dataesr/scientific-paragraphs-categorization huggingface dataset:
These calculated values do not consider any additional volume connected or not to grain boundaries, such as strain-induced cavities or fluid inclusions. Our calculations show that H 2 O content increases with increasing interface density according to a linear relationship. For instance, if grain boundaries have a thickness of 1 nm, we expect between 420 and 750 wt. ppm for the range of 3-D interface density documented in our sample, i. e. , between 1. 2 and 2. 4 µm -1 (Fig. 3a ). In contrast, the linear best-fit correlation of our SIMS dataset follows a very different trend characterized by lower H 2 O contents below ~1. 6 µm -1 , i. e. , in the low-strain zone, and an excess of H 2 O above ~1. 7 µm -1 , i. e. , close by or within the high-strain zone (Fig. 3a ). Furthermore, the linear correlation of our dataset indicates a coefficient (R 2 ) of 0.
3, whereas a graph of the same dataset for H 2 O with respect to the shortest distance from the high-strain zone yields a positive correlation with a linear R 2 of 0. 59 (Fig. 3b ). The distribution of H 2 O in grain boundaries thus correlates better with strain than with interface density. With respect to the bulk H 2 O content in grain boundaries, which corresponds to 1330 ppm (added H 2 O before experiment) minus 700 ppm (550 ppm potentially lost during experiment, plus 150 ppm stored in olivine), we confirm that grain boundaries are characterized by a deficit and then an excess of H 2 O with decreasing distance from the high-strain zone (Fig. 3b ). In Fig. 3c , through normalization of the amount of H 2 O by 3-D interface densities, we further provide an estimate of the H 2 O content per unit of grain boundary segment across the shear zone.
This graph shows that H 2 O increases with decreasing distance from the high-strain zone according to two different signals: one that includes most of the data (39) with a good and positive linear correlation (R 2 = 0. 58) and a second one with a few data (3) out of trend and far above the linear correlation. Together with an excess water storage in the high-strain zone, our dataset therefore highlights 1) an increase of H 2 O per unit of grain boundary with increasing strain, and 2) a few local anomalies of high fluid content with respect to the first-order trend.
2b ). The calculated trends in Fig. 3a  also do not align with our dataset correlation, even if we consider a boundary thickness of 2 nm, which would be needed to account for the surplus of H 2 O. This value is more than twice the thickness observed at pressures higher than 1 GPa  20, 28. Being well in excess of the error bars, these features thus do not support the inference of grain boundaries as unique storage sites for H 2 O. We therefore envisage two other possibilities that we discuss below: (1) an overall expansion of grain boundaries with increasing strain, so that more H 2 O can be included per unit of grain boundary; or (2) creep cavitation forming a volume fraction of cavities in excess of the interface density. The occurrence of a non-uniform boundary film along grain boundaries is very unlikely to occur considering viscous flow at high confining pressure  9.
The olivine matrix deformed by grain-size-sensitive creep with evidence of phase nucleation and grain boundary sliding, which were both active across the shear zone. Together with observations of strain-induced micro-cavities in the high-strain zone  25  , these features support creep cavitation to occur coevally with healing processes during steady-state flow. Considering our SIMS dataset as a proxy of the volume fraction of cavities, we therefore attribute fluid concentration to creep cavitation, either related to a production of more cavities in the high-strain zone, or owing to larger pore sizes as the strain rate increases. Although poorly quantified, the activity of GBS is expected to be inversely related to grain size during diffusion creep  35  : the smaller is the grain size, the higher is the contribution of GBS to deformation with respect to other deformation processes.
The background concentration of H 2 O estimated from the calibration line is ~60 ppm. For data interpolation, we then used the MATLAB software with the griddata function (natural option). Electron backscatter diffraction (EBSD). EBSD was employed for mapping polished sample surfaces (diamond paste of 0. 25 μm followed by colloidal silica) with an EDAX Pegasus system at 20 kV and using a working distance of 15 mm. All maps were acquired using a step size between 0. 1 and 0. 2 μm over areas that averaged ~100 × 100 μm 2 (see Supplementary Fig. S5 ). The data from EBSD maps were processed and "cleaned" using OIM -EDAX software. The "clean-up" procedure involved two iterations of grain dilation and the standardization of both the grain fit and confidence index. The grain size and interface density were then calculated using the open-source MTEX toolbox  44, 45  for MATLAB.
Each spot and related colour coding refers to the measured H 2 O content, including the crystal lattice and grain boundaries. All analyses surrounded by a dotted circle are used in Fig. 3. (c) Mapping of the SIMS dataset across the strain gradient. The interpolation was processed using the griddata function of MATLAB with isocontours increment of 125 ppm. The white line gives the isocontour of added water before experiment. Ol = olivine; Di = diopside; FIB = Focused Ion Beam zone documented in Précigout and Stünitz 25.
Acknowledgements We thank  Etienne Deloule  and  Nordine Bouden  for their help in performing SIMS analyses. We also thank  Rüdiger Kilian  for his help in treating the EBSD data using the MTEX toolbox, as well as  Alexandra R. L. Kushnir  and three anonymous reviewers for their help and comments. This project was funded by the  ETH Zürich  (ETH fellowship application  FEL01 09-3 ),  ERC RHEOLITH  (Grant n°. 290864) and  Labex Voltaire  ( ANR-10-LABX-100-01 ).
A cademic biologists have long advocated for conserving phylogenetic diversity (PD), often (but not exclusively) on the basis that PD is a useful proxy for "feature diversity", defined as the variety of forms and functions represented in set of organisms (see below for an extended discussion of this definition)  [1] [2] [3] [4]. In a recent paper  5  , we assess the extent to which this proxy (which we coined the "phylogenetic gambit") holds in three empirical datasets (terrestrial mammals, birds, and tropical marine fishes) when using functional traits and functional diversity (FD) to operationalize feature diversity. Owen et al. 6  offer a criticism of our methods for quantifying feature diversity with FD and disagree with our conclusions. We are grateful that Owen et al. 6  have engaged thoughtfully with our work, but we believe there are more points of agreement than Owen et al.
Acknowledgments This paper is a joint effort of the sCAP working group funded by sDIV, the  Synthesis Centre of the German Centre for Integrative Biodiversity Research Halle-Jena-Leipzig  and the  Canadian Institute for Ecology and Evolution. FM was supported by an  NSERC   Accelerator Grant  to AOM and a Banting Post-doctoral fellowship. GDR thanks  Mike Steel. We thank  Risa Sergeant  at the  University of Ottawa  for hospitality, and the  Crawford Lab for Evolutionary Studies at SFU  for discussion. M. C. , D. M. , and C. T. are members of the FREE working group at the  CESAB-FRB.
Recording Device Simultaneous audio and video recordings were collected using a waterproof 360° audio-video system named BaBeL (BioAcoustique, Bien-Être et Langage) (López-Marulanda, Adam & Delfour, 2017). Video data were collected using two Kodak SP360 video cameras (wide angle of 214°), one on each side of BaBel to allow a 360° view. These cameras were positioned underneath the waterproof housing of a digital audio recorder ZOOM H6 plugged to five calibrated and automatically synchronized Aquarian H2a-XLR hydrophones. The synchronized hydrophones were positioned to obtain the time delay of arrival in order to provide 3D estimations of dophin positions. Audio recordings were conducted at a 96-kHz sampling frequency and coded on 24 bits. All details about the geometry of the hydrophone array are described in  López-Marulanda et al.
(2017). Two successive claps were made at the beginning of the recording session: one in front of each camera in order to manually synchronize videos with audio recordings during the a posteriori analysis with specific video editing software (Final Cut Pro X 10. 1. 3 © Apple Inc. ). A single video file was created from the two Kodak SP360 video cameras in the same window, which was associated with one of the five audio tracks and its corresponding turning spectrogram (FFT size: 1024, overlap 50%, Hanning window) provided by the free software Audacity 2. 0. 6 (GNU General Public License). We chose to add only one track in the video as a reference.
Data Analysis The five audio tracks from each recording were used for the acoustical analysis, conducted by a custom-made program in MATLAB® version 2013a (Mathworks, Natick, MA)  (Blanchard, 2015). This custom-made program is based on a geometrical localization method that estimates the position of the vocalizing dolphin. The localization given by the TDOA was linked to the video using a conversion position-pixel  (López-Marulanda et al. , 2017). The localized dolphin was identified using body size, color, and any particular body marks. We selected sequences in which the calf was present in the video, a click train was emitted, and our customized program localized the emitter of the vocalization. For these sequences, we used the pulse train analysis function of Avisoft-SASLab Pro version 5.
, 2002; Reiss, 1988). In this study, we presented the BaBeL system and a geometrical localization methodology that allowed analysis of a dolphin's click trains, which occurred in varied circumstances, with the presence of other dolphins around and regardless of its position in relation to the recording device. For the first time, we were able to analyze the ontogenesis of a calf's acoustical exploratory behavior while it remained in its social group. Nevertheless, our methodology presents several limitations. First, the recording device was maintained in close proximity of the wall so that reverberations of the sounds caused our custom-made program to identify the wall as the source of sound in 29. 79% of the analyzed sequences. Second, the identification of the vocalizing dolphin is only possible if the animal is in the range of vision of the video camera  (López Marulanda et al.
, 2014; Mojtahid et al. , 2015). In this study, we explore the potential of using single-chamber Ba/Ca, Mn/Ca, and Na/Ca, analyzed with laser ablation ICP-MS (LA-ICP-MS) in the planktonic foraminifer Globigerinoides ruber and in six species of benthic foraminifera (Bolivina alata, Globobulimina affinis, Gyroidina altiformis, Gyroidina orbicularis, Hanzawaia boueana, Uvigerina peregrina), as potential proxies for past changes in productivity, oxygenation and salinity during sapropel S1. In addition to contributing to a better constraint of the tested paleoproxies for future paleoenvironmental applications, this study presents a unique coupled planktonic-benthic foraminiferal dataset of laser-ICPMS elemental ratios performed on single species from the eastern Mediterranean and during a sapropel event.
cm -2. Time resolved signals were selected for integration, background subtracted, internally standardized to 43 Ca, and calibrated against a glass standard (NIST SRM610), using Thermo Qtegra software version 2. 2. 1465. 44 and reference values from  Jochum et al. (2011). The glass standard was ablated at a higher energy density (5 J cm -2 ). Using different ablation energies for glass and calcite was previously shown not to affect the analyses  (Wit et al. , 2010). Integration windows that separate the calcitic signal from background and detection of any contaminants at the test surface were done using Thermo Qtegra software version 2. 2. 1465. 44. Each laser ablation measurement was screened for contamination and diagenetic surface coatings by monitoring Al, Mn, and Fe. On encountering surficial clay contamination (indicated by Al and Fe peaks) the data integration interval was adjusted to exclude the zone of Al, Mn, and Fe enrichment (if present).
Benthic foraminiferal counts and low oxygen indicative species From ~5. 5 to 10. 9 cal ka BP, thirty-seven samples (every 2 cm) were analyzed for their benthic foraminiferal content. Samples were dried and washed over a 150 μm sieve. Benthic foraminiferal specimens were picked under a stereomicroscope, stored in separate Chapman slides (for each sample), and identified at a species level. In this study we only present the total number of counted specimens and the cumulative percentages of low oxygen indicative species (Cassidulinoides bradyi, Chilostomella oolina, Fursenkoina rotundata and Globobulimina affinis) as defined by Schmiedl et al. (2010) from the nearby sediment core SL112 (Fig. 1a ). To calculate the cumulative percentages, a statistical threshold of 10 individuals was established.
Time series analyses In order to explore the frequencies in the temporal variability of selected parameters (Ba/Alsed, V/Alsed, PFAR, Ba/Cabenthics), we removed the dominant low-frequency 'precession' peak by applying a bandpass filter stopping wavelengths >2. 6 kyr and analyzed the filtered records using REDFIT analyses. These were performed using the PAST software package  (Hammer et al. , 2001). Prior to these analyses, data were resampled (i. e. interpolated between data points) at continuous and even spaced time resolution (according to the average time-resolution; Ba/Al sed and V/Alsed = 39 yrs, PFAR = 175 yrs, and Ba/Ca benthics = 170 yrs). To overcome the large intraspecimen and interspecimen variability that is a common feature in all El/Ca ratios, analyses of Ba/Cabenthics were performed on the 2-pt average values of Ba/Cabenthics measurements including all species.
0 cal ka BP to a maximum of 0. 3‰ at 10. 5 cal ka BP. We observe a large variability in δ 13 CU. peregrina during the S1b phase (Fig. 3b ). No data are available between 10. 0 and 8. 3 cal ka BP because of insufficient amounts of Uvigerina tests being present in this interval. The total number of benthic foraminifera range from a minimum of 0 individuals at 9. 4 cal ka BP to a maximum of 990 counted specimens (~1644 ind. /cm²/ka) at 10. 4 cal ka BP (Fig. 3b ). Overall low values are present across the S1 deposit with two critical periods (9. 6 -8. 5 and at 7. 7 ka cal BP) presenting less than 30 individuals (Fig. 3c ). These periods are characterized by a high percentage of low oxygen indicative species (C. bradyi, C. oolina, F. rotundata and G. affinis) (Fig. 3d ). An interruption at ~8 cal ka BP is observed through an increase in abundances reaching 480 individuals (Fig.
What processes during Sapropel 1 formation can be drawn from El/Ca proxies? Despite the numerous limitations that may question at present the reliability of benthic foraminiferal Ba/Ca, Mn/Ca and Na/Ca ratios as paleo-proxies, the uniqueness of the present study's El/Cabenthicsdataset justifies the following attempt to uncover the environmental signal hidden behind these biases. Amongst the three tested El/Ca proxies, Ba/Cabenthics appears to be the most reliable one, because the increase in Ba/Cabenthics during S1 is coherent with increased sedimentary Ba/Al and hence with the expected enhanced productivity as shown also by the PFAR values  (Mojtahid et al. , 2015)  (Fig. 7 ). In our core study and throughout S1,  Hennekam et al. (2014)  report that export productivity (Ba/Al) and bottom water redox conditions (V/Al) vary simultaneously with Nile discharge (δ 18 OG.
Conclusions This study provides a unique El/Ca-dataset measured on planktonic and benthic foraminifera from the SE Mediterranean. The study of the well-constrained sapropel S1 period allowed us to evaluate the robustness of newly developed proxies (Ba/Ca, Mn/Ca, Na/Ca). We draw the following key conclusions: 1) Ba/Ca, Mn/Ca and Na/Ca ratios in fossil planktonic and benthic foraminifera follow in many cases the expected surface and bottom water characteristics during S1 formation. Ba/CaG. ruber is a reliable tracer for Ba 2+ -enriched Nile freshwaters, whereas Ba/Cabenthics track enhanced paleo(export) productivity. The overall decrease in Na/Ca of both planktonic and benthic foraminifera during S1 is coherent with excess Nile River runoff resulting in a decrease in surface and bottom water salinities in the <500m water column of the Levantine basin.
Acknowledgments This study is part of a project MADHO (MediterraneAn Deltas in the Holocene) financed by the international program MISTRALS PaleoMEX. The "Région Pays de la Loire" is acknowledged for financial support to TANDEM project (PI: M. Mojtahid) involving the 18-month postdoctoral fellowship provided to Sandrine Le Houedec. NWO is acknowledged for financial support to PASSAP cruise and PASS2 and PALM projects. Data to support this article are from University of Angers (France) and University of Utrecht (The Netherlands). The data are available online as supplementary material and/or by contacting the first author (e-mail: meryem. mojtahid@univ-angers. fr).
, 2016 Rahman et al. , , 2017)). Indeed, variations in authigenic Ge burial fluxes are likely responsible for the large seawater Ge/Si fluctuations over glacial-interglacial cycles  (Mortlock et al. , 1991; Hammond et al. , 2004b; Baronas et al. , 2016). A fully constrained global Ge isotope budget and unambiguous interpretation of past δ 74 Ge variations in seawater therefore require knowledge of the chemical and isotopic Ge behavior during marine sediment authigenesis. Here, we present dissolved Ge/Si, δ 74 Ge, and various other solute concentration data at three different continental margin sites. Sediment pore water signatures were used to track the potential isotopic fractionation with progressing sediment diagenesis and authigenesis, while sediment core incubation data were used to constrain the net effect of these processes on the benthic flux.
Ge (‰) FIGURE 2 | Pore water profiles of Gulf of Mexico (GoMex) sediments collected from three cores at Sta. 2 (Table  2 ;  Baronas et al. , 2016). GoMex seawater data are plotted at an arbitrary depth above the sediment-water interface. (A) Ge isotope composition of composite samples; vertical error bars show the depth range of combined samples. Note the reverse x-axis; (B) Ge/Si of composite samples as in (A). Note the log scale of x-axis. The green band shows the estimated δ 74 Ge and Ge/Si composition of bSi in GoMex shelf area affected by the Mississippi River (pink dotted line; see text). The gray bands show the typical composition of lithogenic silicates  (Escoube et al. , 2012; Rouxel and Luais, 2017) ; (C) Ge and Si concentrations, including additional Si data from a separate core MC-5; (D) NH 3 , Fe, and Mn concentrations in MC-5; (E) Sulfate concentrations in MC-5, corrected for salinity.
All the data except for δ 74 Ge were previously published in  Baronas et al. (2016). benthic flux. Orange, most likely FeOx, flock was observed on sediment surface of most cores. In addition, core MC-5A, which had negligible benthic Ge flux, also had a large burrow at the sediment water interface and seemed the most disturbed during recovery, including air bubbles trapped in the core liner. In support of this hypothesis, the benthic dissolved Fe flux at SPB was previously determined by in-situ incubations and water column measurements to often be 1-2 orders of magnitude lower than that based on pore water Fe gradients, suggesting that a large fraction of dissolved Fe is captured near the water-sediment interface  (Elrod, 2004; Severmann et al. , 2010; John et al. , 2012). In summary, the core incubations performed on SPB and SMB sediments together represent a range of bottom redox conditions.
Modeling Ge Isotope Mass Balance During Core Incubations Although the large amount of seawater needed for δ 74 Ge analyses prevents the collection of δ 74 Ge time-series data during core incubations, the final post-incubation δ 74 Ge signature (δ 74 Ge final ) can be used to assess the isotopic composition of Ge flux that has been affected by non-opal phases. To do this, a simple mass balance model was built, partitioning Ge amounts dissolved and sequestered by the various phases, and their associated Ge isotope signatures (Figure  4 ). The model was implemented using MATLAB R2018b, and the source code is given in the Supplementary Material. For each incubated sediment core, the amount of Ge (n i , in mol) in the overlying post-incubation water is the sum of Ge initially present prior to the incubation and the net added via the benthic flux during incubation: n final = n initial + n inc (1) n initial = [Ge] initial • V initial (2) n inc = F inc • t • A (3) where  [Ge]  initial and V initial are the measured Ge concentration and volume of the pre-incubation overlying water.
All results below are reported as the 25-75% confidence interval of the 1 million Monte Carlo calculations. The calculations were performed using MATLAB R2018b, and the source code is given in the Supplementary Material. Here, we use our data from the San Pedro Basin to determine the fraction of lithogenic particulate Ge that gets released into pore waters (f Ge lith-released ) and, in the absence of similar data from other sites, apply this value globally. First, the total lithogenic Ge flux to SPB sediments is calculated as: F SPB lith-total = J SPB detrital • [Ge] UCC M w ( 17 ) where J SPB detrital = 350 ± 30 mg m -2 d -1 is the detrital flux measured via sediment traps  (Collins et al. , 2011) , [Ge] UCC = 1. 4 ± 0. 2 ppm is Ge concentration of average upper continental crust  (Rudnick and Gao, 2014) , and M w = 72.
FUNDING Financial support for the SPB cruise was provided by  US National Science Foundation (NSF)  grant  OCE-1260692  to DH. SMB cruise was supported by  US NSF  grants  OCE-0962209  to  Sergio Sañudo-Wilhelmy ,  OCE-0934073  to  Douglas Capone , and  PLR-1029878  to  William Berelson. Additional support was provided by  US NSF  grant  OCE-1061700  to DH. JB was also supported by a  CUAHSI  Pathfinder graduate student fellowship, an  InterRidge research fellowship , and a  John Montagne Award  from  GSA Quaternary Geology and Geomorphology Division. Support for OR was provided by the  Institut Carnot Ifremer EDROME  and the LabexMer  ANR-10-LABX-19-01.
Climate variability has major implications for marine geochemical cycles and biogenic carbonate production. Therefore, past climate-driven changes in marine environments are often inferred from geochemical data of the marine carbonate archive. Proxy calibration studies are essential for the reconstruction of such past environmental changes. Here, we use the geochemical composition of living specimens of the benthic foraminifer Ammonia tepida at three sites in a seasonally hypoxic (oxygen concentration < 63 µmol/L) marine coastal system (Lake Grevelingen, the Netherlands) to explore the use of Mn/Ca as a proxy for coastal hypoxia. The study is based on samples from three stations along a depth transect, that have contrasting seasonal cycles of Mn 2+ concentrations in the pore water of the surface sediment.
The benefit of Lake Grevelingen is that a large dataset on water column geochemistry combined with pore water and sediment geochemistry is available for the same sites where the specimens of A. tepida were sampled  (Hagens et al. , 2015; Seitaj et al. , 2015 Seitaj et al. , , 2017;; Sulu-Gambari et al. , 2016a ,b, 2017a). Therefore, it is possible to compare the measured Mn/Ca ratios in the foraminiferal tests with corresponding concentrations of Mn 2+ in the pore water. The analyses focused on the penultimate and antepenultimate chambers (n-1 and n-2), supposed to record pore water Mn 2+ concentration prior to sampling, and the central part of the test (n-c), supposed to give an averaged signal of the life span of the specimen. We will investigate whether the incorporated manganese in the foraminiferal test has a potential to reconstruct spatial and temporal variability in pore water Mn 2+.