Home Identification of magnetic mineralogy and paleo-flow direction of the Miocene-quaternary volcanic products in the north of Lake Van, Eastern Turkey
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Identification of magnetic mineralogy and paleo-flow direction of the Miocene-quaternary volcanic products in the north of Lake Van, Eastern Turkey

  • Sercan Kayın EMAIL logo and Turgay İşseven
Published/Copyright: February 15, 2024
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Abstract

One of the major challenges facing geochemistry, petrology, and volcanology researchers is the difficulty in determining the origin and paleo-flow directions of igneous and volcanic rocks. It is not possible to clearly determine origins and paleo-flow directions in areas with numerous volcanic centers. Anisotropy of magnetic susceptibility (AMS) is a valuable method that provides insights into the origins and paleo-flow directions of lavas that are complex to study. The presence of volcanic materials with thicknesses up to 1 km, coming from different sources at varied time intervals in the north of Lake Van, makes this area an ideal setting for implementing AMS in establishing paleo-flow directions. This study presents the magnetic mineralogy and AMS analysis of volcanic rocks from the Miocene to the Quaternary in the Lake Van region. We conducted isothermal remanent magnetization (IRM) and high-temperature susceptibility (HTS) studies to determine the magnetic mineralogy. IRM studies revealed that (titano)magnetite is responsible for the magnetization in most samples, while both (titano)magnetite and hematite are responsible for the rest. Alteration degrees and Curie temperatures of the rock samples were also determined through HTS measurements. There is good agreement between the anticipated directions of lava flow and our findings for nearly all volcanic rocks.

1 Introduction

The Eastern Anatolian Plateau was formed by the collision between the Arabian and Eurasian plates from the Late Oligocene to Early Miocene [1] and is a plateau with an average elevation of 1.5 km [2,3,4,5]. Furthermore, the convergence and collision within the Eastern Anatolian Plateau led to the development of two strike-slip fault systems that converge to the east of Karlıova. These are the North Anatolian Fault Zone (NAFZ), which has a right-lateral NW-SE direction near Karlıova, and the left-lateral East Anatolian Fault Zone, which has an NE–SW direction [5,6,7] (Figure 1). Due to the collision, extensive volcanic activity was present in Eastern Anatolia, which began in the Middle Miocene and covered vast areas, extending from the Erzurum-Kars plateau in the north to the Bitlis Zagros suture belt in the south [7].

Figure 1 
               Simplified tectonic map of the Aegean and Eastern Mediterranean region showing main plate boundaries, major suture zones, fault systems, and tectonic units. The red square represents the study area. EAFZ: East Anatolian Fault Zone; NAFZ: North Anatolian Fault Zone; DSFZ: Death Sea Fault Zone; BZSZ: Bitlis Zagros Suture Zone.
Figure 1

Simplified tectonic map of the Aegean and Eastern Mediterranean region showing main plate boundaries, major suture zones, fault systems, and tectonic units. The red square represents the study area. EAFZ: East Anatolian Fault Zone; NAFZ: North Anatolian Fault Zone; DSFZ: Death Sea Fault Zone; BZSZ: Bitlis Zagros Suture Zone.

In the northeastern region of Lake Van, there are numerous volcanic centers with their volcanic products interweaved. Some of these units comprise the Miocene Aladağ volcanic rocks, the Pliocene volcanic products of the Etrüsk volcano, the Quaternary Girekol volcano, and several extensional fractures, including Yüksektepe, Karnıyarık, and Omruktepe (Figure 2) [8]. Oyan et al. stated that the volcanic rocks produced from these volcanic sources are composed of basaltic, hawaiitic, and mugearitic in composition [8].

Figure 2 
               Geological map of the study area (modified after General Directorate of Mineral Research and Exploration [MTA], 1/500,000 scale geological map [2002]) and distribution of the AMS sampling sites (Red, white, green, and blue dots represent Quaternary aged Girekol, Quaternary aged Karnıyarık – Yüksektepe, Pliocene, and Miocene-aged sample locations, respectively).
Figure 2

Geological map of the study area (modified after General Directorate of Mineral Research and Exploration [MTA], 1/500,000 scale geological map [2002]) and distribution of the AMS sampling sites (Red, white, green, and blue dots represent Quaternary aged Girekol, Quaternary aged Karnıyarık – Yüksektepe, Pliocene, and Miocene-aged sample locations, respectively).

The anisotropy of magnetic susceptibility (AMS) technique is a widely used method in petrofabrics research. This technique relies on gauging the low-field magnetic susceptibility of the sample in various directions. As a result of the measurements, certain properties are calculated to define the magnetic lineation and foliation. These include the size and shape of the AMS ellipsoid and the magnetic fabric. It serves as a marker for determining the direction of magma flow by utilizing these characteristics [9]. The effectiveness of AMS in determining the internal texture, flow direction, and/or flow plane of volcanic rock is well documented in the literature [9,10,11,12,13,14].

The temporal and spatial differences in the volume and composition of volcanic products due to the collision between the Arabian and Anatolian plates and the intermingling of volcanic products from different sources from Neogene to Quaternary in the north of Lake Van have made the study area important in terms of determining paleo-flow directions.

Due to the collisional tectonics, there are thick and widespread volcanic rocks present in Eastern Anatolia. These volcanic rocks have been studied by different researchers in order to uncover the geochemical source and center of volcanism, yet there is no consensus achieved to date. Paleomagnetic and rock magnetic studies are commonly used to contribute to the solution of these problems; however, there are not many paleomagnetic studies that have been carried out in Eastern Anatolia, specifically focusing on paleo-flows of the region.

This study aims to identify the minerals responsible for magnetization and gain a clearer understanding of the paleo-flow directions and emplacement of the different volcanic materials in the north of Lake Van. Therefore, this study is crucial for a better understanding of the area and offers new scientific findings.

2 Geological setting

Due to the convergence between the Arabian and Eurasian plates, a continent–continent collision occurred in the region after the northern and southern branches of the Neotethys Ocean were closed [15,16]. The collision formed the Bitlis–Zagros suture belt along the plate boundaries, the average height of which currently rises to 1.5 km [1,2,3,4,5,17,18,19].

Volcanic activities in the Eastern Anatolia region started in the Middle Miocene (∼15 Ma) [2,20,21,22] and continued more intensely in the Pliocene and Quaternary [8]. This volcanism took place occupying large areas, and the thickness of accumulated volcanic products reached up to 1 km in thickness [23]. The volcanic deposits were formed from volcanic centers such as Ağrı, Nemrut, Süphan, Tendürek, Ağırkaya, and Etrüsk, which also erupted along the extensional fractures. Therefore, the Eastern Anatolia Region is a natural laboratory in terms of the diversity of volcanic rocks due to the existence of different periods and centers of volcanism along with collision tectonism.

Keskin claimed that volcanic activity started earlier in the north and then migrated southwards, with significant variations in lava chemistry over time [24]. While the volcanic products around the Muş–Nemrut–Tendürek volcanoes are alkaline, the ones around the Erzurum Kars Plateau are calc-alkaline [23].

One of the largest areas of young volcanism in Eastern Anatolia is the north of Lake Van [22]. Lebedev et al. determined that using isotopic data, the starting time of volcanic activity in the region is the Serravallian period (∼15 Ma, Middle Miocene). In the region, the second stage of volcanism originated at the beginning of the Late Miocene (∼10 Ma). The Pliocene volcanism started at 5.8 Ma and continued for about 2 Ma, while the Quaternary volcanism in the north of Lake Van started at ∼1 Ma [22].

3 AMS method and sampling

The AMS method has been used by many researchers to study the magnetic fabric in igneous, sedimentary, and metamorphic rocks [9,10,11,25]. AMS refers to the change of magnetic susceptibility in the rock depending on its direction [9]. This change is expressed mathematically with a second-order tensor and is defined as a three-axis ellipsoid [26]. While defining this three-axis ellipsoid in AMS studies, the terms k 1 (k max), k 2 (k int), and k 3 (k min) are referred to as maximum, intermediate, and minimum magnetic susceptibility components, respectively. The long axis (k max) of the magnetic susceptibility ellipsoid defines the magnetic lineation. The short axis (k min) defines the normal plane of the magnetic foliation. In the case of normal fabric, the magnetic lineation coincides with the flow direction, and k min is perpendicular to the flow surface.

Several parameters can be calculated using the magnetic susceptibility components of this ellipsoid to numerically define the degree and shape of anisotropy. These parameters are magnetic lineation (L), magnetic foliation (F), anisotropy degree (P) (equation (1)), mean susceptibility (k m) (equation (2)), corrected anisotropy degree (P j) (equation (3)), and shape parameter (T) (equation 4) (Table 1).

Table 1

AMS parameters of the Miocene–Quaternary volcanic rocks

Site Geog. coord (°) N Age k 1 k 2 k 3 k m L F P P j T k 1 (k max)
Lat (N) Long (E) D (°) I(°)
aci1 38.997 43.504 6 Q 1798.3 1780.9 1737.2 1772.13 1.0098 1.0252 1.0352 1.0363 0.4374 251.4 63.4
aci2 38.997 43.504 8 Q 2845.5 2809.5 2746.8 2800.60 1.0128 1.0228 1.0359 1.0364 0.2787 209 2.3
aci3 39.003 43.494 5 Q 2329.2 2321.1 2264.6 2304.97 1.0035 1.0249 1.0285 1.0311 0.7523 144.6 17.5
cay1 39.112 43.341 4 Q 1458.3 1448.1 1427.6 1444.67 1.0070 1.0144 1.0215 1.0219 0.3402 309.3 15.3
ckk 39.119 43.454 5 Q 1,798 1785.7 1757.3 1780.33 1.0069 1.0162 1.0232 1.0238 0.4004 74.2 28.2
ckk2 39.127 43.438 5 Q 1442.3 1438.1 1398.6 1426.33 1.0029 1.0282 1.0312 1.0346 0.8104 317.4 5.4
dlcy 39.102 43.485 5 Q 1627.5 1,618 1,573 1606.17 1.0059 1.0286 1.0346 1.0371 0.6562 206.5 18.3
hac1 39.121 43.428 5 Q 2,325 2,321 2268.5 2304.83 1.0017 1.0231 1.0249 1.0278 0.8600 317.6 19.1
hac3 39.119 43.418 5 Q 1915.3 1915.2 1868.4 1899.63 1.0001 1.0250 1.0251 1.0290 0.9958 288.9 7.6
kek 39.078 43.462 5 Q 1336.8 1,335 1290.1 1320.63 1.0013 1.0348 1.0362 1.0411 0.9242 243.2 14.3
kek2 39.073 43.410 9 Q 622.8 621.1 603.4 615.77 1.0027 1.0293 1.0322 1.0357 0.8273 199.6 24
koz4 39.032 43.549 5 Q 2378.3 2352.9 2288.5 2339.90 1.0108 1.0281 1.0392 1.0405 0.4421 86.5 41.7
koz5 39.015 43.528 5 Q 1,488 1479.3 1449.1 1472.13 1.0059 1.0208 1.0268 1.0282 0.5573 341.4 65.7
tprk6 39.024 43.509 9 Q 2226.7 2226.2 2,187 2213.30 1.0002 1.0179 1.0182 1.0209 0.9750 181.3 8.3
tprk7 39.025 43.530 3 Q 1337.8 1329.5 1287.7 1318.33 1.0062 1.0325 1.0389 1.0418 0.6739 168.7 46
inc1 39.01 43.488 4 Q 2242.2 2241.2 2114.8 2199.40 1.0004 1.0598 1.0602 1.0696 0.9847 332.4 6.6
ant 38.984 43.549 8 Pl 1011.2 1001.4 948.3 986.97 1.0098 1.0560 1.0663 1.0717 0.6967 274.9 5.9
atok 38.999 43.406 6 Pl 959.9 959.4 935.4 951.57 1.0005 1.0257 1.0262 1.0300 0.9597 208.6 16.2
bbc2 39.085 43.758 5 Pl 1116.2 1110.3 1084.6 1103.70 1.0053 1.0237 1.0291 1.0310 0.6309 135.5 11
drk1 38.964 43.689 8 Pl 714.6 708.6 687.7 703.63 1.0085 1.0304 1.0391 1.0412 0.5605 181.3 47.8
blk 38.979 43.729 7 Pl 1062.4 1050.6 1007.9 1040.30 1.0112 1.0424 1.0541 1.0571 0.5758 37.6 15.2
brj 39.023 43.741 8 Pl 993.5 978.2 958.9 976.87 1.0156 1.0201 1.0361 1.0362 0.1243 202.3 64.4
dere 39.079 43.760 7 Pl 2834.7 2832.5 2757.7 2808.30 1.0008 1.0271 1.0279 1.0319 0.9436 135.3 26.6
drk2 38.967 43.693 7 Pl 621.6 613.4 597.1 610.70 1.0134 1.0273 1.0410 1.0418 0.3395 210.8 24.6
goz1 39.092 43.555 9 Pl 904.2 901.1 877.2 894.17 1.0034 1.0272 1.0308 1.0338 0.7734 149.3 6.8
goz2 39.099 43.581 5 Pl 1339.6 1326.1 1295.2 1320.30 1.0102 1.0239 1.0343 1.0352 0.3990 224.8 10.5
goz3 39.066 43.505 4 Pl 870.3 865.6 823.6 853.17 1.0054 1.0510 1.0567 1.0627 0.8036 210 27.5
goz4 39.051 43.505 7 Pl 1158.8 1143.3 1118.5 1140.20 1.0136 1.0222 1.0360 1.0364 0.2391 310.7 46.3
kmr 39.027 43.738 5 Pl 1497.2 1495.1 1452.9 1481.73 1.0014 1.0290 1.0305 1.0345 0.9065 47.7 7
kmr2 39.033 43.734 9 Pl 719.3 714.9 686.5 706.90 1.0062 1.0414 1.0478 1.0520 0.7371 270.7 17.6
bbc 39.092 43.784 6 Pl 1303.6 1292.8 1264.9 1287.10 1.0084 1.0221 1.0306 1.0316 0.4479 168.5 57.8
isik 39.006 43.429 8 Pl 841.4 841.2 816 832.87 1.0002 1.0309 1.0311 1.0359 0.9845 126.8 20.8
hydr 39.014 43.436 6 Pl 1706.2 1,704 1641.1 1683.77 1.0013 1.0383 1.0397 1.0452 0.9337 19.8 55.9
hydr3 39.011 43.431 4 Pl 939.7 922.7 913.8 925.40 1.0184 1.0097 1.0283 1.0288 −0.3064 187 28.3
hydr2 39.006 43.421 7 Pl 768.9 765.8 740.7 758.47 1.0040 1.0339 1.0381 1.0419 0.7838 194.9 5.3
kmr3 39.039 43.738 8 Pl 387.1 378.6 367.9 377.87 1.0225 1.0291 1.0522 1.0523 0.1271 131 63.6
koz6 39.013 43.564 4 Pl 1,463 1442.9 1409.3 1438.40 1.0139 1.0238 1.0381 1.0385 0.2601 243.9 24.9
krh 38.962 43.668 6 Pl 778.4 769.4 753.2 767.00 1.0117 1.0215 1.0335 1.0339 0.2932 328.6 28.1
kzc2 38.966 43.615 7 Pl 822.8 815 790.7 809.50 1.0096 1.0307 1.0406 1.0424 0.5213 294.9 10.8
tas 39.028 43.469 5 Pl 1174.3 1163.1 1143.2 1160.20 1.0096 1.0174 1.0272 1.0276 0.2859 184.8 17.3
san 39.005 43.408 7 Pl 850.8 850.8 819.4 840.33 1.0010 1.0383 1.0383 1.0443 0.999 240.4 12.4
mur 39.064 43.744 11 Pl 587.8 576.4 564.3 576.17 1.0198 1.0214 1.0416 1.0417 0.0400 102.3 6.7
shl 38.998 43.416 8 Pl 527.3 526.5 514.4 522.73 1.0015 1.0235 1.0251 1.0282 0.8774 287.5 8.4
snty 38.955 43.646 7 Pl 563.5 558.4 543.8 555.23 1.0091 1.0268 1.0362 1.0377 0.4890 167.9 16.2
snty2 38.958 43.655 7 Pl 1044.3 1024.5 987.9 1018.90 1.0193 1.0370 1.0571 1.0580 0.3105 216.8 0.8
tprk2 39.074 43.557 7 Pl 1027.3 1025.6 977.3 1010.07 1.0017 1.0494 1.0512 1.0583 0.9336 157.4 5.6
tprk3 39.070 43.557 5 Pl 547.4 539.7 530.2 539.10 1.0143 1.0179 1.0324 1.0325 0.1125 317.6 20.5
tprk4 39.056 43.541 4 Pl 767.1 764.4 739.6 757.03 1.0035 1.0335 1.0372 1.0411 0.8068 353.1 8
trt 38.989 43.569 5 Pl 565.7 554.9 547.9 556.17 1.0195 1.0128 1.0325 1.0327 −0.2058 75.5 31.7
ukg 38.984 43.589 6 Pl 1349.5 1336.3 1293.5 1326.43 1.0099 1.0331 1.0433 1.0454 0.5361 292.1 21.1
uns 38.969 43.601 7 Pl 1335.7 1320.2 1296.8 1317.57 1.0117 1.0180 1.0300 1.0302 0.2102 185.6 3.5
yeni 39.071 43.756 8 Pl 1352.8 1346.7 1321.3 1340.27 1.0045 1.0192 1.0238 1.0253 0.6164 309.1 44.3
haci 39.130 43.411 8 M 1054.4 1050.9 1012.5 1039.27 1.0033 1.0379 1.0414 1.0461 0.8360 188.5 3
ack 39.128 43.468 4 M 1023.1 1011.7 984.4 1006.40 1.0113 1.0277 1.0393 1.0405 0.4188 270 58.8
hcl 39.117 43.495 7 M 1676.2 1662.3 1651.3 1663.27 1.0084 1.0067 1.0151 1.0151 −0.1128 237.3 6.4
orn1 39.149 43.577 3 M 2432.9 2418.2 2,353 2401.37 1.0061 1.0277 1.0340 1.0362 0.6370 188.3 51.6
pay 39.110 43.525 4 M 420.3 413.6 386.7 406.87 1.0162 1.0696 1.0869 1.0924 0.6143 206.2 10.6
yln2 39.120 43.462 5 M 893.7 878.4 867.9 880.00 1.0174 1.0121 1.0297 1.0299 −0.1790 31.5 21.6

N: number of specimens, k 1, k 2, and k 3, maximum, intermediate, and minimum magnetic susceptibility, respectively, k m: mean susceptibility, L: magnetic lineation, F: magnetic foliation, P: anisotropy degree, P j: corrected anisotropy degree, T: shape parameter, D and I, Declination and inclination angles of k 1 axis, respectively (Q: Quaternary, Pl: Pliocene, M: Miocene).

The magnetic susceptibility (k) of an AMS sample is calculated using the equation “J = k × H,” where H is the applied field and J is the induced magnetization. The mean susceptibility (k m) is calculated by taking the average of the k 1, k 2, and k 3 axes (equation 2). Magnetic lineation (L) is developed when the k 1 axes of the particles are aligned parallel to the lava flow direction. One of the most known and used shape parameters for magnetic susceptibility ellipsoid is T, which takes values between −1 and 1. When T > 0, the shape of the ellipsoid is oblate, and if T < 0, the ellipsoid is prolate. To determine the shape of the AMS ellipsoid, magnetic foliation (F) versus magnetic lineation (L) is plotted. This chart is called the Flinn diagram

(1) L = k 1 / k 2 ; F = k 2 / k 3 ; P = k 1 / k 3 ,

(2) k m = ( k 1 + k 2 + k 3 ) / 3 ,

(3) P j = exp 2 ( ( n 1 n ) 2 + ( n 2 n ) 2 + ( n 3 n ) 2 ) ; n i = ln . k i ; n = n i / 3 ,

(4) T = ( ln F ln L ) / ( ln F + ln L ) .

These parameters calculated as a result of the AMS method are used to define the flow direction of lava, whether it is volcanic or plutonic [9].

In this article, to determine the paleo-flow direction of Miocene-Quaternary aged lavas, AMS measurements were carried out on 58 different sites (a total of 357 volcanic samples) at the north of Lake Van. Volcanic samples were collected from 16 sites from Quaternary Girekol, Yüksektepe, and Karnıyarık lavas, 36 sites from Pliocene Etrüsk Volcano, and 6 sites from Miocene Aladağlar volcanic rocks (Figure 2).

Cylindrical core samples were drilled using a portable petrol-powered motorized drill with water cooling and guided in the field with a magnetic and solar compass. The geographic locations of each site were determined with a hand global positioning system instrument. Before conducting AMS measurements in the laboratory, volcanic core samples were cut into standard cylindrical samples (diameter 2.5 cm, height 2.2 cm) in the KANTEK Paleomagnetism Laboratory.

Miocene to Quaternary volcanic rocks’ magnetic susceptibilities were measured by using Bartington MS2B dual-frequency sensor located in Yılmaz İspir Paleomagnetism Laboratory, Geophysical Engineering Department, at Istanbul University-Cerrahpaşa. The analysis of the AMS data was performed using AMS-Bar software, which calculates the parameters related to AMS from the raw data measured by the Bartington Susceptibility Meter (MS2B). The samples were subjected to AMS measurements in 18 different orientations following standardized processes described by Jelínek [27].

Rock magnetic experiments such as isothermal remanent magnetization (IRM) and high-temperature susceptibility (HTS) measurements were performed on samples from at least one location representing each age group to identify the magnetic mineralogy. HTS measurements were acquired to determine the magnetic phase of the minerals using the Bartington MS2 susceptibility/temperature system with the Bartington MS2 susceptibility meter. The heating and cooling phases of the ground sample between room temperature (24°C) and 650°C were done. Also, stepwise acquisition curves of IRM were created using an ASC Pulse Magnetizer in the Yılmaz İspir Paleomagnetism Laboratory in Istanbul University-Cerrahpaşa up to 1T along the sample Z-axis.

4 Results and discussions

4.1 Magnetic mineralogy

IRM acquisition curves reflect different types of behaviors for the analyzed samples. The IRM curves of “pay,” “kek2,” and “tprk6” sites exhibit saturation in low-to-moderate coercivity phases below 0.3T (Figure 3a, c, and k). This corresponds to titanomagnetite, which has a low coercivity magnetic mineral. At the “hac1” site, the IRM curve requires a stronger field to reach saturation, which saturates at 0.5T (Figure 3e). A field stronger than 1T is required to saturate the IRM curves of “snty2” and “mur” sites (Figure 3g and i). This indicates that there may be a hematite component next to magnetite or titanomagnetite.

Figure 3 
                  Representative IRM acquisition curves (a, c, e, g, i, and k) and HTS curves (b, d, f, h, j, and l).
Figure 3 
                  Representative IRM acquisition curves (a, c, e, g, i, and k) and HTS curves (b, d, f, h, j, and l).
Figure 3

Representative IRM acquisition curves (a, c, e, g, i, and k) and HTS curves (b, d, f, h, j, and l).

HTS curves show that the most common magnetic mineral is titanomagnetite. In these curves, the Curie temperature is around 500–580°C (Figure 3b, d, and f). In Figure 3b, the heating and cooling curves are almost reversible. This result indicates that there is almost no alteration in the rock during the heating and cooling phase. At the same time, a decrease in susceptibility up to 200°C during the heating phase indicates that it is Ti-rich titanomagnetite (Figure 3b and d). Irreversible heating and cooling curves are observed in many of the samples (Figure 3d, f, h, j, and k). This shows that a significant degree of alteration occurred during the heating and cooling phases. The increase in susceptibility during the cooling phase can be explained by the growth of maghemite at high temperatures (Figure 3d).

The decrease in susceptibility during the cooling phase is due to the decomposition of titanomagnetite and its transformation into maghemite or hematite [10]. A small decrease is observed in the heating curves of some samples at around 400–450°C (Figure 3f, h, and j). This decrease in susceptibility indicates that Ti-rich titanomagnetite or maghemite may have transformed into hematite. Figure 3h, j, and l shows that the Curie temperature exceeds 580°C. This indicates further oxidation of the maghemite–hematite phases. The plot of sample “tprk6” in Figure 3l shows the heating curve significantly higher than the cooling curve, without any mineral phase change or alteration. In addition, rock magnetic properties of some of the samples used for AMS in this study were presented and interpreted in detail as IRM and HTS in the rock magnetism studies section of Kayın and İşseven [28].

4.2 AMS scalar results and discussions

The mean susceptibility values (k m) were between 377 × 10−6 SI and 2,808 × 10−6 SI, with most of the sites in the range of 500–1,500 (×10−6 SI) (Figure 4a). Considering these results, many of the volcanic rocks used in this study have relatively low k m values. This indicates that paramagnetic minerals predominate in the magnetic susceptibility of the mentioned samples. The shape parameter (T) values range from 0 to 1; only four sites have negative shape parameter (T) values (Figure 4b). These results point out that the magnetic ellipsoids are predominantly oblate. The graph of P j values shows that it is generally lower than 1.06, and there is an accumulation between 1.02 and 1.05 values (Figure 4c).

Figure 4 
                  (a) Statistical distribution of the mean susceptibility (k
                     m), (b) shape parameter (T), and (c) corrected anisotropy degree (P
                     j) values of Miocene–Quaternary volcanic rocks.
Figure 4

(a) Statistical distribution of the mean susceptibility (k m), (b) shape parameter (T), and (c) corrected anisotropy degree (P j) values of Miocene–Quaternary volcanic rocks.

Mean susceptibility (k m) − corrected anisotropy degree (P j) diagrams of all groups (Figure 5a) show no relationship between P j values and k m values, indicating that P j is independent of the magnetic carriers in the volcanic rocks used in this study. On the other hand, when the corrected anisotropy degree (P j) and foliation (F) parameters’ diagram is analyzed, it is seen that there is a positive correlation between these parameters (Figure 5b).

Figure 5 
                  (a) Mean susceptibility (k
                     m) – corrected anisotropy degree (P
                     j) diagram and (b) corrected anisotropy degree (P
                     j) – foliation (F) parameters diagram of all groups (red, white, green, and, blue dots represent Quaternary-aged Girekol, Quaternary aged Karnıyarık – Yüksektepe, Pliocene, and Miocene, respectively).
Figure 5

(a) Mean susceptibility (k m) – corrected anisotropy degree (P j) diagram and (b) corrected anisotropy degree (P j) – foliation (F) parameters diagram of all groups (red, white, green, and, blue dots represent Quaternary-aged Girekol, Quaternary aged Karnıyarık – Yüksektepe, Pliocene, and Miocene, respectively).

Flinn diagrams display the foliation (F = k 2/k 3) against lineation (L = k 1/k 2) showing that the AMS ellipsoids in the Pliocene and Quaternary volcanic rocks generally have oblate-triaxial shape. AMS ellipsoids of Miocene volcanic rocks are both oblate and prolate in shape (Figure 6a, d, g, and j). Moreover, when the graph of shape parameter (T) versus the corrected degree of anisotropy (P j) is analyzed, mostly positive values are seen, indicating an oblate shape (Figure 6b, e, h, and k). Figure 6c, f, i, and l show equal-area projections of AMS for k 1, k 2, and k 3 axis of the Miocene to Quaternary volcanic rocks of the north of Lake Van.

Figure 6 
                  (a, d, g, and j) Flinn diagram of foliation (F = k
                     2/k
                     3) and lineation (L = k
                     1/k
                     2), (b, e, h, and k) plot of shape parameter (T) versus corrected anisotropy degree (P
                     j), and (c, f, i and l) equal area projection of k
                     1, k
                     2 and k
                     3 axis of the Miocene-Quaternary volcanic rocks of the north of the Lake Van.
Figure 6

(a, d, g, and j) Flinn diagram of foliation (F = k 2/k 3) and lineation (L = k 1/k 2), (b, e, h, and k) plot of shape parameter (T) versus corrected anisotropy degree (P j), and (c, f, i and l) equal area projection of k 1, k 2 and k 3 axis of the Miocene-Quaternary volcanic rocks of the north of the Lake Van.

Figure 7 shows the rose diagram drawn from declination (D°) and inclination (I°) of the maximum susceptibility axis (k 1) as an indication of paleo-flow direction. As can be seen in Figure 7a, the paleo-flow in the Girekol volcanic rocks is distributed in all directions, predominantly NW–SE. Although there are few examples in the Karnıyarık and Yüksektepe volcanic rocks of the same age as the Girekol volcanic rocks in Figure 7b, it can be said that there is a complex paleo-flow in almost all directions. The reason for this is related to the fact that there is more than one volcanic center here. Also, the paleo-current direction of the Pliocene volcanic rocks seen in Figure 7c is almost radial in all directions originating from the Etrüsk volcano. The k 1 axis of the samples obtained from the Miocene-aged Aladağ volcanic rocks is roughly NNE-SSW oriented, indicating that the paleo-current direction of the Miocene volcanic rocks is roughly north-south (Figure 7d).

Figure 7 
                  Rose diagrams drawn from the declination of k
                     1 axis show the paleo-flow directions for (a) Quaternary Girekol and (b) Quaternary Yüksektepe and Karnıyarık, (c) Pliocene and (d) Miocene aged volcanic rocks, respectively. N: sample number.
Figure 7

Rose diagrams drawn from the declination of k 1 axis show the paleo-flow directions for (a) Quaternary Girekol and (b) Quaternary Yüksektepe and Karnıyarık, (c) Pliocene and (d) Miocene aged volcanic rocks, respectively. N: sample number.

Mean values of AMS parameters of the Miocene–Quaternary aged volcanic rocks are analyzed, which shows that the mean lineation (L = k 1/k 2), foliation (F = k 2/k 3), anisotropy degree “P,” and corrected anisotropy degree “P j” parameters of the Miocene-aged rocks are larger than the Pliocene- and Quaternary-aged rocks (Table 2). Also, Pliocene-aged rocks are larger than the Quaternary-aged rocks. Besides, Quaternary-aged rock’s mean k m and T values are larger than the Miocene- and Pliocene-aged volcanic rocks. Mean k m values of Miocene-aged volcanic rocks are larger than k m value’s of Pliocene-aged volcanic rocks. While the average k m value of Miocene-aged rocks is larger than the average k m value of Pliocene aged rocks, the T parameter is small.

Table 2

Ranges and mean values of AMS parameters of the Miocene to Quaternary volcanic rocks

Range Mean Range Mean Range Mean
L F k m
Quaternary 1.0001–1.0128 1.0054 1.0144–1.0348 1.0251 615.77–2800.60 1717.94
Pliocene 1.0000–1.0225 1.0094 1.0097–1.0560 1.0286 377.87–2808.30 975.01
Miocene 1.0033–1.0174 1.0103 1.0067–1.0696 1.0308 406.87–2401.37 1278.15
P Pj T
Quaternary 1.0182–1.0392 1.0329 1.0209–1.0418 1.0329 0.2787–0.9958 0.6554
Pliocene 1.0238–1.0663 1.0383 1.0253–1.0717 1.0405 −0.3064–0.9994 0.4964
Miocene 1.0151–1.0869 1.0414 1.0151–1.0924 1.0439 −0.1790–0.8360 0.3591

L: magnetic lineation, F: magnetic foliation, k m: mean susceptibility, P: anisotropy degree, P j: corrected anisotropy degree, T: shape parameter.

4.3 AMS vector results and discussions

Determining the dip angle of a volcanic rock and knowing whether it has occurred before or after the formation of the rock is very important for the interpretation of its paleomagnetic and rock magnetic properties, just as in AMS studies. It is very difficult to determine the dip angle in regions such as Eastern Anatolia, where 3/4 of its area is covered with volcanic rocks derived from different ages and sources. The fact that the inclination obtained from the data is slightly different from the expected and cannot be explained by topography may indicate that the volcanic rock was exposed to a tectonic event after its formation. In addition, irregularity of topography on the underlying surface, where lava flow occurs, can also cause unexpected differences in the measured principal ellipsoid axes in the AMS.

The scattering of information, such as the anisotropy axes obtained for a determined flow in the volcanic sequence, is not related to the quality of the data. This result points to significant local disturbances that occur during or after the cooling of the lava. Therefore, a large number of samples must be measured and evaluated to define a dominant flow direction within the studied volcanic sequence.

In this article, we present AMS results of the Miocene to Quaternary volcanic rocks from the north of Lake Van, Eastern Turkey. The AMS results of the Miocene volcanic rocks, lava flows from north to south, roughly (Figure 8).

Figure 8 
                  Paleo-flow directions of the Miocene-aged AMS sites. The map was created by using the Generic Mapping Tools software, version 5.1.1. [29].
Figure 8

Paleo-flow directions of the Miocene-aged AMS sites. The map was created by using the Generic Mapping Tools software, version 5.1.1. [29].

Also, Pliocene volcanic rocks located around the Etrüsk Volcano indicate the Etrüsk volcanic center as predicted in previous geochemical studies (Figure 9).

Figure 9 
                  Paleo-flow directions of the Pliocene-aged AMS sites. The map was created by using the Generic Mapping Tools software, version 5.1.1. [29].
Figure 9

Paleo-flow directions of the Pliocene-aged AMS sites. The map was created by using the Generic Mapping Tools software, version 5.1.1. [29].

There are multiple Quaternary volcanic centers (Figure 10) in the study area. These are the Girekol, Yüksektepe, and Karnıyarık volcanic centers. While the Girekol volcanic rocks are located in the northwest part of the area given in Figure 10, the Yüksektepe and Karnıyarık volcanic rocks are located roughly in the middle of the study area.

Figure 10 
                  Paleo-flow directions of the Quaternary-aged AMS sites. Red and white arrows represent Girekol and Yüksektepe & Karnıyarık volcanic rocks, respectively. The map was created by using the Generic Mapping Tools software, version 5.1.1. [29].
Figure 10

Paleo-flow directions of the Quaternary-aged AMS sites. Red and white arrows represent Girekol and Yüksektepe & Karnıyarık volcanic rocks, respectively. The map was created by using the Generic Mapping Tools software, version 5.1.1. [29].

5 Conclusions

The magnetic mineralogies of volcanic rocks of various ages and provenance in the study area were defined using rock magnetism studies such as IRM and HTS. As a result, the mineral responsible for magnetization is generally (titano) magnetite, which has a low to medium coercivity and a Curie temperature of 550–580°C. Furthermore, in addition to (titano) magnetite, the presence of hematite, which is not saturated even at 1T and has a Curie temperature of more than 600°C, is seen in some rocks.

The boundaries of the volcanic sequences derived from different ages and sources in the region have been determined by using geochemistry and petrology methods in previous studies [8,22,30,31]. In this study, we identified the paleo-flow directions of the related volcanic materials using the distribution of the k 1 axis of AMS ellipsoid to determine the paleo-flow directions of these volcanic products. Besides, we calculated different AMS parameters such as lineation (L), foliation (F), shape parameter (T), anisotropy degree (P), and corrected anisotropy degree (P j) and evaluated the relationships between them.

As a result, it has been determined that the paleo-flow direction of the Miocene-aged Aladağ volcanic rocks is roughly from north to south. In addition, the paleo-flow direction of Pliocene volcanic rocks, which are different aged products of the Etrüsk Volcano, spreads radially from the Etrüsk Volcano to almost every direction. Moreover, Pleistocene lavas were produced and distributed from at least three different volcanic centers (Girekol, Yüksektepe, and Karnıyarık) spread over large areas in the study area.

Although different ages and types of volcanic products derived from numerous centers are intertwined with each other, as the result of our AMS study, we identified different volcanic rocks and determined their paleo-flow directions. It can be seen from our results that magnetic lineations reflect the lava flow direction.

Acknowledgments

This research was funded by The Scientific and Technological Research Council of Turkey (TUBITAK) (grant number 115Y208) and Scientific Research Projects of Istanbul Technical University (grant number BAP-38661). The authors thank the administration of Istanbul University-Cerrahpaşa, Geophysical Engineering Department, Yılmaz İspir Paleomagnetism Laboratory for the use of the equipment in the laboratory.

  1. Author contributions: For research articles with several authors, a short paragraph specifying their individual contributions must be provided. The following statements should be used “Conceptualization, S.K. and T.İ.; methodology, S.K.; validation, S.K. and T.İ.; investigation, S. K. and T.İ.; data curation, S. K.; writing – original draft preparation, S.K. and T.İ.; writing – review and editing, S. K. and T.İ.; visualization, S. K.; supervision, T.İ.; project administration, T.İ.; funding acquisition, T.İ. All authors have read and agreed to the published version of the manuscript.”

  2. Conflict of interest: Authors state no conflict of interest.

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Received: 2023-10-31
Revised: 2024-01-02
Accepted: 2024-01-24
Published Online: 2024-02-15

© 2024 the author(s), published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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  111. Spatial–temporal effect of sea–land gradient on landscape pattern and ecological risk in the coastal zone: A case study of Dalian City
  112. Study on the influence mechanism of land use on carbon storage under multiple scenarios: A case study of Wenzhou
  113. A new method for identifying reservoir fluid properties based on well logging data: A case study from PL block of Bohai Bay Basin, North China
  114. Comparison between thermal models across the Middle Magdalena Valley, Eastern Cordillera, and Eastern Llanos basins in Colombia
  115. Mineralogical and elemental analysis of Kazakh coals from three mines: Preliminary insights from mode of occurrence to environmental impacts
  116. Chlorite-induced porosity evolution in multi-source tight sandstone reservoirs: A case study of the Shaximiao Formation in western Sichuan Basin
  117. Predicting stability factors for rotational failures in earth slopes and embankments using artificial intelligence techniques
  118. Origin of Late Cretaceous A-type granitoids in South China: Response to the rollback and retreat of the Paleo-Pacific plate
  119. Modification of dolomitization on reservoir spaces in reef–shoal complex: A case study of Permian Changxing Formation, Sichuan Basin, SW China
  120. Geological characteristics of the Daduhe gold belt, western Sichuan, China: Implications for exploration
  121. Rock physics model for deep coal-bed methane reservoir based on equivalent medium theory: A case study of Carboniferous-Permian in Eastern Ordos Basin
  122. Enhancing the total-field magnetic anomaly using the normalized source strength
  123. Shear wave velocity profiling of Riyadh City, Saudi Arabia, utilizing the multi-channel analysis of surface waves method
  124. Effect of coal facies on pore structure heterogeneity of coal measures: Quantitative characterization and comparative study
  125. Inversion method of organic matter content of different types of soils in black soil area based on hyperspectral indices
  126. Detection of seepage zones in artificial levees: A case study at the Körös River, Hungary
  127. Tight sandstone fluid detection technology based on multi-wave seismic data
  128. Characteristics and control techniques of soft rock tunnel lining cracks in high geo-stress environments: Case study of Wushaoling tunnel group
  129. Influence of pore structure characteristics on the Permian Shan-1 reservoir in Longdong, Southwest Ordos Basin, China
  130. Study on sedimentary model of Shanxi Formation – Lower Shihezi Formation in Da 17 well area of Daniudi gas field, Ordos Basin
  131. Multi-scenario territorial spatial simulation and dynamic changes: A case study of Jilin Province in China from 1985 to 2030
  132. Review Articles
  133. Major ascidian species with negative impacts on bivalve aquaculture: Current knowledge and future research aims
  134. Prediction and assessment of meteorological drought in southwest China using long short-term memory model
  135. Communication
  136. Essential questions in earth and geosciences according to large language models
  137. Erratum
  138. Erratum to “Random forest and artificial neural network-based tsunami forests classification using data fusion of Sentinel-2 and Airbus Vision-1 satellites: A case study of Garhi Chandan, Pakistan”
  139. Special Issue: Natural Resources and Environmental Risks: Towards a Sustainable Future - Part I
  140. Spatial-temporal and trend analysis of traffic accidents in AP Vojvodina (North Serbia)
  141. Exploring environmental awareness, knowledge, and safety: A comparative study among students in Montenegro and North Macedonia
  142. Determinants influencing tourists’ willingness to visit Türkiye – Impact of earthquake hazards on Serbian visitors’ preferences
  143. Application of remote sensing in monitoring land degradation: A case study of Stanari municipality (Bosnia and Herzegovina)
  144. Optimizing agricultural land use: A GIS-based assessment of suitability in the Sana River Basin, Bosnia and Herzegovina
  145. Assessing risk-prone areas in the Kratovska Reka catchment (North Macedonia) by integrating advanced geospatial analytics and flash flood potential index
  146. Analysis of the intensity of erosive processes and state of vegetation cover in the zone of influence of the Kolubara Mining Basin
  147. GIS-based spatial modeling of landslide susceptibility using BWM-LSI: A case study – city of Smederevo (Serbia)
  148. Geospatial modeling of wildfire susceptibility on a national scale in Montenegro: A comparative evaluation of F-AHP and FR methodologies
  149. Geosite assessment as the first step for the development of canyoning activities in North Montenegro
  150. Urban geoheritage and degradation risk assessment of the Sokograd fortress (Sokobanja, Eastern Serbia)
  151. Multi-hazard modeling of erosion and landslide susceptibility at the national scale in the example of North Macedonia
  152. Understanding seismic hazard resilience in Montenegro: A qualitative analysis of community preparedness and response capabilities
  153. Forest soil CO2 emission in Quercus robur level II monitoring site
  154. Characterization of glomalin proteins in soil: A potential indicator of erosion intensity
  155. Power of Terroir: Case study of Grašac at the Fruška Gora wine region (North Serbia)
  156. Special Issue: Geospatial and Environmental Dynamics - Part I
  157. Qualitative insights into cultural heritage protection in Serbia: Addressing legal and institutional gaps for disaster risk resilience
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