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Application of General Linear Models (GLM) to Assess Nodule Abundance Based on a Photographic Survey (Case Study from IOM Area, Pacific Ocean)

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Application of General Linear Models (GLM) to Assess Nodule Abundance Based on a Photographic Survey (Case Study from IOM Area, Pacific Ocean) minerals Article Application of General Linear Models (GLM) to Assess Nodule Abundance Based on a Photographic Survey (Case Study from IOM Area, Pacific Ocean) Monika Wasilewska-Błaszczyk * and Jacek Mucha Department of Geology of Mineral Deposits and Mining Geology, Faculty of Geology, Geophysics and Environmental Protection, AGH University of Science and Technology, 30-059 Cracow, Poland; [email protected] * Correspondence: [email protected] Abstract: The success of the future exploitation of the Pacific polymetallic nodule deposits depends on an accurate estimation of their resources, especially in small batches, scheduled for extraction in the short term. The estimation based only on the results of direct seafloor sampling using box corers is burdened with a large error due to the long sampling interval and high variability of the nodule abundance. Therefore, estimations should take into account the results of bottom photograph analyses performed systematically and in large numbers along the course of a research vessel. For photographs taken at the direct sampling sites, the relationship linking the nodule abundance with the independent variables (the percentage of seafloor nodule coverage, the genetic types of nodules in the context of their fraction distribution, and the degree of sediment coverage of nodules) was determined using the general linear model (GLM). Compared to the estimates obtained with a simple Citation: Wasilewska-Błaszczyk, M.; linear model linking this parameter only with the seafloor nodule coverage, a significant decrease Mucha, J. Application of General in the standard prediction error, from 4.2 to 2.5 kg/m2, was found. The use of the GLM for the Linear Models (GLM) to Assess assessment of nodule abundance in individual sites covered by bottom photographs, outside of Nodule Abundance Based on a direct sampling sites, should contribute to a significant increase in the accuracy of the estimation of Photographic Survey (Case Study nodule resources. from IOM Area, Pacific Ocean). Minerals 2021, 11, 427. https:// doi.org/10.3390/min11040427 Keywords: polymetallic nodules; nodule abundance; general linear models; linear regression; nodule coverage of seafloor; sediment coverage of nodules; Clarion-Clipperton Zone (CCZ); image analysis Academic Editors: Pedro Madureira and Tomasz Abramowski Received: 12 March 2021 1. Introduction Accepted: 12 April 2021 Deposits of polymetallic (manganese-bearing) nodules occurring at the bottom of all Published: 17 April 2021 oceans are an attractive alternative to onshore deposits from the point of view of metal resources such as Ni, Co, Cu, Mn, Li, REE (the rare earth elements), and others. The Publisher’s Note: MDPI stays neutral Clarion–Clipperton Fracture Zone (CCZ) in the tropical NE Pacific is the area of greatest with regard to jurisdictional claims in economic interest for nodules [1–3] (Figure1A). It is expected that the demand for some published maps and institutional affil- metals will soon exceed their supply due to the depletion of onshore ore deposits resulting iations. from the intensive development of modern branches of the economy (high technology, green technology, emerging industries, and military applications). In the future, the shortage of some metals can be covered by the exploitation of offshore deposits. This issue was widely discussed in many publications, e.g., [1,2,4–14]. The exploitation of Copyright: © 2021 by the authors. these deposits, apart from their proper recognition and estimation of their resource [15], Licensee MDPI, Basel, Switzerland. requires solving a number of problems related to the technique of mineral extraction and This article is an open access article ore processing [7,16–18]. distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). Minerals 2021, 11, 427. https://doi.org/10.3390/min11040427 https://www.mdpi.com/journal/minerals MineralsMinerals 20212021, 11,,11 x ,FOR 427 PEER REVIEW 2 of2 17of 17 FigureFigure 1. Location 1. Location of ofB2 B2 Interoceanmetal Interoceanmetal Joint Joint Organization Organization (IOM)(IOM) explorationexploration area area for for polymetallic polymetallic nodules nodules against against the the backgroundbackground of ofthe the Clarion–Clipperton Clarion–Clipperton zone zone [19] [19]( (AA)) and and H22 exploration blockblock ( B(B);); the the location location of of the the box box corer corer sampling sampling sites and seafloor photographs in the H22 exploration block (three variants of training and test subsets) (C). sites and seafloor photographs in the H22 exploration block (three variants of training and test subsets) (C). TheThe development development of of an an appropriate scenarioscenarioand and schedule schedule for for the the future future short short and and medium-termmedium-term exploitation exploitation ofof nodules, nodules, after afte meetingr meeting the environmentalthe environmental protection protection require- re- quirementsments and and solving solving technical technical problems problems of mining, of mining, depends depends on a on detailed a detailed recognition recognition of ofthe the distribution distribution of of nodule nodule abundance abundance and and resources resources and and an an analysis analysis of of the the ocean ocean floor floor topographytopography based based on on reliable reliable contour maps.maps. AnAn accurate accurate assessment assessment of the abundanceabundance ofof polymetallic polymetallic nodules nodules at at seafloor seafloor sites sites locatedlocated far far away away from from direct direct sampling sampling stationsstations causes causes many many problems. problems. They They result result mainly mainly fromfrom the the large large distances distances between between samplingsampling stationsstations (which (which vary vary depending depending on on the the stage stage of recognition of the nodule-bearing areas), high variability of nodule abundance, and of recognition of the nodule-bearing areas), high variability of nodule abundance, and to to a lesser extent, from the inevitable errors during the sampling process [20]. Therefore, a lesser extent, from the inevitable errors during the sampling process [20]. Therefore, the the attempts to combine the estimation of nodule abundance based on the classical direct attemptssampling to (e.g.,combine using the box estimation corers) [of15 ,nodule21] with abundance indirect methods, based on such the classical as photographic direct sam- plingsurveys (e.g., [ 22using–25] box or widelycorers) understood[15,21] with hydro-acousticindirect methods, methods such as [26 photographic,27], seem natural surveys [22–25]and rational. or widely understood hydro-acoustic methods [26,27], seem natural and rational. TheThe routine routine and and continuous continuous video andand photo-profilingphoto-profiling (photographic (photographic survey) survey) of theof the oceanocean floor floor along along the the course course of a research vesselvessel from from which which direct direct sampling sampling is carriedis carried out out providesprovides a ahuge huge number number of photographs. TheirTheir analysis analysis provides provides indirect, indirect, approximate approximate informationinformation on on the the percentage percentage of seafloorseafloor nodulenodule coverage coverage (i.e., (i.e., the the percentage percentage of of seafloor seafloor coveredcovered by by the the nodules, nodules, hereinafter hereinafter abbreviatedabbreviated NC-S), NC-S), the the degree degree of of sediment sediment coverage coverage of nodules (SC), and the dominant genetic type of nodules (GT) between sampling stations [28]. The data obtained from the photographs in sampling sites are correlated with various strengths with the nodule abundance based on box core samples. The previous attempts Minerals 2021, 11, 427 3 of 17 of nodules (SC), and the dominant genetic type of nodules (GT) between sampling sta- tions [28]. The data obtained from the photographs in sampling sites are correlated with various strengths with the nodule abundance based on box core samples. The previous attempts to develop a simple linear regression between the nodule abundance and the percentage of seafloor nodule coverage did not yield unequivocal results. In some parts of the studied area of the Interoceanmetal Joint Organization (IOM), a statistically significant and strong linear correlation between these parameters was found (with linear correlation coefficients of 0.6–0.7), while in other parts there was no statistically significant correlation and the coefficients of linear correlation were close to zero [20,28,29]. The main reasons for the weaker correlation of both parameters can be seen in the varying the degree of sediment coverage of nodules [28–30], diversity of the nodule genotypes [31,32], small scale variability of nodule abundance, different geometrical basis of measurements (area of the bottom covered by the photograph several times larger as compared to the area of the horizontal section of the box corer), and the variation in the quality of seafloor pho- tographs. For these reasons, some researchers introduced various coefficients correcting the relationship between the nodule abundance and the percentage of seafloor nodule coverage determined on the basis of photographs [30,33]. Improvements in the accuracy of the estimates of nodule abundance can be expected when additional independent qualitative variables (ordinal variable),
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