Rare earth element geochemistry of outcrop and core samples from the Marcellus Shale
© Noack et al. 2015
Received: 13 January 2015
Accepted: 3 June 2015
Published: 26 June 2015
In this work, the geochemistry of the rare earth elements (REE) was studied in eleven outcrop samples and six, depth-interval samples of a core from the Marcellus Shale. The REE are classically applied analytes for investigating depositional environments and inferring geochemical processes, making them of interest as potential, naturally occurring indicators of fluid sources as well as indicators of geochemical processes in solid waste disposal. However, little is known of the REE occurrence in the Marcellus Shale or its produced waters, and this study represents one of the first, thorough characterizations of the REE in the Marcellus Shale. In these samples, the abundance of REE and the fractionation of REE profiles were correlated with different mineral components of the shale. Namely, samples with a larger clay component were inferred to have higher absolute concentrations of REE but have less distinctive patterns. Conversely, samples with larger carbonate fractions exhibited a greater degree of fractionation, albeit with lower total abundance. Further study is necessary to determine release mechanisms, as well as REE fate-and-transport, however these results have implications for future brine and solid waste management applications.
Unconventional natural gas and oil resources include tight-gas sands, coal bed methane, and organic-rich black shales . One such shale is the middle-Devonian Marcellus, a ubiquitous formation throughout much of the Appalachian Basin . Saline, metal-enriched produced waters from the Marcellus  are an environmental concern for their potential to contaminate shallow groundwater or surface water . While the water–rock interactions that govern the dissolved constituents of produced waters are not well understood , information regarding the metal contents and mineralogy of the Marcellus Shale is necessary for assessing the potential for metal mobilization in situ or upon disposal of waste cuttings.
Beyond assessing and managing risk, thorough source-rock characterization can elucidate other applications of dissolved constituents in produced waters. Capable source identification tools are necessary in regions, such as the Appalachian basin, where multiple sources of salinity overlap . For example, unique trace metal and isotope chemistry can be used as naturally occurring indicators, or fingerprints, of water–rock interactions and fluid migration and mixing [5–7]. The rare earth elements (REE) have been extensively studied in sedimentary formations (and geologic media in general), typically in the context of inferring depositional environments [8, 9] or diagenic processes [10–12]. Thus, the REE are potential fingerprints of water–rock interactions as well as geochemical signatures of brine sources [13, 14].
Despite years of interest in and study of the formation, [15–17] current data on the trace-metal lithogeochemistry of the Marcellus is limited. Chermak and Schreiber  provided a thorough compilation and analysis of published studies of various oil and gas shales, focusing on the pyrite/calcite balance of the mineralogy as well as the implications of trace-metal abundance for solid waste disposal. However, the majority of reported analyses within that study for the Marcellus were from three core samples: two from Bracht  and one from Werne et al. . Additionally, little or no discussion exists regarding the REE profiles of the Marcellus Shale. Chiarenzelli et al.  included data from a depth-stratified core of the Marcellus in New York State for comparative purposes when using REE profiles when studying the Popple Hill Gneiss. However, the REE data are presented in summary, unaccompanied by mineralogical analysis.
Given this lack of prior art, the objective of this study was to expand the knowledge of REE occurrence in the Marcellus Shale through investigations of elemental abundance and mineralogy. This objective was addressed with three tasks: (1) determine the REE abundance in samples of the Marcellus Shale by LiBO2 fusion and ICP-MS analysis, (2) study the mineralogy of these samples using X-ray diffraction, and (3) hypothesize mineralogy of the REE via statistical analysis of experimental results. Where appropriate, comparisons were made between sample types (i.e. core and outcrop) and between outcrop localities (i.e. northern or southern). This data can subsequently be used to inform focused studies of the potential for metal release by various mechanisms.
Results and discussion
While the samples studied here were not exclusively from gas-bearing members of the Marcellus, if the REE are to be used as tracers it is important to have thorough characterization of the REE in over- and underlying strata. Induced fractures (and therefore fluids) often propagate “out-of-zone” and, at times, hundreds of meters vertically above and below the perforation midpoint . Therefore the variety of strata (within the Marcellus) studied here are generally of interest for naturally occurring tracer applications.
Rare earth element abundance, correlations, and profiles
Sample-wise results of LiBO2 fusion and ICP-MS analysis of Marcellus Shale samples
Canoga, NY (OCM)a
Canoga, NY (OCM)a
Petersburg, WV (N)
Whip Gap, WV
Burlington, WV (1)
Canoga, NY (USM)
Petersburg, WV (W)
Le Roy, NY
Burlington, WV (2)
The REE were also highly, positively correlated in these samples. The median interelement correlation (Spearman’s \(\rho\)) was 0.81 while 95% of all correlations fell between 0.47 and 0.98. The minimum observed correlation (0.33) was between La and Y. In general, REE tended to correlate most strongly with the nearest elements, with Sc correlating better with the LREE and Y with the HREE (Additional file 1: Figure S3). Overall, the high correlations exhibited in these samples were consistent with correlations determined in aqueous media , which was expected given the ubiquitous occurrence and coherent chemical properties of the REE.
Rare earth element concentrations were statistically compared between core and outcrop samples and between outcrop localities to determine if presumed weathering of outcrops or regional variations might yield systematically different REE concentrations. Despite the REE concentrations in the outcrop samples appearing to be more variable than in the core samples (e.g. Eu in Figure 2), no statistically significant differences in element variability were determined between the outcrop and core samples (Ansari-Bradley test for difference in scale parameter; \(P \approx 1\) for all elements following Bonferroni–Holm corrections for multiple comparisons). Similarly, no statistically significant differences were found in the central tendencies of any of the REE between the two sample types (Wilcoxon rank-sum test for location shift; \(P \approx 1\) for all elements, corrected for multiple comparisons). Analogous, parametric tests (Bartlett test for homogeneity of variance and a t test) were performed, also indicating no significant differences (Additional file 1, Section: “Outcrop-core statistical comparison”).
Testing of reduced dimension variables, such as the total REE content, similarly exhibited no differences between sample types. This could indicate that surface weathering processes did not appreciably alter the REE composition. Alternatively, the small sample size leads to aggregation of the samples as “outcrops” since insufficient samples were available to compare among members of the Marcellus (e.g. Union Springs vs. Oatka Creek). This could lead to false negative test results as inter-strata variability could obscure variability due to weathering.
Application of the PERMANOVA test further confirmed the lack of difference between the two sample types in bulk REE content (\(P > 0.5\) from 10,000 permutations). While the apparent differences in dispersion or variance between the types may not be detectable given the small sample size, the similarity of medians corresponds with the findings of Chermak and Schreiber , where numerous, non-REE analytes agreed between core samples from different geographies within the Marcellus.
Similar results (i.e. no statistically significant differences) were obtained for uni- and multivariate comparisons between northern and southern outcrop samples. This indicates that inter-regional variability of the bulk REE composition of the shale may be less significant than intra-regional variability (i.e. at the stratigraphic or mineralogical scale). However, the current dataset is insufficient to make meaningful, statistical comparisons between stratigraphic groups.
Crystalline mineralogy determined by XRD
Similarly, the results of cluster analysis provide little confidence in discernable, mineralogical differences between the regionalized outcrop samples. PERMANOVA testing confirms this observation, with no significant differences as a function of location (P > 0.5 from 10,000 permutations). However, the apparent lack of regionality (with respect to these mineralogical and elemental analyses) may be an artifact of sample size (as other geochemical parameters are known to be highly, regionally variable in the Marcellus play [5, 7]) or may arise from the pooling of samples from unique strata.
Relationships between REE profiles and mineralogy
The Mantel test was used to test for correlation between intersample distances calculated as a function of REE abundance and XRD spectra correlations. A moderate, positive correlation was observed (Spearman’s \(\rho\) = 0.53, P < 0.001), indicating that differences in the crystalline mineralogy of the samples is a significant control on REE profile variability. This hypothesis was further explored by applying Wilcoxon tests to both the degree of fractionation metric and the total REE content using the semi-quantitative XRD results for each mineral as the predictor variable.
Conversely, samples with more calcite were between 54 and 400% more fractionated (HL 95% CI; P < 0.005), with 6–120 ppm less total REE than samples without a major calcite phase (HL 95% CI; P < 0.05), corroborating the conclusions drawn regarding differences in core samples, where dissimilar samples had a significant calcite fraction (Figures 3, 4). LREE-depletion has been observed in carbonate fractions of shales, potentially being excluded from the crystal lattice while MREE and HREE, with more similar ionic radii to Ca, are coprecipitated .
These postulates are supported by analyzing correlations between the major elements of the shale (i.e. Al, Ca, Fe, K, Mg, Na, and Si; reported for the outcrop samples studied here by Dilmore et al. ) and the total REE content as well as the degree of REE-profile fractionation (Additional file 1: Figures S4, S5). Namely, strong positive correlations were observed between total REE content and Al, Fe, K, Mg, and Na. This supports the hypothesis of total REE correlating with clay phases. Given the general abundance of these elements in all geologic media, substantial conclusions cannot be drawn on this data alone. However, Ver Straeten et al.  utilized related multivariate statistics to infer mineral inputs into the Devonian Appalachian Basin. Similar to Condie , no correlation was observed between total REE and P, indicating that minor phosphate minerals, which can be strong REE accumulators [30, 31], did not contribute significantly to the REE content of these samples.
The implications of these hypothesized mineral associations can be related to the potential for these shales to release REE during hydraulic fracturing. Since the REE may be structurally bound within the clays (as opposed to sorbed at surface sites) , it is possible that produced water REE profiles will not resemble those of the bulk shale. Yan et al.  found the REE to reside predominantly in the fine-grained fraction of a glacial till, clayey aquitard, but associated evenly between seven mineral fractions (elucidated through sequential leaching); the REE profiles of the adsorbed and exchangeable cations fraction, which were MREE- to HREE-enriched accounting for 9–10% of the total REE in those samples , most closely resembled the majority of profiles observed here. Conversely, the more readily soluble fractions (such as the carbonates, which often produce LREE-depletion ) may be responsible for REE profiles observed in produced waters, which could be used for source identification in the event of brine intrusion or waste spillage. More study is necessary to determine the release mechanisms of the REE under conditions relevant to hydraulic fracturing and solid waste disposal.
Understanding trace metal geochemistry in shales and hypersaline brines is necessary in the face of expanding global development of unconventional oil and gas reserves through horizontal drilling and high-volume, hydraulic fracturing. Characterizing and managing the risk of fresh water contamination by solid and liquid wastes associated with these developments starts with an understanding of the geochemistry of compounds of interest in the host shales.
Stimulation of these shales during hydraulic fracturing will modify natural rates, extents, and pathways of weathering. These analyses can serve as a starting point for further investigation into the risk of metal mobilization during hydraulic fracturing, solid waste disposal, and throughout the well lifetime. Additionally, these tests provide a basis for understanding the capabilities for leached elements to serve as tracers of water–rock interactions.
For sample fusion, lithium metaborate (LiBO2) was acquired from Acros Organics (99% purity; Lot # A0317552). Trace-metal grade nitric acid (HNO3) was used for fusion dissolution and as the background solvent for ICP-MS analysis (BDH ARISTAR® Plus, VWR; assay 69 wt%; Lot # 1113050). Single element standard solutions (~1,000 µg/L) of the REE and all elements necessary for internal and external standardization were obtained from inorganic ventures. All acid dilutions were performed on a gravimetric basis using ultrapure water (ASTM Type I, 18.2 MΩ/cm), prepared using a Barnstead NANOpure® water purification system.
Rare earth element abundance analysis
Aliquots (~100 mg) of finely powdered sample were fused with ~1 g LiBO2 in graphite crucibles at 1,000°C for 30 min to yield a homogenous, molten fusion. Samples were quickly removed from the furnace and poured into pre-weighed 125 mL HDPE bottles partially filled with 5% HNO3. After all fusions were dispensed, the total volume of digestate was brought up to ~100 mL with 5% HNO3 and weighed. Bottles were then placed into an ultrasonic bath for 2 h to break apart any remaining particulate matter.
Analytical method quality assurance for USGS reference materials BCR-2 and SGR-1 with ICP-MS following LiBO2 fusion
Analyte (MDL; ppm)
Mineralogy of the shale samples was investigated by synchrotron-based X-ray diffraction (XRD). XRD measurements were made on beamline 11-3 at the Stanford Synchrotron Radiation Lightsource (SSRL) using powdered samples. Incident X-rays (\(\lambda =\) 0.9744 Å, 12,735 eV) were focused using a bent cube root I-beam Si (311) monochromator. A MAR345 area detector positioned 120 mm downstream of the sample was used to collect diffraction scans with a dwell time of 90 s. The collected images were integrated and converted into degrees 2θ using area diffraction machine (open source) software. The diffraction patterns were background subtracted and peak matched using Xpert Highscore Plus using a reference library obtained from the Crystallography Open Database, which was converted to synchrotron energy.
Based on previous analyses of Marcellus Shale samples, reported in Chermak and Schreiber , and examination of the patterns reported here, diffraction data were qualitatively partitioned to seven potential minerals (COD code in parentheses): quartz (1011097), calcite (9007867), dolomite (1200014), pyrite (5000115), illite (9013723), chlorite (9000158), and montmorillonite (9002779). The relative volume fraction of each mineral within this model assemblage was estimated for every sample by evaluation of several parameters including total diffraction peak intensity, goodness of peak fits, and contribution to the overall fitting. Additional mineral phases did not constitute significant fractions of the crystalline mineralogy and were not included. A list of the specific reference spectra used is given in the Additional file 1: Table S4.
Rare earth element reduced dimension variables
The overall degree of fractionation in a sample was defined as the sum of the absolute values of one minus each of: HREE/MREE ratios, MREE/LREE ratios, Ce anomalies, and Eu anomalies. This degree of fractionation was used to represent the overall “unevenness” or entropy of the PAAS-normalized profile. By this metric, a sample with 0 fractionation would appear flat on a plot of the PAAS-normalized concentrations for the REE while a sample with high fractionation would be highly bent, with large Ce and Eu anomalies.
The goals of statistical analysis were to test for differences in bulk, REE composition between core and outcrop samples as well as between northern and southern outcrops. These comparisons were made using a variety of uni- and multivariate hypothesis tests. Further, cluster and correlation analyses among XRD spectra were performed to probe differences in mineralogy, and subsequently relate those differences to bulk REE abundance and profiles. Given the small number of samples and potential non-normality of the analytes determined here, all statistical analyses were performed non-parametrically, that is, without distributional assumptions. Moreover, to control familywise error rates, Holm–Bonferroni corrections were made to all p values when utilizing multiple hypothesis tests, e.g. when comparing central tendencies of each element between core and outcrop samples. All analyses were performed using R (Version 3.1.1) and functions from the “vegan” package for multivariate analyses [39, 40]. A detailed description of these statistical methods is provided in Additional file 1 (Section: “Hypothesis tests and cluster analysis for shale comparisons”).
CN carried out ICP-MS analysis of digestates, performed statistical analyses, and co-authored the manuscript; JJ carried out LiBO2 fusions, aided with ICP-MS analysis, and helped to draft the manuscript; JS performed XRD analyses, analyzed diffraction data, performed qualitative fitting, and helped draft the manuscript; JAH and AK conceived of the study and co-authored the manuscript. All authors read and approved the final manuscript.
This technical effort was supported by the Department of Energy, National Energy Technology Laboratory (NETL), an agency of the United States Government, through a support contract (DE-FE0004000) with URS Energy & Construction, Inc. The authors would like to acknowledge Drs. Karl Schroeder, Christina Lopano, Robert Dilmore and Harry Edenborn for assistance in sample acquisition. The authors would like to thank Drs. Kathy Bruner and Richard Smosna and Mr. Thomas Mroz for their efforts collecting the samples used in this study from the field.
Compliance with ethical guidelines
Competing interests The authors declare that they have no competing interests.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
- U.S. Energy Information Administration. Annual Energy Outlook 2014. Early Release Overview 2013. U.S. Energy Information AdministrationGoogle Scholar
- Soeder DJ (2010) The Marcellus Shale: resources and reservations. Eos Trans AGU 91(32):277–278View ArticleGoogle Scholar
- Haluszczak LO, Rose AW, Kump LR (2013) Geochemical evaluation of flowback brine from Marcellus gas wells in Pennsylvania, USA. Appl Geochem 28:55–61View ArticleGoogle Scholar
- Gregory KB, Vidic RD, Dzombak DA (2011) Water management challenges associated with the production of shale gas by hydraulic fracturing. Elements 7(3):181–186View ArticleGoogle Scholar
- Barbot E, Vidic NS, Gregory KB, Vidic RD (2013) Spatial and temporal correlation of water quality parameters of produced waters from Devonian-age shale following hydraulic fracturing. Environ Sci Technol 47(6):2562–2569View ArticleGoogle Scholar
- Wilson JM, Wang Y, VanBriesen JM (2013) Sources of high total dissolved solids to drinking water supply in Southwestern Pennsylvania. J Environ Eng 140(5):B4014003View ArticleGoogle Scholar
- Chapman EC, Capo RC, Stewart BW, Kirby CS, Hammack RW, Schroeder KT et al (2012) Geochemical and strontium isotope characterization of produced waters from Marcellus Shale natural gas extraction. Environ Sci Technol 46(6):3545–3553View ArticleGoogle Scholar
- Murray RW, Buchholtz ten Brink MR, Jones DL, Gerlach DC, Russ GP III (1990) Rare earth elements as indicators of different marine depositional environments in chert and shale. Geology 18(3):268–271View ArticleGoogle Scholar
- Johannesson KH, Hawkins DL Jr, Cortés A (2006) Do Archean chemical sediments record ancient seawater rare earth element patterns? Geochim Cosmochim Acta 70(4):871–890View ArticleGoogle Scholar
- Allaz J, Selleck B, Williams ML, Jercinovic MJ (2013) Microprobe analysis and dating of monazite from the Potsdam Formation, New York: a progressive record of chemical reaction and fluid interaction. Am Miner 98(7):1106–1119View ArticleGoogle Scholar
- Chakrabarti R, Abanda PA, Hannigan RE, Basu AR (2007) Effects of diagenesis on the Nd-isotopic composition of black shales from the 420 Ma Utica Shale Magnafacies. Chem Geol 244(1):221–231View ArticleGoogle Scholar
- Lee S-G, Lee D-H, Kim Y, Chae B-G, Kim W-Y, Woo N-C (2003) Rare earth elements as indicators of groundwater environment changes in a fractured rock system: evidence from fracture-filling calcite. Appl Geochem 18(1):135–143View ArticleGoogle Scholar
- Ma L, Jin L, Brantley SL (2011) How mineralogy and slope aspect affect REE release and fractionation during shale weathering in the Susquehanna/Shale Hills Critical Zone Observatory. Chem Geol 290(1):31–49View ArticleGoogle Scholar
- Darrah T (2012) Using noble gas geochemistry to evaluate fluid migration in hydrocarbon bearing black shales. US 13/297,263Google Scholar
- Roen JB (1984) Geology of the Devonian black shales of the Appalachian Basin. Org Geochem 5(4):241–254View ArticleGoogle Scholar
- Sageman BB, Murphy AE, Werne JP, Ver Straeten CA, Hollander DJ, Lyons TW (2003) A tale of shales: the relative roles of production, decomposition, and dilution in the accumulation of organic-rich strata, Middle–Upper Devonian, Appalachian basin. Chem Geol 195(1–4):229–273View ArticleGoogle Scholar
- Ver Straeten CA, Brett CE, Sageman BB (2011) Mudrock sequence stratigraphy: a multi-proxy (sedimentological, paleobiological and geochemical) approach, Devonian Appalachian Basin. Palaeogeogr Palaeoclimatol Palaeoecol 304(1–2):54–73View ArticleGoogle Scholar
- Chermak JA, Schreiber ME (2014) Mineralogy and trace element geochemistry of gas shales in the United States: environmental implications. Int J Coal Geol 126(1):32–44View ArticleGoogle Scholar
- Bracht R (2010) Geochemistry and depositional environment of the union springs member of the Marcellus Shale in Pennsylvania. M.S. Thesis 2010, The Pennsylvania State UniversityGoogle Scholar
- Werne JP, Sageman BB, Lyons TW, Hollander DJ (2002) An integrated assessment of a “type euxinic” deposit: evidence for multiple controls on black shale deposition in the middle Devonian Oatka Creek formation. Am J Sci 302(2):110–143View ArticleGoogle Scholar
- Chiarenzelli JR, Hudson MR, Dahl PS, deLorraine WD (2012) Constraints on deposition in the Trans-Adirondack Basin, Northern New York: composition and origin of the Popple Hill Gneiss. Precambrian Res 214–215:154–171View ArticleGoogle Scholar
- Davies RJ, Mathias SA, Moss J, Hustoft S, Newport L (2012) Hydraulic fractures: how far can they go? Mar Pet Geol 37(1):1–6View ArticleGoogle Scholar
- Harkins WD (1917) The evolution of the elements and the stability of complex atoms. I. A new periodic system which shows a relation between the abundance of the elements and the structure of the nuclei of atoms. J Am Chem Soc 39(5):856–879View ArticleGoogle Scholar
- Ketris M, Yudovich YE (2009) Estimations of Clarkes for carbonaceous biolithes: world averages for trace element contents in black shales and coals. Int J Coal Geol 78(2):135–148View ArticleGoogle Scholar
- Noack CW, Dzombak DA, Karamalidis AK (2014) Rare earth element distributions and trends in natural waters with a focus on groundwater. Environ Sci Technol 48(8):4317–4326View ArticleGoogle Scholar
- Ettensohn FR (1992) Controls on the origin of the Devonian-Mississippian oil and gas shales, east-central United States. Fuel 71(12):1487–1492View ArticleGoogle Scholar
- Abanda PA, Hannigan RE (2006) Effect of diagenesis on trace element partitioning in shales. Chem Geol 230(1–2):42–59View ArticleGoogle Scholar
- Dilmore R, Bruner K, Wyatt C, Romanov V, Hedges S, Crandall D et al (2012) ICMI carbon storage in depleted shale: Experimental Program Summary Report 2012 (U. S. Department of Energy National Energy Technology Laboratory) URS-RES-1-551Google Scholar
- Condie KC (1991) Another look at rare earth elements in shales. Geochim Cosmochim Acta 55(9):2527–2531View ArticleGoogle Scholar
- Dubinin AV (2004) Geochemistry of rare earth elements in the ocean. Lithol Min Resour 39(4):289–307View ArticleGoogle Scholar
- McArthur JM, Walsh JN (1984) Rare-earth geochemistry of phosphorites. Chem Geol 47(3–4):191–220View ArticleGoogle Scholar
- Munoz-Paez A, Alba MD, Castro MA, Alvero R, Trillo JM (1994) Geometric structures of lanthanide ions within layered clays as determined by EXAFS: from the Lu(III) hydrate to the disilicate. J Phys Chem 98(39):9850–9860View ArticleGoogle Scholar
- Yan X-P, Kerrich R, Hendry MJ (1999) Sequential leachates of multiple grain size fractions from a clay-rich till, Saskatchewan, Canada: implications for controls on the rare earth element geochemistry of porewaters in an aquitard. Chem Geol 158(1–2):53–79View ArticleGoogle Scholar
- McGinnis CE, Jain JC, Neal CR (1997) Characterisation of memory effects and development of an effective wash protocol for the measurement of petrogenetically critical trace elements in geological samples by ICP-MS. Geostand Newslett 21(2):289–305View ArticleGoogle Scholar
- Stolpe B, Guo L, Shiller AM (2013) Binding and transport of rare earth elements by organic and iron-rich nanocolloids in Alaskan rivers, as revealed by field-flow fractionation and ICP-MS. Geochim Cosmochim Acta 106:446–462View ArticleGoogle Scholar
- Nance WB, Taylor SR (1976) Rare earth element patterns and crustal evolution—I. Australian post-Archean sedimentary rocks. Geochim Cosmochim Acta 40(12):1539–1551View ArticleGoogle Scholar
- Lawrence M, Greig A, Collerson K, Kamber B (2006) Rare earth element and yttrium variability in South East Queensland waterways. Aquat Geochem 12(1):39–72View ArticleGoogle Scholar
- Willis SS, Johannesson KH (2011) Controls on the geochemistry of rare earth elements in sediments and groundwaters of the Aquia aquifer, Maryland, USA. Chem Geol 285(1–4):32–49View ArticleGoogle Scholar
- R Core Team (2014) R: a language and environment for statistical computing, 3.0.3. R Foundation for Statistical Computing, Vienna, AustriaGoogle Scholar
- Oksanen J, Kindt R, Legendre P, O’Hara B, Simpson GL, Solymos P et al (2008) vegan: community ecology packageGoogle Scholar
- McGill R, Tukey JW, Larsen WA (1978) Variations of box plots. Am Stat 32(1):12–16Google Scholar