Jean-Luc Maurice

Gervasi Herranz

Christian Colliex

Isabelle Devos

Cécile Carrétéro

Agnès Barthelemy

Karim Bouzehouane

Stéphane Fusil

Dominique Imhoff

Éric Jacquet

J.-L Maurice

A Barthélémy

F Jomard

D Ballutaud

M Basletic

Electron energy loss spectroscopy determination of Ti oxidation state at the (001) LaAlO3/SrTiO3 interface

Keywords: 79, 20, Uv -Electron energy loss spectroscopy 73, 20, -r -Electron states at surfaces and interfaces 73, 61, Ng -Electrical properties of specific thin films: insulators

Introduction. -In a pioneering work, Ohtomo and Hwang [1] have discovered that growing LaAlO 3 (LAO) by pulsed laser deposition (PLD) onto a TiO 2 -terminated (001) surface of SrTiO 3 (STO), produces a metallic system, while both materials are insulators with respective band gaps of 5.6 eV and 3.2 eV [2]. This observation has been the signal for many studies of this system: among remarkable results are the superconductivity observed below 200 mK [3], the magnetism around 300 mK [4], and the field effect on conductivity [5].

In the ionic limit, the perfect interface carries a global positive charge, because the last TiO 2 plane of STO is neutral and faces a first plane of LAO that has composition LaO and carries an uncompensated charge +1/2 per surface unit cell. Such a configuration would lead to a so-called 'polar catastrophe' [6] if it were not balanced by electron or ion rearrangements. In the present case, the capacity of Ti ions to bear a mixed valence may provide the necessary screening, some Ti 4+ (valence in bulk STO) becoming Ti 3+ . In this most simple scheme -essentially confirmed by calculations [16][17][18] -1/2 extra electron per surface unit cell is necessary to maintain electrical neutrality [1]. The spreading of the electron cloud associated with such a delta-doping has been evaluated by solving Poisson's equation: at 300 K, electron concentration should be ∼1.3 × 10 21 cm -3 (∼8 % of the Ti concentration) at the interface, and it should fall to ∼8 × 10 20 cm -3 (5%, the present detection limit, see below) at only 1 nm into the bulk [12].

Several authors have associated the n-type conductivity they have measured with such screening electrons [1,5,7]. However, growth by PLD is a complex process, which will hardly create 'perfect' materials [8,9]. Thus this scheme of interpretation, based on the interface being atomically sharp and chemically stoichiometric, is the object of intense discussion. In our laboratory, we have inferred from Shubnikov-De-Haas oscillations [10] and cross-section conducting-tip atomic-force microscopy (CT-AFM) [11], that, in the samples grown at low-pressure, which exhibited the highest mobilities, the electron gas was 3-dimensional and extended hundreds of µm into the bulk of the substrate. Moreover, Siemons et al. [12], by making measurements before and after oxygen annealing, and Kalabukhov et al. [13], by measuring cathodo-and photoluminescence, concluded that the doping was due to oxygen vacancies that had diffused during the PLD process. In reality, pulsed laser deposition proceeds with species (atoms, ions and clusters) that have a kinetic energy upon landing which depends, among other growth parameters, on the pressure in the chamber: in our case, typically several hundreds of eV in the 10 -2 -10 -4 Pa pressure range, and decreasing at higher pressure [14]. The point defect content of the growing layer thus directly depends on the growth oxygen pressure, not merely because vacuum creates vacancies, but mainly because landing species have enough energy to create irradiation damage. This in turn, makes the growing layer a pressure-dependent reservoir of vacancies for exodiffusion from the substrate. This phenomenon of substrate reduction is however well known in molecular beam epitaxy, where it is utilised for the oxidation of epitaxial layers [15].

If bulk substrate properties thus depend on the growth pressure of the epitaxial layer, the question remains about the interface role on conductivity. With our CT-AFM experiments [11], we have shown that the interface region did exhibit a specific, enhanced, conductivity, but -and this is a key point -with a low electron mobility. Correlatively, we also found that this conductivity depended on growth conditions [11]. Low-mobility and dependence on growth conditions would be both the logical result of an extrinsic source of dopant. It is thus mandatory to characterise the doping level at the interface itself, as a function of growth conditions. This need is further highlighted by a recent result based on X-ray diffraction [9] that shows the existence of a several unit-cell thick layer of metallic La 1-x Sr x TiO 3 at the interface.

Our high-resolution transmission electron microscopy (HRTEM) observations in cross section have shown the existence of a distortion at the interface [19], which could be equally consistent with the delta-doping [17,18] or the La 1-x Sr x TiO 3 hypothesis [9]. But they also exhibited noisy contrasts [18] that would finally back up the latter. Measurements of the Ti 3+ ratio were carried out by electron energy loss spectroscopy (EELS) in the scanning transmission electron microscope (STEM), by David Muller's group [3,20] and ours [18]. The LAO/STO interfaces analysed were in all these cases prepared at relatively low pressures; Ti 3+ was detected at the interface, over a width reaching 5 nm in ref. [20] and closer to the nm in refs. [3,18], thus depending, very likely, on the details of sample growth and preparation.

Here, we bring new STEM-EELS data, obtained this time from a sample grown at 40 Pa (0.4 mbar, 'high pressure'), which was macroscopically insulating, and from a new reference grown at 10 -4 Pa (10 -6 mbar, 'low pressure'), macroscopically conductive. Our results evidence, for the first time to our knowledge, the role of growth conditions on the microscopic interface atomic structure: oxygen pressure in the growth chamber tends to decrease the apparent interface doping. The latter is therefore not only due the intrinsic polarity, but also to extrinsic point defects. We have additionally performed a combined HRTEM, electron-diffraction, and atomic force microscopy study of the two samples, which shows a fundamental change in relaxation of the epitaxial strain as the growth pressure increases. At low pressure, relaxation takes place without dislocations in a way preserving a 2dimensionnal layer by layer growth, most probably with the aid of point defects. At high pressure, relaxation occurs through a 3-dimensionnal growth mode.

Methods. -LAO thin films were grown by pulsed laser deposition (PLD) using a frequency-tripled (λ =355 nm) Nd: yttrium aluminum garnet (YAG) laser on TiO 2 -terminated STO substrates [Surfacenet Gmbh] with growth oxygen pressures PO 2 = 10 -4 Pa and PO 2 = 40 Pa, for the low-and high-pressure specimens, respectively, at a deposition temperature of T = 750 • C. The laser pulse rate was fixed at 2.5 Hz, whereas the energy density was 2.8 Jcm -2 . The target-substrate distance was 55 mm, resulting in a growth rate of about 1 Ås -1 . Once the film deposition was finished, the samples were cooled down to room temperature at the growth oxygen pressure (10 -4 and 40 Pa, respectively). The transport properties of the low-pressure sample are among the best published to date (mobility > 10 4 cm 2 V -1 s -1 at 4K, see details in ref. [10]). In that specimen, the LAO thickness was 20 nm. The other sample was insulating, the LAO in this case was 5nm thick. This choice was made so that point-defect diffusion processes would dominate in the low-pressure sample [10,11] and be negligible in the high-pressure case.

The LAO/STO cross-sectional samples for TEM and STEM-EELS were prepared using standard tripod polishing, without water for the last ∼5 µm on each face. It was completed by a prolonged, grazing incidence, ion milling with 2-keV Ar ions, from the backside (STO) only. This procedure resulted, as shown by the profiles below (see fig. 5), in thin foils with fairly parallel faces. This point is very important as the surfaces of foils are strong sources of Ti 3+ . We otherwise minimised the influence of surfaces by selecting relatively thick regions (∼30-40 nm). We checked by HRTEM the defects created by STEM-EELS recording, and kept only those data sets where they remained invisible. The STEM-EELS measurements were performed with a VG HB501 microscope operated at 100 kV, TEM and HRTEM observations were carried out on a Topcon 002B, working at 200 kV.

We analysed the spatial variations of electron energy loss spectra using spectrum images (3-dimensional data boxes that consist in n × m arrays of p-channel spectra [21]) acquired by scanning a focused probe step by step and recording a spectrum at each step. We typically recorded images consisting in 2 to 8 64-pixel lines perpendicular to the interface, with a pixel size of 0.33 nm to 0.74 nm and a channel size of 0.2 eV. The dwell time varied between 0.2 and 1 s. In order to increase signal/noise Fig. 1: Evolution of the 3d electronic structure of Ti as a function of valence and surroundings. Degeneracy in the case of Ti 4+ in bulk STO is partially lifted by the octahedral crystal field (middle), separating 3d into t2g and eg levels. The two corresponding peaks are well visible in EELS Ti-L2 and Ti-L3 edges (see A, B in fig. 4) [22,24]. In the case of Ti at the interface (right), both valence and site-symmetry are different, which organises the 3d levels in quite a different way [18]. The levels presented correspond to molecular calculations, an additionnal spreading will occur in the actual crystal. This will transform the two peaks into a broad one in the EELS edges.

ratio, the profiles finally used, such as those presented below, were obtained by summing, parallel to the interface, the 2 to 8 lines. Before this, the drift, measured as the shift of the interface from one line to the next, was corrected on pixel position and size. The effective size of the interaction volume was calculated by deconvoluting the measured Ti concentration profiles, assuming a step function for the actual profiles. The intensity distribution of the probe thus defined was quasi-gaussian with a width at half maximum of ∼2nm in the experiments presented below. The energy resolution of the spectrometer was better than 0.6 eV (width at half maximum of zero-loss peak).

The evaluation of the Ti 3+ ratio was carried out using the high sensitivity on this ratio of the fine structure of Ti-L 2,3 edge [22][23][24]. Indeed, this edge corresponds to transitions from 2p discrete levels to the 3d band, which is empty for Ti 4+ in bulk STO, and contains one half an electron per site in the simplest model of Ti 3+/4+ at the interface. Fig. 1 compares the Ti-3d molecular electronic structure in the case of the octahedral crystal field of STO and that of the distorted site [18] at the abrupt LAO-STO interface. The move of energy levels, when going from bulk STO to the interface, will appear in spectra as a fine structure smoothing.

More specifically, both the Ti-L 2 , and Ti-L 3 edges in STO are made of two well defined peaks corresponding to the e g and t 2g levels separated by the octahedral crystal field (see fig. 4 and ref. [22]): a shift a valence towards 3+ will show as a progressive fading of these peaks and an increase of signal in the valley in between (see arrows in fig. 4). It is not possible, of course, to separate geometry from valence contributions in such an evolution. However, as the two are intrinsically related through Jahn-Teller type effects, in the analysis presented below, we have considered that all changes of line shape were associated with a valence change.

We further assumed that the global Ti-L 2,3 cross section did not depend on the oxidation state of Ti, so that all experimental spectra be linear combinations of pure Ti 4+ and Ti 3+ spectra. We performed least squares fits of the experimental Ti-L 2,3 edges with reference Ti 4+ and Ti 3+ spectra. The fits were performed after background subtraction, and after normalising the integral of the remaining signal. The reference Ti 4+ spectrum was picked from the substrate contribution in the same profile where the analysed spectrum came from and the Ti 3+ spectrum was taken in ref. [23].

In such measurements, sources of error are numerous [25]. In order to increase the signal/noise ratio, we also applied the least-squares analyses to Ti-L 2,3 edges obtained after summing as many comparable interface spectra as possible. The summed edges totalised more than 2.5 × 10 6 counts (background subtracted), in both the cases of low and high growth pressure (see fig. 4). Even in such conditions, the error in our measurements, taken as the standard deviation between data points from the experimental and fitting spectra, remained of the order of 3 %, which made in turn our detection limit (3 %: ∼5 × 10 20 cm -3 ).

Point defects in LAO. -We show in the present section that the two samples have undergone different relaxation processes of the epitaxial strain, which we associate with different point-defect contents. We focus in the following on the high pressure sample, where growth appears to be quite different from that usually observed in the LAO/STO system.

Figure 2 shows an atomic force micrograph of this sample where the surface appears significantly rough, contrary to what is generally observed with low pressure growth. We associate this roughness with 3-dimensionnal growth. The strucural analysis of this high-pressure sample by TEM in <100> cross section (fig. 3) indicates that some Fig. 3: HRTEM (a) and corresponding selected area electron diffraction pattern (b) of the high pressure sample. As can be seen with the lateral shift of 302 spot, the in-plane parameter is different in film and substrate, which indicates plastic relaxation, a process that does not occur in the low-pressure sample (not shown, see e.g. ref. [19]). The arrows in (a) indicate valleys between relaxed 3D regions.

plastic relaxation has occurred. Selected area electron diffraction (fig. 3b) shows that the distorted pseudo-cubic parameters a (in-the-plane) and c (out-of-plane) are both modified. Taking the internal reference given by STO (a ST O = 0.3905 nm), the lattice pseudo-cubic parameters of this sample come out at a LAO = 0.3873 nm and c LAO = 0.3748 nm (+/-0.001 nm). Correlatively with the in-plane mismatch, we found some misfit dislocations, but not enough to allow for all the difference measured. Plastic relaxation thus appears to be associated with the 3dimensional growth mode. When compared to the equilibrium pseudo-cubic lattice parameter of LAO (0.3792 nm), the parameters found indicate a volume extension, which may be attributed to an elastic distortion with a Poisson ratio of about 0.22.

In similar TEM experiments carried out on the lowpressure sample (not shown), LAO lattice parameters came out at a LAO = 0.3905 and and c LAO = 0.3818. The low-pressure film thus appeared to be fully strained to the substrate, with a relatively small elastic relaxation out-ofplane as has been noticed previously [3,19]. These values indicate a unit cell volume much larger than in the high pressure case, which is consistent with the presence of a much larger amount of point defects. And indeed, in the observation of the <110> cross section of a sample grown in identical conditions (not shown), we have evidenced the existence of a superstructure which could not be simulated using the exact equilibrium rhombohedral LaAlO 3 unit cell, and had to be due to ordering of large amounts of point defects.

Therefore, the two samples would strongly differ in point-defect content, consistently with their growth conditions: the low-pressure sample having been hit by fast species during growth would contain a much higher level of point defects than the high-pressure one. EELS results. -Fig. 4 presents raw experimental spectra, of which the treatment has been limited to background subtraction and averaging over several spectrumimages. In fig. 5, the data have been deduced from the spectra by the fitting procedure described in sec. 'Methods'. The experimental conditions were quite similar (probe effective size and current, spectrometer setting), so that the two samples in each figure can be directly compared.

In fig. 4, the mean experimental interface spectra are superimposed on bulk spectra, giving the reference Ti 4+ . The effect of the interface on the Ti-L 2,3 edge is clearly visible in the low pressure sample, while it is significantly smaller in the high-pressure case. The fit with reference Ti 3+ and Ti 4+ spectra as described in sec. 'Methods' gives 20% Ti 3+ in the former case and only 10 % Ti 3+ in the latter.

Fig. 5 shows the spatial evolution of Ti 3+ ratio, deduced from such fits, in two profiles taken in the low-(fig. 5a) and high-(fig. 5b) pressure samples. Error bars were set to twice the standard deviation between experimental and fitting spectra. Variations from one profile to the next were negligible in the low-pressure sample, so that the profile shown in fig. 5a is quite representative of this sample. In contrast, such variations were quite significant in the high-pressure sample, probably due to the 3-dimensional relaxation of strain in LAO and its localised effects in the substrate. For the profile presented in fig. 5b we have chosen a region where the interface Ti 3+ level was the lowest. It appears on the figure to be of the order of uncertainty, which is about 5 % in this case.

In order to help reading fig. 5, let us recall that the probe has a gaussian shape with a width at half maximum of 2 nm. Thus, it starts to 'count' Ti and Ti 3+ when it is still centered in pure LAO. This causes the residual Ti profile in LAO, but also, as the proportion of Ti 3+ is the largest at that time, the shift towards LAO of the maximum of Ti 3+ ratio in fig. 5a. Because of these probe convolution effects, it is necessary to compare the present profiles with models to effectively localise the Ti 3+ ions, which we do in the next section.

In turn, as measurement noise is the largest where the Ti signal is the smallest, the actual uncertainty there (see first data point in fig. 5b) is probably larger than our estimate based on fit quality.

Discussion. -We compare in this section our experimental profiles with different models of electron distributions, convoluted with our gaussian experimental response (fig. 6). Let us first note that, once the Ti 3+ profiles from the literature are convoluted, they only slightly emerge from the present detection limit (for the present profiles, the sensitivity is worth ∼5 % or ∼8 × 10 20 cm -3 , of course not as fine as that mentioned above for summed spectra). Thus it is not only justified, but even mandatory, to include our high pressure profile, even though it is almost flat, in such comparisons.

Quite surprisingly, in both our cases of low-(fig. 6a) and high-(fig. 6b) pressures, the best fit is obtained with a model of intrinsic polarity. However, the low-pressureconducting -case appears to fit with a model of localised interface electrons ('Intrinsic delta' in fig. 6a), while the high pressure -insulating -case fits on the contrary with a model of mobile electrons ('Delta + Poisson' in fig. 6b). As this is precisely the opposite of what is expected, we have to attribute an extrinsic contribution to at least one of the two cases.

Given that electrons could hardly stay localised in the conducting low pressure specimen, and given that we have made it so as to increase extrinsic effects, we may appoint it to represent the extrinsic case. Thus, we would rather take the present sharp profile of fig. 6a as the tip of a broad distribution of mobile carriers such as that we present in ref. [11]. If we recall that standard carrier densities are orders of magnitude lower [10,11] than the present detection limit (∼8 × 10 20 cm -3 ), this hypothesis appears quite consistent. Thus this low-pressure profile would be associated with donor-like point defects such as oxygen vacancies or La substituted for Sr. But fast kinetics of oxygen exodiffusion [15] appear uncompatible with the profile sharpness, and allow one to eliminate oxygen vacancies. Consequently, we checked cation interdiffusion by secondary ion mass spectrometry on much thicker samples. And we found indeed an enhanced La-Sr exchange, compared to Al-Ti, that moreover depended on growth pressure [28]. The most likely dopant would thus be Lanthanum rather than the oxygen vacancy. It can be noticed, by the way, that Sr 1-x La x TiO 3 chemical solutions are stable over a large concentration range [26,27]. Thus, we would finally have an extrinsic doping effect, of the type evoked by Willmott et al. [9] (fig. 6a), though in lower amounts.

In the high-pressure case (fig. 6b), the Ti 3+ profile should indeed be closer to a model of intrinsic polarity. But it remains quite surprising that it be the mobilecarrier version of the model, as this sample is macroscopically insulating. An explanation, perhaps difficult to check, would be that the sample is indeed conductive in between the areas where epitaxial stress is concentrated (arrows in fig. 2). The stressed zones would, in turn, act as traps and quench conductivity.

Conclusion. -We have measured the concentration profiles of Ti 3+ ions in the STO substrate in the vicinity of the TiO 2 -terminated (001) interface with LAO using STEM-EELS in cross section. We have studied two growth conditions: 200 s and 10 -4 Pa on the one hand, and 50 s and 40 Pa on the other hand, so that pointdefect effects be maximum in the former case, and minimum in the latter. The concentration of Ti 3+ ions appears to depend significantly on growth conditions: in the low-pressure, thicker sample, Ti 3+ surface concentration comes out at more than twice that in the high-pressure specimen. In the former case, there is thus an additional doping. Among the different possibly active point defects, cations in substitution appear mor likely candidates than oxygen vacancies, in qualitative agreement with previous observations [9].

In summary, we have thus shown that Ti ions bearing valence 3+ are indeed present at the polar interface between LAO and TiO 2 -terminated (001) STO, but we have also shown, for the first time to our knowledge, that their concentration depends on growth conditions, so that their origin is, at least partially, extrinsic.

Fig. 2 :

 2 Fig. 2: Atomic force micrograph of the high-pressure sample exhibiting 3-D features. In the area shown, the largest peakto-valley depth reaches 6 nm, i.e. the film thickness.

Fig. 4 :

 4 Fig. 4: Electron energy loss Ti-L2,3 edge recorded at the interface in both the low-(a) and high-(b) pressure samples, compared in each case with a bulk spectrum recorded nearby, giving the reference Ti 4+ . These normalised spectra were obtained after summing several recordings, see text. Note the two peaks A and B corresponding to t2g and eg levels, and the signal in the valley (arrows), significantly more important in the lowpressure case.

Fig. 5 :

 5 Fig. 5: (colour online) Ti 3+ profiles in the low-(a) and high-(b) pressure samples. Concentrations obtained after fitting all spectra in each profile with Ti 3+ and Ti 4+ references as described in text. Superimposed are the corresponding normalised Ti profiles in each case. The red curves are guides to the eye.

Fig. 6 :

 6 Fig. 6: The Ti 3+ profiles of fig. 5 in the low-(a) and high-(b) pressure samples compared with the EELS response applied to published Ti 3+ distributions. 'Intrinsic delta': localised electrons that would neutralise the intrinsic polarity in the form of a delta distribution at the interface; 'Delta + Poisson': same surface density of electrons, but spread into the bulk following the solution of Poisson equation [12]; Willmott et al.: distribution of Ti 3+ given in fig. 3a of ref. [9].

We thank M. Bibes (IEF-CNRS Université Paris-Sud-XI) for fruitfull discussions and M. Tencé (LPS-CNRS Université Paris-Sud-XI) for his help with STEM-EELS.


Mohamad Hijazi

Mathilde Rieu
email: rieu@emse.fr

Valérie Stambouli

Guy Tournier

Jean-Paul Viricelle

Christophe Pijolat

Modi- Fied Sno2

Modified SnO2-APTES gas sensor for selective ammonia detection at room temperature

Keywords: SnO2, Screen printing, Molecularlly functionalization, APTES, Gas snensors, Ammonia gas, Selectivity, Room temperature detection

come

Introduction

The detection of ammonia gas is of great interest in many fields such as medical and environmental monitoring. Ammonia can be detected by different sensing materials like carbon nanotubes or polyaniline [1]. Metal oxide gas sensors are promising devices because they are small in size, easy to use and less expensive than other spectrometry techniques. Thick films of metal oxide can be produced by screen printing which is simple, reproducible and low cost technique. Tin dioxide material allows the detection of many gaseous compounds. Nevertheless, the SnO 2 -based sensors suffer from two major drawbacks which constitute an obstacle to their development. SnO 2 has lack of selectivity because it has high affinity with many gases. In addition, SnO 2 has high operating temperature between 250 °C and 500 °C. Many approaches were described in the literature to cover these drawbacks e.g. SnO 2 /carbon nanotubes and SnO 2 /polyaniline hybrid sensors. Another way is the surface molecular functionalization of SnO 2 [2]. Functionalization on silicon nanowire field effect transistors has showed changes in the working principle of the sensors, while these sensors are still lack to selectivity. In this case, the interactions are between the gas and the grafted organic layer rather than the metal oxide substrate. These interactions lead to changes in the dipole moment that variate the electrical properties of substrate (e.g. Si) [3]. Molecular modified SnO 2 sensors work at ambient temperature for selective ammonia detection is not reported in literature. This sensors has low power consumption, hence it can be used in smart portable devices.

In this work, we were intended to achieve surface functionalization of SnO 2 thick film. The purpose of functionalization was to passivate the surface states on the SnO 2 sensors by molecular layer aiming to optimize their interactions with ammonia gas. The first step of molecular modification was the attachment of APTES. The second step was to fix alkyl, acid and ester functional groups on APTES modified SnO 2 . These sensors were tested to ammonia gas at room temperature. The selectivity was examined versus ethanol, carbon monoxide and acetone gases.

Experimental section

In this study, SnO 2 thick films are deposited on alumina substrate by screen-printing technique. A semi-automatic Aurel C890 machine was used. The procedures for preparing the SnO 2 ink and sensor fabrication parameters have been described elsewhere [4]. The SnO 2 ink is produced by mixing SnO 2 powder (Prolabo Company) with a solvent and an organic binder. This ink was then screen printed on an alpha-alumina substrate (38×5×0.4 mm 3 ) provided with sputtered gold electrodes. The deposited SnO 2 material is finally annealed for 10 h at 700 °C in air to get SnO 2 film with a thickness of 40 microns. The SnO 2 particles sizes were found to be around 75 nm.

The functionalization of SnO 2 was carried out by two steps which lead to covalent attachment of alkyl, acid and ester end functional groups. The first step is the condensation reaction between the hydroxyl groups present on SnO 2 surface and 3-aminopropyltriethoxysilane (APTES from ACROS Organics). This step generates a film terminated by amine groups (SnO 2 -APTES) which will act as a substrate for the second step of modification. Silanization in liquid phase has been described elsewhere [5]. In a first step, SnO 2 sensors were immersed in 50 mM APTES dissolved in 95 % absolute ethanol and 5 % of deionized water for 5 h under stirring at room temperature. After reaction, the sensors were rinsed with absolute ethanol and dried under N 2 flow. As a second step, these terminal amine groups of APTES allow the coupling reaction with molecules bearing acyl chloride group. In the second step, alkyl, acid and ester end group grafting was achieved by immersing APTES modified SnO 2 in a solution of 10 mM of hexanoyl chloride (98%, ALDRICH, alkyl: C 6 H11ClO), 1,4-butanedicarbonyl chloride (98%, Fluka, acid: C 6 H 8 Cl 2 O 2 ) or methyl adipoyl chloride (96%, Alfa Aesar, ester: C 7 H 11 ClO 3 ), with 5 μL of triethylamine (Fluka) in 5 mL of chloroform as solvent for 12 hours under stirring. The sensors were then rinsed with chloroform and dried under N 2 flow.

The obtained sensors were tested under gases in a test bench at 25 °C to check the effects of functionalization on sensor performance. In this test bench, sensor is installed in an 80 cm 3 glass chamber under constant gas flow of 15 l/h. It is provided with gas mass flow controllers which allow controlling the concentrations of different gases. Sensors selectivity was tested versus ethanol, carbon monoxide and acetone gases.

Results and discussion

Regarding the characterization of the functionalized films by ATR-FTIR, the most important signals corresponding to APTES were found between 800 and 1800 cm -1 as shown in Fig. 1. The peak at 938 cm -1 is attributed to Sn-O-Si stretch [6]. The strong absorption peaks at 1029 and 1125 cm -1 are attributed to Si-O bond of polymerized APTES on the surface. NH 3 + (protonation of amine) and NH 2 vibrational signals are found at 1486 cm -1 and 1570 cm -1 respectively. These peaks confirm the presence of APTES on SnO 2 after silanization.

APTES film was used as a substrate for the second step of functionalization. The second step of sensors modification is the attachment of a film on SnO 2 -APTES, ended with alkyl, acid or ester groups.

Alkyl, acid and ester modified SnO 2 (red, orange and green curves respectively) FTIR spectra presented in Fig. 1 exhibit two peaks at 1547 cm -1 and 1645 cm -1 which correspond to carbonyl stretch mode and N-H bending mode of amide respectively. An additional broad peak between ~ 3000 and ~ 3600 cm -1 corresponds to N-H stretch of amide. These peaks confirm the success of the reaction between amine group of APTES and acyl chloride group and the formation of amide bond. Asymmetrical C-H stretching mode of CH 3 for SnO 2 -APTES-alkyl and for SnO 2 -APTESester appears at 2965 cm -1 . The stretching peak of carbon double bounded to oxygen of ester group of SnO 2 -APTESester is found at 1734 cm -1 (Fig. 1, green curve).

Therefore, FTIR analysis confirms that functionalization is effectively achieved on SnO 2 -APTES after reaction with acyl chloride products by showing the presence of ester, acid and alkyl molecules. The first part of the test under gases was to show the characteristic of the response of different sensors to ammonia gas. As shown in Fig. 2, the sensors were tested to 100 ppm of ammonia balanced with 5% RH air at 25 °C. Figure 2 (red curve) shows that the conductance of pure SnO 2 decreases upon exposure to ammonia gas. This type of response has been founded before by Kamalpreet Khun Khun et al. [7] at temperature between 25 to 200 °C.

APTES modified SnO 2 sensor present no change in conductance upon exposure to 100 ppm of ammonia (Fig. 2, dark green curve). This behavior indicates that the SnO 2 surface is well covered by APTES molecules because the negative response observed on pure SnO 2 is totally inhibited.

SnO 2 -APTES-alkyl, SnO 2 -APTES-acid and SnO 2 -APTES-ester exhibit increase in conductance upon exposure to 100 ppm of ammonia gas as presented in Fig. 2. In addition, the response of SnO 2 -APTES-ester and SnO 2 -APTESacid are more important than of SnO 2 -APTES-alkyl. These responses could be related to the different polarities of the attached end functional groups. Ester and acid are electron withdrawing groups, while alkyl is mostly considered as nonpolar. Ammonia molecule is a nucleophilic molecule (donating). Regarding the interaction between ester and acid from one side and ammonia from the other side, dipole-dipole interaction is taking place. In the contrary, in the case of SnO 2 -APTES-alkyl, the interaction is of induced dipole type because ammonia is a polar molecule and alkyl end group is mostly nonpolar. These two interactions (i.e. dipole-dipole and induced-dipole) result in a modification in the dipole moment which changes the conductance of SnO 2 . It was reported by B. Wang et al. [3], that the dipoledipole interaction is always stronger than induced dipole interaction. That is why the response of ester and acid modified sensors is more significant than alkyl one. Fig. 2. The sensor response of SnO2 (G0=1.4×10 -5 Ω -1 ), SnO2-APTES (G0=7.9×10 -6 Ω -1 ), SnO2-APTES-alkyl (G0=1.5×10 -5 Ω -1 ), and SnO2-APTES-ester (G0=9.5×10 -6 Ω -1 ) to 100 ppm ammonia gas balanced with humid air (5%RH) at 25 °C.

Figure 3 shows that the SnO 2 -APTES-ester sensor has almost no change in conductance upon exposure to 50 ppm of ethanol, carbon monoxide and acetone at 25 °C. This means that ester modified sensor is selective to ammonia, at least in regards of the three tested gases. SnO 2 -APTES-acid is less selective to ammonia than SnO 2 -APTES-ester with respect to ethanol and carbon monoxide. SnO 2 -APTES-acid gives response to ethanol and carbon monoxide which are 1.05 and 1.04 respectively. SnO 2 -APTES-acid shows no response to acetone gas.

Conclusion

Molecularly modified SnO 2 thick films were produced by screen printing and solution chemical processes. The functionalized sensors by APTES were used as an amine terminated substrate for modification by alkyl, acid and ester functional groups. Alkyl, acid and ester modified SnO 2 -APTES sensors show response to ammonia in the opposite sense with respect to SnO 2 . Ester modified sensor is selective to ammonia gas at room temperature with respect to reducing gases like ethanol, carbon monoxide and acetone. The sensitivity of this sensor in real condition with high humidity level, as well as the detection mechanism will be more deeply investigated in the future work.

Fig. 1 .

 1 Fig. 1. ATR-FTIR spectra of SnO2 (black curve), SnO2-APTES (blue curve), SnO2-APTES-alkyl (red curve), SnO2-APTES-acid (orange curve), and SnO2-APTES-ester (green curve) films.

Fig. 3 .

 3 Fig. 3. The sensor response of SnO2-APTES-ester and SnO2-APTES-acid upon exposure to 50 ppm of ammonia, ethanol, and acetone gases in air (5%RH) at 25 °C.


Alistair Dr

Mcnair

Gabriel E Machovsky-Capuska

Mark G R Miller

Fabiola R O Silva

Christophe Amiot

Karen A Stockin

Alistair M Senior

Rob Schuckard

David Melville

David Raubenheimer

The nutritional nexus: linking niche, habitat variability and prey composition in a generalist marine predator

Keywords: niche theory, multidimensional nutritional niche framework, nutritional landscapes, multivariate ellipse-based Bayesian approach, bio-logging, seabirds

1. Our understanding of the niche concept will remain limited while the quantity and range of different food types eaten remains a dominant proxy for niche breadth, as this does not account for the broad ecological context that governs diet. Linking nutrition, physiology and behaviour are critical to predict the extent to which a species adjusts its nutritional niche breadth at the levels of prey ("prey composition niche", defined as the range of prey compositions eaten), and diet ("realized nutritional niche" is the range of diets composed through feeding on the prey).

2. Here we studied adult-chick rearing Australasian gannets (Morus serrator) to propose an integrative approach using sea surface temperature anomalies (SSTa), geographic location and bathymetry over different years, to explore their relationship with the nutritional composition of prey and diets (i.e., prey composition and nutritional niche breadth), habitat use and foraging behavior.

3. We found that gannets feed on prey that varied widely in their nutritional composition (have a broad prey composition niche), and composed diets from these prey that likewise varied in composition (have a broad realized nutritional niche), suggesting generalism at two levels of macronutrient selection.

Introduction

The niche concept is a powerful tool in ecological and evolutionary theory. However, niche definitions can be vague and there are often difficulties in measuring and characterizing niches [START_REF] Pulliam | On the relationship between niche and distribution[END_REF][START_REF] Kearney | Habitat, environment and niche: what are we modelling?[END_REF][START_REF] Newsome | A niche for isotopic ecology[END_REF]. Niche breadth, in particular, has been frequently linked to dietary generalism and is often characterized in terms of food types ingested and/or their energy content [START_REF] Futuyma | The evolution of ecological specialization[END_REF]. Thus, it is widely believed that generalists consume a wide variety of foods and have a wide niche, whereas specialists consume a narrow range of foods and have a narrow niche [START_REF] Ducatez | Ecological generalism and behavioural innovation in birds: technical intelligence or the simple incorporation of new foods[END_REF]. However, the nutritional implications of niche breadth are seldom considered in the application of niche theory. This is an important omission, because nutrients provide the mechanistic link between an animal's foraging choices and fitness, and are therefore

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indispensable for understanding the distributions of animal populations [START_REF] Raubenheimer | Match and mismatch: conservation physiology, nutritional ecology and the timescales of biological adaptation[END_REF].

Nutritional ecology provides a flexible context for understanding the intricate interactions between organisms and their nutritional environment [START_REF] Parker | Nutrition integrates environmental responses of ungulates[END_REF]Raubenheimer, Simpson & Mayntz 2009). A conceptual and analytical framework from nutritional ecology called nutritional geometry (NG) has enabled scientists to gain a new ecological perspective of nutrition by simplifying the complexities of modelling foods (hereafter prey) in relation to foraging behaviour, physiology and geographic processes [START_REF] Raubenheimer | The geometry of compensatory feeding in the locust[END_REF][START_REF] Raubenheimer | Toward a quantitative nutritional ecology: the right-angled mixture triangle[END_REF]. Recently, NG was used to develop a multidimensional nutritional niche framework (MNNF) to unify food choices and diet composition into a multi-level classification of dietary generalism (Machovsky-Capuska et al. 2016a). This novel approach allows the characterization of niche breadth via the macronutrient composition of diets that can sustain a population (i.e. their realized nutritional niche), and the range of prey compositions ("prey composition niche") and physical and ecological attributes of prey that a population can exploit (i.e. their food exploitation niche).

It has been suggested that nutritional niche breadth is shaped by several non-exclusive factors. First, in order to meet potentially changing nutritional requirements, foragers must adjust their foraging behaviour to select combinations of prey available to provide the target mix of nutrients (Machovsky-Capuska et al. 2016b). Second, the location and quality of foods are likely to influence prey consumption and foraging decisions [START_REF] Spitz | Cost of living dictates what whales, dolphins and porpoises eat: The importance of prey quality on predator foraging strategies[END_REF][START_REF] Machovsky-Capuska | Foraging behaviour and habitat use of chick-rearing Australasian Gannets in New Zealand[END_REF]. Third, interactions between bathymetry, physical and biological processes promote nutrient-rich environments with high prey quality [START_REF] Hunt | Comparative foraging ecology of planktivorous auklets in relation to ocean physics and prey availability[END_REF]. Fourth, environmental fluctuations influence the habitat in which a population can forage and subsist [START_REF] Costa | A conceptual model of the variation in parental attendance in response to environmental fluctuation: foraging energetics of lactating sea lions and fur seals[END_REF][START_REF] Carroll | High sea surface temperatures driven by a strengthening current reduce foraging success by penguins[END_REF], for example variation in sea surface temperature [START_REF] Montevecchi | Centurial and decadal oceanographic influences on changes in northern gannet populations and diets in the north-west Atlantic: implications for climate change[END_REF][START_REF] Perry | Climate change and distribution shifts in marine fishes[END_REF]. Former dietary niche

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This article is protected by copyright. All rights reserved. characterizations have been hampered by inadequate consideration of these complex factors.

The MNNF approach, however, attempts to place diet in the context of these variables, thus contributing to a better understanding of the constraints and opportunities that influence diet breadth in animals.

Marine apex predators are long-lived species that forage in complex three dimensional environments, and therefore represent an ideal group to better understand dietary generalism in the wild [START_REF] Österblom | Junk-food in marine ecosystems[END_REF][START_REF] Spitz | Prey preferences among the community of deep-diving odontocetes from the Bay of Biscay, Northeast Atlantic[END_REF][START_REF] Spitz | Cost of living dictates what whales, dolphins and porpoises eat: The importance of prey quality on predator foraging strategies[END_REF][START_REF] Malinowski | Prey use and nutritional differences between reproductive states and age classes in Atlantic spotted dolphins (Stenella frontalis) in the Bahamas[END_REF]Machovsky-Capuska et al. 2016c;[START_REF] Denuncio | Population variance in prey, diets and their macronutrient composition in an endangered marine predator, the Franciscana dolphin[END_REF]. Understanding the foraging goals of marine predators is pivotal to predicting how they will respond to environmental changes in prey availability and composition [START_REF] Tait | Nutritional geometry of gannets and the challenges in field studies[END_REF]. Although habitat use is a central aspect of foraging, marine ecologists often study foraging behaviour in isolation, without addressing the multiple variables and scales that shape their environments [START_REF] Austin | Linking movement, diving, and habitat to foraging success in a large marine predator[END_REF]. Gannets (Morus spp.), in particular, have been extensively studied with respect to both their foraging behaviour and food preferences. Based on the diversity of prey they consume, gannet dietary patterns have often been described as generalist, opportunistic or flexible feeders [START_REF] Bunce | Changes in the diet of the Australasian gannet (Morus serrator) in response to the 1998 mortality of pilchards (Sardinops sagax)[END_REF][START_REF] Lewis | Contrasting diet quality of northern gannets Morus bassanus at two colonies[END_REF][START_REF] Montevecchi | Binary dietary responses of northern gannets Sula bassana indicate changing food web and oceanographic conditions[END_REF][START_REF] Wanless | Later breeding in northern gannets in the eastern Atlantic[END_REF][START_REF] Ropert-Coudert | Underwater wingbeats extend depth and duration of plunge dives in northern gannets Morus bassanus[END_REF][START_REF] Machovsky-Capuska | Foraging behaviour and habitat use of chick-rearing Australasian Gannets in New Zealand[END_REF]. Although a few studies have highlighted the importance of prey quality in different gannet populations [START_REF] Bunce | Prey consumption of Australasian gannets (Morus serrator) breeding in Port Phillip Bay, southeast Australia, and potential overlap with commercial fisheries[END_REF][START_REF] Grémillet | A junk-food hypothesis for gannets feeding on fishery waste[END_REF][START_REF] Tait | Nutritional geometry of gannets and the challenges in field studies[END_REF], the extent to which gannets are dietary generalists or specialists in terms of the foods that they exploit and diets that they compose from those foods remains to be established.

Here we combine niche theory and nutritional geometry, with data from Global Positioning System (GPS) data loggers, dietary analysis, macronutrient composition of prey and diets with a multivariate ellipse-based Bayesian approach to characterize the prey composition niche and realized nutritional niche of Australasian gannets (M. serrator;

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This article is protected by copyright. All rights reserved. hereafter gannets). Specifically, we addressed the following questions: i) To what extent does the nutritional composition of prey and of diets vary spatially and temporally?; ii) Do gannets adjust their foraging behaviour in regards to the macronutrient composition of prey, and iii) Do environmental factors (in this case Sea Surface Temperature anomalies (SSTa) and bathymetry) influence nutritional composition of prey, foraging behaviour and habitat use?

Material and methods

Study area

Fieldwork was conducted on Farewell Spit (FS, New Zealand, 40°33′S, 173°01′E), during the 2 to 5-week-old chick-rearing period in December and January 2011-2012[START_REF] Syväranta | An empirical evaluation of the utility of convex hull and standard ellipse areas for assessing population niche widths from stable isotope data[END_REF][START_REF] Santhanam | Nutritional marine life[END_REF][START_REF] Santhanam | Nutritional marine life[END_REF]-2015and 2015[START_REF] Core | R: A language and environment for statistical computing[END_REF]. FS is a beach colony located at sea level with a population of gannets estimated at 3,900 breeding pairs [START_REF] Schuckard | Diet of the Australasian gannet (Morus serrator) at Farewell Spit, New Zealand[END_REF].

Nutritional composition of prey and diets and niche breadth

Adult gannets captured using a blunt-tip shepherd's crook, were banded with an individually numbered metal ring on their leg and a unique mark on their chest using non-toxic Sharpie markers ©. These techniques enabled us to capture and track always different individuals.

Birds were handled for <10 min, and soon after released at the edge of the colony. This study was conducted under Sydney Animal Ethics Committee (N00/7-2013/3/6016), Massey University Animal Ethics Committee (13/65) and the New Zealand Department of Conservation (35189-FAU).

Regurgitations were collected from different individuals over four breeding seasons (2011-2012 n=24, 2013-2014 n= 35, 2014-2015 n=51, and 2015-2016 n=64). As gannets are known for transporting recently captured undigested prey in their proventriculus, we collected regurgitations as soon as they returned from foraging to the colony (Machovsky-

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This article is protected by copyright. All rights reserved. Capuska et al. 2011a) reducing the loss of prey macronutrient and water content [START_REF] Montevecchi | Dehydration of seabird prey during transport to the colony: effects on wet weight energy densities[END_REF]. Samples were collected from spontaneous regurgitations or after a 30 sec throat massage during handling, and stored in individual polythene bags at -20 °C within five hours of collection.

Samples were defrosted, individual prey items were weighed to 0.1 g and the total length measured to 0.1 mm prior to taxonomic identification using published guides [START_REF] Paulin | New Zealand Fish. A complete guide[END_REF]. Following [START_REF] Duffy | Diet studies of seabirds: a review of methods[END_REF], we calculated: i) the mass contribution of each prey items to the total diet as a mass percentage (M%), ii) the percentage of the total number of prey item contributed by individuals of a particular species as a numerical abundance percentage (N %), and iii) the percentage of gannets that had a particular species in their diet as a frequency of occurrence percentage (F %).

We followed the methodology established by [START_REF] Tait | Nutritional geometry of gannets and the challenges in field studies[END_REF] and only selected prey for proximate composition analyses with the following characteristics: a) undigested prey samples and b) from the most representative prey items that contributed > 1% (wet mass) to the diets of gannets. Given that carbohydrate content is a minimal nutritional component of most marine prey [START_REF] Craig | Comparative estimations of the energy content of fish tissue from bomb calorimetry, wet oxidation and proximate analysis[END_REF] and fresh water is only available to seabirds from food moisture [START_REF] Montevecchi | Dehydration of seabird prey during transport to the colony: effects on wet weight energy densities[END_REF], the proximate composition analysis and our comparisons are based on three essential nutrients: protein (P), lipid (L), and moisture (hereafter water -W-). All samples were oven-dried at 60° C, ground to powder with a laboratory mill and then weighed before laboratory analysis. Protein (estimated as Nitrogen x 6.25) was determined using the Kjeldahl procedure (see AOAC 2005 for more details). The method of Mojonnier was used to measure total lipid (hereafter lipid, AOAC 2005). W was estimated by drying the samples in a convection oven at 125°C and combining the water loss with the initial loss from the overnight dry-down [START_REF] Aoac | Official methods of analysis of AOAC International[END_REF]. Ash was determined by ignition in a furnace at 550 °C [START_REF] Aoac | Official methods of analysis of AOAC International[END_REF].

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Under the MNNF (Machovsky-Capuska et al. 2016a) we linked a well-established proportions-based approach (right-angled mixture triangle -RMT-) that enables the modelling of nutritional niches [START_REF] Raubenheimer | Toward a quantitative nutritional ecology: the right-angled mixture triangle[END_REF]) with a multivariate ellipse-based Bayesian approach that generates Standard Ellipses Areas (SEA) to measure isotopic niches breadth from proportions [START_REF] Jackson | Comparing isotopic niche widths among and within communities: SIBER-Stable Isotope Bayesian Ellipses in R[END_REF]. Following [START_REF] Syväranta | An empirical evaluation of the utility of convex hull and standard ellipse areas for assessing population niche widths from stable isotope data[END_REF], in order to account for small sample sizes, we used corrected versions of SEA (SEAc). Hence, this integrative approach was used to measure realized nutritional niche and prey composition niche breadths (SEAc).

Foraging behaviour

Global Positioning System (GPS) data loggers were deployed on different individual adult chick-rearing gannets during three breeding seasons (2011/2012 n=11, 2014/2015 n=17 and, 2015/2016 n=11). Departing birds were captured immediately after adopting the sky-pointing posture for data logger deployments, as described in [START_REF] Machovsky-Capuska | Foraging behaviour and habitat use of chick-rearing Australasian Gannets in New Zealand[END_REF].

Canmore GT-730FL-S (Taiwan) GPS loggers embedded in a Loksak® waterproof bag (Loksak, USA) weighing 45g, were attached with Temflex 1610 tape to the four central tail feathers. Following [START_REF] Machovsky-Capuska | Foraging behaviour and habitat use of chick-rearing Australasian Gannets in New Zealand[END_REF], loggers were programmed to record data related to position (latitude, longitude, and altitude), speed and time at 1-sec intervals.

Marked birds were recaptured upon arrival at the colony after one foraging trip, and loggers and tape strips were retrieved.

Gannet GPS data were speed filtered following [START_REF] Mcconnell | Foraging ecology of southern elephant seals in relation to bathymetry and productivity of the Southern Ocean[END_REF] (removal of points >75 km/h), and standardized to a 2 second interval between points (minimum interval observed in data; season 2011-2012), prior to analysis. Individual foraging trips were extracted using BirdLife International's 'marine IBA' R package [START_REF] Lascelles | Applying global criteria to tracking data to define important areas for marine conservation[END_REF]. Previous studies have shown that gannet dive durations are primarily between 3-

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This article is protected by copyright. All rights reserved. 8 sec (Machovsky-Capuska et al. 2011b, 2012); in this study dive locations were inferred from interruptions of between 3-8 sec in GPS signals from our high resolution loggers since interruptions exceeding > 10 sec are likely to be related to loss of satellite signal reception [START_REF] Pichegru | Foraging behaviour and energetics of Cape gannets Morus capensis feeding on live prey and fishery discards in the Benguela upwelling system[END_REF]Machovsky-Capuska et al. 2011b[START_REF] Santhanam | Nutritional marine life[END_REF][START_REF] Moseley | Foraging ecology and ecophysiology of Cape gannets from colonies in contrasting feeding environments[END_REF]. Using the GPS data, we calculated a range of movement parameters for each foraging trip including maximum distance away from the colony (MDC), total foraging path (TFP) and foraging trip duration (FTD). To investigate foraging behaviour, we applied Hidden Markov Models (HMM) to the GPS data. We constructed a single HMM for each year of GPS tracking, including an identifier for each trip, using the package 'moveHMM' [START_REF] Michelot | moveHMM: an R package for the statistical modelling of animal movement data using hidden Markov models[END_REF]. For each consecutive GPS point, the step length and turning angle were calculated, producing three distributions consistent with resting (slow sinuous movement), foraging (medium speed sinuous movement) and transiting (fast directed movement) behaviours observed in HMM studies of Sulids [START_REF] Boyd | Movement models provide insights into variation in the foraging effort of central place foragers[END_REF][START_REF] Oppel | Foraging distribution of a tropical seabird supports Ashmole's hypothesis of population regulation[END_REF]. The fitted HMMs were then used to classify each GPS point as either: foraging, resting or transiting, and from this we calculated the foraging time (FT) and transiting time (TT) of each trip [START_REF] Miller | Sexual segregation in tropical seabirds: drivers of sex-specific foraging in the Brown Booby Sula leucogaster[END_REF]. For each gannet, we defined the general use foraging area by estimating the 95% utilization distribution (UD 95) and the prey capture area by obtaining the 50% utilization distribution (UD 50) from kernel analysis of their dive locations (Worton 1987). Kernels were constructed and linked with bathymetry in the package 'adehabitat HR' [START_REF] Calenge | The package 'adehabitat' for the R software: a tool for the analysis of space and habitat use by animals[END_REF]) with a grid size of 0.5 km and a smoothing parameter (h) of 5 km, identified as the most appropriate area-restricted search scale [START_REF] Lascelles | Applying global criteria to tracking data to define important areas for marine conservation[END_REF].

Sea surface temperature and bathymetry

Satellite-derived Sea Surface Temperature (SST, MODIS-Aqua) at a resolution of 0.01° x 0.01° were obtained from Giovanni data portal (http://giovanni.gsfc.nasa.gov/giovanni/).

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Monthly SST was acquired within 4 km of FS colony from December 2006 to December 2016. We obtained the mean SST during December-January of each season (2011-2012: 18.1 ± 0.3; 2013-2014: 17.9 ± 0.6; 2014-2015: 18.7 ± 0.0 and 2015-2016: 19.2 ± 1.3) compared with the 10 years December-January SST mean (18.3 ± 1.0°C) to establish potential warmer or colder anomalies (SSTa) in the gannet's foraging area. We also accessed bathymetry measurements from the New Zealand 250m gridded bathymetric dataset using the National Institute of Water and Atmospheric Research (NIWA) website (https://www.niwa.co.nz/ourscience/oceans/bathymetry).

Nutritional landscapes

For each of the tracked gannets that regurgitated upon logger retrieval (2011-2012, n=3; 2014-2015, n= 8; 2015-2016, n=10), we established "nutritional landscapes" (hereafter nutriscapes), linking the nutritional content of prey (wet mass protein to-lipid ratio -P:L-) to the most likely geographic area of capture and bathymetry. First, considering gannets' overall high success in prey capture (72%, Machovsky-Capuska et al. 2011a, 2012), we linked each individual's area of capture from dive locations (UD 50, estimated above) with the average wet mass P:L ratio of prey items caught during foraging trips. Second, we then mapped all UD 50s from each sampling year together to identify main nutriscapes and their nutritional composition. If UD 50s from one or more gannets overlapped, we assigned the mean nutritional value to that nutriscape (see Supplementary information for codes).

Data analysis

All analyses were performed in the statistical software environment program R version 3.2.4 (R Core Team 2016). Linear and Generalized linear models (LMs and GLMs) were implemented using the 'lm' and 'glm' functions and Linear mixed models (LMMs) were

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This article is protected by copyright. All rights reserved. performed with 'lme4' package [START_REF] Bates | Fitting linear mixed-effects models using lme4[END_REF]. Data analysed using LMs were initially tested using Levene's test for homoscedasticity and Shapiro-Wilk's test for normality.

Inter-annual differences were evaluated by fitting a 4-level categorical predictor denoting the season in which observations were made in LM/GLM. Evaluating differences in the total number of prey items brought to the colony between seasons, we used a quasipoisson (log-link) GLM where the response was the count of each prey species regurgitated by an individual. Variations in weight and length between seasons of prey species were evaluated using LMs. Weight and length of prey were log-transformed and fitted against the categorical predictor for season.

Following Machovsky-Capuska et al. (2016b), linear mixed models (LMMs) were used to evaluate the between-species variation (quantified as standard deviation, -SD-) in the proximate composition of prey. The LMM were implemented with the 'lmer' function in the package 'lme4' [START_REF] Bates | Fitting linear mixed-effects models using lme4[END_REF] and fitted the logit transformation of the wet mass proportions of P, L, W, and log ratio of the proportion of protein to lipid (lnPL) from each individual prey item, with species ID as a random effect. The statistical significance of between-species variance was assessed using a likelihood ratio test with the 'rand' function in the package 'lmerTest' [START_REF] Kuznetsova | lmerTest: Tests for random and fixed effects for linear mixed effect models[END_REF].

To explore whether the nutritional composition (log wet mass proportion of P, L and lnPL and W) of diets fluctuated over seasons, we fitted a LMs with the nutritional composition of interest (as per above) from each diet sample as the response. Seasonal differences in SEAc were estimated via Bayesian interference (SEAb) using Markov chain Monte Carlo simulation with 10 4 iterations with 95% credible intervals (CI) among groups [START_REF] Jackson | Comparing isotopic niche widths among and within communities: SIBER-Stable Isotope Bayesian Ellipses in R[END_REF]. Following [START_REF] Pelletier | Fine-scale spatial age segregation in the limited foraging area of an inshore seabird species, the little penguin[END_REF], this method enables direct interpretations of the differences in SEAb that we tested using LM.

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Seasonal differences in habitat use and foraging behaviour parameters were evaluated by fitting an LM with a 3-level categorical predictor for each season. Following [START_REF] Bonett | Sample size requirements for estimating Pearson, Kendall and Spearman correlations[END_REF], we preformed Pearson correlations to explore possible seasonal relationships between niche breadths (SEAc) with habitat use (UD50 and UD95) and foraging behaviour (TFP and FTD).

Bathymetry differences between seasons were tested using LM. To assess the influence of SSTa on foraging behaviour, habitat use parameters and nutritional composition of prey (as described previously), LMs were used. Here each outcome was fitted against the SSTa of the time at which the observation was made (binary predictor; colder or warmer than the 10 years mean). MDC, FTD, Total dive duration were log (natural) transformed to ensure the data was normally distributed.

Nutritional niche breadths were calculated using SIBER package (Stable Isotope Bayesian Ellipses) in R version 3.2.4. We report parametric data as mean ± standard error (SE) unless otherwise stated. For among-season differences in outcomes, we present overall effects from LMs/GLMs.

Results

Nutritional composition of prey, diets and niche breadth

A total of 172 regurgitations were collected over four breeding seasons (Table 1). A total of 1341 prey items were identified from these samples, including eight species of fish kahawai (Arripis trutta), barracouta (Thyrsites atun), garfish (Hyporhamphus ihi), yellow eye mullet (Aldrichetta forsteri), yellow tail jack mackerel (Trachurus spp.), pilchard (Sardinops neopilchardus), saury (Scomberesox saurus) and anchovy (Engraulis australis), and arrow squid (Nototodarus spp.). From the total number of regurgitations, 84.9% contained only one

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This article is protected by copyright. All rights reserved. species of prey, 13.4% contained two species and 1.7% contained three species. Prey items had a mean weight of 22.4 ± 1.1 g and a mean length of 13.4 ± 0.2 cm. From all the prey species, garfish had the highest wet mass P:L ratio (21.4:1.0) whereas barracouta had the lowest P:L ratio (1.5:1.0, Figure 1). The nutrient composition of the different prey species consumed by gannets showed differences in the wet mass proportions of P (estimated between-prey species SD =0.12, χ 2 =22.7, d.f. = 8, P < 0.0001), L (estimated between-prey species SD = 0.64, χ 2 =10.5, d.f. = 8, P < 0.001), the lnPL (estimated between-prey species SD = 0.74, χ 2 = 11.5, d.f. = 8, P < 0.0001) and W (estimated between-prey species SD =0.03, χ2= 53.8, d.f. = 8, P < 0.0001). The SEAc: 9.19 combined with the wide range of P:L wet mass ratios in the prey consumed over four breeding seasons (from 1.5:1.0 to 21.4:1.0) provide an estimate of breadth of the prey composition niche (Figure 1). The realized nutritional niche breadth was also estimated by combining SEAc: 4.65 and the P:L wet mass ratios from the diets of gannets (from 1.5:1.0 to 15.2:1.0) (Figure 1).

The number of prey items per foraging trip was significantly different between years (GLM, F 3,1337 = 15.41, P <0.0001), with the greatest number observed in 2015-2016 (see Supplementary information Table S1). The weight and length of prey items consumed by gannets differed significantly between seasons (LM weight, F 3,1337 = 45.08, P <0.05 and LM length, F 3,1337 = 55.27, P <0.05), with the lightest and smallest consumed in 2015-2016 (see Supplementary information Table S1). The greater number of prey eaten in 2015-2016 did not, however, compensate for their smaller size, as meal sizes were significantly lighter in 2015-2016 than in other years (LM, F 3,168 = 54.33, P <0.05, see Supplementary information Table S1). Inter-annual differences of the nutritional composition of diets were significant for the wet mass proportion of P (LM, F 3,168 = 20.63, P < 0.0001), L (LM, F 3,168 = 23.14, P < 0.0001), W (LM, F 3,168 = 5.35, P < 0.001) and lnPL (LM, F 3,168 = 27.71, P < 0.0001).

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This article is protected by copyright. All rights reserved. Differences between years were also observed in the breadth dimensions of the prey composition niches (LM, F 3,15996 = 29230, P <0.0001) and the realized nutritional niches (LM, F 3,15996 = 50710, P <0.0001) (Figure 2, also see Supplementary information Table S2).

Foraging behaviour

A total number of 39 foraging trips were collected from birds carrying GPS data loggers (Table 2). The foraging habitat ranged from 1100.89 to 1374.24 km 2 for UD95 and from 222.54 to 273.05 km 2 for UD50 (Table 2), with no difference detected between breeding seasons (UD 50, LM, F 2,36 = 0.95, P= 0.33 and UD 95, LM, F 2,36 = 2.04, P = 0.16) (Table 2).

The mean MDC that gannets travelled away from the colony was 56.1 ± 4.5 km (Table 2). Gannets showed the longest FTD in 2015-2016 (LM, F 2,36 = 4.60, P < 0.05) and spent almost 25% more time foraging (LM, F 2,36 = 6.16, P < 0.01) in deeper areas than during other study years (LM, F 2,36 = 5.82, P < 0.01). Total dive duration showed that longest dives were recorded in 2011-2012 (LM, F 2,36 = 3.42, P < 0.05). No significant differences between seasons were observed in the MDC (LM, F 2,36 = 1.31, P = 0.28) and in the TFP (LM, F 2,36 = 0.42, P = 0.66) (Table 2). Although non-significant, negative seasonal trends were found between realized nutritional niche breadths with foraging behaviour and habitat use parameters (SEAc and UD50, Pearson r = -1.00, P < 0.05, n = 6; SEAc and UD95, Pearson r = -0.81, P = 0.40, n = 6; SEAc and TFP, Pearson r = -0.98, P = 0.13, n= 6 and SEAc and FTD, Pearson r = -0.93, P = 0.24, n = 6).

Sea surface temperature anomalies

Strong negative indices (colder water than average) were recorded in 2013-2014 (December-January: -0.5 °C) and 2011-2012 (December-January: -0.3 °C), whereas strong positive

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This article is protected by copyright. All rights reserved. values (warm water than average) were recorded in 2014-2015 (December-January: +0.4 °C) and 2015-2016 (December-January: +0.9 °C).

Foraging behaviour and habitat used were influenced by SSTa. During warmer water periods (positive SSTa) gannets increased their foraging habitat UD95 (km 2 ), maximum distance to the colony (km), foraging trip duration (h), foraging path length (km), transiting and foraging times (h) and bathymetry depth preference (m), whereas during colder water periods (negative SSTa) gannets showed a significant increase in total dive duration (s) (Table 3). SSTa also influenced the nutritional composition of prey and diets consumed by gannets. During colder water periods (negative SSTa), prey species and gannet diets revealed higher wet mass proportions of P and L and lower lnPL than in warmer periods (positive SSTa, Table 4).

Nutritional landscapes

The nutriscapes varied in the nutritional composition of prey, geographic location and bathymetry over the seasons studied. The wet mass P:L ranged from 7.26 to 13.0 in 2011-2012, 6.06 to 15.28 in 2014-2015, and 6.50 to 11.52 in 2015-2016. Gannets dived predominantly in shallow waters (0-50 m) during 2011-2012, moving to deeper areas (50-100m) in 2014-2015 and in 2015-2016 (50-150m) (Figure 3). There were no differences between tracked birds with and without regurgitations in MDC (LM, F 1,37 = 1.66, P= 0.20), FTD (LM, F 1,37 = 1.57, P= 0.48) and bathymetry (LM, F 1,37 = 1.40, P= 0.24), suggesting that the nutriscapes proposed for each breeding season are representative for the wider tracked population. However, as a consequence of lower sample size of tracked birds that regurgitated, the UD50 of nutriscapes did not fully overlap with the UD50 of the wider tracked population (Figure 3).

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Discussion

A mechanistic understanding of the species' niche, including physiology and especially behaviour, is critical to predict how they will adjust to novel circumstances such as environmental fluctuations [START_REF] Kearney | Habitat, environment and niche: what are we modelling?[END_REF]. A useful and robust measure of dietary niche shape and breadth should contemplate the following factors: i) the range of prey consumed;

ii) the evenness of prey components in the diet over time and iii) foraging behaviour and geographic location [START_REF] Bearhop | Determining trophic niche width: a novel approach using stable isotope analysis[END_REF]) and iv) nutritional composition of prey and diets; and v) the influence of environmental fluctuations (e.g. SSTa) (Machovsky-Capuska et al. 2016a). Accordingly, our study yielded several novel insights into the nutritional niche of gannets at different scales. First, we characterized the prey composition and the realized nutritional niches and provide evidence of their seasonal fluctuations in shape and breadth (criteria i, ii and iv above). Second, we demonstrated the importance of linking foraging behaviour and the influence of environmental conditions (SSTa) with nutritional niche theory (criteria iii and v).

Measuring nutritional niches

The ecological niche concept has been fundamental to ecology since its development fifty years ago [START_REF] Chase | Ecological niches: linking classical and contemporary approaches[END_REF]. Although considerable effort has gone into defining, measuring and quantifying the ecological niche, the concept remains poorly characterized [START_REF] Feinsinger | A simple measure of niche breadth[END_REF][START_REF] Kearney | Habitat, environment and niche: what are we modelling?[END_REF][START_REF] Kearney | Modelling the ecological niche from functional traits[END_REF]. While nutritional niches have often been described using carbon and nitrogen either in the form of isotope ratios [START_REF] Newsome | A niche for isotopic ecology[END_REF] or concentrations in food items [START_REF] González | The multidimensional stoichiometric niche[END_REF], the biological and physiological assumption that these concentrations are surrogate of lipids, proteins and carbohydrates may often be incorrect (Raubenheimer, Simpson & Mayntz 2009;Wilder & Eubanks 2010).

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A growing body of evidence suggests that vertebrate predators consume prey that vary in their nutritional and energetic compositions [START_REF] Mayntz | Balancing of protein and lipid intake by a mammalian carnivore, the mink, Mustela vison[END_REF][START_REF] Lenky | Proximate composition and energy density of nototheniid and myctophid fish in McMurdo Sound and the Ross Sea, Antarctica[END_REF][START_REF] Malinowski | Prey use and nutritional differences between reproductive states and age classes in Atlantic spotted dolphins (Stenella frontalis) in the Bahamas[END_REF]Machovsky-Capuska et al. 2016c, d). Here we demonstrated that there is an appreciable variation in the proportional wet mass contribution of P, L, W and PL ratio in the prey species consumed by gannets, which is consistent with previous findings on gannet prey species [START_REF] Tait | Nutritional geometry of gannets and the challenges in field studies[END_REF]Machovsky-Capuska et al. 2016b). These results further support previous suggestions on the importance of nutrient content rather than just energetic value of prey (Machovsky-Capuska et al. 2016d). As expected, the differences in the nutritional values of prey were then translated into seasonal fluctuation in the breadth (SEAc) of both the prey composition niche and realized nutritional niche.

As a best practice to characterize and measure prey composition and realized nutritional niches, we suggest the use of SEAc combined with nutritional ratios. However, as is generally true of measuring niches in wild populations [START_REF] Chase | Ecological niches: linking classical and contemporary approaches[END_REF]Raubehneimer et al. 2015), careful consideration needs to go into sampling design, including how diet is measured, and the sampling effort required to make reliable estimates of diet breadth. There is no simple answer to these questions; each needs to be addressed in relation to the details of particular study systems and research aims.

In our study, we were able to measure diet by soliciting regurgitations from parent birds when they returned to the nest from foraging. A peculiarity of this method is that regurgitations can combine foods that would contribute to the diet of the parents with those that would be provisioned to chicks [START_REF] Ropert-Coudert | A fine-scale time budget of Cape gannets provides insights into the foraging strategies of coastal seabirds[END_REF]). There is no easy way of distinguishing these, and consequently the use regurgitations can be problematic in studies that aim to assess the dietary composition of reproducing adults or of their chicks. The use of regurgitations does not, however, compromise studies that aim to enumerate dietary niches. This is because the niche concept refers to the resources required to maintain the population,

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This article is protected by copyright. All rights reserved. including all stages of the life cycle [START_REF] Pulliam | On the relationship between niche and distribution[END_REF]. Indeed, sampling regurgitations that might have consisted of both adult and chick foods was a benefit in our study, because this approach efficiently encompasses the diets of both stages of the life cycle.

The question of sampling effort is particularly relevant to demonstrating that a species is a dietary specialist. To establish dietary specialism, it would need to be demonstrated that the range of foods eaten is not an artefact of local or otherwise insufficient sampling, but rather a true reflection of the species' biology. This could be done either by ensuring that sampling effort is adequate to establish an accurate measure of diet, or by demonstrating that the animals feed selectively from a broad range of prey options. In contrast, if the data suggest that a population has a broad dietary range, it is extremely unlikely that additional sampling or measuring food availability will suggest that the animal is in fact a dietary specialist; although additional sampling might of course further expand the documented dietary range.

We are confident that the sampling regime in our study has provided a reliable and unique representation of the prey composition (wet mass P:L from 1.5:1.0 to 21.4:1.0 and SEAc: 9.19) and realized nutritional niches (wet mass P:L from 1.5:1.0 to 15.2:1.0 and SEAc: 4.65) of gannets from the study population. Firstly, our data on prey and diet compositions over four seasons is consistent with a previous study of five years diet in gannets at Farewell Spit colony [START_REF] Schuckard | Diet of the Australasian gannet (Morus serrator) at Farewell Spit, New Zealand[END_REF]. Secondly, the range of macronutrients that we recorded in prey and diets consumed by gannets comprises most of the spectrum of marine fish wet mass concentrations of lipid (0.2% -25.0%) and protein (17.0% -25.0%) [START_REF] Stansby | Nutritional properties of fish oils[END_REF][START_REF] Santhanam | Nutritional marine life[END_REF]), and it is thus unlikely that further sampling would have significantly expanded this. The data therefore strongly suggest that gannets are generalists at prey composition and macronutrient levels, similar to Argentine ants (Linepithema humile) and

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Variables that shape the nutritional niche

It has been suggested that a decrease in food sources will cause individuals to increase their time spent foraging and shift their diet pursuing different resources influencing niche width expansion in a population [START_REF] Svanbäck | Intraspecific competition drives increased resource use diversity within a natural population[END_REF][START_REF] Ceia | Annual and seasonal consistency in the feeding ecology of an opportunistic species, the yellow-legged gull Larus michahellis[END_REF]. If only the amount of prey and their energy value are the main drivers of foraging (Stephens & Krebs 1986), we would expect to support this hypothesis showing that gannets increased their foraging effort and niche breadth (SEAc) under reduced prey availability. However, our MNNF showed that in 2011-2012 gannets had the widest prey composition niche and realized nutritional niche while spending the shortest amount of time foraging closer to the colony (MDC), whereas in 2015-2016 they exhibited their narrowest prey composition and realized nutritional niche breadths while spending more time searching for food (TFP), and foraging (h). A likely explanation could be that both patterns are subject to non-exclusive effects of prey availability and nutritional composition, although this remains to be established.

Variation in prey distribution, densities and quality at sea are driven by environmental factors, oceanographic processes and bathymetric features (Weimerskirch, Gault & Cherel 2005;[START_REF] Garthe | Contrasting foraging tactics by northern gannets (Sula bassana) breeding in different oceanographic domains with different prey fields[END_REF]. SST anomalies are known to drive spatial and temporal changes in the availability of pelagic prey [START_REF] Montevecchi | Centurial and decadal oceanographic influences on changes in northern gannet populations and diets in the north-west Atlantic: implications for climate change[END_REF][START_REF] Perry | Climate change and distribution shifts in marine fishes[END_REF]. These movements are often linked to primary production events [START_REF] Becker | Ocean climate and prey availability affect the trophic level and reproductive success of the marbled murrelet, an endangered seabird[END_REF] and also fish searching for suitable habitats while adjusting their thermal tolerance to survive [START_REF] Bates | Defining and observing stages of climate-mediated range shifts in marine systems[END_REF]. During warm water events (strong positive SSTa values), gannets increased their foraging habitat (UD95, km 2 ), foraging trip duration (h) and total foraging path (km). This is consistent with previous suggestions that warm water events reduce

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This article is protected by copyright. All rights reserved. primary production and negatively influence prey availability [START_REF] Becker | Ocean climate and prey availability affect the trophic level and reproductive success of the marbled murrelet, an endangered seabird[END_REF], imposing greater travel costs (time and distance) upon the forager and likely influencing their offspring [START_REF] Fritz | Scale-dependent hierarchical adjustments of movement patterns in a long-range foraging seabird[END_REF][START_REF] Grémillet | Offshore diplomacy, or how seabirds mitigate intra-specific competition[END_REF].

Although climate fluctuations are known to influence prey quality in marine [START_REF] Wanless | Low energy values of fish as a probable cause of a major seabird breeding failure in the North Sea[END_REF][START_REF] Österblom | Junk-food in marine ecosystems[END_REF]) and terrestrial environments [START_REF] Raubenheimer | Geometry of nutrition in field studies: an illustration using wild primates[END_REF][START_REF] Rothman | Long-term declines in nutritional quality of tropical leaves[END_REF], the mechanisms behind these effects are probably complex and remain unknown. In our study, strong warm water events negatively influenced the nutritional composition of prey species (wet mass proportions of P and L) and also diets consumed by gannets. The likely explanation is that the gannets' main prey are small anchovy, pilchard and garfish that feed mostly on plankton [START_REF] Schuckard | Diet of the Australasian gannet (Morus serrator) at Farewell Spit, New Zealand[END_REF]) and respond to regional plankton blooms under nutrient-rich conditions [START_REF] Hunt | Comparative foraging ecology of planktivorous auklets in relation to ocean physics and prey availability[END_REF][START_REF] Paul | Pilchard (Sardinops neopilchardus) biology and fisheries in New Zealand, and a review of pilchard[END_REF].

However, warmer waters are often more stratified and characterized by nutrient limitation and reduced plankton productivity [START_REF] Richardson | Climate impact on plankton ecosystems in the northeast Atlantic[END_REF][START_REF] Behrenfeld | Climate-driven trends in contemporary ocean productivity[END_REF]). Thus, declines in nutrient availability strongly influence population structure, size, biomass and quality of prey species with subsequent implications on the trophic webs [START_REF] Fuchs | Plankton community properties determined by nutrients and size-selective feeding[END_REF].

Foraging animals, in the laboratory and the wild, link their movements to the distribution of their food sources [START_REF] Masello | How animals distribute themselves in space: variable energy landscapes[END_REF]. Understanding the factors that make a place a foraging 'hot-spot' is vital to unravel the drivers of prey preferences in marine predators. We presented unprecedented evidence in the form of nutriscapes, linking the nutritional composition with the geographic location of prey capture areas (UD50) of foraging gannets. Over the three seasons studied, the nutriscapes were patchily distributed, fluctuated from shallow to deeper areas and had different nutritional composition. Clearly, the temporal extent of this dataset and the proposed approach, brings a novel opportunity to better understand whether the prey consumed by wild predators could be supplementary

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(similar P:L ratios across prey) or complementary (different P:L ratios) with respect to the diet. Thus this approach could become the stepping stone for research of foraging strategies in marine predators by investigating habitat use and food patch selection and depletion in relation to prey and diet composition and nutrition as previously seen in Guerezas (Colobus guereza) [START_REF] Johnson | Macronutrient balancing affects patch departure by guerezas (Colobus guereza)[END_REF].

Bearing in mind that prey and geographic location was obtained from foraging gannets arriving to colony, nutriscapes should not be considered as a surrogate for qualitative or quantitative prey availability. From our point of view, in spite of the small sample size presented herein, this novel approach provides a unique opportunity to reconstruct foraging behaviors and habitat use linked with geographic location, abiotic factors (e.g. salinity, chlorophyll, sea surface temperature, bathymetry and others) and temporal measures of resource acquisition quantified as specific nutrients. The use of bio-logging sensors including Animal-borne Video and Environmental data collection systems (AEVDs) combined with NG has been proven to yield new insights into marine wild predators nutritional ecology (Machovsky-Capuska et al. 2016c) and could be vital to enhance the resolution and the expansion on the use of nutriscapes. This cutting-edge approach could contribute to either marine, freshwater or terrestrial environments, playing a fundamental role in assessing nutritional decisions based on the nutritional composition of a wide range of species in the wild. Nutriscapes can provide fresh insights in a wide range of research fields including: i) predicting the distribution and expansion of invasive species; ii) understanding the dietary needs and the nutritional composition and availability of habitats for endangered species; iii) exploring critical habitats for species translocations; iv) understanding the location and nutritional value of geographic areas prone to human-wildlife conflict (e.g. fisheries); and v) unravelling traveling routes for migratory species based on nutrient composition and availability.

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Dietary generalism has been suggested to evolve in heterogeneous environments, whereas specialism is a response to a homogeneous environment [START_REF] Senior | An overlooked consequence of dietary mixing: a varied diet reduces inter-individual variance in fitness[END_REF].

Overall, our study suggests that gannets: i) display a high degree of prey and diet composition generalism, being able to prey upon species that vary in nutritional composition, and have a wide nutritional range in their diets; ii) across seasons, nutritional landscapes varied in prey composition, over space, time and bathymetry and iii) during warm water events (strong positive SSTa), gannets expanded their foraging habitat, increased their foraging trip duration while consuming prey and diets low in nutritional composition. Our results highlight the importance of quantifying and characterizing the prey composition and realized nutritional niches to test broader ecological questions to better understand the extent of dietary generalism in the wild.

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Figure 1 .

 1 Figure 1. Right-angled mixture triangle(RMT) showing foraging choices of chick-rearing adult Australasian gannets at Farewell Spit colony. Nutritional composition of prey (grey hollow circles) and diets (black solid symbols). Each prey and diet represents a proportional mixture of protein (P), lipid (L) and water (W). To geometrically define prey and diets in an RMT, % P is plotted against % L. Considering that the 3 components in the mixture sum to 100%, plotting % P (first axis) and % L (second axis) will automatically reflect the value of % W in the third axis[START_REF] Raubenheimer | Toward a quantitative nutritional ecology: the right-angled mixture triangle[END_REF]. The prey composition niche (all the prey consumed by gannets, Machovsky-Capuska et al. 2016) breadth is measured as the area of standard ellipse (SEAc: 9.19, grey solid ellipse). The realized nutritional niche breadth of gannets (all individual diets from the four breeding seasons studied(2011-2012: triangle, 2013-2014: square, 2014-2015: diamond and 2015-2016: circle) is measured as the area of standard ellipse (SEAc: 4.65, black dotted ellipse).

Figure 2 .

 2 Figure 2. Inter-annual differences in the nutritional niche breadth of Australasian gannets. The boxplot shows the credible interval (CI) range for the estimated ellipse area (SEAb) for prey composition niches and realized nutritional niches (diets) across seasons. Boxed areas represent the 50, 75 and 95% credible intervals for the estimated ellipse areas. Black dots and the red crosses represent the mode of SEAb and the maximum likelihood estimates SEAc, respectively. All boxed areas denote significant difference (P< 0.0001).

Figure 3 .

 3 Figure 3. Foraging habitat and dive locations of adult chick-rearing Australasian gannets from Farewell Spit colony (New Zealand, green diamond) during three chick-rearing seasons: a) 2011-2012, b) 2014-2015 and c) 2015-2016. Kernel density Utilization Distributions (UD) show habitat used (UD 95: dotted lines) and prey capture areas (UD 50: solid lines). Nutriscapes linking nutritional content of prey (wet mass protein-to-lipid ratios -P:L-) to the most likely geographic area of captured (coloured areas) and bathymetry. Isobaths expressed in meters (m).

Table 2 .

 2 Foraging habitat and trip characteristics of adult-chick rearing Australasian gannets at Farewell Spit colony over three different breeding seasons. Data presented as mean ± standard error (SE).

	Parameter	2011-2012	2014-2015	2015-2016
	Foraging habitat
	Sample size (N)	11	17	11
	UD95 Individuals (km 2 )	1100.89 ± 247.06 1367.41 ± 432.46 1374.24 ± 473.39
	UD50 Individuals (km 2 )	222.54 ± 83.36	238.99 ± 65.48	273.05 ± 131.00
	Bathymetry (m)	44.86 ± 65.15	74.78 ± 28.84	90.65 ± 25.94
	Foraging trip characteristics
	Max. distance to colony (km)	44.93 ± 9.27	60.52 ± 7.48	57.24 ± 5.79
	Total foraging path (km)	227.91 ± 64.72	262.64 ± 35.21	289.55 ± 27.55
	Foraging trip duration (h)	14.71 ± 3.71	14.88 ± 2.34	26.36 ± 2.97
	Transiting time (h)	2.27 ± 1.75	1.82 ± 1.94	3.34 ± 2.82
	Foraging time (h)	2.97 ± 2.45	3.09 ± 3.45	4.21 ± 3.48
	Total dive duration (s)	6.26 ± 0.87	3.66 ± 0.46	5.25 ± 0.63

Table 3 .

 3 Linear Models (LM) testing the interactions between Sea Surface Temperature Anomaly (SSTa) on foraging habitat and foraging behaviour. SSTa-: colder water periods and SSTa+: warmer water periods. Data presented as mean ± standard error (SE). Significant differences marked in bold.

	Parameter	SSTa-	SSTa+	LM	P
	Foraging habitat
	UD95 Individuals (km 2 )	1110.89 ± 100.86	1367.41 ± 101.93	F= 3.72	<0.05
	UD50 Individuals (km 2 )	222.53 ± 34.03	241.48 ± 17.89	F= 0.71	0.40
	Bathymetry (m)	52.23 ± 17.31	88.72 ± 3.29	F= 4.64	<0.01
	Foraging trip characteristics
	Max. distance to colony (km)	58.26 ± 8.32	74.91 ± 5.52	F=6.71	<0.01
	Total foraging path (km)	251.41 ± 22.98	295.09 ± 22.47	F= 4.38	<0.01
	Foraging trip duration (h)	13.51 ± 3.46	21.34 ± 1.79	F= 5.74	<0.01
	Transiting time (h)	2.59 ± 0.67	4.09 ± 0.40	F= 5.26	<0.01
	Foraging time (h)	3.37 ± 0.96	5.71 ± 0.62	F=5 .61	<0.01
	Total dive duration (s)	4.75 ± 0.49	2.67 ± 0.07	F= 55.34	<0.0001

Table 4 .

 4 Linear Models (LM) testing the interactions between Sea Surface Temperature Anomaly (SSTa) on the nutritional composition of prey and diets (wet mass proportions of P, L, W and lnPL) of adult chick rearing Australasian gannets. SSTa-: colder water periods and SSTa+: warmer water periods. Data presented as mean ± standard error (SE). Significant differences marked in bold.

	Parameter	SSTa-	SSTa+	LM	P
	Prey
	Protein	20.88 ± 0.25	19.79 ± 0.32	F=15.66	<0.001
	Lipid	2.68 ± 0.29	2.03 ± 0.16	F=4.39	<0.01
	Water	72.16 ± 0.42	73.68 ± 0.37	F=3.12	<0.05
	LnPL	2.22 ± 0.13	2.47 ± 0.16	F=8.82	<0.001
	Diet
	Protein	21.71 ± 0.17	20.06 ± 0.13	F= 3.62	<0.01
	Lipid	2.89 ± 0.21	2.25 ± 0.06	F= 20.30	<0.0001
	Water	73.64 ± 0.30	75.70 ± 0.11	F=0.34	0.56
	LnPL	2.11 ± 0.07	2.36 ± 0.11	F=20.20	<0.0001

Acknowledgements

We thank M Ogle, W Cook, J and V Melville, P Jones, EC Benn, K Barna, C Rowe, C Purvin, D Cooper and L Angel for their assistance during fieldwork. Special thanks to PHW Leong and P Jones for support on the technical issues with the GPS data loggers, R Waern for assistance with R software, and J. Hewitt and B. Würsig for valuable comments that enhanced early versions of the manuscript. I Tuck provided guidance on how to access SST data. Aspects of this work were funded by Faculty of Veterinary Science DVC compact fund (The University of Sydney). The Department of Conservation, Golden Bay (New Zealand) kindly allowed the use of their house at Farewell Spit and also assisted on the transport of the field gear. This study

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fisheries, and research in the main world fisheries. New Zealand Fisheries Assessment Report

Data Accessibility

Data used in this manuscript are available from Pangea ® Data Repository: https://doi.pangaea.de/10.1594/PANGAEA.890146 (Machovsky-Capuska et al 2018).

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was conducted under permits from Massey University Animal Ethics committee (13/65) and the New Zealand Department of Conservation (35189-FAU). GEM-C is supported by the Loxton research fellowship from the Sydney School of Veterinary Science, The University of Sydney.

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