spectroscopy and the same wet chemical assays.Porites compressa (n = 99) colonies are shown in red and Montipora capitata (n = 48) colonies are shown in blue.

Figure 4 .
Figure 4. Linear regression between field spectroscopy-based estimates and laboratory-based assays of (a) Chl a and (b) Chl c2 concentrations.Panels (c,d) are the same but derived from airborne spectroscopy and the same wet chemical assays.Porites compressa (n = 99) colonies are shown in red and Montipora capitata (n = 48) colonies are shown in blue.
).Reefs 13,25,42,and 44 were comprised of more coral cover relative to reefs 1, 4, and 5, and they were spatially heterogeneous in both Chl a and Chl c2 (Figure 5g-r).Reefs 13 and 42 are generally deeper and more variable in depth than the other reefs (>3 m), and thus they contain a wider range of [Chl].value (Figure 5a-f).Reefs 13, 25, 42, and 44 were comprised of more coral cover rela to reefs 1, 4, and 5, and they were spatially heterogeneous in both Chl a and Chl c2 (Fig 5g-r).Reefs 13 and 42 are generally deeper and more variable in depth than the other r (>3 m), and thus they contain a wider range of [Chl].

Figure 5 .
Figure 5. Chl a and Chl c2 concentration estimates in live corals, as well as water depth, der from airborne imaging spectroscopy collected over Kāne'ohe Bay, O'ahu, using the Global Airb Observatory.Black areas are sand and/or macroalgal cover masked prior to coral symbiont Ch timation.The first, second, and third rows of reefs are for Chl a, Chl c2, and water depth, res tively.Each column is organized by reef number (1, 4, 5, 13, 25, 42, and 44), as shown in Figu Lettering is organized by reef number: Reef 1 (a-c), Reefs 4-5 (d-f), Reef 13 (g-i), Reef 25 (j-l), 42 (m-o), and Reef 44 (p-r) for Chl a, Chl c2, and depth, respectively.

Figure 5 .
Figure 5. Chl a and Chl c2 concentration estimates in live corals, as well as water depth, derived from airborne imaging spectroscopy collected over Kāne'ohe Bay, O'ahu, using the Global Airborne Observatory.Black areas are sand and/or macroalgal cover masked prior to coral symbiont Chl estimation.The first, second, and third rows of reefs are for Chl a, Chl c2, and water depth, respectively.Each column is organized by reef number (1, 4, 5, 13, 25, 42, and 44), as shown in Figure 1.Lettering is organized by reef number: Reef 1 (a-c), Reefs 4-5 (d-f), Reef 13 (g-i), Reef 25 (j-l), Reef 42 (m-o), and Reef 44 (p-r) for Chl a, Chl c2, and depth, respectively.

Figure 6 .
Figure 6.Distributions of coral symbiont Chl a and Chl c2 at 40 cm resolution for all patch reefs combined, derived from airborne imaging spectroscopy.

Figure 7 .
Figure 7. Distributions of (a) Chl a, (b) Chl c2, and (c) the ratio of Chl c2:a by water depth for all patch reefs combined, derived from airborne imaging spectroscopy.

Figure 6 .
Figure 6.Distributions of coral symbiont Chl a and Chl c2 at 40 cm resolution for all patch reefs combined, derived from airborne imaging spectroscopy.

Figure 6 .
Figure 6.Distributions of coral symbiont Chl a and Chl c2 at 40 cm resolution for all patc combined, derived from airborne imaging spectroscopy.

Figure 7 .
Figure 7. Distributions of (a) Chl a, (b) Chl c2, and (c) the ratio of Chl c2:a by water depth patch reefs combined, derived from airborne imaging spectroscopy.

Figure 7 .
Figure 7. Distributions of (a) Chl a, (b) Chl c2, and (c) the ratio of Chl c2:a by water depth for all patch reefs combined, derived from airborne imaging spectroscopy.

Table 2 .
Total, depth-dependent, and patch reef-dependent statistics for mapped Chl concentrations, and the ratio of chlorophyll c2:a, including mean, standard deviation (SD), and median.