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Article

Twin Peaks: Interrogating Otolith Pairs to See Whether They Keep Their Stories Straight

by
Clara Lord
1,*,
Sophie Berland
1,
Vincent Haÿ
1,
Kadda Medjoubi
2 and
Philippe Keith
1
1
UMR 8067, Biologie Des Organismes Et Écosystèmes Aquatiques (BOREA), Sorbonne Université, Muséum National d’Histoire Naturelle, Université de Caen Normandie, Université Des Antilles, CNRS, IRD, CP26, 43 Rue Cuvier, 75005 Paris, France
2
Synchrotron SOLEIL, 91192 Saint-Aubin, France
*
Author to whom correspondence should be addressed.
Crystals 2024, 14(8), 705; https://doi.org/10.3390/cryst14080705
Submission received: 11 July 2024 / Revised: 1 August 2024 / Accepted: 2 August 2024 / Published: 4 August 2024
(This article belongs to the Section Mineralogical Crystallography and Biomineralization)
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Abstract

:
To tackle the question of the reliability of otoliths as recorders of individual life events, we compared the information enclosed in otolith pairs: the sagittae pair and the sagitta/lapillus pair. We used the synchrotron XRF scanning imaging method, which enabled the comparison of this information at both global and hyperfine scales. Using otoliths of diadromous pipefish, we compared element incorporation in each pair with a focus on (i) environment and transition between water bodies with strontium (Sr) and heavy metals, (ii) temporal information and age estimation based on sulphur (S) incorporation, and (iii) otolith growth and biomineralization processes with zinc (Zn). Results show that the global information in terms of Sr and heavy metals given by both otoliths of a pair is the same and that any otolith may be used to retrieve such global data. In terms of S-based growth increment counts, the numbers are the same between two otoliths of the same kind, but the sagitta/lapillus pairs show a significant difference. Hyperfine-scale analysis of element distribution reveals that a given otolith is under the control of specific growth mechanisms, which can lead to heterogeneous elemental incorporation. The present results lead us to consider otolith growth dynamics and biomineralization processes in the context of a fluid mosaic perspective.

1. Introduction

Teleost fishes have, in their inner ears, remarkable calcium carbonate structures (CaCO3), called otoliths. There are three pairs: each otolith is lodged in one of the three pouches forming the otolith end organs at the base of each of the three semi-circular canals of the vestibular apparatus [1]. The astericus is found in the lagena, the lapillus in the utricle and the sagitta in the saccule.
Bony fish use otoliths for balance and hearing, but the extent to which each otolith end organ is used for vestibular senses or audition is yet to be determined. There is a mixed function hypothesis that suggests that each otolith end organ serves both purposes to varying degrees [2], but more recent studies suggest that the utricle may be only involved in fish balance by detecting gravitational forces while the saccule and the lagena would detect sounds [3,4]. For bony fish, the otolith end organ represents a morphological and physiological entity composed of a sensory epithelium (macula) overlain by the otolith itself, the contact between both structures being mediated by an acellular matrix called the otolithic membrane [5,6].
Otoliths are not subject to mineral resorption [7]. They grow throughout the life of the fish from the maternally inherited core. Growth is incremental, safekeeping temporal information on fish life. In addition, elements other than CaCO3 are incorporated in each increment, signing for the physiological state of the fish and its environment [7,8]. Because of these properties, the otolith has often been compared to a black box and used to reconstruct life history traits or study fish physiology [9]. The otolith is then the tool used to deduce important information on fish life, be it biological or environmental, information in turn used for fish stock assessment and management, or for conservation purposes [10,11].
Today, recently emerging 2D X-ray imaging methods allow sub-micron resolution, deepening the microchemical analysis of otoliths and bringing new insights into biomineralization processes [12,13,14]. These methodologies in otolith microchemistry applications push forward the stories the “ear stones” can tell. Indeed, these highly precise analyses allowed the understanding of element incorporation and showed an unsuspected heterogeneous distribution, especially for well-studied elements like strontium: this heterogeneity is hypothesized to be under the control of endogenous drivers, which take over mineralization chemistry [14]. That is why the black box paradigm needs to be revised or even confronted. If heterogeneity is present within one otolith, is it also the case between otoliths of a matched pair? Do all otoliths integrate elements in the same way, knowing that they have different shapes, maybe different roles, and are in different areas of the inner ear? These are important questions to address to know whether the information retrieved from one otolith out of the three pairs is reliable and if we can use it with equanimity.
To test these issues, we have made highly precise 2D maps of otolith elements with synchrotron-based scanning X-ray fluorescence 2D mapping. This methodology offers fine-scale precision, at the sub-micron scale (0.5 micron here) and gives 2D maps over the entire meridian section of the otolith down to the core with a quantification of the elements targeted. In the present work, we analysed three otolith pairs: one pair of the same kind, the left and the right sagittae and two pairs of right sagitta vs. right lapillus, from individuals belonging to two pipefish species (Teleostei: Syngnathidae), Microphis brachyurus (Bleeker, 1854) and Microphis nicoleae Haÿ et al., 2023. Both species are found in Pacific Island rivers and have an amphidromous life cycle [12,14]. Adults live in freshwater; after hatching, the juveniles go to the sea, where they spend a variable amount of time before returning to rivers to colonise the adult habitat. We chose amphidromous species, as by focusing on strontium (Sr), we can easily trace the migration between water bodies of different salinities, as Sr incorporation in the otolith is highly dependent on the environmental concentration of Sr. Sr is more abundant in marine environments than in freshwater [15,16]. The focus on Sr in an amphidromous species is a good point of entry for comparison: the return to rivers after the marine phase is visualised on the otolith by a sharp decline in Sr concentration, as seen when mapping the Sr:Ca molar ratio (Sr:Ca) concentrations over cross sections of the otolith. Lord et al. [14] have delimited three concentric zones in the sagittal otoliths of these amphidromous species driven by Sr concentration: the central zone (Z1) corresponds to hatching in freshwater, the second zone (Z2) corresponds to the juvenile marine phase, and the outlying zone (Z3) corresponds to adult life in freshwater. The first comparison to address between otoliths of a matched pair is to assess whether the sharp Sr decline between Z2 and Z3 is equally visible, both in terms of stoichiometry and of the timing of this break with respect to fish age as it enters freshwater to spend its adult life there.
Otolith growth is continuous throughout the life of the fish; they are made of successive discrete layers of CaCO3, crystalline microstructural growth increments. These increments are usually formed on a regular basis, with alternating light zones (L-zones), areas rich in calcium carbonate, and dark zones (D-zones), rich in organic material [7]. Counting the growth increments gives an estimate of fish age or the duration of specific events [9]. Age determination in pipefish is complex, as their otoliths are small and often lack growth marks discernible with classic observation tools. Very few studies have tried to tackle this problem [17]. Recently, Haÿ et al. [12] have developed a synchrotron-based method to chemically count growth increments by highlighting sulphur (S) distribution based on a pattern superimposed on the D-zones. S would have been incorporated into the otolith as a component of the organic matrix, in particular sulphated proteins and proteoglycans, whose role in the biomineralization process has been documented [18].
While increments are deposited, they integrate chemical elements from the surrounding environment. Apart from elements used as environmental tracers (like Sr, barium and manganese), there is very little literature on the incorporation of elements, which trace the growth or physiology of the fish. The most studied trace elements are magnesium (Mg), zinc (Zn), copper (Cu) and phosphorus (P) as they are tracers of growth [19]. To undertake the comparison between otoliths of a pair, we analysed the signals of a series of heavy metals for which the detection is allowed by the method: chromium (Cr), iron (Fe), cobalt (Co), nickel (Ni) and Cu, which are incorporated in minute quantities as part of otolith trace elements. In the present work, the main aim is to compare heavy metal distribution in the pairs; however, the results represent a strong basis for further analysis of their signatures or roles. Zn was also chosen to understand biomineralization processes. Indeed, in many calcifying systems, Zn is reported to be a cofactor for metalloenzymes involved in carbonated biomineralization processes such as carbonic anhydrase, ubiquitously involved in carbon dioxide conversion to bicarbonate ions [20].
We test here the limits of the reliability of results based on the study of one of the six otoliths. Studies usually focus on the sagitta, as it is often the largest otolith, although the lapillus is increasingly used [21]. We will check here whether there are significant differences in element incorporation between otoliths of a matched pair, and, if so, if they can lead to possible misinterpretations of individual life history. To do so, we compare element incorporation in the various otolith pairs at three different levels: (i) environmental tracers (migration between water bodies with Sr; heavy metals), (ii) temporal information with age estimation based on sulphur incorporation and (iii) otolith growth and biomineralization processes (Zn).

2. Materials and Methods

2.1. Sample Preparation

Otoliths were obtained from the Muséum national d’Histoire naturelle (MNHN, Paris, France) collections: fish were collected during field campaigns and authorization was given by the curators to retrieve the otoliths. Freshwater Syngnathidae were sampled from different locations in the Indo-Pacific realm and preserved in 95% ethanol, a preservation medium that has been shown not to hamper microchemical analysis [22]. We used a total of three specimens: one Microphis brachyurus from New Caledonia (right vs. left sagittae), one Microphis brachyurus from French Polynesia (lapillus vs. sagitta) and one Microphis nicoleae from the Solomon Islands (lapillus vs. sagitta). Their standard length was consistent with syngnathids in adulthood (Table 1).
The otoliths, sagittae and lapillus, were removed from the saccules and utricles, respectively, of the inner ear of each sample, thoroughly rinsed with MilliQ water, and kept dry until they were individually embedded in epoxy resin (Araldite 2020, Escil, Chassieu, France). The embedded otolith was halved along the longest transverse axis using a low-speed diamond-bladed saw (Buehler, Leinfelden-Echterdingen, Germany) and ground on carbide silicon abrasive discs of decreasing grain size (Escil, Chassieu, France), to expose a frontal section down to the core. A slice less than 200 µm thick was cut from the suited sample preparation bloc through the same process. The slice (chiefly a cross section through the core area) was checked by light microscopy.
Utmost care was taken to prevent impurity deposition and, especially, metal contamination during the slice preparation and handling at every step of the process up to their positioning on the beam. No other sample preparation was required except for handling and mechanical fixation to avoid movement during the beam time, which was the purpose of resin embedding.

2.2. Synchrotron-Induced X-ray Fluorescence Scanning

The X-ray fluorescence spectrometry (XRF) was performed by scanning the full-size areas of the otolith cross sections at the Nanoscopium Nanoprobe CX3-scanning spectromicroscopy beamline of the Synchrotron Soleil (Saint-Aubin, France). The beamline allows the focusing of a high-energy and coherent X-ray beam from a U18 X-ray source undulator for diffraction and imaging with fine-scale spatial resolution. The incident monochromatic photon beam was set to 17.5 keV energy and focused by a Kirkpatrick–Baez mirror and Fresnel (FZP) lenses, which allowed us to adjust the resolution of the maps from 1 × 1 down to 0.3 × 0.3 (horizontal (H) × vertical (V), µm2) [23].
The sample was mounted on an X and Z translation stage, allowing displacement with a positioning accuracy down to 100 nm and with a travel range of up to 1 cm. Two silicon drift detectors (SDD VITUS H50, KETEK GmbH, Munich, Germany) were mounted at 120° to the incident X-ray beam to measure the X-ray fluorescence emitted by the sample in the range of detection of the beamline, starting from aluminium (Al KL3: 1.48 keV XRF emission energy) and proceeding up to strontium (Sr KL3M1: 14.16 keV XRF emission energy). Spot-by-spot data were collected under continuous scanning by using the available FLYSCAN mode at the beamline [24]. As XRF is a full-spectral technique, the signal is simultaneously collected from all elements that fluoresce under the experimental conditions. Quantitative reconstruction of the data was conducted by an in-house process of raw data optimization by reducing the noise, removing artefact signals and measuring the discrete energy intensities of the target elements.
Energy calibration, a crucial step for element identification, was performed in a standard way from each data detector separately by selecting at least two known X-ray lines [25] and specifying the energy confidence limits allowed to contain the characteristic XRF emission energy for each element. Then, each element derivation of the XRF spectrum was obtained by summing the energy signals from all the channels over which the characteristic peak of the element extends. All the samples were subjected to the same beam conditions, with a spot size of 0.5 µm and a dwell time of 40 ms, ensuring robustness in the quantitative analysis of the otolith pairs. The large amount of output data consisted of a set of 2D elemental distributions encoded in Tag Image File Format (.TIF) used during the beamtime to guide the experiment and a hyperspectral dataset stored in Hierarchical Data Format (HDF) for further analysis after the beamtime.

2.3. Element Distribution Analysis

Each element signal reconstruction was performed on the hyperspectral dataset by integrating on each spectrum per pixel the characteristic peak of the element (the integration interval was defined by the full width at half maximum (FWHM) of the peak). This process, on the HDF file, was done by using Fiji (Fiji Is Just ImageJ) software, the collaborative open-source project with a self-updating capability for scientific image analysis [26]. The slices corresponding to the energy range for such a maximum and a robust signal intensity were selected and summed to make the subsets’ element-specific maps, which can be displayed on purpose as distribution maps.

2.4. Sr:Ca Molar Ratio Processing

Ca and Sr XRF scan data were loaded as images using Fiji software and an open-source image processing software package [27]. Each image (32 bits) was displayed with grey values matching the element’s X-ray signal intensity by assigning the black colour to the pixels with the lowest fluorescence intensity signal and white to the pixel with the highest intensity, and then scaling the in-between intensities accordingly. The encoded pixel value still recalls the actual energy intensity figures in any of the calculations made by image processing, provided the high dynamic range (32 bits in a TIFF image) was maintained. Sr:Ca 2D rasters were obtained through the “divide function” of the “image calculator” package. This tool performed the arithmetic operations pixel by pixel between the two “images”.
To retrieve the actual Sr mass fraction in the CaCO3 matrix in each sample, a calibration process was performed with PyMca stand-alone open-source software (version 5.9.2; Grenoble, France), institutionally supported and updated by the European Synchrotron Radiation Facility (ESRF) for spectral analysis [28,29,30], by using the experiment parameters. The corrected mass fraction was then translated to a molar fraction of Sr:Ca for all the acquisitions. The Sr:Ca molar ratio colour maps were displayed by assigning a colour to the existing pixel’s grey value with colour allocation at the pixel size ranked on the molar ratio value using the look-up table transformation tool of Fiji software. On the other hand, the maps were exported as Sr:Ca molar ratio intensity datasets (values on the z-axis). Computation for the Sr:Ca molar ratio frequency distribution was performed using basic tools of the collaborative open-source R project [31] (R is a free software environment for data computing and graphic production, hereafter named R) (version 4.2.3; Vienna, Austria). Data were processed using the “dplyr” package and the "summarise" function in order to aggregate the Sr:Ca value frequencies. The figures were set up by running the ggplot package geom_area function.

2.5. Trace Elements

The z-values of each sample’s XRF energy signal reconstruction were extracted as .csv files from the hyperspectral dataset using Fiji tools. The characterisation and semi-quantification of elements above the detection limits were obtained by processing the data using PyMca software. The entire samples’ z-values were displayed as the spectrum trace of the XRF signal intensity along the emission energy range in the x-axis. After appropriate calibration of the spectrum with the Ca and Sr peaks, the target element abundance (count) was computed from under the peak area of the fitted curve.
Despite the exposed set of detectable peaks, which enabled us to retrieve the values of each trace metal element separately—namely, chromium (Cr), iron (Fe), cobalt (Co), nickel (Ni) and copper (Cu)—these were quite hampered by neighbour peaks with overlapping bases. Because of this, the quantification output for each element analysed on its own was quite low, and to enhance the visible signal of heavy metal integration in the otoliths, the signals for Cr, Fe, Co, Ni and Cu were stacked on unique distribution maps. Prior to that, the co-location of these heavy metals was checked.
The method allowed for detecting zinc (Zn) and sulphur (S), for which distribution patterns were interpreted for their implications regarding the otolith growth dynamics. Zn distribution maps were made as described above.

2.6. Sulphur and Increment Addressing

The reconstruction of the sulphur XRF emission signal was carried out using the hyperspectral dataset and displayed as a 32-bit image using Fiji software. Transects going from the ground zero-point coordinates (deemed the otolith core) to the most distal edges on both sides of the otolith were drawn (each measure has been replicated with a slight distal offset) and the z-values (signal intensities) were exported with respect to the Cartesian coordinates using the Z-profile tool. Then, the S signal intensity variation along the transect was analysed using R. The S signal intensity trace was searched for the turn points by using the "pastecs" package’s dedicated function, which determines the position and statistics of extrema (turn points) after transforming the data into a time series. Spatialisation was enabled by addressing the Cartesian coordinates to the S signal intensity inflexion points (hereafter named S-peaks), which were interpreted as increment marks, and, therefore, summed for age determination purposes.

3. Results

The position of the sagittae, lapillus and astericus otoliths in the cranium of a Microphis brachyurus specimen and the set of the three pairs of otoliths used in the present work are shown in Figure 1. The sample description is provided in Table 1. RTNC139 is the specimen for which the two sagittae were compared, and the figure shows that the Ca XRF maps exhibit an unsurprisingly uniform distribution. The two sagitta/lapillus pairs showed no specific growth marks on their cross sections when observed by light microscopy, which is unusual for otoliths and justifies the use of spectroscopic methods to uncover biological information. The core was the only visible structure. The results of XRF element mapping presented hereafter aim to test the reliability and repeatability of the information recorded in two otoliths belonging to a given individual by retrieving both global and hyperfine information about elemental integration in the otoliths.

3.1. Global and Hyperfine Sr Integration in the Otoliths

Figure 1 (PFV39) shows that calcium distribution is smooth and uniform. Figure 2 shows a zonal pattern on the Sr:Ca distribution image, indicating that the spatial distribution of the ratio is driven by the Sr variation [12]. For all our samples, whatever the pair, the 2D Sr:Ca (mmol.mol−1) maps show high Sr:Ca during the early life phase and the juvenile growth phase (called Z1 and Z2, respectively, by Lord et al. [14]). There is a clear transition to the lowest Sr:Ca levels in the marginal area of the otolith (called Z3 by Lord et al. [14]), which is visualised on the colour maps by a decrease from beige to blue colours and is consistent with a marine to freshwater transition at the Z2-Z3 limit. Each otolith analysed validates a diadromous life history, with the same global information given by Sr:Ca on both sagittae of M. brachyurus RTNC139 and on both sagittae/lapillus pairs.
Figure 3 shows the frequency distribution of the Sr:Ca molar ratio values computed from each otolith’s complete 2D map. For each of the three pairs, the frequency distributions are superimposed when the Sr:Ca ratio is low, corresponding to a freshwater signal; this shows that the information is the same on both otoliths when considering life in freshwater (Z3). The Sr:Ca cut-off value between marine and freshwater conditions is the same between both otoliths of a pair (Figure 2 and Figure 3): 2 mmol.mol−1 for the sagittae pair RTNC139 (Figure 3a); between 3 and 4 mmol.mol−1 for the PFV39 sagitta/lapillus pair (Figure 3b) and between 2 and 3 mmol.mol−1 for the 18253 sagitta/lapillus pair (Figure 3c). For the early life and juvenile phases (Z1-Z2) (colours purple to beige in Figure 2) considered together, whatever the pair, Sr integration seems different at a hyperfine scale, giving rise to different granular maps from the core of the otolith to the marine/freshwater limit (the sharp decrease between Z2 and Z3). These differences are visualised in Figure 3, as the frequency distributions greater than 4 mmol.mol−1 do not completely overlap. For instance, for the two sagitta/lapillus pairs (Figure 3a,b), the two otoliths show different frequency peaks and the Sr:Ca frequency shows a greater spread of values for the sagittae than for the lapilli. For the pair of sagittae (Figure 3a), the same result is noted, with a greater spread of values for the right sagitta than for the left.

3.2. Sulphur-Based Counting of Growth Increments

Figure 4 gives the number of sulphur peaks, corresponding to growth increments, counted from the core to edge, from the core to the Z2/Z3 limit and, for that of Z3, along the longest radius and shortest radius. Each count has been replicated, and all replicates give approximately the same number of increments, which ensures the robustness of the results (Figure 4). For an easier read, only one count per radius will be exemplified hereafter. For the pair of sagittae (Figure 4A), the total numbers of increments (from the core to the edge) are very similar with, respectively, Left 98/Right 92 for the long radius and Left 67/Right 75 for the short radius. On the long radius, the numbers of increments from the core to the Z2/Z3 cut-off limit are Left 58/Right 61, and they are Left 34/Right 31 for Z3. On the short radius, the numbers of increments from the core to the Z2/Z3 limit are Left 39/Right 52, and Left 32/Right 24 for Z3.
For the sagitta/lapillus pairs, there are noticeable differences between the two otoliths. For instance, for the PFV39 sagitta/lapillus pair (numbers presented in this order) (Figure 4B), the longest radius shows 107/79 increments. The short radius shows 57/51 increments. The differences are mostly due to a greater number of increments for the sagittae than in the lapillus in the early life and marine phase, with 86/62 increments from the core to the marine/freshwater limit (Z1-Z2) on the longest radius and 45/36 on the shortest radius. The numbers of increments are more similar in Z3, with 21/18 on the long radius and 12/12 on the short radius. For the 18253 sagitta/lapillus pair (numbers presented in this order) (Figure 4B), the total numbers of increments are 90/66 on the long radius and 70/63 on the short radius. Similarly to the previous pair, the differences are mostly due to a greater number of increments in the sagittae than in the lapillus in the early life and marine phase, with 50/35 increments from the core to the limit and 40/31 for Z3 on the longest radius. On the short radius, however, the numbers are similar from the core to the limit, with 28/29 increments, and Z3 shows 42/34 increments.

3.3. Trace Element Distribution

The z-values of each otolith’s entire cross section are shown as the spectrum trace of the XRF signal intensity along the emission energy range in the x-axis (Figure 5). The peak position of each displayed element is given in the corresponding table. Eight peaks are labelled on the spectrum (Ca, Cr, Fe-Co, Ni, Cu, Zn), and the target element abundance (count) was computed from under the peak area of the fitted curve. The broad peaks at 3.69 keV and 14.16 keV are characteristic X-ray emissions from Ca and Sr, respectively. The XRF peak intensities that allowed the identification of the other elements are presented on the spectrum at the top of the figure. The individual spectra of the otolith samples are displayed by pairs and show that the traces are superimposed. The characteristic element peak position for each otolith is given in the table below each graph. For each pair, the spectrum is represented on the same graph to visualise whether both otoliths had overlapping global information. For each of the three pairs, the spectra completely overlap, with a very close peak summit position for each element considered, so the global information is the same for both otoliths in each comparison.
The overlapping bases of iron (Fe), cobalt (Co) and nickel (Ni) peaks hamper the robust mapping of each single element. But each heavy metal was mapped individually to visualise its localisation in each otolith, and they were co-localised, enabling us to stack the information for Cr, Fe-Co, Ni and Cu on a unique map (Figure 6). For the RTNC139 sagitta/sagitta pair, heavy metals seem to be scattered in the entire otolith, with, however, a higher concentration in Z3, but only in the area corresponding to the longest radius. This phenomenon is the same in both otoliths. For both sagitta/lapillus pairs, heavy metals are also co-localised only on one side of the otoliths, mainly in the freshwater adult phase, as the highest concentration appears after the marine/freshwater limit. This information is identical for both otoliths, whatever the pair considered. This result of the highly heterogeneous integration of heavy metals highlights the importance of complete 2D mapping as it reveals interesting element incorporation dynamics.
Maps of the cumulated X-ray emissions of Zn (Figure 7) show a scattered signal in the entire otolith, whatever the pair considered. A higher intensity of the signal may be noted on the edge. This observation is also repeated on both otoliths of each pair.

4. Discussion

Otoliths were compared at different scales: the global information contained over the entire surface of the otolith section, the number of increments, and the integration of various elements at a hyperfine scale made available by the synchrotron XRF methodology.

4.1. Sr/Ca Global Maps

Tropical island streams are colonised by amphidromous species, which migrate between freshwater and marine water during their life cycle. The amphidromous life cycle is considered an adaptation to the colonisation of island rivers, which are fragmented and subject to extreme climatic and hydrological variations [32]. The marine phase ensures species sustainability in these labile habitats. Results of recent research have validated the amphidromous life cycle of M. brachyurus and M. nicoleae [12,14] with synchrotron Sr XRF mapping, and Lord et al. [14] defined three concentric zones in the otoliths from the core to the edge. The central Z1 growing from the core corresponds to the early life stages in freshwater, but it often barely signals a freshwater environment. This could be because these species migrate to estuarine regions so that their eggs can hatch close to the marine environment [33]. In Z2, nevertheless, the global Sr:Ca information is of a high concentration (from 4 to 14 mmol.mol−1), in accordance with the signature of a marine environment, but the integration in the otolith of Sr at a hyperfine scale shows granularity. The heterogeneous integration of Sr in this fast-growing phase is thought to be disrupted by growth and ontogenetic processes, leading to this patchy distribution [14]. The return to freshwater corresponds to a rapid and important decrease in Sr:Ca in the otolith, and there is a clear cut-off limit between Z2 and the adult freshwater Z3.
The global information contained in the sagittae pair was the same in terms of transitions between water bodies of different salinity. The drastic decrease in [Sr] marking the return to freshwater after the marine phase was recorded at 2 mmol.mol−1 in both otoliths. The results are the same for the two sagitta/lapillus pairs, with a cut-off limit at 3–4 mmol.mol−1 for PFV39 and at 2–3 mmol.mol−1 for 18253 (Figure 2 and Figure 3). The information contained in Z3 is also the same in each pair, as Figure 3 shows, with an overlap of the frequency distribution of the Sr:Ca molar ratio values. These results are consistent with the general knowledge on Sr otolith incorporation: the environmental [Sr] mainly drives its integration in the otoliths [19,34]. But in addition to the trivial Sr incorporation driven by environmental ionic conditions, there is an unusual granular arrangement of Sr distribution in Z2. In the present paper, we show that this granularity and patchy distribution of Sr:Ca is different between otoliths of a pair, underlining the existence of unknown influences on the growth dynamics of an otolith. Otoliths are surrounded by endolymphatic fluid in which elements occur before being integrated into the mineral matrix [35]. Otoliths, therefore, have access to these elements, but their integration in each otolith must result in specific and localised mechanisms during the biomineralization process, leading to these slight differences between otoliths of a matched pair. We propose to consider the otolith as a mosaic where the elements are housed according to the concordance of driving forces, which include the principles of the physics and chemistry of mineralized systems. On top of these purely mechanistic processes, the biological control over element integration—especially growth during early life stages—may overrule stoichiometry. The physiological state in which the fish is at this early growth stage may influence the incorporation of Sr in the otoliths [14,36,37].

4.2. Sulphur Peaks

S is correlated with D-zones (areas rich in organic material) and is incorporated in the otolith as a component of the organic matrix [38]. Higher S concentrations in D-zones are probably mostly associated with proteins and sulphated proteoglycans [39,40], and we have demonstrated the effectiveness of counting growth increments by means of sulphur pace (S-peaks) [12]. Here, we compared the number of S-peaks in both otoliths of each pair. The total count of S-peaks from the core to the edge for the pair of sagittae is identical, both on the long and short radiuses (c. 90 on the long radius and c. 70 on the short radius) (Figure 4A). The comparison of two sagittae of the same individual corresponds to having a replicate of the experiment using the XRF mapping method, and our result validates this. It also validates that left or right sagittae may be used randomly to retrieve age information. By using diadromous organisms, we were able to compare the timing of the return to freshwater on both otoliths. The number of S-peaks from the core to the Z2/Z3 cut-off limit on the long radius is also the same for both sagittae (RTNC139 specimen), with a return to freshwater at around 60 increments after birth. The Z3 zone, from the cut-off limit to the edge, counts the same number of increments in both otoliths, with c. 34 S-peaks. On the short radius, however, although the total number of S-peaks is the same (c. 70), the timing of the laps to the cut-off limit is different (39/50 S-peaks), as is the S-peak count in Z3 (31/23). On the short radius, the information is, thus, different between both otoliths when looking at precise events like the return to freshwater. Many studies show that increments usually appear daily [41,42]. It has been validated for two species of pipefish, Stigmatopora argus (Richardson, 1978) and S. nigra Kaup, 1856: for both species, increments were deposited daily [17]. So, when it comes to age determination, the long radius would suggest the fish is around 90 days old, while the short radius would give it 20 days fewer. Due to the repeatability of the information from the long radius (identical timing of the return to freshwater), we would suggest that counting growth increments on the long radius seems to be more accurate. Although the total number of increments is the same on the short radiuses of both sagittae, there is a certain variability in the information contained within this growth direction, suggesting otolith-specific growth dynamics, as already seen for Sr. The lower number of increments on the short radius, or the difference in their organisation compared to the long radius, probably also has an impact on element distribution in the otolith, supporting our results finding a labile Sr integration in the mineral lattice. The fewer number of S-peaks on the short radius does not necessarily mean that there are fewer increments. We cannot rule out a resolution limitation, and we may be beyond the threshold. Here, the hyperfine resolution offered by the method allows noting S-peaks that are tightly set at the microscale, but closely neighbouring increments may be mistaken for only one. We worked on each otolith with the same definition, so we can make a truthful comparison from the dataset. This is also supported by the close features obtained for the sagittae analysed in the three individuals of putative similar age as they are similar in length (Table 1): we found between 90 and 107 total increments on the long radiuses (Figure 4A,B).
When comparing the sagitta and lapillus, the total number of S-peaks, whatever the radius, is always greater for the sagitta than for the lapillus. The difference in the number of increments is greater during the juvenile phase than during the adult phase after the return to freshwater. Both otoliths are usually a similar size at formation, but there are studies that show that the sagitta grows faster, quickly outgrowing the lapillus, during the juvenile phase [9,21,43]. This results in a distinct size difference during the early life phase [44,45]. Some studies report the existence of sub-daily increments that may appear on the sagitta, which can cause an overestimation of age, whereas this seems not to occur in lapilli [44]. In a few studies comparing age determination with sagittae and lapilli, the lapillus is considered more reliable for age estimation, especially during the larval and juvenile stages [44,46]. The ontogenetic development from the circular, larval otolith to the oblong adult otolith is known for a wide range of species [47]. The shapes of sagittae and lapilli are quite different, with a more elongated shape for sagittae and a more rounded shape for lapilli. Both genetic and environmental factors have an influence on the determination of the shape of the otolith [48]. The rate of the shape change is high, probably because the shape of the otolith is linked to its role in hearing and/or balance; so, the morpho-functional change takes place early in life [49]. Severe changes in otolith morphology during ontogeny render otolith increments inconsistent proxies for daily somatic growth through habitats [50]. The fact that diadromous pipefish undergo two environmental shifts during their life phases (larval and juvenile) may also have consequences on the supposedly daily increment formation.
In the present case, we note a difference in the number of growth increments between the sagitta and the lapillus, a difference which has been noted by previous authors.

4.3. Trace Element Incorporation

Heavy metal incorporation in otoliths has mainly been used to assess environmental pollution [51,52]. Studies examining the occurrence of heavy metals in the otoliths have mainly assessed their use as tracers of water quality, with a few examples in the context of mining activities [53]. Otoliths have also been considered as bioaccumulation structures, but results show that high environmental concentrations of a given element are not necessarily reflected in the otoliths [54]. For calcified organisms other than fish, like corals or foraminifera, the composition of the external skeleton tends to reflect the composition of the ambient water [7]. The accumulation of trace metals in otoliths is also influenced by water chemistry, but it is also linked to diet, bioavailability, physiological affinity of calcium carbonate for different metals and exposure time, in addition to endogenous factors which remain to be understood [7,14,19,55]. The pathway of any given element or ion from the environment into the otolith is highly regulated, more than in any other calcified structure. For instance, bone [56] and scale [57] contain higher concentrations of most elements than do otoliths. The elements pass through various barriers [7] from the environment to the mineral lattice (gut or gill membrane, blood plasma, endolymph). Ion concentrations can then be altered across each interface, and these ions can also be made unavailable by protein-binding processes and re-distributed in the body via plasma transport [19]. Heavy metals are in such minute quantities in the otoliths that otoliths are usually analysed as a solution of dried otoliths [51,52], or with 1D transect methods from the core to the edge or along the edge of the otolith [58]. Heavy metal location in the entire otolith has never been examined. The number of heavy metals studied is also limited and usually concerns Cu, Ni or lead (Pb), e.g., [59,60,61,62]. Fe appears on rare occasions [60,63,64], as well as Co [7,52]. Additionally, most of these studies focus on larvae or juveniles. XRF mapping allowed us to visualise heavy metal incorporation in three pairs of otoliths. Because heavy metals are incorporated in such low concentrations, we stacked maps of Cr, Fe, Co, Ni and Cu to enhance the signal, with each individual signal being checked prior to the stacking. Indeed, each heavy metal map taken separately showed that these four heavy metals were co-localised in the otolith. For the pair of sagittae, the global XRF signals mainly overlap, although the right sagitta seems to have slightly higher counts as the curve is slightly above that of the left sagitta (Figure 5). But the peak positions are the same on both otoliths, once again demonstrating the repeatability and reliability of the XRF method. Concerning the maps, the heavy metal signal is scattered on the entire surface of the otolith, with a higher intensity for the right otolith explaining the slightly higher curve in Figure 5. Although the signal is scattered, one side of the otolith appears to be more concentrated, and this is true for both otoliths of the pair. The higher concentration is located after the marine/freshwater cut-off point, with a higher incorporation of Cr, Fe-Co, Ni and Cu during the adult phase when the fish is in freshwater. The repeatability of the information from both otoliths shows once again that both right and left sagittae can be used as they give the same information. The same results were obtained for the two sagitta/lapillus pairs. The XRF signals completely overlap (Figure 5), showing that the global concentration of heavy metals is the same. For both otoliths, there is also an asymmetric incorporation, with one side of the otolith that is more concentrated in heavy metals than the other, where the signal is non-existent. This higher concentration is also in the adult freshwater phase, after the fish has returned to freshwater. The asymmetrical incorporation shows that 2D mapping techniques allow the extraction of localisation information, whereas 1D methods would overlook this information. The heterogeneous incorporation of heavy metals shows that the intake of metallic ions and their capture in the biomineral lattice is governed by several constraints of otolith growth dynamics. Most studies on heavy metal incorporation focus on marine fish; when these are compared to studies on freshwater fish, it usually shows that heavy metal concentrations in their otoliths are lower than in marine fish otoliths [7]. The results we obtained for the three pairs of pipefish otoliths are, therefore, quite surprising because the higher concentrations of heavy metals are found in an area deposited during the adult freshwater phase, but insular rivers flow on a quite specific metal-rich volcanic substrate [65]. The hyperfine-scale mapping of elements offered by XRF methods is promising for the study of environmental markers and the trending processes of heavy metal distribution arrangements.

4.4. Cues from Specific Location and Concentration Patterns of Trace Metal Elements

The information contained in the otoliths must be studied by unravelling the information enclosed at imbricated scales. With the hyperfine-scale mapping of elements in each otolith, we observed element patchiness and differences between both otoliths of a pair, although the global information was mainly the same. The mechanisms that lead to these observations are yet to be clarified, although we can propose, hereafter, food for thought from the present results.

4.4.1. Zinc Incorporation

Zinc peaks for each pair are in the same position and overlap (Figure 5). Maps show the same results for the three pairs of otoliths studied. The Zn signal is scattered on the entire otolith map and shows a homogeneous distribution, unlike the rest of the heavy metals studied. Zn, although evenly distributed in the entire otolith, shows areas of higher concentration on the edge of the otolith. This higher Zn signal on some parts of the edge is otolith-specific, i.e., it is not necessarily the same on both otoliths of a matched pair. This Zn concentration on the otolith edge likely reflects undocumented biomineralization mechanisms, which influence the growth and element integration of each otolith, specifically at a microscale. The mapping of Zn allowed us to propose a hypothesis as to the hyperfine-scale differences observed between two otoliths of a pair, regarding what may have led to the otolith’s element patchiness.

4.4.2. Zinc as a Proxy of Biomineralization Processes

Zn would seem to be involved in the biomineralization process of otoliths. Zn is bound to proteins involved in the calcification process of the otolith [58]. Carbonic anhydrases (CAs) are ubiquitous metalloenzymes with a Zn cofactor that catalyses the hydration of carbon dioxide into bicarbonate. Among numerous roles in physiological processes, carbonic anhydrases play an important role in biomineralization, as documented in many marine prokaryotic and eukaryotic calcifying organisms [20,66]. CAs are involved in the inorganic carbon supply for calcification and/or the regulation of pH at the calcification site [67]. The high concentration of Zn observed in the organic lining covering the outer surface in the foraminifera test suggests a possible localisation of the CAs associated with this lining, which could be a transmembrane or membrane-associated form [20]. The existence and localisation of CAs in otoliths remain to be investigated but CAs could be in the gelatinous membrane or macula, surrounding the otolith and endolymph.

4.4.3. Zinc Localisation and Otolith Element Patchiness

The higher concentration of Zn on the very edge of the otoliths may be a visualisation of biomineralization processes taking place: the otolith is under active biomineralization, with Zn as a cofactor of biomineralization proteins clearly visible on the edge of the otolith. XRF fine-scale mapping, however, shows that the biomineralization process is not equally undertaken at the entire periphery of the otoliths in zones with higher Zn-related activity spots. Increments would then be “constructed” little by little around the otolith rather than simultaneously formed. One can then understand at the microscale and nano-scale the heterogeneous incorporation of all other elements in the increments, leading to a patchy distribution, as seen on the Sr and heavy metal maps (Figure 2 and Figure 6). The otolith will uptake and incorporate the available element in the endolymphatic fluid at the precise site of biomineralization, where the activity is highest, as seen on Zn maps, i.e., when Zn is in higher concentrations. XRF hyperfine-scale mapping unravels, here, specific growth and biomineralization mechanisms of a given otolith. It has been shown that the distribution of the various compounds found in the endolymph is not uniform [68,69] and that the endolymph composition undergoes daily variations [39]; elements probably move and fluctuate in the fluid, and their incorporation in each increment will depend on their accumulation with high biomineralization activity. For elements in high concentrations, like Sr (in a marine environment), they will be incorporated on the entire increment, although with micro-variations in the concentration (this paper and [14]).

4.4.4. Integrated Chemical and Biological Processes

The presence of Zn inside growth increments may be linked to its concentration in the environment, and not only as it is regulated by the physiology of the fish [58]. The relative concentration of trace elements such as Sr, Zn, Pb, Mn, Ba and Fe in freshwater and marine otoliths is consistent with an environmental effect [7]. So, part of the Zn in high concentration on the edge is likely to be incorporated into the otolith, and part of it is adsorbed to fulfil its role in the biomineralization process. Conversely, part of it may remain available at the interface with the macula. The main Zn information contained in the otoliths is, therefore, the same between the otoliths of each pair, with a Zn signal scattered in the entire otolith and heterogeneous biomineralization activity on the edge. A closer look at the hyperfine maps reveals that growth dynamics are specific to each otolith [14].

5. Conclusions

Biomineralization leads to the formation of inorganic crystals with unique, ordered, refined shapes that are regulated by specific macromolecules [40], but specific growth dynamics at the microscale may lead to heterogenous element distribution within the otolith itself, and even to slight differences between two otoliths of the same individual. XRF elemental analysis provides the possibility to study the composition of an otolith on its entire surface, even for elements in minute quantities, in addition to the localisation of these elements. Studying otolith pairs is a means to test both the robustness of the method and the reliability of the information given by the otoliths when studying the biology of fish. Our results show that the global information in terms of Sr and heavy metals given by both otoliths of a matched pair (sagittae or sagitta/lapillus) is the same, and that any otolith may be used to retrieve such global data. In terms of growth increment counts, the numbers are the same between two sagittae, but there is a significant difference between the sagitta and the lapillus, with a lower number for the lapillus, probably because of a developmental desynchrony between the two otolith types and because of a different otolith morphology linked to its biological role. Finally, hyperfine-scale analysis of Sr, S, heavy metals (Cr, Fe-Co, Ni, Cu) and Zn shows that each otolith is under the control of specific growth mechanisms, which lead to micro and nano-scale heterogeneous element incorporation. Zn has a specific behaviour and acts as a biomineralization initiator, and the increment formation seems to occur gradually and not simultaneously around the otolith. This formation, such as a crystallising liquid gradually surrounding the otolith, will incorporate elements in the mineral. The uneven distribution of elements in the endolymph and the gradual formation of increments lead to the hyperfine heterogeneous element distribution in the otolith. This paper encompasses a descriptive comparison of otolith pairs; it leads us to address the understanding of the biomineralization and growth dynamics of otoliths in the context of a fluid mosaic perspective.

Author Contributions

Conceptualization, C.L., S.B. and P.K.; methodology, S.B. and K.M.; investigation, V.H. and S.B.; writing—original draft preparation, C.L. and S.B.; writing—review and editing, C.L., S.B. and P.K.; supervision, P.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

Data available at https://data.indores.fr/dataset.xhtml?persistentId=doi:10.48579/PRO/DFWN6T, accessed on 5 July 2024.

Acknowledgments

We acknowledge SOLEIL for the provision of synchrotron radiation facilities, and we would like to thank K. Medjoubi and A. Somogyi for their assistance in using beamline “NANOSCOPIUM” and monitoring Proposals 20191306 and 20210141. The authors would like to acknowledge assistance from their colleagues and the support groups of Soleil for their contributions, continuous help, and outstanding technical support. Data were obtained on the Nanoscopium beamline. For these, special thanks go to the beamline crew, K. Medjoubi and A. Somogyi, for their advice and constructive suggestions. For French Polynesia, we would like to thank V. Mazel (Ichtyo-Pacific). For the Solomon Islands, we would like to thank D. Boseto (ESSI) for his invaluable help on the field, the landowners and tribes of the Solomon Islands for allowing the expedition team to enter their customary lands, and the government for the support and facilitation of the legal process. We want to thank all the responsible Chiefs of the areas investigated for their kind permission, and the village communities, who have always heartily received us and helped us in our prospecting of rivers. For New Caledonia, we would like to thank the New Caledonian government and the New Caledonian North and South Provinces, the DAFE (C. Fort), J.J. Cassan, and N. Charpin from the NGO “Vies d’Ô Douce” for his help on the field.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Schulz-Mirbach, T.; Ladich, F.; Plath, M.; Heß, M. Enigmatic ear stones: What we know about the functional role and evolution of fish otoliths. Biol. Rev. 2019, 94, 457–482. [Google Scholar] [CrossRef] [PubMed]
  2. Popper, A.N.; Fay, R.R. Sound detection and processing by fish: Critical review and major research questions (part 2 of 2). Brain Behav. Evol. 1993, 41, 26–38. [Google Scholar] [CrossRef]
  3. Anken, R.H.; Ibsch, M.; Breuer, J.; Rahmann, H. Effect of hypergravity on the Ca/Sr composition of developing otoliths of larval cichlid fish (Oreochromis mossambicus). Comp. Biochem. Physiol. Part A Mol. Integr. 2001, 128, 369–377. [Google Scholar] [CrossRef] [PubMed]
  4. Inoue, M.; Tanimoto, M.; Oda, Y. The role of ear stone size in hair cell acoustic sensory transduction. Sci. Rep. 2013, 3, 2114. [Google Scholar] [CrossRef] [PubMed]
  5. Dunkelberger, D.G.; Dean, J.M.; Watabe, N. The ultrastructure of the otolithic membrane and otolith in the juvenile mummichog, Fundulus heteroclitus. J. Morphol. 1980, 163, 367–377. [Google Scholar] [CrossRef] [PubMed]
  6. Lychakov, D.V.; Rebane, Y.T.; Lombarte, A.; Fuiman, L.A.; Takabayashi, A. Fish otolith asymmetry: Morphometry and modeling. Hear. Res. 2006, 219, 1–11. [Google Scholar] [CrossRef] [PubMed]
  7. Campana, S.E. Chemistry and composition of fish otoliths: Pathways, mechanisms, and applications. Mar. Ecol. Prog. Ser. 1999, 188, 263–297. [Google Scholar] [CrossRef]
  8. Campana, S.E.; Thorrold, S.R. Otoliths, increments, and elements: Keys to a comprehensive understanding of fish populations? Can. J. Fish. Aquat. Sci. 2001, 58, 30–38. [Google Scholar] [CrossRef]
  9. Lecomte-Finiger, R. L‘otolithe: La ≪boîte noire≫ des Téléostéens. Annee. Biol. 1999, 38, 107–122. [Google Scholar] [CrossRef]
  10. Bergenius, M.A.; McCormick, M.I.; Meekan, M.G.; Robertson, D.R. Environmental influences on larval duration, growth and magnitude of settlement of a coral reef fish. Mar. Biol. 2005, 147, 291–300. [Google Scholar] [CrossRef]
  11. Grammer, G.L.; Morrongiello, J.R.; Izzo, C.; Hawthorne, P.J.; Middleton, J.F.; Gillanders, B.M. Coupling biogeochemical tracers with fish growth reveals physiological and environmental controls on otolith chemistry. Ecol. Monogr. 2017, 87, 487–507. [Google Scholar] [CrossRef]
  12. Haÿ, V.; Berland, S.; Medjoubi, K.; Somogyi, A.; Mennesson, M.I.; Keith, P.; Lord, C. Unmasking pipefish otolith using synchrotron-based scanning X-ray fluorescence. Sci. Rep. 2023, 13, 4794. [Google Scholar] [CrossRef] [PubMed]
  13. de Pontual, H.; MacKenzie, K.M.; Tabouret, H.; Daverat, F.; Mahé, K.; Pecheyran, C.; Hüssy, K. Heterogeneity of Otolith Chemical Composition from Two-Dimensional Mapping: Relationship with biomineralization mechanisms and implications for microchemistry analyses. J. Fish. Biol. 2024, 104, 20–33. [Google Scholar] [CrossRef] [PubMed]
  14. Lord, C.; Haÿ, V.; Medjoubi, K.; Berland, S.; Keith, P. Travelling in Microphis (Teleostei: Syngnathidae) Otoliths with Two-Dimensional X-ray Fluorescence Maps: Twists and Turns on the Road to Strontium Incorporation. Biology 2024, 13, 446. [Google Scholar] [CrossRef] [PubMed]
  15. Zimmerman, C.E. Relationship of otolith strontium-to-calcium ratios and salinity: Experimental validation for juvenile salmonids. Can. J. Fish. Aquat. Sci. 2005, 62, 88–97. [Google Scholar] [CrossRef]
  16. Zimmerman, C.E.; Swanson, H.K.; Volk, E.C.; Kent, A.J. Species and Life History Affect the Utility of Otolith Chemical Composition for Determining Natal Stream of Origin for Pacific Salmon. Trans. Am. Fish. Soc. 2013, 142, 1370–1380. [Google Scholar] [CrossRef]
  17. Parkinson, K.L.; Booth, D.J.; Lee, J.E. Validation of otolith daily increment formation for two temperate syngnathid fishes: The pipefishes Stigmatopora argus and Stigmatopora nigra. J. Fish Biol. 2012, 80, 698–704. [Google Scholar] [CrossRef] [PubMed]
  18. Lowenstam, H.A. Minerals formed by organisms. Science 1981, 211, 1126–1131. [Google Scholar] [CrossRef]
  19. Hüssy, K.; Limburg, K.E.; de Pontual, H.; Thomas, O.R.B.; Cook, P.K.; Heimbrand, Y.; Blass, M.; Sturrock, A.M. Trace Element Patterns in Otoliths: The Role of Biomineralization. Rev. Fish. Sci. Aquac. 2021, 29, 445–477. [Google Scholar] [CrossRef]
  20. de Goeyse, S.; Webb, A.E.; Reichart, G.J.; de Nooijer, L.J. Carbonic anhydrase is involved in calcification by the benthic foraminifer Amphistegina lessonii. Biogeosciences 2021, 18, 393–401. [Google Scholar] [CrossRef]
  21. Smith, N.G.; Jones, C.M. Substituting otoliths for chemical analyses: Does sagitta = lapillus? Mar. Ecol. Prog. Ser. 2006, 313, 241–247. [Google Scholar] [CrossRef]
  22. Hedges, K.J.; Ludsin, S.A.; Frayer, B.J. Effects of ethanol preservation on otolith microchemistry. J. Fish Biol. 2004, 64, 923–937. [Google Scholar] [CrossRef]
  23. Somogyi, A.; Medjoubi, K.; Baranton, G.; Le Roux, V.; Ribbens, M.; Polack, F.; Philippot, P.; Samama, J.P. Optical design and multi-length-scale scanning spectro-microscopy possibilities at the Nanoscopium beamline of Synchrotron Soleil. J. Synchrotron Rad. 2015, 22, 1118–1129. [Google Scholar] [CrossRef] [PubMed]
  24. Medjoubi, K.; Leclercq, N.; Langlois, F.; Buteau, A.; Lé, S.; Poirier, S.; Mercère, P.; Sforna, M.C.; Kewish, C.M.; Somogyi, A. Development of fast, simultaneous and multi-technique scanning hard X-ray microscopy at Synchrotron Soleil. J. Synchrotron Rad. 2013, 20, 293–299. [Google Scholar] [CrossRef] [PubMed]
  25. Bergamaschi, A.; Medjoubi, K.; Messaoudi, C.; Marco, S.; Somogyi, A. MMX-I: Data-processing software for multimodal X-ray imaging and tomography. J. Synchrotron Rad. 2016, 23, 783–794. [Google Scholar] [CrossRef] [PubMed]
  26. Fiji. Available online: http://fiji.sc/cgi-bin/gitweb.cgi (accessed on 5 June 2024).
  27. Schindelin, J.; Arganda-Carreras, I.; Frise, E.; Kaynig, V.; Longair, M.; Pietzsch, T.; Preibisch, S.; Rueden, C.; Saaldfeld, S.; Schmid, B.; et al. Fiji: An open-source platform for biological-image analysis. Nat. Methods 2012, 9, 676–682. [Google Scholar] [CrossRef] [PubMed]
  28. PyMca, version 5.9.2; European Synchrotron Radiation Facility: Grenoble, France, 2004. Available online: http://pymca.sourceforge.net/(accessed on 6 June 2024).
  29. Solé, V.A.; Papillon, E. PyMca–X-Ray Spectrum Analysis in Python; European Synchrotron Radiation Facility (ESRF): Grenoble, France, 2004; p. 38043. [Google Scholar]
  30. Solé, V.A.; Papillon, E.; Cotte, M.; Walter, P.; Susini, J.A.A. Multiplatform Code for the Analysis of Energy-Dispersive X-Ray Fluorescence Spectra. Spectroc. Acta Part B At. Spectrosc. 2007, 62, 63–68. [Google Scholar] [CrossRef]
  31. R Development Core Team. R, version 4.2.3; R Foundation for Statistical Computing: Vienna, Austria, 2020. Available online: https://www.R-project.org/(accessed on 15 March 2023).
  32. Keith, P. Biology and Ecology of Amphidromous Gobiidae of the Indo-Pacific and the Caribbean Regions. J. Fish. Biol. 2003, 63, 831–847. [Google Scholar] [CrossRef]
  33. Potter, I.C.; Tweedley, J.R.; Elliott, M.; Whitfield, A.K. The ways in which fish use estuaries: A refinement and expansion of the guild approach. Fish Fish. 2015, 16, 230–239. [Google Scholar] [CrossRef]
  34. Elsdon, T.S.; Gillanders, B.M. Consistency of patterns between laboratory experiments and field collected fish in otolith chemistry: An example and applications for salinity reconstructions. Mar. Freshwater Res. 2005, 56, 609–617. [Google Scholar] [CrossRef]
  35. Thomas, O.R.B.; Ganio, K.; Roberts, B.R.; Swearer, S.E. Trace element–protein interactions in endolymph from the inner ear of fish: Implications for environmental reconstructions using fish otolith chemistry. Metallomics 2017, 9, 239–249. [Google Scholar] [CrossRef] [PubMed]
  36. Jessop, B.; Cairns, D.; Thibault, I.; Tzeng, W. Life history of American eel Anguilla rostrata: New insights from otolith microchemistry. Aquat. Biol. 2008, 1, 205–216. [Google Scholar] [CrossRef]
  37. Brown, R.J.; Severin, K.P. Otolith chemistry analyses indicate that water Sr:Ca is the primary factor influencing otolith Sr:Ca for freshwater and diadromous fish but not for marine fish. Can. J. Fish. Aquat. Sci. 2009, 66, 1790–1808. [Google Scholar] [CrossRef]
  38. McFadden, A.; Wade, B.; Izzo, C.; Gillanders, B.M.; Lenehan, C.E.; Pring, A. Quantitative electron microprobe mapping of otoliths suggests elemental incorporation is affected by organic matrices: Implications for the interpretation of otolith chemistry. Mar. Freshw. Res. 2015, 67, 889–898. [Google Scholar] [CrossRef]
  39. Borelli, G.; Guibbolini, M.E.; Mayer-Gostan, N.; Priouzeau, F.; De Pontual, H.; Allemand, D.; Puverel, S.; Tambutte, E.; Payan, P. Daily variations of endolymph composition: Relationship with the otolith calcification process in trout. J. Exp. Biol. 2003, 206, 2685–2692. [Google Scholar] [CrossRef] [PubMed]
  40. Arias, J.L.; Neira-Carrillo, A.; Arias, J.I.; Escobar, C.; Bodero, M.; David, M.; Fernandez, M.S. Sulfated polymers in biological mineralization: A plausible source for bioinspired engineering. J. Mater. Chem. 2004, 14, 2154–2160. [Google Scholar] [CrossRef]
  41. Iida, M.; Watanabe, S.; Tsukamoto, K. Oceanic larval duration and recruitment mechanism of the amphidromous fish Sicyopterus japonicus (Gobioidei: Sicydiinae). Reg. Stud. Mar. Sci. 2015, 1, 25–33. [Google Scholar] [CrossRef]
  42. Bounket, B.; Gibert, P.; Gennotte, V.; Argillier, C.; Carrel, G.; Maire, A.; Logez, M.; Morat, F. Otolith shape analysis and daily increment validation during ontogeny of larval and juvenile European chub Squalius cephalus. J. Fish Biol. 2019, 95, 444–452. [Google Scholar] [CrossRef] [PubMed]
  43. Fey, D.P.; Lejk, A.M.; Greszkiewicz, M. Daily deposition of growth increments in sagittae and lapilli of laboratory-reared larval northern pike (Esox lucius). Fish. Bull. 2018, 116, 302–309. [Google Scholar] [CrossRef]
  44. Morioka, S.; Machinandiarena, L. Comparison of daily increment formation pattern between sagittae and lapilli of ling (Genypterus blacodes) larvae and juveniles collected off Argentina. N. Z. J. Mar. Freshw. Res. 2001, 35, 111–119. [Google Scholar] [CrossRef]
  45. Campana, S.E. Photographic Atlas of Fish Otoliths of the Northwest Atlantic Ocean, In Canadian Special Publication of Fisheries and Aquatic Sciences; NRC Research Press: Ottawa, Canada, 2004; Volume 133, pp. 1–11. [Google Scholar]
  46. Morales-Nin, B. Review of the growth regulation processes of otolith daily increment formation. Fish. Res. 2000, 46, 53–67. [Google Scholar] [CrossRef]
  47. Hüssy, K. Otolith shape in juvenile cod (Gadus morhua): Ontogenetic and environmental effects. J. Exp. Mar. Bio. Ecol. 2008, 364, 35–41. [Google Scholar] [CrossRef]
  48. Vignon, M.; Morat, F. Environmental and genetic determinant of otolith shape revealed by a non-indigenous tropical fish. Mar. Ecol. Prog. Ser. 2010, 411, 231–241. [Google Scholar] [CrossRef]
  49. Vignon, M. Ontogenetic trajectories of otolith shape during shift in habitat use: Interaction between otolith growth and environment. J. Exp. Mar. Bio. Ecol. 2012, 420, 26–32. [Google Scholar] [CrossRef]
  50. Baumann, H.; Gagliano, M. Changing otolith/fish size ratios during settlement in two tropical damselfishes. Helgol. Mar. Res. 2011, 65, 425–429. [Google Scholar] [CrossRef]
  51. Protasowicki, M.; Kosior, M. Long-term observations of selected heavy metals contained in otoliths of cod from the Southern Baltic. Kieler Meeresforsch. Sonderh. 1988, 6, 424–431. [Google Scholar]
  52. Arslan, Z.; Secor, D.H. Analysis of trace transition elements and heavy metals in fish otoliths as tracers of habitat use by American eels in the Hudson River estuary. Estuaries 2005, 28, 382–393. [Google Scholar] [CrossRef]
  53. Hansson, S.V.; Desforges, J.P.; van Beest, F.M.; Bach, L.; Halden, N.M.; Sonne, C.; Mosbech, A.; Søndergaard, J. Bioaccumulation of mining derived metals in blood, liver, muscle and otoliths of two Arctic predatory fish species (Gadus ogac and Myoxocephalus scorpius). Environ. Res. 2020, 183, 109194. [Google Scholar] [CrossRef] [PubMed]
  54. Daros, F.A.; Condini, M.V.; Altafin, J.P.; de Oliveira Ferreira, F.; Hostim-Silva, M. Fish otolith microchemistry as a biomarker of the world’s largest mining disaster. Sci. Total Environ. 2022, 807, 151780. [Google Scholar] [CrossRef] [PubMed]
  55. Sturrock, A.M.; Hunter, E.; Milton, J.A.; EIMF; Johnson, R.C.; Waring, C.P.; Trueman, C.N. Quantifying physiological influences on otolith microchemistry. Methods Ecol. Evol. 2015, 6, 806–816. [Google Scholar] [CrossRef]
  56. Miller, P.A.; Munkittrick, K.R.; Dixon, D.G. Relationship between concentrations of copper and zinc in water, sediment, benthic invertebrates, and tissues of white sucker (Catostomus commersoni) at metal-contaminated sites. Can. J. Fish. Aquat. Sci. 1992, 49, 978–984. [Google Scholar] [CrossRef]
  57. Pender, P.J.; Griffin, R.K. Habitat history of barramundi Lates calcarifer in a north Australian river system based on barium and strontium levels in scales. T. Am. Fish. Soc. 1996, 125, 679–689. [Google Scholar] [CrossRef]
  58. Daverat, F.; Lanceleur, L.; Pécheyran, C.; Eon, M.; Dublon, J.; Pierre, M.; Schäfer, J.; Baudrimont, M.; Renault, S. Accumulation of Mn, Co, Zn, Rb, Cd, Sn, Ba, Sr, and Pb in the otoliths and tissues of eel (Anguilla anguilla) following long-term exposure in an estuarine environment. Sci. Total Environ. 2012, 437, 323–330. [Google Scholar] [CrossRef] [PubMed]
  59. Andronis, C.; Evans, N.J.; McDonald, B.J.; Nice, H.E.; Gagnon, M.M. Otolith microchemistry: Insights into bioavailable pollutants in a man-made, urban inlet. Mar. Pollut. Bull. 2017, 118, 382–387. [Google Scholar] [CrossRef] [PubMed]
  60. Fowler, A.J.; Campana, S.E.; Thorrold, S.R.; Jones, C.M. Experimental assessment of the effect of temperature and salinity on elemental composition of otoliths using solution-based ICPMS. Can. J. Fish. Aquat. Sci. 1995, 52, 1421–1430. [Google Scholar] [CrossRef]
  61. Forrester, G.E. A field experiment testing for correspondence between trace elements in otoliths and the environment and for evidence of adaptation to prior habitats. Estuaries 2005, 28, 974–981. [Google Scholar] [CrossRef]
  62. Hicks, A.S.; Closs, G.P.; Swearer, S.E. Otolith microchemistry of two amphidromous galaxiids across an experimental salinity gradient: A multi-element approach for tracking diadromous migrations. J. Exp. Mar. Bio. Ecol. 2010, 394, 86–97. [Google Scholar] [CrossRef]
  63. Gauldie, R.W.; Nathan, A. Iron content of the otoliths of tarakihi (Teleostei: Cheilodactylidae). N. Z. J. Mar. Freshw. Res. 1977, 11, 179–191. [Google Scholar] [CrossRef]
  64. Begg, G.A.; Cappo, M.; Boyle, S. Waters of eastern Australia by analysis of minor and trace. Fish. Bull. 1998, 96, 653–666. [Google Scholar]
  65. Keith, P.; Lord, C.; Maeda, K. Indo-Pacific Sicydiine Gobies: Biodiversity, Life Traits and Conservation; Société Française d’Ichtyologie: Paris, France, 2015. [Google Scholar]
  66. Perfetto, R.; Del Prete, S.; Vullo, D.; Sansone, G.; Barone, C.; Rossi, M.; Capasso, C. Biochemical characterization of the native α-carbonic anhydrase purified from the mantle of the Mediterranean mussel, Mytilus galloprovincialis. J. Enzyme Inhib. Med. Chem. 2017, 32, 632–639. [Google Scholar] [CrossRef] [PubMed]
  67. de Nooijer, L.J.; Toyofuku, T.; Kitazato, H. Foraminifera promote calcification by elevating their intracellular pH. Proc. Natl. Acad. Sci. USA 2009, 106, 15374–15378. [Google Scholar] [CrossRef] [PubMed]
  68. Borelli, G.; Mayer-Gostan, N.; De Pontual, H.; Boeuf, G.; Payan, P. Biochemical relationships between endolymph and otolith matrix in the trout (Oncorhynchus mykiss) and turbot (Psetta maxima). Calcif. Tissue Int. 2001, 69, 356–364. [Google Scholar] [CrossRef] [PubMed]
  69. Payan, P.; De Pontual, H.; Bœuf, G.; Mayer-Gostan, N. Endolymph chemistry and otolith growth in fish. C. R. Palevol 2004, 3, 535–547. [Google Scholar] [CrossRef]
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Figure 1. Top image: microtomography (CT-scan) of a pipefish specimen (Microphis brachyurus) with a focus on a transverse section of the posterior skull pointing out the positioning of otolith pairs in their respective end organ: astericus, sagitta and lapillus. Bottom images: otolith pair samples. RTNC139 individual: otolith cross section images show calcium coverage (XRF scan) of the left and right sagittae. PFV39 and 18253 individuals: sagitta/lapillus pairs were observed under polarized light over their meridian section down to the core (white arrow). L: left; R: right.
Figure 1. Top image: microtomography (CT-scan) of a pipefish specimen (Microphis brachyurus) with a focus on a transverse section of the posterior skull pointing out the positioning of otolith pairs in their respective end organ: astericus, sagitta and lapillus. Bottom images: otolith pair samples. RTNC139 individual: otolith cross section images show calcium coverage (XRF scan) of the left and right sagittae. PFV39 and 18253 individuals: sagitta/lapillus pairs were observed under polarized light over their meridian section down to the core (white arrow). L: left; R: right.
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Figure 2. 2D XRF maps of the Sr:Ca molar ratio (mmol.mol−1) distribution over the meridian section down to the core for each otolith pair. Each otolith exhibits a zonal distribution of the Sr:Ca molar ratio, fairly centred on the core, highlighting the environmental transition encountered by diadromous fish. The transition from marine to freshwater is well marked, and the Sr:Ca molar ratio cut-off limit is represented by the inner white line on the smaller representation of each otolith. The outer rim (turquoise colour range) has the lowest Sr:Ca molar ratio, a signature of a freshwater habitat for adult fish (Z3). Z1-Z2: area enclosed prior to the cut-off limit.
Figure 2. 2D XRF maps of the Sr:Ca molar ratio (mmol.mol−1) distribution over the meridian section down to the core for each otolith pair. Each otolith exhibits a zonal distribution of the Sr:Ca molar ratio, fairly centred on the core, highlighting the environmental transition encountered by diadromous fish. The transition from marine to freshwater is well marked, and the Sr:Ca molar ratio cut-off limit is represented by the inner white line on the smaller representation of each otolith. The outer rim (turquoise colour range) has the lowest Sr:Ca molar ratio, a signature of a freshwater habitat for adult fish (Z3). Z1-Z2: area enclosed prior to the cut-off limit.
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Figure 3. Sr:Ca molar ratio (mmol.mol−1) frequency distribution computed from the overall surface of the meridian section down to the core of each otolith. Each otolith pair is represented on one graph: (a) RTNC139; (b) PFV39); (c) 18253. The red dashed line represents the cut-off limit value between the adult freshwater phase and the marine juvenile phase. For each otolith pair, the frequency distributions are quite superimposed for low Sr:Ca molar ratio values (<2–3 mmol.mol−1) representing adult life in freshwater (Z3). For every pair, for values >3 mmol.mol−1 (Z1-Z2), there is a mismatch in the Sr:Ca molar ratio frequency distribution, with a difference in the spread of values between otoliths of a matched pair, revealing unpaired Sr integration at a hyperfine scale. S: sagitta; L: lapillus; rg: right; lf: left.
Figure 3. Sr:Ca molar ratio (mmol.mol−1) frequency distribution computed from the overall surface of the meridian section down to the core of each otolith. Each otolith pair is represented on one graph: (a) RTNC139; (b) PFV39); (c) 18253. The red dashed line represents the cut-off limit value between the adult freshwater phase and the marine juvenile phase. For each otolith pair, the frequency distributions are quite superimposed for low Sr:Ca molar ratio values (<2–3 mmol.mol−1) representing adult life in freshwater (Z3). For every pair, for values >3 mmol.mol−1 (Z1-Z2), there is a mismatch in the Sr:Ca molar ratio frequency distribution, with a difference in the spread of values between otoliths of a matched pair, revealing unpaired Sr integration at a hyperfine scale. S: sagitta; L: lapillus; rg: right; lf: left.
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Figure 4. Sulphur-based counting of growth increments. Sulphur-based increment counting was performed along a long radius (lg rad.) and a short radius (sh rad.), i.e., two transects running from the core to the edges of the longest and shortest sides of each otolith. Each count has been replicated with a slight distal offset. Above each otolith, the replicated total numbers of increments counted along the entire long and short radiuses are given. Replicated counts are featured for each segment: from the core (light blue spot) to the marine/freshwater transition limit (grey boxed line, Z1-Z2) and from the cut-off limit to the edge of the otolith (freshwater adult phase—yellow boxed line, Z3), along both radiuses. (A) pair of sagittae for RTNC139 specimen; (B) sagittae/lapillus pairs for PFV39 and 18253 specimens.
Figure 4. Sulphur-based counting of growth increments. Sulphur-based increment counting was performed along a long radius (lg rad.) and a short radius (sh rad.), i.e., two transects running from the core to the edges of the longest and shortest sides of each otolith. Each count has been replicated with a slight distal offset. Above each otolith, the replicated total numbers of increments counted along the entire long and short radiuses are given. Replicated counts are featured for each segment: from the core (light blue spot) to the marine/freshwater transition limit (grey boxed line, Z1-Z2) and from the cut-off limit to the edge of the otolith (freshwater adult phase—yellow boxed line, Z3), along both radiuses. (A) pair of sagittae for RTNC139 specimen; (B) sagittae/lapillus pairs for PFV39 and 18253 specimens.
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Figure 5. Diagnostic plots of the cumulated synchrotron-based X-ray fluorescence emissions in the otolith samples. Energy intensities (x-axis) are displayed with their count (y-axis). The broad peaks at 366 eV and 1399 eV are characteristic X-ray emissions from calcium (Ca) and strontium (Sr), respectively. The XRF peak intensities that allowed the identification of the other elements are presented on the spectrum at the top of the figure. The individual spectra of the otolith samples are displayed in pairs at the bottom of the figure. The characteristic element peak position for each otolith is given in the table below each graph. S: sagitta; L: lapillus.
Figure 5. Diagnostic plots of the cumulated synchrotron-based X-ray fluorescence emissions in the otolith samples. Energy intensities (x-axis) are displayed with their count (y-axis). The broad peaks at 366 eV and 1399 eV are characteristic X-ray emissions from calcium (Ca) and strontium (Sr), respectively. The XRF peak intensities that allowed the identification of the other elements are presented on the spectrum at the top of the figure. The individual spectra of the otolith samples are displayed in pairs at the bottom of the figure. The characteristic element peak position for each otolith is given in the table below each graph. S: sagitta; L: lapillus.
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Figure 6. Heavy metal distribution in the otoliths. Otolith pair maps of the cumulated X-ray emissions in the range of 639 eV to 826 eV (chromium, iron, cobalt, nickel and copper) show the heavy metals are co-localised within each otolith and exhibit similar concentration areas in the pairs, mainly at the area corresponding to the freshwater adult period of life. Light blue line inside the otoliths corresponds to the cut-off limit between marine and freshwater life phases. Core position is marked by the blue spot; rg: right.
Figure 6. Heavy metal distribution in the otoliths. Otolith pair maps of the cumulated X-ray emissions in the range of 639 eV to 826 eV (chromium, iron, cobalt, nickel and copper) show the heavy metals are co-localised within each otolith and exhibit similar concentration areas in the pairs, mainly at the area corresponding to the freshwater adult period of life. Light blue line inside the otoliths corresponds to the cut-off limit between marine and freshwater life phases. Core position is marked by the blue spot; rg: right.
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Figure 7. Zinc (Zn) distribution within the otoliths. Otolith pair maps of the cumulated X-ray emissions of Zn (1.03 to 1.107 keV) showing a scattered signal displayed in the entire otoliths. There is a noticeable higher concentration of the signal on some parts of the edge of the otoliths. The otolith outline and core position are provided on the top left of the Zn distribution maps, which only feature the Zn signal to maximise its visualisation.
Figure 7. Zinc (Zn) distribution within the otoliths. Otolith pair maps of the cumulated X-ray emissions of Zn (1.03 to 1.107 keV) showing a scattered signal displayed in the entire otoliths. There is a noticeable higher concentration of the signal on some parts of the edge of the otoliths. The otolith outline and core position are provided on the top left of the Zn distribution maps, which only feature the Zn signal to maximise its visualisation.
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Table 1. Sampling. Fish species; ID: field number; collection N°: National Museum of Natural History (MNHN, Paris, France) collection number; SL: fish standard length (mm); country and river of collection; otolith pair analysed.
Table 1. Sampling. Fish species; ID: field number; collection N°: National Museum of Natural History (MNHN, Paris, France) collection number; SL: fish standard length (mm); country and river of collection; otolith pair analysed.
SpeciesIDCollection N°SLCountryRiverOtolith Pair
Microphis brachyurusRTNC139MNHN-IC-2021-0322105.57New CaledoniaGaranaLeft Sagitta
Right Sagitta
Microphis brachyurusPFV39MNHN-IC-2023-0052109.36French PolynesiaPapenooRight Sagitta
Right Lapillus
Microphis nicoleae18253MNHN-IC-2023-004797.65Solomon IslandsRakataRight Sagitta
Right Lapillus
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Lord, C.; Berland, S.; Haÿ, V.; Medjoubi, K.; Keith, P. Twin Peaks: Interrogating Otolith Pairs to See Whether They Keep Their Stories Straight. Crystals 2024, 14, 705. https://doi.org/10.3390/cryst14080705

AMA Style

Lord C, Berland S, Haÿ V, Medjoubi K, Keith P. Twin Peaks: Interrogating Otolith Pairs to See Whether They Keep Their Stories Straight. Crystals. 2024; 14(8):705. https://doi.org/10.3390/cryst14080705

Chicago/Turabian Style

Lord, Clara, Sophie Berland, Vincent Haÿ, Kadda Medjoubi, and Philippe Keith. 2024. "Twin Peaks: Interrogating Otolith Pairs to See Whether They Keep Their Stories Straight" Crystals 14, no. 8: 705. https://doi.org/10.3390/cryst14080705

APA Style

Lord, C., Berland, S., Haÿ, V., Medjoubi, K., & Keith, P. (2024). Twin Peaks: Interrogating Otolith Pairs to See Whether They Keep Their Stories Straight. Crystals, 14(8), 705. https://doi.org/10.3390/cryst14080705

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